Browse Topic: Maintenance, repair and overhaul (MRO)

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ME-YOLO: Aircraft Corrosion Defect Detection Model Based on Multi-Directional Edge Perception and Multi-Scale Feature Fusion2026-99-2321To be published on 10/30/2026
Detecting surface defects on aircraft is critical to safety in the aerospace field. The current detection methods suffer from low efficiency, high false positive rate and poor adaptability to complex environment. Although the existing target detection algorithms have achieved notable performance in this field, at present, many models in this field still face considerable challenges. For example, due to the constraints of hardware platforms, machines that can be deployed on edge devices such as UAVs and robots need lightweight and easy-to-deploy models, but lightweight designs often a certain degree of accuracy degradation. At the same time, most of the surface defects of the aircraft are small targets, which impose higher demands on the model. In order to solve these limitations, this paper proposes an improved YOLO model ME-YOLO (multi directional edge fusion YOLO) based on edge enhancement and multi-scale fusion. Firstly, the EdgePyramid module is designed, which uses the rich edge responses extracted by the Multi Orientation Attention Sobel (MOAS) module and through the three-layer cascade pool structure to construct the three-scale edge features aligned with the backbone network. Then, the EdgeEnhance module is introduced to adaptively fuse the conventional convolution features and edge features at the corresponding resolution, effectively enhancing the sensitivity of the model to the corrosion boundary. Experimental results show that, compared with the baseline YOLOv11, ME-YOLO improves mAP@0.5 by 2.7% and simultaneously increases Recall by 2.3%, which helps reduce missed detections of corrosion targets. Although the introduction of multi-directional edge priors brings a slight increase in parameters (+3.66M) and a minor decrease in inference speed (--8.6%), the model still maintains a real-time detection capability of 97.54 FPS, meeting the deployment requirements for edge devices such as UAVs. This strategy of trading a modest computational overhead for improved detection rates in safety-critical tasks offers a potentially practical and robust alternative for intelligent operation and maintenance of aviation equipment.
Zhou, Xing, Li, Yuan
Research on Trajectory Planning Based on High-Precision Improved C-W Equation2026-99-2329To be published on 10/30/2026
In today’s space environment, the number of tumbling objects such as abandoned satellites, uncontrolled spacecraft, and space debris has increased dramatically. Therefore, in-orbit services such as maintenance, recovery, and capture of rolling targets is an urgent topic that needs to be explored. In this paper, for the mission of spacecraft approaching the tumbling target at close range, the trajectory planning method is studied by using the high-precision relative equation of motion as the orbital dynamic model. Firstly, the error of the relative equation of motion of the center of mass is analyzed, and a method to improve the accuracy of the C-W (Clohessy-Wiltshire) equation is considered to construct a higher-precision orbital dynamics model. The constraints such as attitude dynamics, line-of-sight range, control ability and keep-out zone are mathematically described, and the optimal control problem of pose synchronization is established. On this basis, this paper takes the traditional C-W equation and the improved C-W equation as the relative motion models of the centroids, and, based on the adaptive pseudospectral method and sequential convex optimization, solves the position and attitude synchronization planning problem. This article focuses on analyzing the errors of the C-W equation before and after improvement, as well as the impact of linearization on these errors, studies the accuracy improvement brought by the improved equation and the safe obstacle avoidance of position and attitude trajectories, and compares the advantages and disadvantages of the two methods. Simulations verify the accuracy and efficiency of this trajectory optimization algorithm and confirm the accuracy improvement of the improved C-W equation. The improved C-W equation has significant application potential in trajectory planning tasks in complex orbital environments with high-precision requirements.
Zhang, Chao, Yao, Zihao, Gou, Jingwen, Zhang, Yumei, Wang, Yuzhi, Li, Shunli
Research on an EPHM Methodology Based on Gas Path Performance Parameters2026-99-2305To be published on 10/30/2026
Gas path faults in aero-engines are a major factor affecting flight safety and maintenance costs. To achieve the transition from time-based maintenance to condition-based maintenance and enhance fault prediction and health management capabilities, this paper conducts research on intelligent diagnostic methods based on performance parameters for engine gas path components. Firstly, a component-level nonlinear steady-state model of a dual-spool turbofan engine is established, employing a variable specific heat capacity method to improve computational accuracy and provide a healthy baseline for diagnosis. Secondly, addressing the strong nonlinearity and measurement underdeterminacy in fault diagnosis, a diagnostic framework integrating a multi-population genetic algorithm and multi-operating-point analysis is proposed. The multi-population genetic algorithm effectively enhances global optimization capability and solution stability through parallel evolution, migration operators, and an elite population strategy; multi-operating-point data increases information content and strengthens fault isolation capability. Finally, simulation experiments under ground test conditions are conducted to validate the diagnosis of single-component faults in the low-pressure compressor, high-pressure compressor, high-pressure turbine, and low-pressure turbine. The results show that the proposed method can accurately invert component performance degradation, with a high fault identification accuracy rate, verifying the effectiveness of the proposed model and algorithm. This research provides a feasible technical solution for intelligent condition monitoring and precise diagnosis of aero-engines.
Cai, Na, Li, Ming, Li, BianJiang, Yu, GuangHui, Ma, ZhongYuan
A Multi-dimensional Evaluation System for Satellite Constellations: Health and Efficiency Assessment2026-99-291110/19/2026
This paper presents a multi-dimensional evaluation system designed for the health and efficiency assessment of satellite constellations. Aiming at addressing the core demands of on-orbit satellite operation monitoring, performance evaluation, and maintenance decision-making, the system constructs a hierarchical and multi-dimensional index system with a tree structure for constellations, satellites, subsystems, and devices to realize hierarchical assessment. For health assessment, the system includes various algorithms including expectation envelope, multi-interval, and expert scoring, and adopts Gaussian basis function to realize continuous and smooth scoring. For efficiency assessment, the system is built on the ADC algorithm framework, defining Availability vector and Dependability matrix based on fault statistics, and designs five Capability models for key efficiency indicators such as power supply capacity, energy storage capacity and attitude stability. Validated by a series of real cases, the system achieves accurate calculation of evaluation indicators, providing valuable support for on-orbit operation and maintenance.
Gao, Haoran, Yang, Zelong, Liu, Peng, Zhang, Xiangyan, Han, Hongbo
Edge-Intelligent Real-Time Evaluation System for Aerospace Manufacturing Skill Training2026-99-292010/19/2026
The evaluation of practical skills in aerospace manufacturing, maintenance, repair, and overhaul (MRO) conventionally relies on examinations or observations from instructors. However, these methods deliver slow feedback, reduce the efficiency of skill acquisition and require substantial instructional workload. To overcome these challenges, this study proposes an edge-intelligent real-time evaluation system for skill training in the field of aerospace manufacturing. Specifically, the system comprises five sensing modalities, which are then processed through a hierarchical three-layer structure. Then, the neural architecture search (NAS) is introduced to identify the optimal network structure and the quantization-aware training (QAT) approach is employed to improve the inference speed. In addition, temporal modeling is used to realize real-time inference and multi-level evaluation. Moreover, a conflict-aware adaptive fusion algorithm is introduced to ensure robust scoring under harsh workshop conditions and deliver interpretable feedback. Finally, federated learning and the differential privacy mechanism are used for cross-institutional model improvement without raw data exposure. Empirical results on turbofan engine MRO assembly, airframe structural component CNC manufacturing, and aviation maintenance human factors training show that the system achieves low latency, high expert correlation, improved learning efficiency and strong robustness, which offers a scalable and privacy-aware solution for competency-based vocational training in the aerospace manufacturing field.
