Verification of Fault Control Measures Based on Fault Injection for MCU Control System

2014 ◽  
Vol 484-485 ◽  
pp. 325-331
Author(s):  
Dao Sen Niu ◽  
Xiao Dong Liu ◽  
Shou Qun Sun ◽  
Yang Liu
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Fault Injection ◽  
Short Circuit ◽  
Experimental Results ◽  
Control Measures ◽  
Level Variation ◽  
Software Fault ◽  
Hardware Faults ◽  
Software Measures

To verify the validity of fault control measures, a verification platform with software fault injection and hardware fault injection is developed to conduct fault diagnosis measures for MCU control system. For the faults occurring in the internal units of a controller, program debugger is employed to simulate software or hardware faults by varying the data; for the faults occurring in peripheral circuits, a circuit of fault-settings is employed to simulate hardware faults, i.e., open-/short-circuit and electrical level variation. This verification platform is applied to evaluate software measures to control the faults/errors in accordance with IEC60335/IEC60730/UL1998/CSA22.2.08, and a case of induction cooker is presented shows how it works. Experimental results show that the verification platform runs stably and accurately, and has a big value in practice.

Fault Diagnosis for Electrical Control System of Automobile Based on Support Vector Machine

2014 ◽  
Vol 666 ◽  
pp. 203-207
Author(s):  
Jian Hua Cao
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Control System ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Experimental Results ◽  
Support Vector ◽  
Electrical Control ◽  
Diagnosis Method ◽  
The Common

This paper is to present a fault diagnosis method for electrical control system of automobile based on support vector machine. We collect the common fault states of electrical control system of automobile to analyze the fault diagnosis ability of electrical control system of automobile based on support vector machine. It can be seen that the accuracy of fault diagnosis for electrical control system of automobile by support vector machine is 92.31%; and the accuracy of fault diagnosis for electrical control system of automobile by BP neural network is 80.77%. The experimental results show that the accuracy of fault diagnosis for electrical control system of automobile of support vector machine is higher than that of BP neural network.

scholarly journals Fault Injection Model of Induction Motor for Stator Interturn Fault Diagnosis Research Based on HILS

2021 ◽  
Vol 12 (4) ◽  
pp. 170
Author(s):  
Xuhao Zhang ◽  
Kun Han ◽  
Hu Cao ◽  
Ziying Wang ◽  
Ke Huo
Keyword(s):  
Fault Diagnosis ◽  
Induction Motors ◽  
Fault Injection ◽  
Short Circuit ◽  
Rail Transportation ◽  
Hardware In The Loop ◽  
Healthy State ◽  
Proposed Model ◽  
Injection Model ◽  
First Time

Recently, in order to ensure the reliability and safety of trains, online condition monitoring and fault diagnosis of traction induction motors have become active issues in the area of rail transportation. The fault diagnosis algorithm can be developed and debugged in a real-time environment based on hardware-in-the-loop simulation (HILS). However, the dynamic space model of induction motors with stator interturn short-circuit faults faces the problem that the faulty state and the healthy state are not compatible, which is inconvenient for the HILS. In this paper, a fault injection model is proposed for the first time, which can realize the online switching between the healthy state and the faulty state of the motor. The feasibility and effectiveness of the proposed model are verified by simulation experiments the based on MATLAB/Simulink and dSPACE HILS platforms.

Research on fault tolerant control system based on optimized neural network algorithm

2020 ◽  
Vol 39 (6) ◽  
pp. 9073-9083
Author(s):  
Xianming Shan ◽  
Huixin Liu ◽  
Yefeng Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Control System ◽  
Fault Diagnosis ◽  
Network Model ◽  
Fault Tolerant ◽  
Rapid Development ◽  
Fault Tolerant Control ◽  
Control Measures ◽  
Depth Sensor

Due to the strict personnel control measures in COVID-19 epidemic, the control system cannot be maintained and managed manually. This puts forward higher requirements for the accuracy of its fault-tolerant performance. The control system plays an increasingly important role in the rapid development of industrial production. When the sensor in the system fails, the system will become unstable. Therefore, it is necessary to accurately and quickly diagnose the faults of the system sensors and maintain the system in time. This paper takes the control system as the object to carry out the fault diagnosis and fault-tolerant control research of its sensors. A network model of wavelet neural network is proposed, and an improved genetic algorithm is used to optimize the weights and thresholds of the neural network model to avoid the deficiencies of traditional neural network algorithms. For the depth sensor of a certain system, an online fault diagnosis scheme based on RBF (Radial Basis Function) neural network and genetic algorithm optimized neural network was designed. The disturbance fault, “stuck” fault, drift fault and oscillation fault of the depth sensor are simulated. Simulation experiments show that both online fault diagnosis schemes can accurately identify sensor faults and the genetic algorithm optimized neural network is superior to RBF neural network in both recognition accuracy and training time under the influence of COVID-19.

scholarly journals ACIMS: Analog CIM Simulator for DNN Resilience

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 686
Author(s):  
Dong Ding ◽  
Lei Wang ◽  
Zhijie Yang ◽  
Kai Hu ◽  
Hongjun He
Keyword(s):  
Energy Efficient ◽  
Fault Injection ◽  
Experimental Results ◽  
Hardware Accelerators ◽  
The Real ◽  
Analog Computing ◽  
Real Hardware ◽  
Computationally Intensive ◽  
Hardware Faults

Analog Computing In Memory (ACIM) combines the advantages of both Compute In Memory (CIM) and analog computing, making it suitable for the design of energy-efficient hardware accelerators for computationally intensive DNN applications. However, their use will introduce hardware faults that decrease the accuracy of DNN. In this work, we take Sandwich-Ram as the real hardware example of ACIM and are the first to propose a fault injection and fault-aware training framework for it, named Analog Computing In Memory Simulator (ACIMS). Using this framework, we can simulate and repair the hardware faults of ACIM. The experimental results show that ACIMS can recover 91.0%, 93.7% and 89.8% of the DNN’s accuracy drop through retraining on the MNIST, SVHN and Cifar-10 datasets, respectively; moreover, their adjusted accuracy can reach 97.0%, 95.3% and 92.4%.

