Browse Topic: Maintenance and Aftermarket

Items (10,052)
Reducing vehicle numbers and enhancing public transport can significantly cut emissions in the transport sector. Hydrogen-fueled and battery electric buses show the potential for decarbonization, but a Life Cycle Assessment (LCA) is essential to evaluate carbon emissions from energy production and manufacturing. In addition, even associated pollutant emissions, together with components’ wear, must be taken into account to evaluate the overall environmental impact. Total Cost of Ownership (TCO) analysis complements this by assessing long-term expenses, enabling stakeholders to balance environmental and economic considerations. This study examines carbon and pollutant emissions alongside TCO for innovative urban mobility powertrains (compared with diesel), focusing on Italian current and future hydrogen and electricity mix scenarios, even considering 100 % green hydrogen (100GH), the goal being to support sustainable decision-making and to promote eco-friendly transport solutions. The
Brancaleoni, Pier PaoloDamiani Ferretti, Andrea NicolòCorti, EnricoRavaglioli, VittorioMoro, Davide
This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the electric Lubrication Oil Pump (eLOP), a crucial component within a vehicle's powertrain system. The proposed eLOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the Digital Twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's lifecycle. The
Khan, JalalD'Alessandro, StefanoTramaglia, FedericoFauda, Alessandro
The rapid expansion of the electric vehicle (EV) market has intensified the need for robust charging infrastructure. The quality of their experiences at public charging stations has become crucial to sustaining this transition. Key factors such as station accessibility, charging speed, and pricing transparency significantly affect user satisfaction. In Guangzhou, a China's major metropolitan city with an EV penetration rate exceeding 50%, this city offers an ideal context to assess the alignment between expanding EV infrastructure and user needs. This study examines user satisfaction with EV public charging stations in Guangzhou using a dataset of over 2,000 user comments from Amap. The comments are first processed using the Jieba segmentation library, with sentiment analysis conducted through the Natural Language Processing tool SnowNLP, categorizing comments by sentiment (419 positive, 156 neutral, and 1,690 negative). Term Frequency-Inverse Document Frequency(TF-IDF) is then applied
Guo, HaifengOu, Shiqi (Shawn)Jing, HaoQi, HaoShi, Lanxin
SAE J1939 is a CAN-based standard used for connecting various ECUs together within a vehicle. There are also some related protocols sharing many of the features of SAE J1939 across other industries including ISO11783, RVC and NMEA 2000. The standard has enabled the easy integration of electronic devices into a vehicle. However, as with all CAN-based protocols, several vulnerabilities to cyberattacks have been identified and are discussed in this paper. Many are at the CAN-level, whilst others are in common with those protocols from the SAE J1939 family of protocols. This paper reviews the known vulnerabilities that have been identified with the SAE J1939 protocol at CAN and J1939-levels, along with proposed mitigation strategies that can be implemented in software. At the CAN-level, the weaknesses include ways to spoof the network by exploiting parts of the protocol. Denial of Service is also possible at the CAN-level. At the SAE J1939-level, weaknesses include Denial of Service type
Quigley, Christopher
The problem of monitoring the parametric failures of a traction electric drive unit consisting of an inverter, a traction machine and a gearbox when interacting with a battery management system has been solved. The strategy for solving the problem is considered for an electric drive with three-phase synchronous and induction machines. The drive power elements perform electromechanical energy conversion with additional losses. The losses are caused by deviations of the element parameters from the nominal values during operation. Monitoring gradual failures by additional losses is adopted as a key concept of on-board diagnostics. Deviation monitoring places increased demands on the information support and accuracy of mathematical models of power elements. We take into account that the first harmonics of currents and voltages of a three-phase circuit are the dominant energy source, higher harmonics of PWM appear as harmonic losses, and mechanical losses in the rotor and gearbox can be
Smolin, VictorGladyshev, SergeyTopolskaya, Irina
The trend for the future mobility concepts in the automotive industry is clearly moving towards autonomous driving and IoT applications in general. Today, the first vehicle manufacturers offer semi-autonomous driving up to SAE level 4. The technical capabilities and the legal requirements are under development. The introduction of data- and computation-intensive functions is changing vehicle architectures towards zonal architectures based on high-performance computers (HPC). Availability of data-connection to the backend and the above explained topics have a major impact on how to test and update such ‘software-defined’ vehicles and entire fleets. Vehicle diagnostics will become a key element for onboard test and update operations running on HPCs, as well as for providing vehicle data to the offboard backend infrastructure via Wi-Fi and 5G at the right time. The standard for Service Oriented Vehicle Diagnostics (SOVD) supports this development. It describes a programming interface for
