Browse Topic: Fault detection

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A Machine Learning Framework for Fault Detection, Isolation, and Severity Prediction of Autonomous VTOL AircraftSM-2026-VLADA-52151/27/2026
Fault detection in autonomous VTOL aircraft is critical because even minor degradations can quickly destabilize multirotor vehicles in safety-critical environments. However, real-flight fault detection remains challenging due to sensor noise, environmental disturbances, and the nonlinear aeromechanics of multirotor platforms. This study proposes a comprehensive machine-learning framework for rotor fault detection, isolation, and severity prediction using real flight data. A convolutional neural network (CNN) architecture is developed to learn spatio-temporal patterns from multivariate flight dynamics, enabling direct inference of both the faulty rotor and its damage level. The framework is first validated using simulated data generated by our in-house flight dynamic model. Next, to verify the framework using real flight data, a hexcopter was designed, fabricated and flight tested for both nominal and faulty cases by introducing controlled blade-tip breakage. The trained model achieves rotor-wise fault classification accuracies above 99% and sample-wise severity estimation accuracy of 96% within a ±1% tolerance in experimental data, demonstrating strong generalization and supporting real-time health monitoring for autonomous VTOL systems.
Sarker, Rippon, Dabaghian, Pedram, Halder, Atanu, Goyal, Raman
Guidelines for Specifying LVDTs and RVDTsARP5554 (Current)11/26/2025
As per Committee/Henry E. Harschburger recommendations
A-6B1 Hydraulic Servo Actuation Committee
Estimating the Length of a Bearing Spall Using Tach from VibrationF-0080-2024-11095/7/2024
Rolling element bearing failures form one of rotating equipment's most critical failure modes. Vibration analysis has been successfully used for bearing fault detection and diagnostics but does not estimate the spall length of the bearing. An estimate of the spall length would provide insight into the degrading reliability of a drivetrain as the fault propagates. This would improve the timeliness of scheduling a maintenance action. In this paper, a synthetic tachometer signal is generated from the bearing fault itself. It is synchronous to the rolling element, allowing for a time-domain representation of waveform using the time-synchronous average. From this, an estimate of the length of the bearing fault can be determined.
Bechhoefer, Eric, Bortman, Jacob, Matania, Omri
Use of Hunting Tooth for Gear Fault DetectionF-0079-2023-180935/16/2023
Becchoefer, Eric
Rotor Fault Detection and Identification on Multicopter based on Statistical Data-driven Methods: Experimental Assessment via Flight TestsF-0078-2022-175565/10/2022
ABSTRACT
Dutta, Airin, Wang, Jianxi, Kopsaftopoulos, Fotis, Gandhi, Farhan
Unified Statistical Framework for Rotor Fault Diagnosis on a Hexacopter via Functionally Pooled Stochastic ModelsF-0077-2021-168085/10/2021
ABSTRACT
Geyer, William, Gordon,  Barbara, Mattei,  Christopher, Robinson,  Dwight
Development of Fault Detection and Emergency Control for Application to Autonomous Vehicle2021-01-00754/6/2021
This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely. The Adaptive convergence time concept proves a mathematical convergence of the vehicle control time after a failure occurs. As soon as the error occurred, the error was proved to always converge to zero within the final time. Thus, the proposed method introduces the concept of convergence time, and mathematically demonstrates that the state reached the reference target within the specified time when a failure occurred. In the emergency control part, two processing unit hardware structures are adopted to comply with SAE International standard J3016 and NHTSA autonomous vehicle safety report standards. The proposed fail-safe detection algorithm is evaluated through vehicle test data, and the fail-safe control algorithm evaluates through computer simulation and vehicle tests.
Jong Min, Lee, Oh, Kwang Seok, Song, Taejun
Design, Development and Test Criteria - Solid State Proximity Switches/Systems for Landing Gear ApplicationsAIR1810C (Current)2/3/2021
This document examines the most important considerations relative to the use of proximity sensing systems for applications on aircraft landing gear. In general, the recommendations included are applicable to other demanding aircraft sensor installations where the environment is equally severe.
A-5B Gears, Struts and Couplings Committee NEW Name Goes Her
“Rds_on” Based OBD for Pre-Supply Fuel Pump Driver ModulesSAE-PP-001601/26/2021
In automotive electronics on-board diagnostics does the fault diagnosis and reporting. It provides the level of robustness required for the control electronics against various faults. The amount of diagnostic information available via on board diagnostics are depends on the type of vehicle. Pre-supply fuel pump is the component in the common rail hydraulic system. It pumps the fuel from the fuel tank to the inlet valve of the high pressure fuel pump. Electronic control unit synchronizes its operation with high pressure fuel pump. A dedicated driver module in the ECU controls the operation of pre-supply fuel pump. The driver module consist of an ASIC with internal voltage, current monitoring modules for the fault diagnosis and the pre-drivers to control external HS and LS power stages. The software part of the OBD programmed in the internal memory of the ASIC. The “Rds_on” of the power MOSFETs are used for the fault detection purpose. The module designed to operate in dual frequencies and variable duty cycles. It ensures the optimum hydraulic performance of the pump and provides maximum possible diagnostic coverage against various faults. The on-board diagnosis against the faults such as motor inrush current, rotor Lock, short circuit to ground, short circuit to battery, line to line fault (short circuit between high side and low side pins) and open load are discussed in this paper. The wiring harness impedance has significant influence on the fault detection duration. The wiring harness length depends on the position of ECU and pump in the vehicle. Pre-supply fuel pump normally immersed in the fuel tank and ECU normally kept either in the dash board or mounted on the body of engine. The resistance and inductance of the wiring harness are the functions of wire diameter and length. The below are the parameters influences the fault diagnostics of the driver module discussed in this paper. • Fault detection threshold (Vth), • The “Rds_on” of the MOSFET, • Fault current magnitude, • Frequency at which power stage operates, • Duty cycle, • Thermal response of the MOSFET, • Safe operating conditions, • Blind bands and MOSFET turn on/off delays. These parameters possesses typical relationships each another depending on the operating modes of engine and ambient conditions.
