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IEEE OPEN JOURNAL OF POWER ELECTRONICS 2024年 5卷 802-811页

作者： Liao, Yantao Zhang, Yi You, Jun Jin, Long Xu, Zhike Shen, Zhan Southeast Univ Dept Elect Engn Nanjing 210096 Peoples R China Aalborg Univ AAU Energy DK-9220 Aalborg Denmark

Determining threshold values in model based fault detection (MBFD) is a longstanding challenge, which is often addressed through empirical and ambiguous adjustments. To tackle this issue, this paper proposes an uncertainty-informed framework for quantitative threshold assessment. The framework comprises three stages: 1) identifying uncertainties by explicitly understanding the implemented MBFD method, 2) quantifying fault detection residual through uncertainty propagation, and 3) determining and optimizing threshold values based on the quantified misdiagnosis rates. To validate the effectiveness of the proposed approach, a case study of a modular multilevel converter is selected. The proposed method not only enables a quantified threshold assessment but also enhances the robustness of the fault detection by accounting for uncertainties.

关键词： Uncertainty fault detection Voltage measurement Probabilistic logic Power electronics Optimization Multilevel converters model-based fault detection modular multilevel converters uncertainty quantification threshold assessment

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model-based fault simulation and detection for gauge-sensorized strain wave gears 11

Model-based fault simulation and detection for gauge-sensori...

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11th Vienna International Conference on Mathematical modelling (MATHMOD)

作者： Kisskalt, Julian Michalka, Andreas Strohmeyer, Christoph Horn, Maik Graichen, Knut Friedrich Alexander Univ Erlangen Nurnberg Chair Automat Control Erlangen Germany Schaeffier Technol AG & Co KG Herzogenaurach Germany

Strain wave gears (SWG) are important parts to drive robots. Yet, they are susceptible to wear and degradation carrying high risk for malfunction of the robot. Hence, the detection of faults in SWGs is of great interest for the robot's safe operation. In this paper, the capability of a simulation chain is shown to generate faulty SWGs' signals of strain gauge sensors mounted on the back of their flex spline with qualitatively similar behavior to real-world measurement signals. Furthermore, the simulated sensor signals are used for a data-driven detection of faults in measurement data showing the practicality of this approach for real-world applications. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： strain wave gear simulation chain fault modeling model-based fault detection

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model-based fault detection in DC Microgrids

Model-Based Fault Detection in DC Microgrids

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Smart Gird Conference (SGC)

作者： Salimi, Asaad Batmani, Yazdan Bevrani, Hassan Univ Kurdistan Smart Micro Grids Res Ctr Dept Elect Engn Kurdistan Sanandaj Iran

ISBN: (纸本)9781728158945

Recently DC Microgrids (DC-MGs) are more attractive and effective in renewable energy resources (RERs). In this paper, for the protection of devices and detecting parametric faults, two model-based fault detection strategies are presented for DC-MGs. The proposed strategies include a fault detection filter (FDF), named H_/H-infinity based filter, and Kalman based filter. H_/H-infinity based filter can minimize disturbance effects and maximize the fault effects on the so-called residual signal. The results of H_/H-infinity based filter are compared with the Kalman based filter. Results show that the H_/H-infinity based filter is more effective for detection of parametric faults in DC-MGs.

关键词： component faults DC Microgrid H_/H-infinity based fault detection Kalman filter model-based fault detection

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model-based fault simulation and detection for gauge-sensorized strain wave gears

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IFAC-PapersOnLine 2025年第1期59卷 271-276页

作者： Julian Kißkalt Andreas Michalka Christoph Strohmeyer Maik Horn Knut Graichen Chair of Automatic Control Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Schaeffler Technologies AG & Co. KG Herzogenaurach Germany

Strain wave gears (SWG) are important parts to drive robots. Yet, they are susceptible to wear and degradation carrying high risk for malfunction of the robot. Hence, the detection of faults in SWGs is of great interest for the robot’s safe operation. In this paper, the capability of a simulation chain is shown to generate faulty SWGs’ signals of strain gauge sensors mounted on the back of their flex spline with qualitatively similar behavior to real-world measurement signals. Furthermore, the simulated sensor signals are used for a data-driven detection of faults in measurement data showing the practicality of this approach for real-world applications.

