Browse Topic: Failure analysis

Items (2,605)
Vehicles with SAE J3016TM Level 3 systems are exposed to road infrastructure, Vulnerable Road Users (VRUs), traffic and other actors on roadways. Hence safe deployment of Level 3 systems is of paramount importance. One aspect of safe deployment of SAE Level 3 systems is the application of functional safety (ISO 26262) to their design, development, integration, and testing. This ensures freedom from unreasonable risk, in the event of a system failure and sufficient provisions to maintain Dynamic Driving Task (DDT) and to initiate Minimum Risk Maneuver (MRM), in the presence of random hardware and systematic failures. This paper explores leveraging ISO 26262 standard to develop architectural requirements for enabling SAE Level 3 systems to maintain DDT and MRM during fault conditions and outlines the importance of fail-operability for Level 3 systems, from a functional safety perspective. At a high-level, UN Regulation No. 157 – Automated Lane Keeping Systems (ALKS) is used as a baseline
Mudunuri, Venkateswara RajuJayakumar, Namitha
Trajectory tracking control is a key component of vehicle autonomous driving technology. Compared with traditional vehicles, Distributed Driven Electric Vehicle (DDEV) is an ideal vehicle for trajectory tracking control because of its high space utilization, redundant control freedom and fast system response. However, the chassis execution system of DDEV has a relatively large number of sensors, which significantly increases its probability of failure. In this paper, we propose a trajectory tracking fault-tolerant control method for DDEV considering steering actuator faults. Firstly, we establish the dynamic model of the steering actuator and the trajectory tracking model of DDEV. The model is linearized and discretized by using Taylor series expansion and forward Euler method. Next, considering multi-objective constraints such as motion comfort, actuator saturation and road adhesion boundary, the trajectory tracking control strategy of DDEV is designed by using model predictive
Wang, DepingLi, LunTeng, YuhanZhu, BingChen, Zhicheng
Several challenges remain in deploying Machine Learning (ML) into safety critical applications. We introduce a safe machine learning approach tailored for safety-critical industries including automotive, autonomous vehicles, defense and security, healthcare, pharmaceuticals, manufacturing and industrial robotics, warehouse distribution, and aerospace. Aiming to fill a perceived gap within Artificial Intelligence and ML standards, the described approach integrates ML best practices with the proven Process Failure Mode & Effects Analysis (PFMEA) approach to create a robust ML pipeline. The solution views ML development holistically as a value-add, feedback process rather than the resulting model itself. By applying PFMEA, the approach systematically identifies, prioritizes, and mitigates risks throughout the ML development pipeline. The paper outlines each step of a typical pipeline, highlighting potential failure points and tailoring known best practices to minimize identified risks. As
Schmitt, PaulSeifert, Heinz BodoBijelic, MarioPennar, KrzysztofLopez, JerryHeide, Felix
Opening a tailgate can cause rain that has settled on its surfaces to run off onto the customer or into the rear loadspace, causing annoyance. Relatively small adjustments to tailgate seals and encapsulation can effectively mitigate these effects. However, these failure modes tend to be discovered relatively late in the design process as they, to date, need a representative physical system to test – including ensuring that any materials used on the surface flow paths elicit the same liquid flow behaviours (i.e. contact angles and velocity) as would be seen on the production vehicle surfaces. In this work we describe the development and validation of an early-stage simulation approach using a Smoothed Particle Hydrodynamics code (PreonLab). This includes its calibration against fundamental experiments to provide models for the flow of water over automotive surfaces and their subsequent application to a tailgate system simulation which includes fully detailed surrounding vehicle geometry
Gaylard, Adrian PhilipWeatherhead, Duncan
Image-based machine learning (ML) methods are increasingly transforming the field of materials science, offering powerful tools for automatic analysis of microstructures and failure mechanisms. This paper provides an overview of the latest advancements in ML techniques applied to materials microstructure and failure analysis, with a particular focus on the automatic detection of porosity and oxide defects and microstructure features such as dendritic arms and eutectic phase in aluminum casting. By leveraging image-based data, such as metallographic and fractographic images, ML models can identify patterns that are difficult to detect through conventional methods. The integration of convolutional neural networks (CNNs) and advanced image processing algorithms not only accelerates the analysis process but also improves accuracy by reducing subjectivity in interpretation. Key studies and applications are further reviewed to highlight the benefits, challenges, and future directions of
Akbari, MeysamWang, AndyWang, QiguiYan, Cuifen
High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured
Jan, JonathanPreston, JoshuaJuncker, John
In cold and snowy areas, low-friction and non-uniform road surfaces make vehicle control complex. Manually driving a car becomes a labor-intensive process with higher risks. To explore the upper limits of vehicle motion on snow and ice, we use an existing aggressive autonomous algorithm as a testing tool. We built our 1:5 scaled test platform and proposed an RGBA-based cost map generation method to generate cost maps from either recorded GPS waypoints or manually designed waypoints. From the test results, the AutoRally software can be used on our test platform, which has the same wheelbase but different weights and actuators. Due to the different platforms, the maximum speed that the vehicle can reach is reduced by 1.38% and 2.26% at 6.0 m/s and 8.5 m/s target speeds. When tested on snow and ice surfaces, compared to the max speed on dirt (7.51 m/s), the maximum speed decreased by 48% and 53.9%, respectively. In addition to the significant performance degradation on snow and ice, the
Yang, YimingBos, Jeremy P.