Mayer, JulianBschor, StefanFieth, Oliver
This paper presents Matchit, a novel method for expediting issue investigation and generating actionable insights from textual data. Recognizing the challenges of extracting relevant information from large, unstructured datasets, we propose a domain-adaptable approach by integrating expert domain knowledge to guide Large Language models (LLMs) to automatically identify and categorize key information into distinct topics. This process offers two key functionalities: fully automatic topic extraction based solely on input data, providing a concise overview of the problem and potential solutions, and user-guided extraction, where domain experts can specify the type of information or pre-defined categories to target specific insights. This flexibility allows for both broad exploration and focused analysis of the data. Matchit's efficacy is demonstrated through its application in the automotive industry, where it successfully extracts repair diagnostics from diverse textual sources like
Wang, LijunArora, Karunesh
Growth in the EV market is resulting in an unprecedented increase of electrical load from EV charging at the household level. This has led to concern about electric utilities’ ability to upgrade electrical distribution infrastructure at an affordable cost and sufficient speed to keep up with EV sales. Adoption of EVs in the California market has outpaced the national average and offers early insight for other regions of the United States. The Sacramento Municipal Utility District (SMUD) partnered with two grid-edge Distributed Energy Resource Management System (DERMS) providers, the OVGIP (recently incorporated as ChargeScape, a joint venture of Ford, BMW, Honda, and Nissan) and Optiwatt, to deliver a vehicle telematics-based active managed charging pilot. The pilot program, launched in Summer 2022 enrolled approximately 1,200 EVs over two years including Tesla, Ford, BMW, and GM vehicles. The goal of this pilot program was to evaluate the business case for managed charging to mitigate
Liddell, ChelseaSchaefer, WalterDreffs, KoraMoul, JacobKay, CarolAswani, Deepak
This paper describes a novel invention which is an Intrusion Detection System based on fingerprints of the CAN bus analogue features. Clusters of CAN message analogue signatures can be associated with each ECU on the network. During a learning mode of operation, fingerprints can be learnt with the prior knowledge of which CAN identifier should be transmitted by each ECU. During normal operation, if the fingerprint of analogue features of a particular CAN identifier does not match the one that was learnt then there is a strong possibility that this particular CAN identifier’s message is symptomatic of a problem. It could be that the message has been sent by either an intruder ECU or an existing ECU has been hacked to send the message. In this case an intruder can be defined as a device that has been added to the CAN bus OR a device that has been hacked/manipulated to send CAN messages that it was not designed to (i.e. could be originally transmitted by another device). It could also be
Quigley, ChristopherCharles, David
When the aircraft towbarless towing vehicle (TLTV) drives on road surfaces that are wet, icy, oily, or covered with debris, as well as under conditions such as overloaded towing, uneven distribution of aircraft weight, sudden acceleration and sharp turns, brake system failures, or severe tire wear, it may slip due to a mismatch between traction force and ground adhesion. As a key piece of ground support equipment at airports, the anti-slip performance of TLTV is crucial for ensuring safe and efficient ground movement of aircraft. With continuous advancements in control technology, extensive research has been conducted on anti-slip control strategies for TLTV. This paper reviews relevant literature in the field of anti-slip control for TLTV in recent years, focusing on the current status of anti-slip control technology development, control strategies, and the application of co-simulation technology in anti-slip control. Based on co-simulation using Matlab and Adams software, this paper
Yao, YananXu, YitongZhu, Hengjia
In sheet metal simulation, computation time is significantly influenced by the number of elements used to discretize the sheet blank, which covers the shape of forming tool geometry. Based on particle kinematics, motion of material point is modeled, and the concept of zero circumferential motion material line (ZML) is proposed. The slope ratio of material line (SRML) is proposed to quantify the circumferential deviation for determining the ZML. Based on the SRML, a method is developed to segment sheet blank and apply constraints. The method is demonstrated through forming simulation on a Hishida geometry. The proposed method, with its minimal to no circumferential motion along ZMLs, exhibits high level of accuracy retention while simultaneously impressively reducing computation time (up to 77%). This combination of efficiency and precision makes it a compelling approach for reducing simulation cost.