Li, Xin, Li, Zhaokang, Yu, Lina
Carbon Fiber Fabric Repair Prepreg, 120 °C (250 °F) Vacuum Curing, Part 6 - Material Specification: Carbon Fiber Fabric Reinforced Epoxy Prepreg for Repair, Plain Weave Fabric, 193 g/m2, Adhesive Film for Repair and Non-Structural Glass Fiber Fabric Reinforced Epoxy Prepreg, 105 g/m2AMS3970/6A (Current)9/22/2026
AMS3970/6 Material Specification (MS) defines the requirements of carbon fiber plain weave fabric, 193 g/m2, reinforced epoxy structural prepreg for repair, curing under vacuum at 120 °C (250 °F), and a companion non-structural glass fiber fabric reinforced epoxy prepreg, 105 g/m2, used in repair of carbon fiber reinforced epoxy structures and qualified according to AMS3970/1 and AMS3970/2 for aerospace applications. The prepreg system may include an epoxy film adhesive to be applied in a co-curing process with the prepreg for joint and sandwich bonding. The need for a film adhesive shall be established during screening tests. If included, the requirements to be met by the adhesive are also defined in this document.
AMS CACRC Commercial Aircraft Composite Repair Committee
Real-time Vehicle Speed Detection Based on YOLOv11 and DeepSORT2026-99-15959/11/2026
The technology of real-time and effective vehicle speed detection is considered a key technology to improve traffic monitoring efficiency and traffic safety management grade. To address the limitations of traditional speed detection schemes—including reliance on dedicated hardware, poor environmental adaptability, and high construction and maintenance costs—this paper proposes a r10eal-time vehicle speed detection system based on YOLOv11 and the DeepSORT algorithm. The proposed system uses the YOLOv11 target detection algorithm as its primary model. DeepSORT multi-target tracking technology is integrated to enhance tracking performance. Speed measurement is implemented using a virtual detection line. This approach enables accurate vehicle detection, continuous tracking, and real-time speed measurement within video frames. Through the experiments, the result shows that the improved YOLOv11n model reaches mAP@0.5 of 0.982 and a recall rate of 0.956 in the test set, higher than the YOLOv8n and YOLOv5s models. The speed detection error can be restricted to 3 km/h, satisfying the real-time detection need. There is no need for road surface modification, and the detection system has a flexible layout, providing a dynamic basis for traffic law enforcement and traffic data support for road construction and traffic control optimization.
Jin, Guowei, Ma, Wenlong, Jiang, Dali, Li, Nan
Research on Heavy-Haul Train Operation Adjustment Considering the Degree of Chaos in Train Timetable2026-99-15229/11/2026
Heavy-haul railway development is as important a strategic direction for China’s railway sector as high-speed railway development. With the continuous expansion of heavy-haul railway operational mileage and the growing transportation demand, the complexity of operational adjustment in heavy-haul railways continues to escalate. The operational adjustment for heavy-haul trains subjected to speed restrictions following maintenance windows, aimed at maximizing the restoration of timetable regularity and guaranteeing freight volume, constitutes a critical and urgent research problem. Grounding on the operational principle of heavy-haul railways that prioritizes freight volume preservation over strict punctuality, this paper proposes a rescheduling model that incorporates the timetable disruption level. By adopting the order entropy theory, the model is formulated to minimize the total system disruption level and freight time cost, thereby framing the rescheduling problem as an order entropy optimization problem. The train disruption level is a metric that quantifies the perturbation intensity of a rescheduled timetable relative to the original operational plan within a given railway section. By initializing the entropy value of the pristine operational order to zero, any subsequent entropy variation directly facilitates a systematic investigation into the evolution of train operational order. Effective timetable adjustment strategies are subsequently derived, contingent upon the available buffer time and freight volume constraints. Guided by actual operational timetables and sectional line characteristics, this research designs a case study. The Gurobi solver is employed to obtain a rescheduled heavy-haul train timetable that successfully restores the original freight volume. The proposed methodology contributes to the enrichment of railway transportation organization theory and provides robust decision-making support for the strategic deployment of heavy-haul train services.
Fu, Lu, Lin, Li, Xu, Shichao, Ji, Guanggang, Li, Zheng
A Life Prediction-Driven Maintenance Decision Method for Aircraft Engines2026-99-14069/11/2026
As the operating conditions of aircraft engines become more complex, the traditional maintenance strategies based on experience or fixed cycles are difficult to balance economic efficiency and reliability. This paper tentatively proposes a maintenance decision-making method driven by life prediction for aircraft engines. In the life prediction stage, considering the complex spatio-temporal coupling relationships contained in the degradation signals of multiple sensors, a spatio-temporal feature fusion transformation network is designed to jointly model the spatial dependence and temporal dynamics. At the same time, a probabilistic deep learning model is introduced to model the mean and uncertainty of the remaining life, providing risk warnings beyond point estimation. In the maintenance decision-making stage, the predicted distribution parameters are introduced into the Markov decision process state space. Based on the deep Q-network, a reward function is designed, and cost constraints are considered, thereby achieving a balance between safety and economy. Experimental results based on the C-MAPSS dataset show that this method achieves reasonable performance in common prediction indicators and demonstrates certain advantages over traditional maintenance strategies in the comparison experiments of maintenance decisions. The effectiveness of the method has been verified.
Yu, Sijia
Track De-icing and Road Maintenance Method Based on Induction Heating Technology2026-99-15369/11/2026
In order to solve the problems of long preheating time and high energy consumption caused by the traditional resistance heating track deicing technology and large power supply load, this paper presents a track deicing and road maintenance method based on electromagnetic induction heating. This paper studies the operational bottlenecks of the resistance heating system in a certain marshalling yard. It explains the eddy current heating from the principle of electromagnetic induction heating and designs an appropriate coil for turnouts and derives its power calculation formula. A mathematical model for the 'solid-liquid' phase transformation in the melting of snow is created and the melting parameter α = 0.623. In comparative experiments, compared to a 4kW electromagnetic induction heating device with no preheating time which melts snow up to 5cm in 40 minutes and consumes 40kW · h of energy in 1 hour, a 13kW resistance heating device needs 150 minutes to preheat, 180 minutes to melt, and consumes 130kW · h of energy. Use 70% less energy and help with track and road de-icing and upkeep with this technology.