Automotive industry is growing rapidly with innovations leading to increase in new features and improving the Quality of vehicles. These new components are developed with the available design standards across global OEMs. This Quality research paper aims to address the need of revision of design standards due to environmental factors prevailing in India. With the increase towards autonomous mobility, the number of electronics is also increasing, and this involves hardware & software evaluation. The hardware testing is a point of concern due to increase in the failure rate from the markets. Environment changes are very much evident with the growing economies and OEMs are developing the components with innovation, but if the basic design standards are not revised in parallel with the changing environment, the issues will continue to trouble the end customers. The failed cases data received from across the country was analyzed and observed that the cases are majorly reported from urban
Marwah, RamnikPyasi, PraveenBindra, RiteshGarg, Vipin
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
Battery safety is a paramount concern in the development of electric vehicles (EVs), as failures can lead to catastrophic consequences, including fires and explosions. With the rapid global adoption of EVs, understanding how battery cells perform under extreme conditions such as mechanical or thermal abuse is crucial for ensuring vehicle safety. This study investigates the abuse response of lithium-ion batteries under high-speed mechanical loading. Our research systematically examines the response of these cells at different states of charge (SOC) through controlled dynamic tests. These tests offer insights into the failure response of the cells. By analyzing the data, we gain a deeper understanding of the conditions that could trigger thermal runaway under mechanical abuse loadings, representative of EV crashes, a critical safety concern in EV battery systems. The experimental setup and methodologies are presented in this paper, alongside key findings that highlight the importance of
Patanwala, HuzefaKong, KevinChalla, VidyuDarvish, KuroshSahraei, Elham
Continuing prior work, which established a simulation workflow for fatigue performance of elastomeric suspension bushings operating under a schedule of 6-channel (3 forces + 3 moments) road load histories, the present work validates Endurica-predicted fatigue performance against test bench results for a set of multi-channel, time-domain loading histories. The experimental fatigue testing program was conducted on a servo-hydraulic 3 axis test rig. The rig provided radial (cross-car), axial (for-aft), and torsional load inputs controlled via remote parameter control (rpc) playback of road load data acquisition signals from 11 different test track events. Bushings were tested and removed for inspection at intervals ranging from 1x to 5x of the test-equivalent vehicle life. Parts were sectioned and checked for cracks, for point of initiation and for crack length. No failure was observed for bushings operated to 1 nominal bushing lifetime. After 3 nominal bushing lifetimes, cracks were
Mars, WillBarbash, KevinWieczorek, MatthewPham, LiemBraddock, ScottSteiner, EthanStrumpfer, Scott
The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements, arises the need for increased electric current supply to motors. Increased amperage through the stator causes higher losses resulting in elevated temperature across the motor components and its housing. In most of the cases, stator is mounted on the housing through interference fit to avoid any slippage during operation conditions. High temperature across the stator and housing causes significant thermal expansions of the components which is uneven in nature due to the differences in corresponding coefficient of thermal expansion (CTE) values. Housings are generally made of aluminium and tends to expand more having higher value of CTE than that of steel core of stator which may give rise to a failure mode related to stator slippage. To address this slippage if the amount of interference fit is increased, that’ll result in another failure mode
Karmakar, NilankanPrasad, Praveen