Sheng, ZiQiangAsimba, BrianCabral, Kleber
This document establishes the minimum requirements for an environmental test chamber and test procedures to carry out anti-icing performance tests according to the current materials specification for aircraft deicing/anti-icing fluids. The primary purpose for such a test method is to determine the anti-icing performance under controlled laboratory conditions of AMS1424 Type I and AMS1428 Type II, III, and IV fluids.
G-12ADF Aircraft Deicing Fluids
There is a lack of data to support the efficacy of traditional mileage and time-based criteria for oil changes in vehicles. In this study, used-oil samples from 63 vehicles were collected and analyzed. Besides dynamic viscosity, viscosity index and activation energy were evaluated as measures of thermal stability of viscosity. The results revealed that mileage and time of use are not significantly correlated with (p > 0.05) and are thus poor indicators of oil viscosity and viscosity thermal stability measures. These findings highlight the limitations of current criteria and underscore the need for new sensing and evaluation methods to reduce costs, waste, and environmental impact while ensuring vehicle performance.
Salvi, NileshTan, Jinglu
Real-time traffic event information is essential for various applications, including travel service improvement, vehicle map updating, and road management decision optimization. With the rapid advancement of Internet, text published from network platforms has become a crucial data source for urban road traffic events due to its strong real-time performance and wide space-time coverage and low acquisition cost. Due to the complexity of massive, multi-source web text and the diversity of spatial scenes in traffic events, current methods are insufficient for accurately and comprehensively extracting and geographizing traffic events in a multi-dimensional, fine-grained manner, resulting in this information cannot be fully and efficiently utilized. Therefore, in this study, we proposed a “data preparation - event extraction - event geographization” framework focused on traffic events, integrating geospatial information to achieve efficient text extraction and spatial representation. First
Hu, ChenyuWu, HangbinWei, ChaoxuChen, QianqianYue, HanHuang, WeiLiu, ChunFu, TingWang, Junhua
Airline passenger satisfaction is important for airline operation service quality management. When airline companies carry out advertisement campaigns or plan a marketing strategy, the resources and budgets are not unlimited. Thus, an airline can only focus on improving a few factors that drive passenger satisfaction. To understand the key satisfies for the young and the old adults, respectively, we leverage five airline passenger satisfaction methods to identify the key factors that explain the airline service satisfaction of different passengers. In particular, we investigate and compare the ridge and the Lasso regularization in terms of the resulting model’s sparsity and computational efficiency. The top three important factors that influence the old’s satisfaction are departure and arrival time convenience, legroom service, and baggage handling. Our findings indicate that the young people place a higher value on entertainment, while the old adults place a higher value on usefulness
Ma, JieHu, SongWang, Haipeng
This SAE Aerospace Recommended Practice (ARP) provides methods and guidelines for isolating dissimilar repair patch materials from carbon fiber reinforced plastic (herein also referred to as carbon composite) structure during a repair operation.
AMS G9 Aerospace Sealing Committee
The generation of data plays a vital role in machine learning (ML) techniques by providing the foundation for training and improvement of forecast models. As one application area for these models, in-vehicle systems, like vehicle diagnostics, have the potential to enhance the reliability and durability of vehicles by utilizing ML models in the testing phases. However, acquiring a high volume of quality onboard diagnostics (OBD) data is time-consuming and poses challenges like the risk of exposing sensitive information. To address this issue, synthetic data generation offers a promising alternative that is already in use in other domains. Thereby, synthetic data allows the exploitation of knowledge found in original data, ensuring the privacy of sensitive data, with less time costs of data acquisition. The application of such synthetically generated data could be found in predictive maintenance, predictive diagnostics, anomaly detection, and others. For this purpose, the research
Vučinić, VeljkoHantschel, FrankKotschenreuther, Thomas
This SAE Standard covers fittings, couplers, and hoses intended for connecting service hoses from mobile air-conditioning systems to service equipment such as charging, recovery, and recycling equipment (see Figure 1). This specification covers service hose fittings and couplers for MAC service equipment service hoses, per SAE J2843 and SAE J2851, from mobile air-conditioning systems to service equipment such as manifold gauges, vacuum pumps, and air-conditioning charging, recovery, and recycling equipment.