MobrxivNonAdmin, Lindsay
Rotor Fault Detection and Identification for a Hexacopter Based on Control and State Signals via Statistical Learning MethodsF-0076-2020-1632510/5/2020
A robust framework for fault detection and identification of rotor degradation in multicopters while effectively rejecting the effects of gusts is introduced. The rotor fault detection and identification methods employed in this study are based on excitation-response signals of the aircraft under ambient turbulence to distinguish between an aircraft response to gusts and rotor faults. A concise overview of the development of statistical time series model for healthy aircraft using the aircraft attitudes as the output and controller commands as the input is presented. This model is utilized to extract quality features for training a simple neural network to perform effective online rotor fault detection and identification in a hexacopter exceptional speed of making a decision and accuracy of fault classification. It is shown that using a statistical time series model assisted neural network employed for online monitoring is capable of rejecting gusts, sensitive to even 20% rotor degradation and achieves fault detection and identification in less than 2 s after the fault with an accuracy over 99%.
Dutta, Airin, Gandhi, Farhan, Kopsaftopoulos, Fotis, McKay, Michael
Rotor Fault Detection and Identification on a Hexacopter under Varying Flight States Based on Global Stochastic ModelsF-0076-2020-1627510/5/2020
This work introduces the use of "global" stochastic models to detect and identify rotor failures in multicopters under different operating conditions, turbulence, and uncertainty. The identification of an extended class of time-series models known as Vector-dependent Functionally Pooled AutoRegressive models, which are characterized by parameters that depend on both forward velocity and gross weight, using scalar or vector aircraft response signals under white noise excitation has been described. A concise overview of the residual based statistical decision making schemes for fault detection and identification of rotor failures is provided. The scalar and vector statistical models, along with residual variance and residual uncorrelatedness methods were validated and their effectiveness was assessed by a proof-of-concept application to aircraft flight for healthy and faulty states under severe turbulence and intermediate operating conditions. The results of this study demonstrate the effectiveness of all the proposed residual-based time series methods in terms of prompt rotor fault detection, although the methods based on Vector AutoRegressive models exhibit improved performance compared to their scalar counterparts with respect to their performance in identifying rotor failures in the post-failure controller compensated state.
Dutta, Airin, McKay, Michael, Kopsaftopoulos, Fotis, Gandhi, Farhan
Compound Rotorcraft Yaw Control Fault DetectionF-0076-2020-1639510/5/2020
Emerging vertical flight concepts being proffered for solutions to the Future Vertical Lift (FVL) mission set such as compound high speed rotorcraft can be designed with multiple, coupled control effectors thus creating redundant systems in one or two more axes to generate control forces and moments which allow for a range of trim states. In the FVL mission area future rotorcraft will be asked to fly into high threat environments where potential failure modes can be encountered due to enemy fire or mechanical failure causing reduction of the safe flight envelope. Fault detection creates options to increase the survivability of the crew and passengers allowing an emergency flight envelope to be proposed. One of the more serious potential failures due to enemy fire is a loss of yaw control. Faults in yaw control can be detected in a compound rotorcraft with a vectored thrust ducted propeller (VTDP) or similar anti-torque thruster. An online Kalman filter (KF) for a dimensional yaw moment coeff icient model will be used to estimate vehicle yaw coeff icients. Deviation from the nominal coefficients will be monitored based on the KF statistics in the case of both rudder and tail rotor failure at 60, 40, and 20 ft/s in forward flight. Both frozen zero rudder and ganged sector faults as well as failed tail rotor faults were successfully detected at all airspeeds except the failed tail rotor at 60 ft/s. For the yaw control faults considered, post fault excitation appears airspeed dependent. An online KF estimator for yaw control fault detection could successfully be integrated into the design of a compound rotorcraft with VTDP thereby increasing system safety.