Vibration qualification tests are indispensable for vehicle manufacturers and suppliers. Carmakers’ specifications are therefore conceived to challenge the mechanical endurance of car components in the face of numerous in-service detrimental phenomena: In automotive industries, components are commonly qualified by means of a test without failure, the goal being to determine whether it will or not "pass" customer requirements. Validation of newly designed components is obtained via bench test and structural simulation. Simulation has gained traction in recent years because it represents the first step of the design validation process. In particular, FEA simulations are powerful to predict the dynamic behavior of physical testing on prototypes, enable engineers to optimize the design and predict the durability. This paper illustrates how FEA simulations were applied to product validation in the pre-serial phase to optimize manufacturing process. In particular, we will focus on the PCB of
Duraipandi, Arumuga PandianLeon, RenanBonato, MarcoRaja, Antony VinothKumar, LalithNiwa, Takehiro
This paper introduces an innovative digital solution for the categorization and analysis of fractures in Auto components, leveraging Artificial Intelligence and Machine Learning (AI/ML) technologies. The proposed system automates the fracture analysis process, enhancing speed, reliability, and accessibility for users with varying levels of expertise. The platform enables users to upload images of fractured parts, which are then processed by an AI/ML engine. The engine employs an image classification model to identify the type of fracture and a segmentation model to detect and analyze the direction of the fracture. The segmentation model accurately predicts cracks in the images, providing detailed insights into the direction and progression of the fractures. Additionally, the solution offers an intuitive interface for stakeholders to review past analyses and upload new images for examination. The AI/ML engine further examines the origin of the fracture, its progression pattern, and the
Sahoo, PriyabrataRawat, SudhanshuGarg, VipinNaidu, GarimaSharma, AmitNarula, RahulBindra, RiteshKhera, PankajGoel, PoojaMondal, Arup
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
The trends of intelligence and connectivity are continuously driving innovation in automotive technology. With the deployment of more safety-critical applications, the demand for communication reliability in in-vehicle networks (IVNs) has increased significantly. As a result, Time-Sensitive Networking (TSN) standards have been adopted in the automotive domain to ensure highly reliable and real-time data transmission. IEEE 802.1CB is one of the TSN standards that proposes a Frame Replication and Elimination for Reliability (FRER) mechanism. With FRER, streams requiring reliable transmission are duplicated and sent over disjoint paths in the network. FRER enhances reliability without sacrificing real-time data transmission through redundancy in both temporal and spatial dimensions, in contrast to the acknowledgment and retransmission mechanisms used in traditional Ethernet. However, previous studies have demonstrated that, under specific conditions, FRER can lead to traffic bursts and
Luo, FengRen, YiZhu, YianWang, ZitongGuo, YiYang, Zhenyu
A key challenge for manufacturers of automotive systems, hardware components and software products with no contribution to driving automation is the stringent requirements imposed on elements while being integrated into vehicles with driving automation. The result is increased development cost and low reusability. For such elements or components with no contribution to driving automation, their functions and failure modes remain unchanged when comparing vehicle integration with and without driving automation. The influence of driving automation is not accounted for in the current approach of classifying risk while conducting a Hazard Analysis and Risk Assessment (HARA). Functional safety standards for on-road vehicles rely on human intervention as a parameter to classify risk. Since current safety standards for on-road vehicles are not inclusive of driving automation concepts, classification of risk, based on existing definitions of parameters such as controllability, leads to
Shah, MihirIbarra, Ireri
Combined with a modified Zener-Hollmon parameter, a recently proposed ductile failure criterion is further improved to predict the forming limit of boron steel at hot stamping temperatures. The ductile failure criterion takes into account the critical damage at localized necking or at fracture as a function of strain path and initial sheet thickness. The modified Zener-Hollomon parameter accounts for both effect of varying strain rate and temperature for Boron steel. Working FEM simulation, the capability of the ductile failure criterion is further demonstrated by predicting forming limit of a boron steel in an isothermal Nakajima dome test. Comparison shows the prediction matches quite well with the measurement.