Song, Zongying, Li, Zhongming, Wei, Dong, Yang, Jin, Wang, Xingzhong, Liu, Jingwei, Zhang, Xiaoyu
Application of Two-Component Flocculant Underwater Non-Dispersible Concrete in Ship Lock Engineering2026-99-12829/4/2026
To tackle the challenges of pronounced dispersion and inadequate cohesion of concrete in the underwater repair of ship lock engineering, this study presents a novel approach involving acrylate copolymer emulsion (PAE) and waterborne polyamine curing agent (WE) as the two-component flocculant, integrated with fiber modification technology, to fabricate non-dispersible concrete tailored for ship lock underwater rehabilitation. Mechanical property tests and elastic modulus analyses demonstrate that the resultant concrete exhibits significantly improved scour resistance, endowing it with robustness against erosion in complex subaqueous environments. This work thus offers a dependable technical solution for the structural repair and toughening of ship lock structures.
Li, Jun, Zhu, Xunsong, Yang, Ning, Meng, Xingyu, Zong, Jiawei
Navy Flight-Tests 3D-Printed Composite Repairs for F/A-18 Super HornetsTBMG-558259/1/2026
Naval Air Warfare Center Aircraft Division Patuxent River, MD
Research on Data-Driven Intelligent Monitoring and Prediction System for Fatigue Damage in Metallurgical Cranes2026-99-02167/31/2026
Metallurgical cranes have a high risk of structural fatigue damage and failure under complex working conditions such as high temperature, heavy load, and strong electromagnetic interference. This article proposes a data-driven structural fatigue damage health monitoring system. This system integrates fiber Bragg grating sensing technology, rigid flexible coupling multi-body dynamics simulation, and big data analysis methods to construct a sensor optimization layout strategy based on rigid flexible coupling virtual prototype simulation, achieving real-time perception of stress states in key parts such as the mid span and end beam corners of the main beam. Develop a visualization system that integrates health monitoring, damage diagnosis, and life prediction. This system can dynamically evaluate the structural health status of metallurgical cranes and predict the remaining life of the structure based on a nonlinear cumulative damage model. On site engineering applications have shown that the monitoring and prediction visualization system can effectively improve the intelligent and safe operation and maintenance level of metallurgical cranes, providing a data foundation and possibility for their predictive maintenance.
Chen, Li, Zhang, Xu, Ding, Keqin
Advancing Reliability Centered Maintenance: A Robust Statistical Approach for MTBF Estimation in Aero-Engine Fleets via Subgrouping Strategy and Dual Weibull Modeling2026-99-02137/31/2026
Fleet heterogeneity, from manufacturing variations and diverse operating conditions, complicates reliability analysis by obscuring true failure patterns in aero-engines. This is a critical challenge in an industry as inaccurate Mean Time Between Failures (MTBF) estimates threaten safety and inflate operational costs, by forcing a choice between inefficiently conservative maintenance or the risk of in-service failures. Conventional analysis often fails by pooling all fleet data. To address this, our paper presents an analytical framework that improves predictive accuracy by filtering, rather than aggregating statistical noise. The methodology uses a Randomized Block Design (RBD) and ANOVA hypothesis test to screen a diverse dataset and isolate statistically homogeneous subgroups. This filtration identifies a core fleet with a consistent failure signature, providing a purified dataset for modeling. This refined data is then modeled using both Weibull and the Exponentiated Inverse Weibull distributions to ensure the results are robust and not model-dependent. Applying this framework to a 25-engine dataset that experienced 66 failures, we isolated a stable failure pattern, yielding a primary MTBF of 171.16 hours and a cross-validated MTBF of 176.35 hours. The close 3% convergence between these models validates our approach. By providing a dependable MTBF, this work establishes a stronger foundation for data-driven Reliability Centered Maintenance (RCM). It empowers maintenance planners to move toward evidence-based intervals, safely extending engine time-on-wing, optimizing spare parts inventory, and significantly reducing direct operational costs for airlines.
Jubaid, Mayin Uddin, Bebe, Gibson, Bigyen, Musa Pethuel, Anik, S M Kullul Mehedee, Yasmin, Ashrafi, Sahran, Mohamed Sideek Mohamed
Design and Control of a Target Plate Fastener Assembly and Disassembly Actuator for Divertor Maintenance in Fusion Reactors2026-99-01827/31/2026
With the development of controlled nuclear fusion technology, the tokamak device, as the most promising magnetic confinement fusion reactor for advanced engineering applications, requires remote maintenance of its internal components, which has become a key factor affecting both operational efficiency and safety. As a critical component directly exposed to high-temperature plasma, the divertor target plate needs to be periodically replaced and carefully maintained to ensure stable and reliable reactor operation. However, this region is subject to extreme conditions, including high temperature, high vacuum, and intense radiation, making conventional manual maintenance infeasible. This necessitates the development of intelligent and automated teleoperation systems. To address the automated assembly and disassembly requirements of divertor target plates, this study designs an integrated target plate actuator comprising key functional units: a positioning module, a screwing module, a quick-change module, and a passive compliance structure. The actuator achieves rapid and precise alignment with target plate holes, accommodates bolts of different specifications, and exhibits excellent impact resistance. Furthermore, stiffness and mechanical analyses, supported by finite element simulations, verify the actuator’s safety and reliability under high loads and impact forces. To further enhance operational performance, a segmented disassembly and assembly control strategy based on reinforcement learning is proposed, enabling the actuator to adaptively handle torque variations and ensure precise and stable bolt operations. The results demonstrate that the proposed actuator and control strategy significantly improve the accuracy, stability, and efficiency of target plate operations under complex working conditions, providing a reliable solution for automated divertor maintenance in tokamak devices.
Zang, Xizhe, Yu, Xingzu, Cao, Zhangbin
Design and Analysis of a Large Hydraulic Cylinder Maintenance Device2026-99-02147/31/2026
Addressing the challenges in maintaining large hydraulic cylinders and the lack of specialized equipment, this study presents a dedicated maintenance system developed through a case study of a large hydraulic lifting cylinder. Through a comprehensive analysis of maintenance requirements, we developed a six-component maintenance system comprising a foundation base, a mounting bracket, a cylinder support frame, a piston rod bracket, a drive cylinder bracket, and hydraulic components. The paper systematically explains the structural configurations and functional specifications of each component, details the operational workflow of the maintenance system, and conducts theoretical design and strength verification for critical load-bearing brackets using principles from theoretical mechanics and structural mechanics. A static analysis module from ANSYS Workbench finite element software was employed to validate the overall structure. Results demonstrate that the key components meet operational strength requirements. This innovative maintenance system proves highly feasible and serves as a valuable reference for designing similar hydraulic cylinder systems.
Qiao, Xiaodong, Du, Chao, Long, Yuheng
Desulfurization and Acid Resistance of Multifunctional Protective Coatings in Severe Environment2026-99-02387/31/2026
Desulfurization equipment in electric power industry is in a multi-field coupled corrosion environment with high temperature, high humidity, strong acid and solid-containing slurry. The annual direct economic loss of corrosion exceeds 5 billion yuan, and the equipment replacement cycle is only 1.5-2 years. Traditional protective coatings are difficult to meet the needs. The concept of “bionic barrier-intelligent response-in-situ purification” is proposed to construct multifunctional protective coatings: The Langmuir-Blodgett technique was used to alternately assemble MXene nanosheets and polysilazane. Ti-O-Si covalent bonds enhanced the interface bonding, resulting in a coating hardness of 4H and an elongation of 200%. After 1500 hours of extreme environment test, the coating has low weight loss rate, high self-repair and antibacterial rate, and its service life is extended by 8 times. The engineering application makes the maintenance period of desulfurization tower of a 660MW unit extended from 8 months to 6 years, saving 1.2 million yuan annually, and increasing 200,000 yuan annually by recovering H ˇ SO 2. It provides a cross-scale scheme for electric power corrosion protection.