Interior Climate Control Service Committee
The purpose of this ARP is to provide the sample selection criteria and endurance time test procedures for SAE Type I aircraft deicing/anti-icing fluids required for the generation of endurance time data of acceptable quality for review by the SAE G-12 Holdover Time Committee. A significant body of previous research and testing has indicated that all Type I fluids formulated with conventional glycols, as defined in 3.1.1 of AMS1424, perform in a similar manner from an endurance time perspective. This applies to Type I deicing/anti-icing fluids formulated with propylene glycol, ethylene glycol, and diethylene glycol only. As a result, Type I deicing/anti-icing fluids containing these glycol bases no longer require testing for endurance times. The methods described in this ARP shall be employed, however, if endurance time testing of a conventional glycol-based Type I deicing/anti-icing fluid is desired or requested by a fluid manufacturer, operator, or other organization. Fluids
G-12HOT Holdover Time Committee
Monitoring the safety and structural condition of tunnels is crucial for maintaining critical infrastructure. Traditional inspection methods are inefficient, labor-intensive, and pose safety risks. With its non-contact, high-precision, and high-efficiency features, mobile laser scanning technology has emerged as a vital tool for tunnel monitoring. This paper presents a mobile laser scanning system for tunnel measurement and examines techniques for calculating geometric parameters and processing high-resolution imaging data. Empirical evidence demonstrates that mobile laser scanning offers a reliable solution for evaluating and maintaining tunnel safety.
Lianbi, YaoZhang, KaikunDuan, WeiSun, Haili
Tunnel linings are an important safeguard for the integrity and stability of tunnels. However, cracks in the tunnel lining may have extremely unfavourable consequences. With the acceleration of urbanisation and the increasing construction of tunnels, the problem of cracks in the concrete lining is becoming more and more prominent. These cracks not only seriously affect the stability of the structure, but also pose a serious threat to the safety of tunnel operation. If left unchecked, the cracks may expand further and cause various safety hazards, such as water leakage and falling blocks. This in turn will undermine the normal function of the tunnel and endanger the lives of tunnel users. It has been proved that the traditional manual method of detecting cracks in tunnels has problems such as low accuracy and low efficiency. In order to solve this problem, it is very necessary for this study to pioneer an intelligent method for identifying tunnel lining cracks using the YOLOv11
Zhang, YalinNiu, PeiGuo, FengYan, WeiLiu, JianKou, Lei
High-speed railway (HSR) hubs play a pivotal role in the integrated transport system, efficiently connecting various modes of transport and facilitating transport integration. Characterized by their large scale, complex functional spatial layouts, and diverse interchange types, these hubs see a growing proportion of passenger traffic annually. Thus, studying the interchange impedance in high-speed railway passenger transport hubs is crucial for enhancing interchange efficiency and service quality. However, current research lacks a quantitatively comparable impedance model for high-speed railway hubs, particularly under peak passenger flow conditions. This paper addresses this gap by examining the internal node impedance at Nanjing South Railway Station, focusing on the entry gate turnstile node and security check node. It begins by analyzing passenger passing behavior at these nodes and then constructs a integrated queuing model for inbound gates and security checks, considering the
Zhang, ZhenyuWang, Jian
The recent public release of the PPP-B2b service, along with advancements in multi-frequency and multi-GNSS systems, has opened up significant new opportunities for the development of Precise Point Positioning (PPP) technology. Utilizing the precise orbit and clock corrections provided by PPP-B2b and the increasing availability of multi-frequency signals, this paper introduces a novel tri-frequency, dual ionosphere-free PPP model based on PPP-B2b services. The model is designed with twelve unique tri-frequency combinations, tailored to various frequency choices, combination methodologies, and single/dual GNSS systems. Results from static positioning experiments indicate that the BDS-only tri-frequency dual ionosphere-free model offers substantial improvements over traditional models. Specifically, it achieves approximately a 25% increase in vertical accuracy and reduces convergence time by around 30% when compared to the BDS-only tri-frequency undifferenced uncombined model. This
Xu, DaweiGao, ChengfaXu, ZhenhaoZhan, KaidiGuo, Songlin
Compared to manual driving, autonomous driving is more prone to the rapid development and deterioration of pavement distress due to the concentration of driving paths. Therefore, a reasonable and efficient maintenance strategy is required. To address the challenges posed by the numerous constraints and objectives in the maintenance strategy generation process, this paper proposes a multi-objective optimization-based method for generating pavement maintenance strategies. The approach leverages advanced pavement distress detection technologies to establish an initial maintenance program, incorporating a range of constraints and maintenance objectives, such as cost-efficiency, performance longevity, and environmental impact. The method applies a genetic algorithm (GA) to iteratively refine and optimize the maintenance strategy, ensuring that the solutions align with both immediate and long-term performance goals for autonomous vehicle operations. A case study utilizing real-world road