Sheng, ZiQiangMallick, Pankaj
With the development of automated vehicle (AV), it is essential to ensure their safety even in the presence of system faults or function inefficiency. Safety controllability refers to the ability to manage and control the vehicle, ensuring that it remains safe even in the presence of faults with unexpected conditions. This study proposed a data driven method to evaluate quantitatively safety controllability for AVs. Safety analysis is conducted to identify the potential hazard events. Taking system function and architecture into consideration, the failure modes of the vehicle hazards are identified with hazardous driving situation. Based on the identified failure modes, fault injection tests are conducted with critical scenarios. According to the vehicle dynamic performance, the improved analytic hierarchy process (AHP) can be explored to quantitatively evaluate the safety controllability based on fault injection test results. In particular, this study focuses on the case study to
Ye, XiaomingYang, YandingLi, LingyangZhang, YaguoWang, Yongliang
As electric vehicles (EVs) become increasingly prevalent, ensuring the safety of their battery systems is paramount. Lithium-ion batteries, present unique safety challenges due to their high energy density and the potential for failure under certain conditions. There is an extensive amount of research on pouch and cylindrical cells, however, prismatic cells have not received similar attention. This study presents an extensive series of experimental tests conducted on prismatic cells from two different manufacturers. These tests include flat punch, hemispherical punch, axial compression and three-point bending tests, all designed to assess the cells’ mechanical properties and failure behavior. A model was developed simulating the behavior of the cell under local loading scenarios. While this paper focuses primarily on testing methodologies, initial findings and an introductory FEA model, future work will incorporate these experimental results into detailed FEA models across all loading
Patanwala, HuzefaSong, YihanSahraei, Elham
As the electrification of chassis systems accelerates, the demand for fail-safety strategies is increasing. In the past, the steering system was mechanically connected, so the driver could respond directly to some extent. However, the Steer-by-Wire (SbW) system is composed of the column and rack bar as electrical signals, so the importance of response strategies for steering system failure is gradually increasing. When a steering system failure occurs, a differential braking control using the difference in braking force between the left and right wheels was studied. Recently, some studies have been conducted to model the wheel reaction force generated during a differential braking. Since actual tires and road surfaces are nonlinear and cause large model errors, model-based control methods have limited performance. Also, in previous studies assumed that the driver normally operates the steering wheel in a failure situation. However, if limited to a situation such as autonomous driving
Kim, SukwonKim, Young GwangKim, SungDoMoon, Sung Jin
Designing for the durability of motor vehicles requires accounting for various stress factors, including tractive loads, electrical loads, thermal loads, and structural loads. For electric vehicle propulsion systems, it is crucial to consider not just the magnitude and repeats of these loads but also their temporal sequence throughout the vehicle’s lifespan. The order and timing of these loads influence factors such as, charge and discharge cycles or active motor heating, which ultimately impact the damage to the propulsion system components like the cell and the motor. Traditionally, lifetime loads for durability assessments are derived from a single-user load profile consisting of a set of ‘representative’ drive cycles accounting for the cumulative damage equivalent to the real-world damage covered under warranty. This profile is typically based on historical usage data, user scenarios, and industry experience, but may not capture the diverse failure modes of the different propulsion
Ramakrishnan, SankaranKhapane, Prashant
The automotive industry leverages Fused Filament Fabrication (FFF) -based Additive Manufacturing (AM) to reduce lead time and costs for prototypes, rapid tooling, and low-volume customized designs. This paper examines the impact of print orientation and raster angle on the tensile properties of Polylactic Acid (PLA), selected for its ease of use and accessibility. Dog bone samples were designed to the ASTM D638 tensile testing standard and printed solid with a 0.2 mm layer height, two outer walls, and varying raster-fill angles, with layers alternating by 90°. Testing was conducted on the MTS Criterion Model 43, 50 kN system. Varying print orientation along the X and Y axes (double angle builds) produced a Young's modulus (YM) range of 0.7519, reflecting a 34.42% increase between the witnessed minimum and maximum values. These builds exhibited more brittle behavior than most single angle builds, except for X10 Y10 Z0 at a 45° raster (the lowest recorded YM) and X0 Y15 Z0 at a 30
Strelkova, DoraUrbanic, Ruth Jill
Since aluminum alloys (AA) are widely used as structural components across various industries, higher requirements for shape-design, load-bearing, and energy-absorption capacity have been put forward. In this paper, we present the development of a numerical model, integrated with a compensation method, that effectively predicts processing defects in the bumper beam of a vehicle, resulting in a marked improvement in its forming quality. Specifically, different constitutive models are investigated for their applicability to the beam, enabling a precise evaluation of its structural performance under large deformation. The Johnson-Cook failure model is introduced to better characterize the fracture behavior of the beam under severe structural damage. The three-point bending experiment served as a rigorous examination, demonstrating good consistency between the experimental and simulation results. Furthermore, a prediction model for assessing the forming quality during the bending process
