Although convolution neural network (CNN) has achieved certain success in fault detection and diagnosis (FDD) tasks the chemical engineering industry, performance credibility of CNN-based FDD methods are greatly limited by two factors. First, CNN relies upon strong temporal/spatial correlation data, which is very difficult to obtain generic tabular data. Second, most have poor interpretability ...

Actuator fault diagnosis problem is studied for a class of nonlinear systems with relative degrees from the inputs to the outputs higher than one. This type of nonlinear systems include many mechanical systems, and their actuator fault diagnosis problem can be very challenging because of nonlinearities and high relative degrees. In this paper, in order to solve the actuator fault diagnosis prob...

vehicle driveline system and its working accuracy play an important role in the performance of car. the purpose of this study is to provide an appropriate mechanism for investigating, identifying and determining the position and size of defects in the vehicle power transmission system. this is based on the patterns of the residual signal, obtained from a simulated model of the system. neuro-fuz...

in this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for v47/660kw wind turbine operated in manjil wind farm, gilan province, iran. according to the acquired data from iran wind turbine industry, common faults of the wind turbine such as sensor fault...

A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC...

SoC Functional Intellectual Property Infrastructure that differ by minimal set of the embedded diagnosis processes in real time and enables to realize such services like functional testing on basis of generable input patterns and analysis of output reactions; SoC diagnosis with given resolution of fault location; fault simulation to carry out the first two procedures on basis of the fault detec...

A reliable and accurate diagnosis of inter-turn short circuit faults is a challenging problem in the area of fault diagnosis of electrical machines. The purpose of this challenge is to be more efficient in fault detection and to provide a reliable method with low-cost sensors and simple numerical algorithms which not only detect the occurrence of the fault, but also locate its position in the w...

This paper presents a fault detection, diagnosis, and reconfiguration method based on support vector machines. This method is appropriate for certain or predetermined faults and involves a fault detection and diagnosis unit and an online controller selection type reconfiguration mechanism. In this method, when a fault is detected and diagnosed by the fault detection and diagnosis unit, a suitab...

A fault diagnosis and compensation problem for two-dimensional discrete time systems with time-varying state delays is studied in this paper. The concerned two-dimensional systems are described by the Fornasisi– Marchesini second model and are subject to unknown disturbances. First, a fault detection and diagnosis module is designed to obtain the information on sensor faults; a new fault detect...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...