Nie, Pengfei, Gao, Jiangyu, Chen, Wei
Design and Application of Simulation-Based Lifting Tool for Fabric Truck Roller Replacement2026-99-01377/31/2026
In the process of replacing the rollers of the fabric cart of the tobacco storage cabinet, in order to solve the problems of low replacement efficiency and high safety risk.This article proposes a specialized lifting tool for fabric cart rollers with a self-locking and adopts the screw lifting structure, which facilitates roller maintenance operations, and conducts SolidWorks Simulation calculations and dynamic simulation methods. Jinan Cigarette Factory fine cigarettes special line leaf silk temporary storage cabinet fabric car roller replacement, for example, the results show that: the average operating personnel reduced by 50%, the replacement time from 6.7h to 1.2h, efficiency increased by 458%, This innovation significantly reduces the labor intensity of maintenance personnel and ensures a safe and reliable replacement process.
Zhang, Lei, Xue, Yifei, Zhang, Ge, Sun, Yanzhao, Wang, Hongbin, Cheng, Linfeng
Development and Performance Validation of a Maintenance Platform for 10kV Switchgear Trolleys2026-99-02047/31/2026
With the development of the power industry, 10kV switchgear (circuit breaker switches) are increasingly widely applied in power grids. When performing power-off maintenance or testing on 10kV switchgear (circuit breaker switches) at substations, maintenance personnel require transport carts to move the equipment to suitable locations for operation. Traditional transfer carts suffer from structural design flaws and significant shortcomings. These include difficulty operating in the confined spaces of switchgear cabinets, high risks associated with manual handling, low efficiency in secondary transfers, and poor adaptability across multiple workstations. These issues collectively pose safety hazards during power-off maintenance or testing. When operating in a 3m×5m high-voltage room, traditional maintenance carts achieve less than 0.5 units transported per hour, with equipment damage rates reaching 3% annually due to drops, resulting in low work efficiency. To address these challenges, a 10kV switch cart maintenance platform has been developed. This standardized equipment facilitates 10kV switch cart maintenance, supporting the intelligent upgrade of power grid operation and maintenance.
Yang, Sen, Zhou, Han, Su, Hainan, Yu, Xin, Hu, Yutao, Wang, Xisheng
Cross-Condition Bearing Multistage Degradation Identification Based on Health Indicator Matrix and Transition Sample Enhanced Network with Multi-Branch Encoding2026-99-08587/30/2026
Precisely detecting multi-stage degradation (MD) in rolling bearings is crucial for keeping equipment in good shape. Yet, health indicator (HI) crafted with current single-method strategies often can't balance degradation sensitivity and monotonicity across different operating conditions. Also, common MD detection methods struggle to spotransitional samples between degradation stages in cross-condition settings. To tackle these challenges, this paper introduces a new cross-condition MD detection approach for bearings, which relies on a health indicator matrix (HIM) and a transition sample enhanced network with multi-branch encoding (TSEN-MBE). First, a degradation-sensitive health indicator (DSHI) is constructed by integrating the least absolute shrinkage and selection operator (LASSO) algorithm — with comprehensive fault frequency energy (CFFE) as the regression target — and the grey wolf optimizer (GWO), capturing intrinsic degradation characteristics of bearings. Meanwhile, to enhance the monotonicity of unsupervised HIs, a time-weighted Wasserstein distance (TWWD) metric is proposed by incorporating temporal degradation features into the Wasserstein distance-based HI construction. The DSHI and TWWD are subsequently combined to generate the HIM. This HIM serves as the driving force for the Gath-Geva (GG) fuzzy clustering algorithm, enabling it to adaptively allocate MD labels according to varying operating conditions. Ultimately, the TSEN-MBE model is constructed, employing multi-branch Transformer encoders integrated with multi-head attention mechanisms to encode and combine heterogeneous features. A joint loss (JL) function — comprising transition sample enhancement (TSE), local maximum mean discrepancy (LMMD), and cross-entropy (CE) losses — is designed to enhance the recognition of transitional samples and improve cross-condition MD identification accuracy. Experimental results on the XJTU-SY dataset validate the effectiveness and superiority of the proposed method, showing that DSHI achieves the highest average degradation angles, TWWD obtains optimal monotonicity, and TSEN-MBE outperforms comparative methods in cross-condition recognition tasks.
Ma, Jinghua, Wei, Lai, Hu, Guangqiao, Yu, Xiaoxia
Design and Analysis of a Lightweight Offshore Gangway2026-99-08517/30/2026
During offshore wind power operation and maintenance activities, personnel transfer and boarding procedures involve numerous safety risks. is a highly effective solution for enhancing safety during ship transfers at sea. This paper designs a compact active motion-compensating lightweight gangway capable of compensating for multi-degree-of-freedom motions induced by sea waves, including roll, pitch, yaw, and heave. The structural design is first established, and based on this configuration, the output forces of the rotary electric cylinder, roll electric cylinder, and pitch electric cylinder are analyzed. A finite element method was employed to conduct a static analysis of the gangway under extreme loading conditions. Analysis of the first six modal orders revealed that the first natural frequency of the designed gangway is significantly higher than the wave frequency, thereby effectively preventing resonance phenomena. The forward transformation matrix of the gangway was simulated using the Denavit-Hartenberg (DH) method. Simulation results indicate that the working space of the lightweight gangway meets the preset motion range requirements, thereby validating the design’s feasibility. The designed compact passageway features simple operational control, high cost-effectiveness, minimal installation footprint, and low installation and control complexity, demonstrating high practicality.
Yu, Zhigang, Fu, Wanli, Zheng, Bowen, Wang, Zhuoqun, Fang, Jiwen
Design and Analysis of Offshore Wind Power Operation and Maintenance Shipborne Pitch Compensation Trestle Structure2026-99-08077/30/2026
In light of the significant roll/pitch experienced by traditional shipboard trestles due to wave action during the transfer of maintenance personnel from the operation and maintenance vessel to the offshore wind turbine base, an analysis of ship motion states was conducted under various sea conditions and ship manufacturing parameters. The kinematic capabilities and characteristics of the actuator were defined, and the mapping relationship between the wave compensation capability of the active wave compensation trestle and key design parameters, such as actuator power, was established. Consequently, an active wave compensation trestle executive mechanism was developed, incorporating lightweight research into its design. A prototype of the active wave compensation trestle was constructed and subjected to motion compensation testing. The results indicate that the prototype can effectively maintain stability between the ship and the offshore facility, thereby enhancing the safety of transferring personnel and improving maintenance efficiency.