Zhang, ShizhenMeng, DejianGao, Yunkai
This study introduces a probabilistic analysis approach to evaluate the gear tooth strength for the hypocycloid engines, which are particularly significant in internal combustion (IC) engine applications due to their unique design and critical requirements for both efficiency and durability. The research utilizes the stress–strength interference (SSI) theory within a “design for reliability” framework to develop a robust methodology for designing the internal gear mechanism required for the hypocycloid gear mechanism (HGM) engine, in accordance with American Gear Manufacturers Association (AGMA) standard gear rating practices. This approach incorporates probabilistic factors to address variations in HGM component parameters, gear material properties, and engine operational conditions. To validate the design and ensure accuracy, a finite element method (FEM)-based verification is employed, to identify potential failure points and enhance the overall reliability of the HGM engine. The
ElBahloul, Mostafa A.Aziz, ELsayed S.Chassapis, Constantin
This study presents a novel reinforcement learning (RL)-based control framework aimed at enhancing the safety and robustness of the quadcopter, with a specific focus on resilience to in-flight one propeller failure. This study addresses the critical need of a robust control strategy for maintaining a desired altitude for the quadcopter to save the hardware and the payload in physical applications. The proposed framework investigates two RL methodologies, dynamic programming (DP) and deep deterministic policy gradient (DDPG), to overcome the challenges posed by the rotor failure mechanism of the quadcopter. DP, a model-based approach, is leveraged for its convergence guarantees, despite high computational demands, whereas DDPG, a model-free technique, facilitates rapid computation but with constraints on solution duration. The research challenge arises from training RL algorithms on large dimension and action domains. With modifications to the existing DP and DDPG algorithms, the
Qureshi, Muzaffar HabibMaqsood, AdnanFayyaz ud Din, Adnan
Introducing connectivity and collaboration promises to address some of the safety challenges for automated vehicles (AVs), especially in scenarios where occlusions and rule-violating road users pose safety risks and challenges in reconciling performance and safety. This requires establishing new collaborative systems with connected vehicles, off-board perception systems, and a communication network. However, adding connectivity and information sharing not only requires infrastructure investments but also an improved understanding of the design space, the involved trade-offs and new failure modes. We set out to improve the understanding of the relationships between the constituents of a collaborative system to investigate design parameters influencing safety properties and their performance trade-offs. To this end we propose a methodology comprising models, analysis methods, and a software tool for design space exploration regarding the potential for safety enhancements and requirements
Fornaro, GianfilippoTörngren, MartinGaspar Sánchez, José Manuel
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
In a complex and ever-changing environment, achieving stable and precise SLAM (Simultaneous Localization and Mapping) presents a significant challenge. The existing SLAM algorithms often exhibit limitations in design that restrict their performance to specific scenarios; they are prone to failure under conditions of perceptual degradation. SLAM systems should maintain high robustness and accurate state estimation across various environments while minimizing the impact of noise, measurement errors, and external disturbances. This paper proposes a three-stage method for registering LiDAR point cloud. First, the multi-sensor factor graph is combined with historical pose and IMU pre-integration to provide a priori pose estimation; then a new method for extracting planar features is used to describe and filter the local features of the point cloud. Second, the normal distribution transform (NDT) algorithm is used as coarse registration. Third, the feature to feature registration is used for
Li, ZhichaoTong, PanpanShi, WeigangBi, Xin
Since the rapid development of the shipping and port industries in the second half of the twentieth century, the introduction of container technology has transformed cargo management systems, while simultaneously increasing the vulnerability of global shipping networks to natural disasters and international conflicts. To address this challenge, the study leverages AIS data sourced from the Vessel Traffic Data website to extract ship stop trajectories and construct a shipping network. The constructed network exhibits small-world characteristics, with most port nodes having low degree values, while a few ports possess extremely high degree values. Furthermore, the study improved the PageRank algorithm to assess the importance of port nodes and introduced reliability theory and risk assessment theory to analyze the failure risks of port nodes, providing new methods and perspectives for analyzing the reliability of the shipping network.