Lewis, Jeffrey, Iyer, Venkatakrishnan, Johnson, Eric
Modern Battery Systems – the eMobility Enabler Virtual Pre-Conference CertificationC20178/7/2020
eMobility presents enormous challenges to engineers who have been engaged primarily in non-electrical sectors of vehicle engineering. Yet, eMobility also presents exciting opportunities to those who are ready to understand how high voltage batteries contribute to the success of eMobility. This seminar will bring together all the materials in an easy to follow format geared to a wide range of participants from engineers to technicians to sales staff to executives. To grasp the opportunities, we need to understand a small number of topics that describe how a battery system contributes to eMobility applications. However, that is only one aspect of how to develop a successful product. As the history of automotive engineering has demonstrated in the marketplace time after time, if the customer is not satisfied with the product, success will be elusive. This seminar will take us, in a team-based problem-solving session, through what we think the customer needs and wants are. As importantly, we’ll look at who the customers are and how that influences their wants and needs. Once these requirements are established, we can cover how cells behave, what materials are used in them and how they need to be handled. All of these are then important factors in cell design and battery design to support the expected levels of performance in energy and power. A lithium ion battery’s sensitivity to its environment and how to manage that sensitivity will also be explored. We will also look at the need to keep all cells performing together rather than as individuals. Another team-based exercise will examine one of the key concerns for consumers – range anxiety. We will explore how range can be estimated and what sensitivities drive this calculation. If range anxiety is a key issue still today, when will it not be so. We’ll look at what can be expected in battery performance beyond today in areas such as solid state, lithium sulfur and others. As important as skillful battery design is, it is just as important to verify that the battery will indeed, perform as promised in the specifications. Verification comes through a through a thorough testing program structured as part of the APQP (Advanced Product Quality Planning) disciplines. We will look at what is contained in such a test program and the regulations and standards that drive the tests. We’ll look at what makes up the safety and abuse test program of lithium ion batteries. We will look at media reports of electric vehicle fires in context of expectations of lithium ion batteries as a part of electric vehicle safety. The hazards that can be expected when working with high voltage lithium ion batteries will be examined and related to the management of the associated risks. The hazards will be related to the sensitivities of lithium ion cells and what can cause these hazards in a team-based session. We will look at common practices to measure and manage the risks in the various environments such as manufacturing, assembly, installation, R&D, testing fault detection, repair, disassembly and undefined states. No battery will be commercially successful if it is not cost competitive. On this subject we will examine product cost and its constituents such as material costs, overhead costs, labour costs and legacy costs. The three-day session will include short quizzes at key points as well as a post seminar short question set. In addition, early registrants are invited to submit battery technology related problems which will be used to pose a team-based challenge to be solved on the afternoon of the last day of the seminar. By attending this seminar, you will be able to: Identify the handling risks of the battery system Respect the risks and work with them Develop a safety program to manage the risks Capture customer wants and expectations of the battery system Identify factors that drive power and energy requirements Determine test program structure Compare and contrast the newest relevant battery technologies Calculate estimates of electric range and quantify the assumptions Critically assess media claims of new battery discoveries CEUs
Automated Diagnosis of Engine Misfire Faults Using Combination Classifiers02-13-02-00076/26/2020
Existing on-board diagnostics vehicle systems can detect the existence of faults, but their diagnostic (fault isolation) capabilities are rather low. Extensions to on-board diagnostics are needed in order to provide a high degree of automated diagnostic support. In this context, we study in this article the problem of internal combustion engine misfires, which constitute a class of automotive faults known to be difficult to diagnose, and present a combination classifier that has excellent performance in classifying the various root causes of misfire faults. We first obtained real-life data and built a database consisting of 2,299 time instances of actual misfire and misfire-free cases. Fault data were captured on several different vehicle makes and models, with each misfire fault belonging to one of three different categories (air-intake, coil-ignition, and fuel-injection), further subdivided into a total of seven subcategories. We then developed a combination classifier (referred to as TMF, “Trees for MisFires”) and obtained its performance on the real-life misfire fault dataset. Extensive simulation results show that TMF outperforms a variety of other standard classifiers (whether single or ensemble) as well as other combination classifiers, both for “low-resolution” diagnosis (classification consisting of three misfire fault categories plus misfire-free) and “high-resolution” diagnosis (classification consisting of seven misfire fault subcategories plus misfire-free). Moreover, these results hold even when the training set is restricted to be a very small portion of the available dataset, which is a valuable asset of a realistic classifier.
Suda, Jessica L., Kagaris, Dimitri
Observer for Faulty Perception Correction in Autonomous Vehicles2020-01-06944/14/2020
Operation of an autonomous vehicle (AV) carries risk if it acts on inaccurate information about itself or the environment. The perception system is responsible for interpreting the world and providing the results to the path planning and other decision systems. The perception system performance is a result of the operating state of the sensors, e.g. is a sensor in fault or being adversely affected by the weather or environmental conditions, and approach to sensor measurement interpretation. We propose a trailing horizon switched system observer that minimizes the difference between reference tracking values developed from sensor fusion performed at an upper level and the values from a potentially faulty sensor based upon the convex combination of different sensor observation model outputs; the sensor observations models are associated with different sensor operating errors. The preferred observer target is a stationary landmark so as to remove additional uncertainty resulting from tracking of moving targets. Results for five scenarios show the observer identifies the appropriate sensor model in no more than a few sample intervals.
Omwansa, Mark, Meyer, Rick, Asher, Zachary, Goberville, Nick
Bearing Fault Diagnosis of the Gearbox Using Blind Source Separation2020-01-04364/14/2020
Gearbox fault diagnosis is one of the core research areas in the field of rotating machinery condition monitoring. The signal processing-based bearing fault diagnosis in the gearbox is considered as challenging as the vibration signals collected from acceleration transducers are, in general, a mixture of signals originating from an unknown number of sources, i.e. an underdetermined blind source separation (UBSS) problem. In this study, an effective UBSS-based algorithm solution, that combines empirical mode decomposition (EMD) and kernel independent component analysis (KICA) method, is proposed to address the technical challenge. Firstly, the nonlinear mixture signals are decomposed into a set of intrinsic mode function components (IMFs) by the EMD method, which can be combined with the original observed signals to reconstruct new observed signals. Thus, the original problem can be effectively transformed into over-determined BSS problem. Then, the whitening process is carried out to convert the over-determined BSS into determined BSS, which can be solved by the KICA method. Finally, the ant lion optimization (ALO) is adopted to further enhance the performance of the EMD-KICA method. The proposed solution is assessed through simulation experiments for non-linearly mixed bearing vibration signals, and the numerical result demonstrates the effectiveness of the proposed algorithmic solution.