Sun, Tierui, Zhao, Pengfei, Xin, Ran, Qiu, Jicheng, Yang, Xiaotao, Shiyuan, E
Accurate Control of Refueling Volume for a New Type of Oil Change Device in the Reducer of Tobacco Machinery Equipment2026-99-16187/24/2026
In order to achieve precise control of refueling volume, improve oil change efficiency, reduce oil pollution and waste, a new oil change device for the reducer of the range hood equipment is studied. We design a new oil change device that integrates oil discharge and refueling functions based on the operating characteristics of the reducer in the range hood equipment. Using the rotational speed of the power pump and the flow rate of the oil pipeline as variables, we determine the refueling flow rate using a one-dimensional quadratic formula. Based on direct control theory, we optimize the relative position parameters of each component of the device, establish a control matrix, and achieve precise control. The experimental results show that the new oil change device exhibits good performance during both one-time oil discharge and refueling processes, meeting the precise control standards for refueling volume. The design and application of a new oil change device can effectively improve the efficiency and accuracy of oil change in the reducer of the range hood equipment, and have practical application value.
He, Pengtao, Wei, Bo, Liang, Zhiyuan, Deng, Weiren, Liang, Wenbin, Xing, Yuquan
Carbon Fiber Fabric Repair Prepreg, 120 °C (250 °F) Vacuum Curing, Part 3 - Purchasing Specification for Carbon PrepregAMS3970/3B (Current)7/13/2026
This Purchasing Specification (PS), AMS3970/3, specifies the batch release and delivery requirements for carbon fiber fabric epoxy prepreg used for repair. This specification is applicable only when the carbon fiber fabric epoxy prepreg is used as part of the repair system defined in AMS3970 and AMS3970/1. This specification also defines the procedure and requirements for storage life extension of materials purchased against this specification. It is only applicable for materials that are qualified against AMS3970 (refer to PRI QPL AMS3970) and shall be carried out within the responsibility of the purchaser and under control of its Quality organization.
AMS CACRC Commercial Aircraft Composite Repair Committee
Carbon Fiber Fabric Repair Prepreg, 120 °C (250 °F) Vacuum Curing, Part 5 - Purchasing Specification for Companion Non-Structural Glass Fiber Fabric PrepregAMS3970/5A (Current)7/13/2026
This Purchase Specification (PS), AMS3970/5, specifies the batch release and delivery requirements for the companion non-structural glass fiber fabric prepreg. This specification also defines the procedure and requirements for storage life extension of materials purchased against this specification. It is only applicable for materials which are qualified and shall be carried out within the responsibility of the purchaser and under control of its Quality organization.
AMS CACRC Commercial Aircraft Composite Repair Committee
Human Reliability in Aircraft Maintenance Operations: A Quantitative Analysis Through Evidential Reasoning-Enhanced SPAR-H Methodology2026-99-05947/10/2026
The reliability of aviation maintenance personnel directly impacts flight safety, yet systematic methodologies for the quantitative prediction of human error probability (HEP) in this domain remain lacking. To address this gap, a novel human factors reliability analysis method for aviation maintenance is proposed, extending the SPAR-H model through Evidential Reasoning (ER). This method is implemented as follows: Maintenance tasks are decomposed into subtasks. Subsequently, the eight types of Performance Shaping Factors (PSFs) for each subtask are evaluated by domain experts according to defined PSF levels. Expert judgments are then aggregated using Evidential Reasoning theory, enabling the calculation of aggregated PSF levels. These aggregated levels are interpolated to determine the corresponding impact multipliers. Finally, the HEP for aviation maintenance operations is calculated by integrating the SPAR-H basic error probability model with task series/parallel logic rules. The proposed methodology is validated using an inspection operation case study. This study establishes a methodological framework for human factors reliability analysis in aviation maintenance, providing a theoretical foundation for developing scientifically grounded prevention and control measures to enhance aviation safety levels.
Meng, Meng, Ma, Ning, Guan, Zhongqing, Han, Zuyang, Nan, Wenxue, Cai, Hongbin
Design and Testing of a Quasi-Zero-Stiffness Vehicle-Mounted Isolation System with Additional Inerter2026-99-05207/10/2026
Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.
Li, Kai, Lv, Sibo, Sun, Ning, Dai, Shijie
BAND, MALE COUPLING, 6 INCH AIR DUCTAS7365/9A (Current)6/23/2026
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Automotive Air-Conditioning Service Ports Task Force Field Survey ResultsJ3267_202606 (Current)6/23/2026
The automotive air-conditioning service ports task force conducted a field survey with MACS (Mobile Air Climate Systems Association) in June 2021. The scope of this survey was to determine the types of failures reported primarily at member service shops related to automotive air-conditioning service ports.
ICTMS Supplier Committee
Identification and Assessment of Damage to Composite Aircraft Structures Training DocumentAIR6825 (Current)6/10/2026
Individuals who complete the applicable modules aligned with this training document will be able to define the type of damage, define the extent of damage, determine if further inspection is required, evaluate the damage against published allowable damage limits, and provide accurate documentation of the damage. The intended outcome of the training is increased safety such that no aircraft is released with unknown damage and that the aircraft meets continued airworthiness requirements. The goal is to change the culture from damage discovery to damage reporting while also reducing or eliminating flight delays due to incorrect or insufficient information. Teaching levels have been assigned to the curriculum to define the knowledge, skills, and abilities graduates will need. Minimum hours of instruction have been provided to ensure adequate coverage of all subject matter including lecture and practical exercise. These minimums may be exceeded and may include an increase in the total number of training hours and/or increases in the teaching levels. The modules are intended to be a competency-based training approach. Each curriculum is a subpart of this document. Module 1 is the Composite Awareness curriculum, independent of the application. Module 2 is the Initial Inspection and Damage Mapping curriculum. Module 3 is the Special Inspection Tools curriculum. Module 4 is the Reporting, Recording, and Assessment curriculum. NOTE: While the modules in this document are technically interrelated, each module can be trained independently; modules may be selected as applicable to an operator’s or maintenance organization’s needs. The combination of the modules represents the applicable identification and assessment process for damage to composite aircraft structures (see Figure 1). Module 1 is prerequisite for attendance to the other modules. The contents of Module 1 may also be used for composite awareness training of a broader target audience, including line mechanics.