Li, DingCheng, ChengZhao, XingxiLi, Zengshuang
This paper discusses the design and analysis of the Three-point linkage of an agricultural tractor for uncommon abusive usage practices during haulage applications. Some operators use the Three-point linkage for generating additional traction to navigate gradient surfaces, which requires additional wheel torque to overcome road slope when the trailer is attached. These maneuvers induce higher loads on Three-point linkage components, such as the lower link, lift rod, and powertrain components, which may lead to structural failures. A virtual simulation and lab-level test methodology need to be established to simulate the usage pattern upfront and predict potential failures. Multi-body dynamics (MBD) simulation was deployed to simulate the physics and extract realistic loads for Computer Aided Engineering (CAE) analysis. Data acquisition was carried out to record the strain levels during the uncommon haulage usage practices, which will be used for further studies. CAE analysis has been
Kumar, YuvarajPerumal, SolairajV, Ashok KumarSavsani, SmitkumarSubbaiyan, Prasanna BalajiBhandwalkar, AnandV V H Krishna Prasad, Tadikamalla
In the Agricultural tractor- transmission system plays major role to transfer power from Engine to final drive through gear box enabling Forward/Reverse (F/R) movements during field operations and transportation conditions. The F/R retainer plate with idler gear, shaft is located between clutch housing and transmission gear box housing. If the retainer housing plate gets failure, then power will not be able to transfer from engine to transmission gear box main drive. In one of the tractor model retainer plate failures was observed during field testing. To simulate the failure mode from field to lab condition, the resultant forces and angle were calculated based on the drive line assembly. Resultant loads were applied on Idle gear shaft assembly through servo actuator in cyclic mode at lab. The failure was observed in the retainer plate and the location of failure was matching with field failure. CAE virtual simulation was carried out for measured load as per the laboratory boundary
V, SaravananMani, SureshKumar, SasiMore, AmitDumpa, Mahendra Reddy
In commercial vehicle, Hydraulic Power Assisted Steering (HPAS) gear plays a vital role to utilize the hydraulic force to assist the steering application. HPAS gear consists of housing, sector shaft, side cover, worm shaft, valve housing and rack piston. Side cover assembly is connected with the housing assembly through bolts which is in exposure to high pressure working hydraulic fluid. Since, some of the bolts are exposed to the fluid environment in the inner surface of the housing, during high pressure running condition, torque relaxation in the bolt is observed which leads to the loosening of bolts and tends to hydraulic fluid leakage through bolts. The current phosphate coated bolts are getting relaxed and loosened due to the bolts that exposed to the oil environment which have insufficient coefficient of friction in the bolt head and thread. To overcome the bolt failure during high pressure hydraulic application, various bolt coating analysis is experimented to withstand the
Ayyappan, RakshnaGovindarasu, AnbarasuP, RajasekarD, Senthil Kumar
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
In some IC engines, fuel injection pump is driven by camshaft; thus, these camshafts are designed for bending and torsional loads. Conventionally, camshafts are built-to-specification. Typically, durability assessment of camshaft happens at engine level, this calls for proto or calibration engine to be made and available for testing. As there are limited number of engine level proto testing, the overall scatter in camshafts due to manufacturing/process variations is not possible to be covered. This poses a risk of camshaft failures in the final stages of product development. To mitigate this risk, a component level standard test method is needed for quickly validating design and manufacturing process of camshafts for second source suppliers. The current paper discusses the process followed for arriving at a standard test setup and overcoming the challenges in terms of capturing the appropriate physics for camshaft failure during the engine level testing. Camshaft rear end experiences
Chakraborty, AbhirupS, AravamuthanK, Karthikeyan
Lithium-ion batteries are prone to thermal failures under extreme conditions, leading to thermal runaway and safety risks such as fire or explosion. Therefore, effective temperature prediction and diagnosis are crucial. This paper proposes a thermal fault diagnosis method based on the Informer time series model. By extracting temperature-related features and conducting correlation analysis, a 9-dimensional input parameter matrix is constructed. Experimental results show that the model can maintain an absolute temperature prediction error within 0.5°C when predicting 10 seconds in advance, with higher accuracy than the LSTM model. Additionally, a three-level warning mechanism based on the forgetting coefficient further enhances diagnostic accuracy. Validation using test data and real vehicle data demonstrates that this method can efficiently diagnose and locate thermal faults in batteries, with low computational costs, making it suitable for online applications.