Zhong, Hong, Liu, Jingxing, Wang, Liangmo, Ding, Yang, Qian, Yahui
Proton Exchange Membrane Fuel Cell Fault Rapid Diagnosis Method Based on Electrochemical Impedance Spectroscopy and Fuzzy C-Means Algorithm2019-01-503211/4/2019
Water management is a key research direction for the performance and lifetime of proton exchange membrane fuel cell (PEMFC) stacks. The paper is aimed to develop an online fault diagnosis method that distinguishes different degrees of flooding and drying within a fuel cell stack by unobservable variables. In our research, the equivalent circuit model is established and electrochemical impedance spectroscopy (EIS) is utilized. The mathematical methods are used to extract the fault features. Fuzzy C-means is used to classify the selected features and the diagnostic rules are automatically extracted from the data. Through verification, the interpretability and computational efficiency of the proposed method are achieved.
Zhou, Su, Zheng, Shoujian, Hu, Zhe
2019 'Create the Future' Electronics/Sensors/IOT Category Winner: Early Detection of Battery FaultsTBMG-3544711/1/2019
Fault Detection in Single Stage Helical Planetary Gearbox Using Artificial Neural Networks (ANN) and Decision Tree with Histogram Features2019-28-015110/11/2019
Drive train failures are most common in wind turbines. Lots of effort has been made to improve the reliability of the gearbox but the truth is that these efforts do not provide a lifetime solution. Majority of failures are caused by bearing and gearbox. It also states that wind turbine gearbox failure causes the highest downtime as the repair has to be done at Original Equipment Manufacturer [OEM]. This work aims to predict the failures in planetary gearbox using fault diagnosis technique and machine learning algorithms. In the proposed method the failing parts of the planetary gearbox are monitored with the help of accelerometer sensor mounted on the planetary gearbox casing which will record the vibrations. A prototype has been fabricated as a miniature of single stage planetary gearbox. The vibrations of the healthy gearbox, sun defect, planet defect and ring defect under loaded conditions are obtained. The signals show the performance characteristics of the gearbox condition. These characteristics and their number of occurrences were plotted in a histogram graph. Predominant statistical features which represent the fault condition were selected using decision tree algorithm. Using these features the Artificial Neural Network (ANN) and J48 algorithms were trained and tested to classify the faults. The accuracy of the machine learning algorithm greatly helps in deciding the optimum time to carry out the required maintenance operation.
Shaul Hameed, Syed, Vaithiyanathan, Muralidharan, Kesavan, Mahendran
Software Applications for the Control and Management of the Amine Swingbed ExperimentTBMG-3526510/1/2019
The Swingbed software applications provide for the control, command, fault detection, fault recovery, and telemetry monitoring aspects of the Amine Swingbed experiment. These software components are the Swingbed Loader Computer Software Configuration Item (CSCI), the Swingbed Control Module, and the Swingbed Ground Controller applications. As a whole, the Amine Swingbed experiment provides a means for investigating the removal of carbon dioxide from the International Space Station (ISS) crews’ breathing environment via a system of a vacuum-regenerated amine pressure swing absorption reaction beds. Its development and deployment aboard the ISS as an Express Rack pay-load serves to advance the use of the amine-based pressure swing absorption technology towards a level of technology readiness suitable for use in future space transportation systems, where the use of consumables for the removal of carbon dioxide from the breathable environment is not desirable.
The Right Stuff for Aging Electronics/Intermittence/No Fault Found2019-01-18899/16/2019
For those in the avionics repair and maintenance business, the acronyms NFF (No Fault Found), NTF (No Trouble Found), and CND (Cannot Duplicate) are, unfortunately, all too familiar terms. After several decades of frustration with this illusive phenomenon, it continues to consume an enormous amount of test and diagnostic effort and is the source of considerable cost and discomfort within the multi-level avionics repair model. There are undoubtedly many causes of NFF and all of them should be addressed. The question is: Where do you start and which solution will be the most beneficial? Our particular efforts have focused on the literal or statistical analysis of NFF, recognizing that if the system’s MTBF (Mean Time Between Failure) has decreased, or if the device's NFF rate has increased with age and deterioration, a physical fault is most likely present. However, if it isn’t found during conventional testing then it probably only fails intermittently. Similarly, having an intermittent failure mode, it in all probability cannot be detected or diagnosed at testing time because of known and demonstrated limitations in the conventional measurement equipment used to perform the tests. In this paper we will outline the problem of intermittence and its testing difficulties. More importantly, we will describe the unique equipment and process which has produced overwhelming success in Intermittence / NFF resolution and MTBF extension. Our team-developed overhaul system called IFDIS 2.0 (Intermittent Fault Detection and Isolation System 2.0) incorporates all the necessary testing procedures and technological capabilities that are proving to be critical to the resolution of the chronic intermittent / NFF problem.
Knudsen, Hector I.
Safety Analysis: The Key to a Single-Pass ISO26262 Random Fault WorkflowTBMG-346296/1/2019
Advanced driver-assistance systems and autonomous drive technologies increase the complexity of automotive integrated circuits (ICs), making it harder to ensure that ICs are protected from random hardware faults. Safety mechanisms must be inserted to identify and control these unpredictable functional failures, and ISO26262 requires that the effectiveness of every safety mechanism is proven.
Rotor Fault Detection and Identification on a Hexacopter Based on Statistical Time Series MethodsF-0075-2019-147565/13/2019
This work introduces the use of statistical time series methods to detect rotor failures in multicopters. A concise overview of the development of various time series models using scalar or vector signals, statistics, and fault detection methods is provided. The fault detection methods employed in this study are based on parametric time series representations and response-only signals of the aircraft state, as the external excitation is non-observable. The comparative assessment of the effectiveness of scalar and vector statistical models and several residual-based fault detection methods are presented in the presence of external disturbances, such as various levels of turbulence and uncertainty, and for different rotor failure scenarios. The results of this study demonstrate the effectiveness of all the proposed residual-based time series methods in terms of prompt rotor fault detection, although the methods based on Vector AutoRegressive (VAR) models exhibit improved performance compared to their scalar counterparts with respect to their robustness and effectiveness for different turbulence levels and ability to distinguish between healthy and fault compensated condition after rotor failure.