关键词： strain wave gear simulation chain fault modeling model-based fault detection

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model-based fault detection for generator cooling system in wind turbines using SCADA data

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WIND ENERGY 2016年第4期19卷 593-606页

作者： Borchersen, A. B. Kinnaert, M. Aalborg Univ Dept Elect Syst Sect Automat & Control Fredrik Bajers Vej 7C DL-9220 Aalborg Denmark Univ Libre Bruxelles Dept Control Engn & Syst Anal CP165-5550 Ave FD Roosevelt B-1050 Brussels Belgium

In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an appropriate statistical change detection algorithm in order to detect faults in the cooling system. To validate the method, it has been tested on 3years of historical data from 43 turbines. During the testing period, 16 faults occurred;15 of these were detected by the developed method, and one false alarm was issued. This is an improvement compared with the current system that gives 15 detections and more than 10 false alarms. In some cases, the method detects the fault a long time before the turbine reports an alarm. A further advantage of the method is that it is based on supervisory control and data acquisition data that are available for the operator of all modern turbines. Thereby, the method can be implemented without the need to modify or install additional components in the turbines. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： SCADA data extended Kalman filter model-based fault detection wind turbine validation on real data

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Practical design considerations for successful industrial application of model-based fault detection techniques to aircraft systems

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ANNUAL REVIEWS IN CONTROL 2016年 42卷 224-231页

作者： Zolghadri, A. Cieslak, J. Efimov, D. Goupil, P. Dayre, R. Univ Bordeaux CNRS IMS Lab Automat Control Grp 351 Cours Liberat F-33405 Talence France INRIA LNE NonA Project Parc Sci Haute Borne40 Ave Halley F-59650 Villeneuve Dascq France AIRBUS Operat SAS EYCCC Flight Control Syst 316 Route Bayonne F-31060 Toulouse France

This paper discusses some key factors which may arise for successful application of model-based fault detection (FD) techniques to aircraft systems. The paper reports on the results and the lessons learned during flight V&V (Validation & Verification) activities, implementation in the A380 Flight Control Computer (FCC) and A380 flight tests at Airbus (Toulouse, France). The paper does not focus on new theoretical materials, but rather on a number of practical design considerations to provide viable technological solutions and mechanization schemes. The selected case studies are taken from past and on-going research actions between Airbus and the University of Bordeaux (France). One of the presented solutions has received final certification on new generation Airbus A350 aircraft and is flying (first commercial flight: January 15, 2015). (C) 2016 International Federation of Automatic Control. Published by Elsevier Ltd. All rights reserved.

关键词： model-based fault detection Aircraft and flight systems Flight tests Abnormal control surface position

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PARALLEL model based fault detection ALGORITHM FOR ELECTRONIC PARKING BRAKE SYSTEM

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INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY 2014年第3期15卷 483-494页

作者： Moon, B. J. Jung, H. G. Lee, S. G. Kim, D. H. Dae Duk Coll Dept Automot Engn Taejon 305715 South Korea Hanyang Univ Dept Automot Engn Seoul 133791 South Korea Kyung Hee Univ Dept Mech Engn Gyeonggi 446701 South Korea Kyung Hee Univ Dept Elect Engn Gyeonggi 446701 South Korea

This paper describes a parallel model-based fault detection algorithm for an electronic parking brake (EPB) system, which consists of an electronic control unit with built-in current sensor and braking force sensor. For the EPB system to supply sufficient parking force to a vehicle, the parking force sensor is of utmost importance. If a fault occurs in this sensor, sufficient parking force may not be supplied, thereby seriously threatening the safety of the vehicle. Thus, a fault detection method is required for the parking force sensor of the EPB system to improve the safety of vehicles. For this purpose, a highly reliable fault detection method is needed to detect abnormal fault signals, which cannot be detected by the existing on-line sensor monitoring fault detection methods. This paper proposes a novel parallel model-based fault detection algorithm for the EPB system, which compares the physical sensor data with the mathematical model, the fuzzy model, and the neural network model at the same time. In order to reduce false alarms, the magnitude of thresholds and the operation counts are changed adaptively. When the proposed parallel model-based fault detection algorithm detects severe failures of the force sensor, it warns the driver in advance to prevent accidents due to the failures. The proposed algorithm is verified by hardware-in-the-loop simulations in various situations.