Yang, LiwenyunLi, WeiChen, Leilei
In recent years, the issue of highway maintenance has become increasingly prominent. How to precisely detect and classify fine cracks and various types of pavement defects on highways through technical means is an essential foundation for achieving intelligent road maintenance. This paper first constructs the DenseNet201-PDC and MobileNetV2-PDC sub-classification networks that incorporate the three-channel attention judgment mechanism MCA. Secondly, based on the principle of parallel connection, a brand-new dual-branch fusion convolutional neural network DBF-PDC capable of classifying pavement defects in highway scenarios is proposed. Finally, this paper builds the Pavement Distress Datasets of Southeast University and conducts relevant ablation experiments. The experimental results demonstrate that both the attention mechanism module and the feature fusion strategy can significantly enhance the network's ability to classify pavement defects in highway scenarios. The average
Zhang, ZiyiZhao, ChihangShao, YongjunWang, Junjun
The increasing traveling demands are putting higher pressure on urban networks, where the efficient driving modes highly depend on various non-intrusive ITS equipment for interaction, which asks for higher maintenance scheduling plans minimizing network loss. Current studies have researched methodologies with the aspects of deterministic methods and metaheuristic algorithms under different scenarios, but lack the simulation considering maintenance work type, urban traffic characteristics as well as the ITS equipment. This study aims to optimize the maintenance scheduling plan of urban ITS systems by using the genetic algorithm (GA) and Dijkstra algorithm, as well as other judgmental algorithms to minimize traffic delays caused by maintenance activities, and presents a novel method to assess economic losses. A mixed integer programming model is established simulating the real urban network while considering multiple constraints, including the route selection principle, network updating
Pei, HaoyiJi, YanjieChen, Ziang
This study investigates the forced vibration characteristics of a functionally graded material (FGM) beam possessing a square cross-section and featuring a V-shaped crack. The FGM beam exhibits a gradual transition in mechanical composition from a ceramic to a metallic surface. Employing finite element analysis software, a comprehensive numerical analysis is conducted to evaluate the frequencies and mode shapes of the cracked FGM beam under simply supported boundary conditions. The study meticulously explores the effects of various crack parameters, including crack opening width, depth, and location. The findings highlight the significant influence of the crack opening width on the frequencies, indicating that wider cracks result in decreased frequencies across all mode shapes. Conversely, the impact of crack depth and location on the dynamic behavior of the cracked FGM beam within the studied ranges appears relatively minor. These insights offer valuable perspectives into the
D, ManishC V, PrasshanthN, SuhasBhaskara Rao, Lokavarapu
This document contains information and guidance necessary for the development of a representative, repeatable validation program that may be utilized to assess the capability of SHM systems. The nature of SHM data differs from that seen in traditional nondestructive evaluation (NDE) applications in that the position of SHM sensors is fixed and SHM data can be available much more frequently (if not continuously) over time. This document presents methodologies that can be used to arrive at SHM capability while considering the unique nature of SHM deployment. Each SHM system must be considered independently to determine the applicability and limitations of the guidance contained here for each SHM system being assessed.
Aerospace Industry Steering Committee on Structural Health
State of health (SOH) estimation is essential to ensure safety and reliability in the operation of Proton Exchange Membrane Fuel Cells (PEMFCs). The aging of fuel cells results from the deterioration of multiple internal components, and the aging degree of some key components even directly determines the end of cell life. Due to the complexity of the internal reactions in fuel cell, many internal parameters cannot be measured or recorded during aging tests. In addition, external characteristics do not reflect the internal changes in the cell. Therefore, establishing a multi-scale metric based on fuel cell components is very important for fuel cell life research. During the aging process of a fuel cell, the contributions of different components to the overall aging vary significantly. Additionally, the allocation of indicator parameters presents a challenge in multi-scale modeling. To address these issues, this paper proposes a method to construct multi-scale indicators for fuel cells
Lin, YipengMin, HaitaoSheng, XiaZhang, ZhaopuSun, Weiyi
This SAE Standard was prepared by Technical Committee 1, Engine Lubrication, of SAE Fuels and Lubricants Council. The intent is to improve communications among engine manufacturers, engine users, and lubricant marketers in describing lubricant performance characteristics. The key objective is to ensure that a correct lubricant is used in each two-stroke-cycle engine.