Dutta, Airin, McKay, Michael, Kopsaftopoulos, Fotis, Gandhi, Farhan
Study of Replacing the Traditional Electromechanical Relay with the Full Semiconductor Solution of Bussed Electrical Center2019-01-04844/2/2019
To face the challenges of CO2 emission and automated driving, the electrical distribution system (EDS), as the basis of all electronic loads, needs to be continuously changed. Traditional bussed electrical center (BEC) has limited functions such as simple switch and fuse protection, while the full semiconductor solution of smart BEC can provide more accurate diagnosis, faster response, higher reliability with lower power loss and smaller space. This paper will introduce the practical function of the smart BEC: in normal operation of the car, the voltage and current of the loads can be detected by the smart BEC. Once in abnormal, immediate feedback will be transferred from smart BEC to the whole system and a related response will be triggered in time, while the cost of power harness can also be optimized. In parking mode, the quiescent current of the loads from KL30 can be detected by smart BEC, which could prevent against leakage. Automated driving is a hot topic, many people focus on functional safety and redundancy of the actuators in the car, which can only be realized by the safe power supply. Therefore, this paper will also describe the fail safe and fail operational of power supply with smart BEC. Of course, replacing traditional relays with semiconductors will face many challenges, such as the switch off energy for inductive load, inrush current for capacitive load, thermal problem of the system, cost optimization and so on. The paper will introduce the solutions to these challenges. These solutions have practical significance because they are based on analysis of the loads in the real car. Finally, the paper will show the actual comparison with the traditional BEC and the smart BEC in terms of weight, size, power loss, wiring saving, and cost in the real car.
Tian, Xia, Shen, Ning, Wang, Xingwei
Modeling and Learning of Object Placing Tasks from Human Demonstrations in Smart Manufacturing2019-01-07004/2/2019
In this paper, we present a framework for the robot to learn how to place objects to a workpiece by learning from humans in smart manufacturing. In the proposed framework, the rational scene dictionary (RSD) corresponding to the keyframes of task (KFT) are used to identify the general object-action-location relationships. The Generalized Voronoi Diagrams (GVD) based contour is used to determine the relative position and orientation between the object and the corresponding workpiece at the final state. In the learning phase, we keep tracking the image segments in the human demonstration. For the moment when a spatial relation of some segments are changed in a discontinuous way, the state changes are recorded by the RSD. KFT is abstracted after traversing and searching in RSD, while the relative position and orientation of the object and the corresponding mount are presented by GVD-based contours for the keyframes. When the object or the relative position and orientation between the object and the workpiece are changed, the GVD, as well as the shape of contours extracted from the GVD, are also different. The Fourier Descriptor (FD) is applied to describe these differences on the shape of contours in the GVD. The proposed framework is validated through experimental results.
Chen, Yi, Wang, Weitian, Zhang, Zhujun, Krovi, Venkat N, Jia, Yunyi
A Fault Tolerant Time Interval Process for Functional Safety Development2019-01-01104/2/2019
During development of complex automotive technologies, a significant engineering effort is often dedicated to ensuring the safe performance of these systems. An important aspect to consider when assessing the viability of different safety designs or strategies is the time period from the occurrence of a fault to the violation of a Safety Goal (SG). This time period is commonly referred to as the Fault Tolerant Time Interval (FTTI). In Automotive Safety, ISO 26262 [1] calls for the identification and appropriate partitioning of the FTTI, however very little guidance is provided on how to do this. This paper presents a process, covering the entire safety development lifecycle, for the identification of timing constraints and the development of associated requirements necessary to prevent Safety Goal violations.
Denomme, Daniel, Hooson, Sam, Winkelman, James
Battery Management System Based on AURIX Multi-Core Architecture2019-01-13104/2/2019
Battery management system (BMS) is the core component of the new energy vehicle battery system. With the increase of energy density of new energy vehicle battery, its control algorithm becomes more and more complex, and the work of the battery management system will be heavier. In order to solve the limits, the hardware, software and control strategy model of battery management system are developed based on AURIX multi-core microcontroller. The microprocessor control unit is developed by using dual-core chip, which meets the functional safety requirements. Dual-core processing of control strategy and individual information acquisition are realized, and the processing efficiency is improved. A four-tier software architecture of battery management system is developed to handle the Dual-core processing. The graphical development of battery management system strategy model is realized by using MATLAB / Simulink. The results of bench test and real vehicle test show that the developed battery management system meets the application requirements of new energy vehicles.
Huang, Denggao, Zhu, Zhongwen, Zhao, Jing, Wang, Xu, Tian, Yongjun
Regression Techniques for Parameter Estimation of a Synchronous Machine from Sudden Short-Circuit Testing2019-01-13543/19/2019
A sudden short-circuit (SSC) laboratory test of an electric machine is a commonly used procedure to estimate model parameters that accurately represent the dynamic response of the machine. While the graphical interpretation of the short-circuit current is often discussed in great detail, the numerical methods used to determine the solution for the machine parameter estimation is a challenging proposition. In this paper, the authors present an integral regression technique to fit the characteristic equation of the short-circuit current to a curve that is composed of exponential decays that trail off to an unknown steady-state value in the presence of noise. The proposed estimation method is applied to laboratory data from an aerospace synchronous machine.