Sun, YefanZhu, XiaopengZhang, ZhengjiePeng, ZhaoxiaYang, ShichunLiu, Xinhua
This paper focuses on the weak fault diagnosis of a dual - axes precision gear transmission system. Firstly, it elaborates on the structure and working principle of the system. Comprising components like azimuth and pitch channels, motors, and control units, the pitch channel's gear transmission chain is a key research area. Subsequently, fault modes and their harmfulness are analyzed. Different faults such as tooth surface wear and pitting are considered. These faults can lead to serious consequences like system failure and mission deviation. Based on this, a test system is constructed. It includes sensors and a data acquisition system to simulate faults and collect vibration signals. The signals are then analyzed to understand the system's behavior. Finally, a weak fault feature index based on time - domain entropy is developed. A threshold setting method based on severity index is also proposed. These methods together enable the accurate diagnosis of weak faults in the system, which
Han, WeiChang, Yingjie
A 20-cell self-humidifying fuel cell stack containing two types of MEAs was assembled and aged by a 1000-hour durability test. To rapidly and effectively analyze the primary degradation, the polarization change curve is introduced. As the different failure modes have a unique spectrum in the polarization change curve, it can be regarded as the fingerprint of a special degradation mode for repaid analysis. By means of this method, the main failure mode of two-type MEAs was clearly distinguished: one was attributed to the pinhole formation at the hydrogen outlet, and another was caused by catalyst degradation only, as verified by infrared imaging. The two distinct degradation phases were also classified: (i)conditioning phase, featuring with high decay rate, caused by repaid ECSA change from particle size growth of catalyst. (ii) performance phase with minor voltage loss at long test duration, but with RH cycling behind, as in MEA1. Then, an effective H2-pumping recovery is conducted
Pan, ChenbingWu, HailongRuyi, Wang
To enhance the operating performance of the common-bus open-winding permanent magnet synchronous motor under single-phase open-circuit faults, this paper proposes a model predictive torque control strategy with torque ripple suppression. First, the operating principles of the model predictive torque control system for both normal operation and single-phase fault conditions are analyzed. Based on this analysis, the electromagnetic torque controller in the model predictive torque control system is restructured. However, if the conventional space vector modulation strategy used during fault-free operation is continued, the required stator voltage cannot be achieved. Therefore, analyze the phase relationship of the current before and after the fault, derive a new Clark transformation matrix, and then based on the principle of torque invariance that can be generated by the fundamental magnetic flux, derive the coefficients of the Park transformation of the two-phase current. To simplify the
Zhang, DongdongMo, FushenLin, Xiaogang
This SAE Aerospace Recommended Practice (ARP) establishes design, manufacturing performance and test requirements for linear mechanical actuators intended to be used for linear motion applications in response to manual or automatic power control system inputs. It is applicable, but not confined to, ball screws, sliding contact screws, roller screws, helical splines, rack and pinion assemblies, and skewed roller actuators. It is a reference for preparing detail specifications for mechanical actuators compatible and applicable to military or commercial aircraft systems.
A-6B3 Electro-Mechanical Actuation Committee
This document presents minimum criteria for the design and installation of LED assemblies in aircraft. The use of "shall" in this specification expresses provisions that are binding. Nonmandatory provisions use the term "should."
A-20C Interior Lighting
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
Thoracic injuries, most frequently rib fractures, commonly occur in motor vehicle crashes. With an increased reliance on human body models (HBMs) for injury prediction in various crash scenarios, all thoracic tissues and structures require more comprehensive evaluation for improvement of HBMs. The objective of this study was to quantify the contribution of costal cartilage to whole rib bending properties in physical experiments. Fifteen bilateral pairs of 5th human ribs were included in this study. One rib within each pair was tested without costal cartilage while the other rib was tested with costal cartilage. All ribs were subjected to simplified A-P loading at 2 m/s until failure to simulate a frontal thoracic impact. Results indicated a statistically significant difference in force, structural stiffness, and yield strain between ribs with and without costal cartilage. On average, ribs with costal cartilage experienced a lower force but greater displacement with a longer time to
Schaffer, RoseKang, Yun-SeokMarcallini, AngeloPipkorn, BengtBolte, John HAgnew, Amanda M
Autonomous vehicles for mining operations offer increased productivity, reduced total cost of ownership, decreased maintenance costs, improved reliability, and reduced operator exposure to harsh mining environments. A large flow of data exists between the remote operation and the ore haul vehicle, and part of the data becomes information for the maintenance sector which it monitors the operating conditions of various systems. One of the systems deserving attention is the suspension system, responsible for keeping the vehicle running and within a certain vibration condition to keep the asset operational and productive. Thus, this work aims to develop a digital twin-assisted system to evaluate the harmonic response of the vehicle’s body. Two representations were created based on equations of motion that modeled the oscillatory behavior of a mass-damper system. One of the representations indicates a quarter of the ore transport truck’s hydraulic system in a healthy state, called a virtual
Rosa, Leonardo OlimpioBranco, César Tadeu Nasser Medeiros