Fuels and Lubricants TC 1 Engine Lubrication
Instructions on this chart are intended to be used as a ready reference by personnel responsible for servicing off-road self-propelled work machines described in SAE J1116, categories 1, 2, 3, and 4. Detailed maintenance and service guidelines are reserved for maintenance, operator, and lubrication manuals as defined in SAE J920.
Machine Technical Steering Committee
The AS6224 specification covers environment resistant, permanent insulation repair sleeves for repairing different types of insulation damages of wire or cable jackets in installed applications. The repair sleeve is intended to repair damaged primary wire or cable jacket covers where the shielding and wire conductors are not damaged.
AE-8C2 Terminating Devices and Tooling Committee
This manual contains information regarding aircraft deicing/anti-icing surfaces and areas.
G-12M Methods Committee
Organizations need to maintain their processes at high levels of efficiency to be competitive, asset management and industrial maintenance are extremely important to obtain positive results in optimizing operating costs, saving energy resources, reduction of environmental impacts among other characteristics that are considered differential for organizations. In this scenario, methods are increasingly being sought to assist managers in decision-making processes that contain several alternatives and selection criteria involved. The AHP and TOPSIS methods have been widely associated with prioritization studies, cost evaluation, resource selection, suppliers, among others. Thus, the selection of equipment and industrial elements can be evaluated by means of multicriteria decision methods where the criteria considered important by specialists in the area are inserted into the model. The objective of this article was to present a selection process for spur gears based on stress analysis and
de Oliveira, Geraldo Cesar Rosariode Oliveira, Vania Aparecida RosarioSilva, Carlos Alexis AlvaradoGuidi, Erick SiqueiraSalomon, Valério Antonio PamplonaRosado, Victor Orlando Gamarrade Azevedo Silva, Fernando
Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for
Cury, RudonielGioria, GustavoChandrasekaran, Balaji
Engines subject to dust, industrial pollution, saltwater contamination or other chemically laden atmosphere (including pesticides and herbicides) lose performance due to deposits of contaminants on surfaces in the aidgas flow path. Engine wash and engine rinse procedures are utilized to restore turbine engine performance. These procedures are generated by the engine manufacturer and are included in the Engine Maintenance/Service Manuals. For most turbine engines these procedures are similar in concept and practice; however, application details, choice of solvents and many other service features can vary from engine manufacturer to engine manufacturer and may even vary within the range of engine models produced by any manufacturer. The intent of this SAE Aerospace Information Report (AIR) is to outline the general nature, considerations, and background of engine wash and engine rinse and is directed towards the needs of the entry level engineer, service engineer, and those involved in
S-12 Powered Lift Propulsion Committee
This SAE Aerospace Information Report (AIR) provides guidelines for the design of portable Controlled Contamination Areas (CCAs) that can provide localized environmental control when processing a repair at the airplane or in a hangar environment. The use of a portable CCA may result in a better quality repair. The use of a portable CCA may assist in achieving the environmental requirements for bonded repairs specified in an approved repair procedure. This provides an option to accomplish a repair on nonremovable structure or difficult to remove components.
AMS CACRC Commercial Aircraft Composite Repair Committee
Cameras are crucial sensors in intelligent driving systems. Due to the optical windows of these cameras generally being exposed, they are highly susceptible to contaminant from external dust, mud, and other contaminants. These contaminants can degrade the vehicle’s perception capabilities, posing safety risks. Therefore, research on the identification and automatic cleaning of optical window surface contamination for automotive cameras is essential. This paper constructs a dataset of contaminated images of automotive cameras using a method based on shooting and image fusion. By introducing the SE attention mechanism and replacing the YOLOv8 backbone network with FasterNet, this paper proposed the SEFaster-YOLOv8 model. Experimental results show that the SEFaster-YOLOv8 model reduces the parameter count by 37.6% compared to the original YOLOv8 model. The mAP@0.5 and mAP@0.5:0.95 reach 95.7% and 66.9%, respectively, representing improvements of 1.8% and 1.1% over the original YOLOv8
Ran, LujiaHu, ZongjieLu, XiangxiangWu, Zhijun
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