Robbins, Brett A., Perdikakis, Will, Yost, Kevin J.
Self-Stabilizing, Distributed, Symmetric, Fault-Tolerant SynchronizationTBMG-339233/1/2019
Distributed systems have become an integral part of safety-critical computing applications, necessitating system designs that incorporate complex fault-tolerant resource management functions to provide globally coordinated operations with ultra-reliability. As a result, robust clock synchronization has become a required fundamental component of fault-tolerant, safety-critical distributed systems. Since physical oscillators are inherently imperfect, local clocks of nodes of a distributed system, driven by these oscillators, do not keep perfect time and can drift with respect to real time and one another. Thus, the local clocks of the nodes must periodically be re-synchronized. As a result, a fault-tolerant system needs a clock synchronization algorithm that tolerates imprecise local clocks and faulty behavior by some processes.
Management of RAM Fault for Safety Applications2019-26-03651/9/2019
As safety compliance (ISO 26262) has become a norm for automotive embedded software development, the OEMs and Tier1 are pushed to follow the safety guidelines during hardware, software development process. This demands the microcontroller to not only detect internal faults but also find the exact root cause of the failure and have a self-healing mechanism. This paper presents proposed fault detection, injection, testing and shows comparison of microcontroller fault handling with respect to ISO26262 safety standard between proposed method and traditional method by giving the example of RAM test. Also gives an overview of software implementation of this concept as per AUTOSAR standard.
Ganapathi, Anavaratha Selvan
Smart Actuators Deliver on the Promise of Industry 4.0TBMG-3335712/1/2018
As Industry 4.0 initiatives bring more and more industrial axes of motion into the realm of automation, the need for cost-effective control across them grows as well. Advances in robotics, connectivity, cloud computing, artificial intelligence, data analysis, mobility, and numerous other areas are converging to push global industry to new plateaus of operational efficiency and creating roles for automated actuators in places previously thought impractical.
The Fault-Augmented Approach for the Systematic Simulation of Fault Behavior in Multi-Domain Systems in Aerospace2018-01-191710/30/2018
A library for modelling faults in multi-domain physical systems is introduced. The library is based on the simulation of fault effects on the system’s behavior. The motivation of how and why to model faults systematically as well as a description of the Modelica®-based library structure with a wizard supporting the semi-automatic augmentation process of faults are outlined. The fault types are classified into continuous and discrete with dedicated type definitions. The application of the Fault library is exemplified in the field of aerospace electrohydraulic actuator. The actuator is equipped with hydromechanical, electrical and digital systems for mitigating failures, which should be tested at an early stage of design. To perform the tests, a multi-domain, dynamic system model is created, wherein failures are systematically simulated using a special approach for fault augmentation. In addition, several complementary tests are obtained by a variants simulation and the simulation results of the fault augmented model are analyzed and using supervised machine learning classifier are demonstrated. Different classification algorithms were compared to each other and analyzed. The accuracy of an appropriate machine learning classifier is analyzed in detail to classify several faults from different domains and to localize their impact by changing a control mode. The selection of relevant output values for the fault classification in the electrohydraulic control system is executed based on the extraction of the feature’s importance.
Kolesnikov, Artem, Andreev, Maxim, Abel, Andreas
DC Arc Fault Detection Methods in MEA Distribution Systems2018-01-193410/30/2018
Direct current (DC) for primary power distribution is a promising solution that is being explored by aircraft system integrators for MEA applications to enable the paralleling of non-synchronized engine off-take generators, and to enable the reduction of energy conversion stages required to supply electronically actuated loads. However, a significant challenge in the use of DC systems is the reliable detection of arc faults. Arcing presents a significant fire risk to aircraft and their presence can result in critical system damage and potentially fatal conditions. Series arc faults in DC systems are particularly challenging to detect as the associated reduction in system current eliminates the use of conventional overcurrent and current differential methods for fault detection. This paper provides an overview of series arc faults in DC systems and presents both simulation and hardware results to illustrate key trends, characteristics and discriminating features. It also presents a comprehensive review of arc fault detection and diagnosis techniques that have been proposed for a wide range of aerospace and other applications. The paper concludes with a discussion on the unique challenges and opportunities for the application of both deterministic and probabilistic methods in MEA systems.
Thomas, Jeffy, Telford, Rory, Rakhra, Puran, Norman, Patrick, Burt, Graeme
ARC FAULT CIRCUIT BREAKER - AIRCRAFT, TRIP FREE, 25 TO 35 AMP, TYPE 1AS5692/4 (Current)9/2/2018
AE-7P Protective and Control Devices
ARC FAULT CIRCUIT BREAKER - AIRCRAFT, TRIP FREE, 1 TO 20 AMP, TYPE IAS5692/3 (Current)9/2/2018
AE-7P Protective and Control Devices
Guidelines for Testing and Support of Aerospace, Fiber Optic, Inter-Connect SystemsARP5061A (Current)8/16/2018
ARP5061A provides guidelines for optical performance testing of short haul fiber optic inter-connection systems used in aerospace vehicles. The focus of this document is to introduce the proper testing tools and establish common pre- and post-installation test methods and troubleshooting methodologies.
AS-3 Fiber Optics and Applied Photonics Committee
Power Outlet Analyzes Electrical Current UsageTBMG-324798/1/2018
Electrical interruptions, or “nuisance trips,” occur when a detector installed behind the wall trips an outlet's electrical circuit when it senses something that could be an arc-fault — a potentially dangerous spark in the electric line. The problem with today's arc-fault detectors is that they often err on the side of being overly sensitive, shutting off an outlet's power in response to electrical signals that are actually harmless.