The traditional braking system has been unable to meet the redundant safety requirements of the intelligent vehicle for the braking system. At the same time, under the change of electrification and intelligence, the braking system needs to have the functions of braking boost, braking energy recovery, braking redundancy and so on. Therefore, it is necessary to study the redundant braking boost control of the integrated electro-hydraulic braking system. Based on the brake boost failure problem of the integrated electro-hydraulic brake system, this paper proposes a redundant brake boost control strategy based on the Integrated Brake Control system plus the Redundant Brake Unit configuration, which mainly includes fault diagnosis of Integrated Brake Control brake boost failure, recognition of driver braking intention based on pedal force, pressure control strategy of Integrated Brake Control brake boost and pressure control strategy of Redundant Brake Unit brake boost. The designed control
Dexing, LaoLuping, YanQinghai, SuiLong, CaoShang, GaoZhigang, ChenMingxing, RenZhicheng, Chen
SBW(Steer-by-wire) is a steering system that transmits the driver’s request and gives feedback to the driver through electrical signals. This system eliminates the mechanical connection of the traditional steering system, and can realize the decoupling of the steering wheel and the road wheel. In addition, this system has a perfect torque feedback system, which can accurately and delicately feedback the road surface information to the driver. However, vehicle driving deviation is one of the most common failure modes affecting vehicle performance in the automotive aftermarket, this failure mode can exacerbates tire wear, reducing their life cycle, at the same time, the driver must apply a counter torque to the steering wheel for a long time to maintain straight-line travel during driving. This increases the driver’s operational burden and poses safety hazards to the vehicle’s operation. Based on the steer-by-wire system and vehicle driving deviation characteristics, this paper proposes
Xiangfei, XuQu, Yuan
LIDAR-based autonomous mobile robots (AMRs) are gradually being used for gas detection in industries. They detect tiny changes in the composition of the environment in indoor areas that is too risky for humans, making it ideal for the detection of gases. This current work focusses on the basic aspect of gas detection and avoiding unwanted accidents in industrial sectors by using an AMR with LIDAR sensor capable of autonomous navigation and MQ2 a gas detection sensor for identifying the leakages including toxic and explosive gases, and can alert the necessary personnel in real-time by using simultaneous localization and mapping (SLAM) algorithm and gas distribution mapping (GDM). GDM in accordance with SLAM algorithm directs the robot towards the leakage point immediately thereby avoiding accidents. Raspberry Pi 4 is used for efficient data processing and hardware part accomplished with PGM45775 DC motor for movements with 2D LIDAR allowing 360° mapping. The adoption of LIDAR-based AMRs
Feroz Ali, L.Madhankumar, S.Hariush, V.C.Jahath Pranav, R.Jayadeep, J.Jeffrey, S.
In demanding automotive coolant applications characterized by extreme pressure and temperature conditions, a variety of Mechanically Attached Fittings (MAFs) are offered by multinational corporations (MNCs). These engineered fittings have been designed to meet the rigorous requirements of various industries, providing a cost-effective and reliable means to seal engine/motor coolant hose joints. Mechanical fitting assemblies are critical in various engineering systems and are used for connecting various fluid-carrying locations. Understanding leakage phenomena from MAFs is essential for ensuring their reliability and efficiency. This study explores the deployment of Fluid Pressure Penetration Technique (FPPT) available in Abaqus FEA software to comprehensively analyze leakage paths in mechanically joined fittings. The FPPT offers a systematic approach to model fluid penetration behavior within fitting joints under many loading conditions. By utilizing Abaqus software, a powerful finite
Aher, Ravi KautikJivani, ChinmayOlesnavich, MichaelLima, JosePillai, Pramod
With the trend of increasing technological complexity, software content and mechatronic implementation, there are increasing risks from systematic failures and random hardware failures, which is to be considered within the scope of functional safety. ISO 26262 series of standards provides guidance to mitigate these risks by providing appropriate requirements and processes. To develop a safe product with respect to above mentioned complexities, it is very critical to develop a safe system and hence a thorough and robust “Technical Safety Concept” is very important to ensure absence of unreasonable risk due to hazards caused by malfunctions of E/E systems. ISO26262-Part 4 provides guidelines for “Product development at the system level”, to design safety-related systems that include one or more electrical and/or electronic (E/E) systems and that are installed in series production road vehicles. Defining requirements at system level for each individual technology and systematically
Cheni, Dileep KumarDesai, Priyanka Pradeep
This study meticulously examines the ignition coil (IG), a pivotal component in engine operation, which transforms the low voltage from the battery into the high voltage necessary for spark plug electrode flashover, initiating the combustion cycle. Considering the importance of IG coils in engine operation which has a direct impact on the engine performance. Any failure in the IG coils is judged as a critical failure and encompasses severe repercussions. The paper details an investigation into the issue of ‘White Deposition’ on IG coils. White deposit was observed in IG Coils during new model development in bench level durability test. A comprehensive failure analysis was conducted, employing vibration analysis, thermal analysis, and chemical analysis of the white deposits to ascertain the root cause. Subsequent to identifying the root cause, the study elaborated on hardware design enhancements as a solution. These design changes were rigorously tested on engine benches, confirmed for
Patel, Hardik ManubhaiGupta, VineetChand, SubhashKumar, Nitish
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