AMS CACRC Commercial Aircraft Composite Repair Committee
A Parametric Cradle-to-Grave Life Cycle Assessment Tool for Comparative Evaluation of Passenger Car CO₂ Emissions2026-37-00406/9/2026
This work presents the development of a user-oriented software tool for the cradle-to-grave Life Cycle Assessment (LCA) of passenger cars, enabling robust comparisons of greenhouse gas emissions across heterogeneous vehicle configurations. The tool supports informed decision-making by quantifying and visualizing environmental impacts associated with alternative mobility choices over the full vehicle life cycle, including production, use, maintenance, and end-of-life stages. The proposed framework allows key parameters describing both the vehicle and its usage to be explicitly defined, including powertrain type, dimensions and weight, ownership profile (new or second-hand vehicles, partial ownership periods, leasing scenarios), annual mileage, vehicle lifetime assumptions, and the carbon intensity of fuels or electricity sources. Country-specific energy mixes are incorporated, enabling the same vehicle to be assessed under different geographic contexts and highlighting the strong dependence of use-phase emissions on local energy systems. Results are reported both as total life-cycle emissions and as a phase-resolved breakdown, improving transparency and supporting a clear interpretation of trade-offs between production, operation, maintenance, and end-of-life stages. Representative scenarios demonstrate that, under a standard European context, battery electric vehicles (BEVs) achieve a reduction of approximately 32% in yearly greenhouse gas emissions compared to a baseline Euro 5 gasoline vehicle. However, this trend reverses for low-mileage users relying on second-hand vehicles, for which emissions can increase by about 15%, emphasizing the critical role of usage patterns and ownership strategies in determining environmental benefits. The tool is designed to accommodate updated datasets, emission factors, and evolving energy scenarios, ensuring long-term applicability and enabling forward-looking analyses. Its capabilities are demonstrated across scenarios covering short- and long-term usage, multiple national contexts, and different powertrain technologies. The result is a robust and transparent assessment platform that enables users and policymakers to evaluate vehicle replacement strategies, providing quantitative insights into the interplay between technology, usage, and sustainability in mobility transitions.
Gastaldi, Chiara, Cibrario, Luca
SAE TOMORROW TODAY - Turning Streetlights Into EV Chargers135706/8/2026
What if the streetlights in your neighborhood could charge your EV overnight? Voltpost is making this vision a reality by transforming existing lampposts into modular, upgradeable EV charging stations managed by a mobile app. By partnering with utilities, the company is accelerating EV charging infrastructure deployment by retrofitting what's already in place. Listen in as we sit down with James Everley, Director of Business Development, to explore how Voltpost's streetlight EV charging solutions blend seamlessly into the urban landscape. From pricing that respects overnight charging habits to design choices that fit historic districts, you'll discover why low-power, on-street Level 2 charging is a critical piece of the broader EV ecosystem. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
Aircraft Cabin Diagnosis – Inspection of the Aircraft Cabins and Seats Using AI2026-26-07896/1/2026
Aircraft interior defects, including seat structural damage, cushion degradation, liquid contamination, and foreign object presence, contribute to increased maintenance burden, extended ground time, and operational inefficiencies. Current inspection practices rely predominantly on manual visual checks, which are time-intensive and limited in detecting concealed anomalies. This paper presents a non-contact, AI-enabled inspection framework integrating millimeter-wave (mmWave) radar sensing with high-definition optical imaging for automated aircraft seat condition assessment. The proposed system captures interior scans when the aircraft is unoccupied and compares them against a digitally established baseline reference obtained under certified, defect-free conditions. Data fusion and machine learning algorithms analyze deviations to identify surface and subsurface defects at seat-level resolution and generate zone-based maintenance maps. The primary technical contribution lies in combining subsurface-capable mmWave sensing with AI-driven deviation analytics to enable detection of concealed cushion defects and foreign objects, including service tools, which are not reliably identified through conventional visual inspection alone. The system outputs structured maintenance reports identifying seat location, defect classification, and severity prioritization, thereby supporting targeted corrective action and reducing troubleshooting time. In addition to in-service aircraft applications, the framework is extendable to seat production and final assembly inspection environments. Establishing a digital baseline during manufacturing enables inline quality validation, structural compliance verification, and traceable lifecycle data creation. This unified digital inspection approach supports predictive maintenance modeling, reduces rework and downstream maintenance events, and enhances overall aircraft interior safety and reliability assurance.
Nagoal, Chandrasekhar Reddy, Prathipati, Krishna Chaitanya, Kandukuri, Ravindra
Enabling Circularity in the Aerospace Maintenance Ecosystem through Generative-AI Driven Back-to-Birth Traceability of Life-Limited Engine Parts2026-26-07196/1/2026
Circular-economy principles are increasingly central to aerospace sustainability strategies, aiming to extend asset life, improve asset valuations, and enhance benefits to stakeholders in the part ownership and maintenance lifecycle. In aircraft engines, achieving circularity hinges on safe reuse, repair, and recirculation of high-value components. Life-Limited Parts (LLPs) are among the most critical in this context, but their reuse is strictly contingent on complete Back-to-Birth (BtB) traceability. Any gap in BtB records—often due to fragmented data across multiple airline operators, shop visits, document formats, and time expanse—renders otherwise serviceable LLPs unusable, leading to premature scrappage and lost circular value. This paper presents a Generative AI (GenAI)-driven methodology to reconstruct and validate complete LLP BtB histories from heterogeneous, unstructured, and legacy maintenance datasets. By combining aerospace domain-trained language models with embedded life accounting logic and regulatory compliance reasoning, the approach produces audit-ready documentation that assists the asset owners in meeting regulatory standards from aviation authorities such as EASA and FAA. Enhancing traceability to LLPs enables their safe re-entry into operational service, supports the module swaps market, and optimizes part pooling strategies. The result is a digital enabler for circularity in the engine lifecycle—preserving material value and maintaining uncompromised safety and compliance in aviation.
Bhate, Ujwal, Jain, Dilip Kumar, Kulkarni, Ninad, Kalaiyarasan, Aravindh, Jha, Ashish, Shenoy, Karthik
Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction2026-26-07186/1/2026
Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds, and (2) a data-driven Recurrent Neural Network (RNN), specifically a Long Short-Term Memory (LSTM) network, for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, high-fidelity synthetic run-to-failure dataset under varying operational loads, accurately simulating realistic mission profiles. This approach addresses the critical "data scarcity" challenge in aviation. To ensure operational reliability, the framework incorporates Uncertainty Quantification (UQ) using Monte Carlo Dropout and addresses the "Sim-to-Real" gap through Transfer Learning on the NASA IMS bearing dataset. The HDT demonstrates a significant improvement in prognostic accuracy, achieving a Root Mean Square Error (RMSE) reduction of over 71% compared to baseline models. Furthermore, a cost-benefit analysis suggests a potential fleet savings of $240,000 per 100 engines by avoiding false negatives. This computationally efficient approach supports the Digital Engineering Transformation theme by providing a scalable blueprint for the virtual qualification of critical mechanical components.
Mohamed, Abbas
Transforming Aircraft MRO with Agentic AI and Context Engineering2026-26-07886/1/2026
Aircraft Maintenance, Repair, and Overhaul (MRO) operations are highly complex, involving coordination among multiple stakeholders including airlines, MRO providers, OEMs, and regulatory authorities. A significant challenge in this space is managing unplanned events such as Aircraft on Ground (AOG) conditions, where delays can lead to major financial losses to airlines and safety risks. Engineers must quickly diagnose the damage, evaluate compliance against regulatory limits, coordinate with OEMs, and make critical decisions—all while navigating a fragmented ecosystem of disconnected systems, diverse document types, and time-sensitive processes. This paper presents a real-world, intelligent MRO solution that addresses these challenges through the use of Agentic AI and context engineering. The system is designed to automate and augment key MRO workflows such as damage detection, repair pathway selection, compliance verification, and supplier coordination. At its core, the solution is powered by a set of autonomous agents—each responsible for specific tasks like interpreting repair manuals, evaluating damage severity, or communicating with OEM portals. A key innovation of this system is its use of context engineering, which enables agents to share a unified, real-time view of the aircraft condition, document references, decisions made, and deadlines involved. This shared memory—dynamically updated using modern data stores and retrieval systems—ensures that agents and human experts operate with full situational awareness. The solution facilitates measurable improvements in reducing aircraft downtime, speeding up OEM coordination, and ensuring real-time continuous regulatory compliance. Engineers can take faster, more informed decisions with confidence, while human-in-the-loop oversight was preserved for critical steps such as compliance sign-off and final approvals. Overall, this intelligent MRO system transforms static, document-heavy processes into a dynamic, context-aware workflow. It brings together agent collaboration, regulatory alignment, and real-time information flow to solve one of the most pressing operational problems in aviation today. By improving inspection-to-repair cycles, enhancing SLA adherence, and enabling traceable, data-driven decision-making, this work lays the foundation for the next generation of digital MRO ecosystems that are efficient, safe, and scalable.