A Fault-Tolerant Control Method for 4WIS/4WID Electric Vehicles Based on Reconfigurable Control Allocation2018-01-05604/3/2018
This paper presents a fault-tolerant control (FTC) method for four-wheel independently driven and steered (4WIS/4WID) electric vehicles based on a reconfigurable control allocation to increase the flexibility for vehicle control and improve the safety of vehicle after the steering actuator fails. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle steering condition, detects and diagnoses actuator failures; 2) an upper controller that computes the generalized forces/moments to track the desired vehicle motion and trajectory; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels. The FTC approach based on the reconfigurable control allocation reallocates the generalized forces/moments among healthy steering actuators and driving motors once the actuator failures is detected. If one of the steering actuators fails (the road wheel cannot steer), the FDD module will diagnose the actuator failures by the steering wheel angle sensors. Then the reconfigurable control allocator accommodates faulty driving motors and reconfigures the control allocation law of the healthy motors to achieve the desired vehicle motion, maximize the vehicle-road grip margin and minimize the deviation from the desired trajectory to the utmost extent. Simulations using a high-fidelity, full-vehicle model have been conducted to verify the proposed algorithm. It has been shown from the simulations that the proposed fault-tolerant control (FTC) method can make the vehicle track the desired motion and trajectory when the steering actuator failure occurs so that it can improve the safety and maneuverability of vehicle.
Zhang, Youpeng, Zheng, Hongyu, Zhang, Jiaxu, Cheng, Cheng
An Online Fault Detection and Isolation Method for Permanent Magnet Synchronous Machine2018-01-04514/3/2018
An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.
Zhong, Zaimin, Zhou, Shuihua, Chen, Xueping, Hu, Chengyu
Optical Networking TerminologyAIR6004 (Current)1/23/2018
AS-3 Fiber Optics and Applied Photonics Committee
Soil Moisture Active-Passive Project Spacecraft Flight SoftwareTBMG-281601/1/2018
The Soil Moisture Active-Passive (SMAP) Project Spacecraft Flight Software controls all aspects of command and data handling (CDH) in the SMAP spacecraft. Required capabilities include uplink and command, telemetry and downlink, vehicle attitude control, science instrument control, onboard science data storage and downlink, spacecraft deployments, and spacecraft fault detection and response.
Designing With MIL-STD-1553B ComponentsTBMG-2793812/1/2017
The interconnected backbone of a MIL-STD-1553B vehicle depends on the electrical and mechanical reliability of the components, the design, and the installation. With the vast array of MIL-STD-1553B specified sub-assemblies, there are factors that can go overlooked for passive components such as couplers, cables, and connectors. Often built with kilometers of wiring, aircraft in particular can be difficult to troubleshoot and must be inspected frequently for potential failures such as intermittent connections, shorts, and corrosion. Still, these passive components that make up the network can be individually assessed to operate with a high level of integrity.
Document for 270 Voltage Direct Current (270 V DC) SystemARP4729A (Current)11/30/2017
This SAE Aerospace Recommended Practice (ARP) provides technical design and application information related to the generation, distribution, control, and utilization of aircraft 270 V DC electrical power systems and support equipment. This document also provides references and definitions to permit comparisons of various electrical systems and components.
AE-7C Systems
Fault Detection and Diagnosis of Diesel Engine Lubrication System Performance Degradation Faults based on PSO-SVM2017-01-243010/8/2017
Considering the randomness and instability of the oil pressure in the lubrication system, a new approach for fault detection and diagnosis of diesel engine lubrication system based on support vector machine optimized by particle swarm optimization (PSO-SVM) model and centroid location algorithm has been proposed. Firstly, PSO algorithm is chosen to determine the optimum parameters of SVM, to avoid the blindness of choosing parameters. It can improve the prediction accuracy of the model. The results show that the classify accuracy of PSO-SVM is improved compared with SVM in which parameters are set according to experience. Then, the support vector machine classification interface is fitted to a curve, and the boundary conditions of fault diagnosis are obtained. Finally, diagnose algorithm is achieved through analyzing the centroid movement of features. According to Performance degradation data, degenerate trajectory model is established based on centroid location. And normal faults and performance degradation faults of diesel engine lubrication system are diagnosed. Results show that classification accuracy of the proposed PSO-SVM model achieved is 95.06% and 97.04% in two verify samples, it can meet the needs of fault diagnosis; and two typical faults and performance degradation fault of diesel engine can be diagnosed based on the proposed diagnosis method through simulation model based on AMESim.
Wang, Yingmin, Cui, Tao, Zhang, Fujun, Wang, Sufei, Gao, Hongli
Combined Discrete-Continuous Simulation for Maintenance Training and Execution2017-01-20259/19/2017
One of the most important activities associated with the Aerospace or Defense industry is maintenance. Maintainability procedures have a direct impact on safety and operational availability of systems. The processes and procedures that are used during maintenance activities, whether removing and replacing a component of a system, or conducting troubleshooting, are generally discrete by design, and in most cases, a maintainer, or a field service representative (FSR), will follow a sequence of steps as part of a maintenance work package or work instruction to complete the necessary tasks. Depending on the system, those maintenance activities could be complex, requiring a large maintenance window and the availability of resources to ensure completion. In order to successfully accomplish those complex tasks, besides having access to the required hardware/software and tools, one of two alternatives need to exist: either the maintainer is well trained and experienced, or the maintenance work instructions are extremely detailed and precise; both options can be time consuming and expensive to achieve. In addition, and depending on the FSR, or how the work instructions were captured, the maintenance task will be done in a particular way, not leaving room for process improvement. Maintenance activities are generally conducted by utilizing a series of discrete steps, although the process of developing maintenance procedures can be open to interpretation, depending on how and who created the procedure. By utilizing the maintenance procedures, system data, and the information on the component(s) affected, the approach users take to accomplish the particular maintenance task can be collected in the form of quantitative data. Utilizing that data, discrete-continuous models can be generated for specific maintenance activities in order to maximize efficiency and reduce system downtime.