Development of a monitor to simultaneously measure dissolved ozone and organic matter in ozonated water

1998 ◽  
Vol 37 (12) ◽  
pp. 285-292 ◽  
Author(s):  
Hiroshi Tsugura ◽  
Tetufumi Watanabe ◽  
Hiroshi Shimazaki ◽  
Shoichi Sameshima
Keyword(s):  
Organic Matter ◽  
Control System ◽  
Sodium Thiosulfate ◽  
Experimental Results ◽  
Uv Absorption ◽  
Uv Absorbance ◽  
Absorption Method ◽  
Ozonated Water

A method for measuring both dissolved ozone (DO3) concentration and UV absorbance was developed adopting ultraviolet (UV) absorption method (JWWA, 1993) using sodium thiosulfate (Na2S2O3) solution for removing residual ozone in ozonated water. A DO3 monitor based on this method was tested. This method was proven to be effective from experimental results. The performance of the monitor was examined with continuous ozonated water. As a result, the monitor performed stably during about 2 months, so that both DO3 concentration and UV absorbance in the ozonated water could be accurately measured. Therefore, the authors have proposed the new aquatic control system with this monitor for ozonation.

Sliding Mode Control for Wheeled Inverted Pendulum

2014 ◽  
Vol 971-973 ◽  
pp. 714-717 ◽  
Author(s):  
Xiang Shi ◽  
Zhe Xu ◽  
Qing Yi He ◽  
Ka Tian
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
High Performance ◽  
Inverted Pendulum ◽  
Sliding Mode ◽  
Experimental Results ◽  
Control Law ◽  
Collaborative Simulation ◽  
Mode Control ◽  
Wheeled Inverted Pendulum

To control wheeled inverted pendulum is a good way to test all kinds of theories of control. The control law is designed, and it based on the collaborative simulation of MATLAB and ADAMS is used to control wheeled inverted pendulum. Then, with own design of hardware and software of control system, sliding mode control is used to wheeled inverted pendulum, and the experimental results of it indicate short adjusting time, the small overshoot and high performance.

scholarly journals Modeling and Fault Diagnosis of Interturn Short Circuit for Five-Phase Permanent Magnet Synchronous Motor

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jian-wei Yang ◽  
Man-feng Dou ◽  
Zhi-yong Dai
Keyword(s):  
Parameter Estimation ◽  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Fault Tolerant ◽  
Short Circuit ◽  
Estimation Method ◽  
Trust Region ◽  
Fault Tolerant Control ◽  
Trust Region Algorithm ◽  
Parameter Estimation Method

Taking advantage of the high reliability, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSM and six-phase PMSM, are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing literatures, the fault diagnosis problem focuses on the three-phase PMSM. In this paper, compared to the most existing fault diagnosis approaches, a fault diagnosis method for Interturn short circuit (ITSC) fault of five-phase PMSM based on the trust region algorithm is presented. This paper has two contributions. (1) Analyzing the physical parameters of the motor, such as resistances and inductances, a novel mathematic model for ITSC fault of five-phase PMSM is established. (2) Introducing an object function related to the Interturn short circuit ratio, the fault parameters identification problem is reformulated as the extreme seeking problem. A trust region algorithm based parameter estimation method is proposed for tracking the actual Interturn short circuit ratio. The simulation and experimental results have validated the effectiveness of the proposed parameter estimation method.

Fault Diagnosis Method for a Network Control System with Long-Time Delay and Data Packet Loss Based on H∞ Filtering

2013 ◽  
Vol 846-847 ◽  
pp. 795-798
Author(s):  
Jiao Meng ◽  
Qi Hua Xu ◽  
Xiao Xiao
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Time Delay ◽  
Packet Loss ◽  
Estimation Error ◽  
Network Control ◽  
Data Packet ◽  
Practical Significance ◽  
Network Control System ◽  
Long Time

Improving network control system---NCS reliability and safety has important practical significance because NCS is a hot research subject in these years. Fault diagnosis methods are researched in this paper according to NCS with long-time delay and data packet loss. Firstly, given a NCS with long-time delay, a state observer is structured. Secondly, make the state estimation error equation equivalent to an asynchronous dynamical system having event incidence constraint according to whether the system having data packets loss. The problem of fault diagnosis is converted to filtering problem through structuring filtering residual system based on the observer, then giving a corresponding filter designing algorithm. The designed fault diagnosis filter system not only make sure the stability of the closed loop system but also make the residual systems norm less than given reduction level. Finally, the simulation results prove that the algorithm can diagnose faults effectively.

FAULT DIAGNOSIS IN A PROCESS EXPERIMENTAL CONTROL SYSTEM WITH UNKNOWN FACTORS

2008 ◽  
Vol 07 (01) ◽  
pp. 151-155 ◽  
Author(s):  
AKIRA INOUE ◽  
MINGCONG DENG
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Experimental System ◽  
Detection Problem ◽  
Experimental Control ◽  
Blind System Identification ◽  
Experimental Process ◽  
Identification Approach ◽  
Simulation Results ◽  
Detecting Method

A fault detection problem in a process control experimental system with unknown factors is presented in this paper. The fault detecting method is based on blind system identification approach. The experimental system actuator output includes unknown dynamics and unknown fault signal. By using the fault detecting method, the fault signal is detected. Simulation results for the experimental process are presented to show the effectiveness.

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