Abburu, Sunitha, G.V.V., Ravi Kumar, Poovalingam, Sundaresan, Vaderahobli, Devaraja Holla
Retrofit Vibration Mitigation of Launch Vehicle Structures Using Thin Viscoelastic Coatings: Acoustic and Modal Study2026-26-07366/1/2026
Acoustic-induced vibrations pose a significant risk to launch vehicle hardware and payload reliability during critical phases such as lift-off and transonic phase. Reducing such vibrations is especially challenging when the hardware has already been fabricated, limiting the possibility of structural redesign. This study demonstrates a practical post-fabrication solution using a thin viscoelastic polymer coating applied externally to fully assembled hardware. Comprehensive evaluations were conducted using both acoustic testing and Experimental Modal Analysis (EMA) before and after coating application. During acoustic test, a substantial decrease in structure response from 150Hz to 2000Hz, with a reduction of approximately 50% in the grms values was observed for the coated structure demonstrating significant vibration mitigation over a wide frequency range. In contrast, EMA measurements using impact excitation revealed that the response transfer functions did not show a significant reduction within the band considered and modal properties remained largely unchanged upto 200 Hz, indicating that the coating did not significantly alter the structural properties. The apparent enigma calls for a detailed study. A brief overview on the results and the plausible reasons are detailed in the paper. Out of the probable causes, the observed vibration reduction can be primarily attributed to the operational damping and mass addition effects of the PC10 coating. These findings highlight an effective and practical approach for mitigating acoustic-induced vibrations in aerospace structures, with direct application to launch vehicle stages and other aerospace hardware where post-fabrication solutions are critically needed.
Avirah, Nohin K, Panda, Ajay Kumar, Shaikh, Altafhusen
INTELLIGENT POWER DISTRIBUTION will change the way vehicles are designed26AUTP06_056/1/2026
Electronic fuse (eFuse) technology can create electronic power distribution modules (ePDMs) for architectural flexibility, higher reliability, greater safety, and proactive maintenance. Automotive engineers who design vehicles and vehicle assemblies, especially for electric vehicles, strive to maximize efficiency in every subsystem. Electrification and intelligence are deployed across numerous vehicle subsystems, including drive trains, braking, and collision avoidance. Nevertheless, one area that has been overlooked, until now, is power distribution. Electronic fuse (eFuse) technology has emerged that can provide overcurrent protection similar to that of traditional fuses along with new programmable features. Integrating eFuse technology into an intelligent electronic power distribution module (ePDM) significantly impacts how vehicles are designed and serviced.
Drew, Matthew
European Researchers Develop Self-Healing Composite Material for Spacecraft26AERP06_116/1/2026
Researchers from CompPair and the European Space Agency have developed a new composite material for spacecraft with an embedded healing agent. European Space Agency, Paris, France Healable spacecraft structures could soon be possible thanks to cutting-edge composite technology. Swiss companies CompPair and CSEM, and Belgian company Com&Sens have partnered with the European Space Agency (ESA) to modify their self-healing carbon fiber product for use in space transportation. Project Cassandra - an abbreviation for Composite Autonomous Sensing and Repair - includes sensors and a heating element within a composite carbon-fiber material, allowing spacecraft to autonomously repair initial stages of damage.
Standard Contaminant for Testing Aerospace CleanersAMS7201 (Current)5/27/2026
This specification establishes requirements for a standard contaminant that can be used to represent typical soils encountered in aerospace cleaning. This standard contaminant consists of materials that are common contaminants found in aircraft maintenance depots and manufacturing facilities.
AMS G9 Aerospace Sealing Committee
Research on Fault Diagnosis Agent of Monorail Crane Based on Knowledge Graph and Lightweight Large Model2026-99-07415/15/2026
The monorail crane is important in mining operations, and its operation affects both safety and efficiency. Currently, fault diagnosis for monorail cranes has several challenges, such as heterogeneous mixing of multimodal data, poor use of knowledge, low real-time requirements, and high deployment costs for large-scale models. To solve these problems, we present an agent framework using a multimodal knowledge graph and a lightweight large model. In particular, we construct a fault knowledge graph for monorail cranes, organizing professional knowledge about components, failure modes, symptoms, and maintenance. By employing retrieval-augmented generation (RAG) technology, the knowledge graph is merged with the Qwen lightweight large model (low-rank adaptation) for fine-tuning to develop a diagnostic agent with task planning, tool invocation and memory. The experimental results show that the agent framework reduces “machine hallucination” and outperforms conventional diagnostic accuracy, response speed and resource efficiency, thus offering a safe and efficient solution for intelligent operation and maintenance of mining equipment.
Zhang, Yixuan, Xue, Shun, Bi, Xiang, Wei, Xing, Kang, Ranyu, Jue, Jie, Cheng, Liruiran
Fire Prevention on Forestry MachineryJ1212_202605 (Current)5/7/2026
This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.
MTC4, Forestry and Logging Equipment
Smart Duplex A Digital Inspection Strategy for Duplex BearingsF-0082-2026-01065/5/2026
Rolling-element bearings in rotorcraft dynamic systems are critical components susceptible to rolling contact fatigue (RCF), a dominant degradation mechanism manifesting through subsurface-initiated spalling, surface micropitting, and fatigue fractures. Robust inspection strategies compliant with EASA and FAA requirements are therefore essential. Traditional methods are often invasive, requiring disassembly, and are susceptible to human-factor errors. Smart Duplex introduces a design-for-monitoring architecture integrating in-situ videoscopic and coherence scanning interferometry (CSI) for high-resolution 3D surface mapping, including under partial grease coverage. This paper details a repeatability and reproducibility (R&R) framework ensuring metric consistency; a maintainability assessment projecting significant man-hour reductions and high availability; certification rationale emphasizing airworthiness improvements via enhanced detectability, workload reduction, and digitized inspection records; and an airworthiness mapping supporting threat assessments, Airworthiness Limitations Section (ALS) entries, and usage-based maintenance credits. By embedding sensing capability and digitizing inspection records, Smart Duplex minimizes downtime, mitigates human-factor errors, and facilitates predictive maintenance, optimizing cost, enhancing performance, and ultimately improving safety.