Rodriguez, Eugenio
On the Use of Built In Test Effectivity Analysis2017-01-20519/19/2017
Testability measures the extent to which a system or unit supports fault detection and fault isolation in a confident, timely and cost-effective manner. The incorporation of adequate testability, including Built-In Test (BIT), requires early and systematic management attention to testability requirements, design and measurement. Whilst the design of BIT has become a standard design practice for a complex control system, the process to measure the effectiveness of such circuitry (both hardware and software) remains qualitative. The Built-In Test Effectivity Analysis (BEA) tries to quantify such analysis at each phase; identifying requirement gaps that help design safer products. The BEA modifies standard reliability programme to use Failure Modes and Effects and Criticality Analysis (FMECA), and reliability prediction of each functional group to generate a measure of how thoroughly the system can check itself. Initially discussed by Collet et al, this method is restricted by assumptions such as exclusion of generic faults and incorruptible BIT circuitry. This paper aims to optimize the present methodology by using a modified Failure Mode Effects Summary (FMES) template to identify and isolate faults that help determine hardware/software requirements that can mitigate BIT circuitry faults as well as generic failures.
Thanigaivelu, Vasanth, Choksi, Samir
Integration of an End-of-Line System for Vibro-Acoustic Characterization and Fault Detection of Automotive Components Based on Particle Velocity Measurements2017-01-17616/5/2017
The automotive industry is currently increasing the noise and vibration requirements of vehicle components. A detailed vibro-acoustic assessment of the supplied element is commonly enforced by most vehicle manufacturers. Traditional End-Of-Line (EOL) solutions often encounter difficulties adapting from controlled environments to industrial production lines due the presence of high levels of noise and vibrations generated by the surrounding machinery. In contrast, particle velocity measurements performed near a rigid radiating surface are less affected by background noise and they can potentially be used to address noise problems even in such conditions. The vector nature of particle velocity, an intrinsic dependency upon surface displacement and sensor directivity are the main advantages over conventional solutions. As a result, quantitative measurements describing the vibro-acoustic behavior of a device can be performed at the final stage of the manufacturing process. This paper presents the practical implementation of an EOL system based on data acquired with a single 3D probe containing three orthogonally placed acoustic particle velocity sensors. Aspects such as installation process, feature extraction, classification, fault detection and diagnosis are hereby discussed. The presented results provide experimental evidence for the viability of particle velocity-based solutions for EOL control applications.
Fernandez Comesana, Daniel, Carrillo Pousa, Graciano, Tijs, Emiel
Value of Optimal Wavelet Function in Gear Fault Diagnosis2017-01-17716/5/2017
Gear fault diagnosis is important in the vibration monitoring of any rotating machine. When a localized fault occurs in gears, the vibration signals always display non-stationary behavior. In early stage of gear failure, the gear mesh frequency (GMF) contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. This paper presents the value of optimal wavelet function for early detection of faulty gear. The Envelope Detection (ED) and the Energy Operator are used for gear fault diagnosis as common techniques with and without the proposed optimal wavelet to verify the effectiveness of the optimal wavelet function. Kurtosis values are determined for the previous techniques as an indicator parameter for the ability of early gear fault detection. The comparative study is applied to real vibration signals. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an envelope analysis enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the output joint shaft flanges. The gearbox used for experimental measurements is the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive.
El morsy, Mohamed, Achtenova, Gabriela
Model-Based Adaptive Fault Diagnosis in Lithium Ion Batteries: A Comparison of Linear and Nonlinear Approaches2017-01-11923/28/2017
In this paper, multiple-model adaptive estimation techniques have been successfully applied to fault detection and identification in lithium-ion batteries. The diagnostic performance of a battery depends greatly on the modeling technique used in representing the system and the associated faults under investigation. Here, both linear and non-linear battery modeling techniques are evaluated and the effects of battery model and noise estimation on the over-charge and over-discharge fault diagnosis performance are studied. Based on the experimental data obtained under the same fault scenarios for a single cell, the non-linear model based detection method is found to perform much better in accurately detecting the faults in real time when compared to those using linear model based method.
Sidhu, Amardeep, Izadian, Afshin, Anwar, Sohel
Robust Observer Roll Rate Sensor Fault Detection2017-01-15723/28/2017
The detection and diagnosis of sensor faults in real-time is necessary for satisfactory performance of vehicle Electronic Stability Control (ESC) and Roll Stability Control (RSC) systems. This paper presents an observer designed to detect faults of a roll rate sensor that is robust to model uncertainties and disturbances. A reference vehicle roll angle estimate, independent of roll-rate sensor measurement, is formed from available ESC inertial sensor measurements. Residuals are generated by comparing the reference roll angle and roll rate, with the observer outputs. Stopping rules based on the current state of the vehicle and the magnitude of the residuals are then used to determine if a sensor fault is present. The system’s low order allows for efficient implementation in real-time on a fixed-point microprocessor. Modification of the roll rate sensor signal during in vehicle experiments shows the algorithm’s ability to detect faults. Different vehicles and multiple driving surfaces are tested to show the fault detection is independent of vehicle parameters, sensor noise and driving conditions.
Kerstens, Wesley
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