关键词： Electronic parking brake model-based fault detection Mathematical model Fuzzy model and neural network model

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Mitigating pressure fluctuations in a faulty axial piston pump using rearrangement of pistons

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JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2024年第5期46卷 1-13页

作者： Gupta, Rishabh Sonkar, Neeraj Prakash, Jatin Miglani, Ankur Kankar, Pavan Kumar Indian Inst Technol Dept Mech Engn Syst Dynam Lab Indore 453552 Madhya Pradesh India Indian Inst Technol Dept Mech Engn Microfluid & Droplet Dynam Lab Indore 453552 Madhya Pradesh India

Axial piston pumps (APP) are prone to internal leakage due to tight clearances between slipper-swash plate, piston-cylinder, and barrel-port plate, which can deteriorate the pump performance significantly. This study proposes a novel method of enabling reusability of the APP with leakage fault in single and multiple cylinders. Using a model-based approach is presented to identify the best rearrangement of faulty piston-cylinders that results in the lowest peak-to-peak pressures fluctuations at the outlet of an APP. The system network model consisting of an APP is developed in MATLAB Simulink, which can simulate the pump response as a function of the number of faulty piston-cylinders and the different levels of leakage. In this study, three possible geometrical arrangements of faulty piston-cylinders, namely inline, random, and unform, are analyzed at three levels of leakage fault, i.e., an annular clearance of 20 mu m, 60 mu m, and 100 mu m are validated with an experimental study from the literature. The arrangement of faulty piston-cylinders is defined based on their relative position in the cylinder barrel in terms of the configuration ratio, which is the normalized linear distance between them (for two or less) and the normalized area of an enclosed polygon in case of more than two faulty piston-cylinder. It is shown that the uniformly distributed faulty piston-cylinders are characterized by the highest configuration ratio and exhibit minimum peak-to-peak pressure fluctuations, which represents the best case under fault conditions. In contrast the inline arrangement represents the worst case while the random arrangement represents the intermediate case between the two. The results demonstrate that the faulty piston-cylinders can be repositioned in a uniform arrangement to minimize the pressure fluctuations resulting and the associate vibration effects. This can help improve the utility of an otherwise faulty pump, thereby reducing the maintenance downtime and th

关键词： Axial piston pump model-based fault detection Hydraulics Leakage flow Piston-cylinder

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model-based Approach Towards Correctness Checking of Neuromorphic Computing Systems 29

Model-Based Approach Towards Correctness Checking of Neuromo...

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29th Pacific Rim International Symposium on Dependable Computing

作者： Mishra, Abhishek Das, Anup Kandasamy, Nagarajan Drexel Univ Elect & Comp Engn Dept Philadelphia PA 19104 USA

ISBN: (纸本)9798331540746;9798331540753

Neuromorphic hardware that emulates the neural structure of the human brain can implement machine learning models in an extremely energy-efficient manner. It is especially suitable for executing spiking neural networks (SNNs) which comprise spiking neurons interconnected via synapses. The underlying computation is based on spike trains in which the location and frequency of spikes that occur within the network guide the execution. This paper develops a fault detection and isolation (FDI) methodology to monitor the correctness of a neuromorphic program's execution using model-based redundancy in which a software-based monitor compares discrepancies between the behavior of neurons mapped to hardware and that predicted by a corresponding mathematical model. We identify properties of spike trains generated by neurons that can be used for fault detection and build machine learning models to forecast these properties. Predictions from these models, which describe the nominal behavior of neurons, when combined with real-time observations, form the basis for FDI. Experiments using CARLSim, a high-fidelity SNN simulator, show that the proposed approach achieves high fault coverage using models that can operate with low computational overhead in real time.

关键词： Neuromorphic computing spiking neural networks model-based fault detection online monitoring

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model-based supervised sensor placement optimization to detect propellant leak in a liquid rocket engine

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ACTA ASTRONAUTICA 2022年 195卷 234-242页

作者： Omata, Noriyasu Satoh, Daiwa Tsutsumi, Seiji Kawatsu, Kaname Abe, Masaharu Japan Aerosp Explorat Agcy Sagamihara Kanagawa 2525210 Japan Japan Aerosp Explorat Agcy Tsukuba Ibaraki 3058505 Japan Ryoyu Syst Co Ltd Nagoya Aichi 4450024 Japan Hitachi Ltd Hitachi Ibaraki 3191292 Japan

The sensor selection for leak detection and diagnosis in a reusable liquid rocket engine was studied. Sufficient amounts of normal and leaked training data were generated by Monte Carlo simulations considering variations in system conditions based on past firing test results. A multivariate supervised analysis, in which measurements are linearly projected onto a vector that characterizes the difference between distributions of normal and leaked cases, successfully detected the simulated leaks that could not be detected by conventional univariate red-line judgment and unsupervised principal component analysis. Significant sensors for leak detection were selected using the greedy approach based on the detection performance score. It was found that only 11 of the 27 sensors were sufficient to maintain the detection performance.

关键词： Sensor placement optimization Supervised fault detection model-based fault detection Liquid rocket engine

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