Delli Paoli, Michele, Anaclerio, Mario Alberto
The Impact of Hybrid Electric Propulsion Technologies on Medium Lift Rotorcraft PerformanceF-0082-2026-02185/5/2026
This paper explores the potential of three different hybridization solutions for a medium-sized rotorcraft: an electric tail rotor, an "eco-mode", and a "boost-mode". The solutions were evaluated as a retrofit to a generalized medium lift rotorcraft and the impact on performance across five mission types, representative of the typical use cases for a military rotorcraft, was assessed. Two separate rotorcraft performance modelling tools were used to carry out the assessment, allowing for the results to be cross-examined. The models predicted performance gains for the eco-mode configuration when utilizing the single engine cruise capability for low-speed applications. Likewise, the models predicted improved performance for the boost-mode configuration when operating at hot and high (6,000 ft, 95°F) conditions due to the increased power provided by the battery system. However, all three solutions suffered from increased platform empty weight which negatively impacted performance at certain flight states.
Hopkins-Bain, Aaron, Vegh, Michael, Goldberg, Chana
The Advanced Tiltrotor Aircraft by Leonardo: Design Drivers and FeaturesF-0082-2026-02425/5/2026
This paper describes the characteristics of the Leonardo Advanced Tiltrotor Aircraft (ATA) concept, focusing on the relationship between goals, targeted improvements and enabling design features. The paper shows the design drivers such as performance, operational capabilities, and maneuverability and it describes how the attributes of the concept originated, showing trade-off and compromises approached during the genesis of the concept. The design drivers are translated into areas of interests, including download, drag, aerodynamic efficiency, rolling and yawing inertia, detectability, maintainability and engine retrofit ability. Finally, these areas are linked to the physical features of the concept, showing how they have been selected and combined to achieve the best overall benefit at platform level.
Bianco Mengotti, Riccardo, Viganò, Luca, Cassinelli, Carlo, Sampugnaro, Luca, Pecoraro, Matteo, Lilliu, Cristian, Medici, Luca
A Knowledge Graph - RAG based Troubleshooting Guide for Helicopter SystemsF-0082-2026-03285/5/2026
Helicopter maintenance troubleshooting faces significant challenges due to fragmented documentation, outdated procedural manuals, and reliance on human expertise, all of which threaten flight safety and operational efficiency. While Knowledge Graphs (KGs) effectively model hierarchical system relationships and causal dependencies, they struggle with dynamic unstructured data. Conversely, Retrieval-Augmented Generation (RAG) systems access technical manuals but risk hallucinating unsafe procedures without structural grounding. This paper introduces KG-RAG, a novel hybrid troubleshooting framework specifically engineered for helicopter systems, addressing a critical gap as existing work focuses predominantly on fixed-wing aircraft. The framework merges knowledge graphs modeling fault causality and maintenance history with multi-dimensional retrieval combining graph-based reasoning, vector embeddings, and keyword-based search. This integration enables contextual interpretation of ambiguous fault descriptions, generation of precise diagnostics aligned with operational constraints, and dynamic adaptation to new fault patterns without retraining. By transforming fragmented maintenance knowledge into a verifiable, context-aware troubleshooting guide, the framework directly addresses aviation's persistent obstacles: data incompleteness, knowledge erosion, and slow safety-critical decisions. This work positions KG-RAG not merely as a tool but as a foundational shift toward cognitively augmented maintenance, elevating human expertise through AI that reasons like an engineer and contextualizes like a veteran technician for enhanced safety-critical decision-making in complex helicopter operations.
Majeti, Rohin, Wende, Gerko, Raddatz, Florian, Raju, Bhavana
Developments in Debris Monitoring of Hybrid BearingsF-0082-2026-02645/5/2026
Hybrid bearings, which pair traditional bearing-steel raceways with ceramic rolling elements, can offer improved performance over full-metal bearings, particularly in aerospace applications. Because rolling-element bearings are critical components, effective condition monitoring is essential to prevent in-flight failures and support proactive maintenance strategies. Wear-debris monitoring is widely used in these applications to detect and diagnose bearing fault modes. To compare degradation behavior and monitoring signatures, bearing life tests were conducted on hybrid and full-metal bearings under matched Hertzian stress conditions. The results showed that differences in degradation curves between the two bearing types were small relative to the overall variability in bearing life. Additionally, hybrid bearings that develop rolling-element pitting were observed to progress toward raceway spall formation. This paper was presented at ERF Forum 51 but has been updated with new findings addressing questions over the effect of impact energy on the degradation rate between hybrid and full-metal bearings.
Mahmoud, Hassan, Oszmian, Adam
Can Multi-Fingered Robots Transform Shipboard Operations and Autonomous Maintenance?26AERP05_125/1/2026
USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics. University of Southern California, Los Angeles, CA In dynamic, unstructured environments like ship decks and even home kitchens, robots today still struggle to perform precision tasks such as tightening bolts or handling wires. This makes critical ship maintenance tasks difficult. USC researcher, Erdem Bıyık, aims to advance robots' finger manipulation and integrate human feedback to enable real-time learning for robots in an upcoming three-year, $750,000 project funded by the Office of Naval Research (ONR).
Can Multi-Fingered Robots Transform Shipboard Operations and Autonomous Maintenance?TBMG-551285/1/2026
In dynamic, unstructured environments like ship decks and even home kitchens, robots today still struggle to perform precision tasks such as tightening bolts or handling wires. This makes critical ship maintenance tasks difficult.
Enabling Sustainable E-Mobility: An Edge–Cloud Collaborative Framework for Battery Lifecycle Health Management in Electric Vehicles2026-01-04604/7/2026
The rapid adoption of electric vehicles (EVs) is a cornerstone of the transition to sustainable transportation. However, uncertainty regarding battery degradation remains a significant obstacle, hindering vehicle energy efficiency, operational safety, and the recovery of end-of-life value. Accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are therefore critical for sustainable vehicle lifecycle management. This study proposes an edge–cloud collaborative intelligent framework for in-vehicle deployment that leverages a Transformer-based architecture to jointly model SOH and RUL. The cloud-side model retains the full configuration to capture long-term degradation trajectories for high-accuracy RUL prediction. A lightweight edge-side model, engineered via pruning and knowledge distillation, delivers millisecond-level inference for real-time SOH estimation onboard the vehicle. To ensure efficiency, only four core health indicators are extracted for end-to-end prediction. Experimental validation across 77 battery cells demonstrates that the framework achieves SOH estimation with a root mean square error (RMSE) of 1.41% and RUL prediction with an RMSE of 2.59% (78 cycles). Furthermore, a periodic cloud-side update and over-the-air deployment mechanism ensure long-term adaptability and cross-platform scalability without full local retraining. This intelligent prognostic framework directly enhances EV reliability and sustainability by providing health-informed decision support for optimal vehicle operation, maintenance scheduling, and the reuse of second-life batteries. Consequently, it serves as a vital tool for advancing resource optimization and circular economy principles within the E-mobility ecosystem.
Gao, Weimin, Lv, Zhilong, Ou, Shiqi(Shawn)
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