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...

rotating machinery is the most common machinery in industry. the root of the faults in rotating machinery is often faulty rolling element bearings. this paper presents a technique using optimized artificial neural network by the bees algorithm for automated diagnosis of localized faults in rolling element bearings. the inputs of this technique are a number of features (maximum likelihood estima...

Fault detection is a crucial step in condition based maintenance requiring. The importance of fault diagnosis necessitates an efficient and effective failure pattern identification method. Artificial Neural Networks (ANN) and Support Vector Machines (SVM) emerging as prospective pattern recognition techniques in fault diagnosis have been showing its adaptability, flexibility and efficiency. Reg...

The aim of this paper is to develop an intelligent diagnosis method for fault detection and isolation in induction motors. We consider failures in three components of induction motor: bearing, stator winding and rotor winding. Firstly, a model-based nonlinear observer in the proposed method is designed based on available information. The fault detection decision is carried out by comparing the ...

this paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. the methodology is based on a modified sliding mode observer (smo) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. the faults are reconstructed using the equivalent output error i...

Steering assist system controls the force transfer behavior of the steering system and improves the steering probability of the vehicle. Moreover, it is an interface between the diver and vehicle. Fault detection in electrical assisted steering systems is a challenging problem due to frequently use of these systems. This paper addresses the fault detection and reconstruction in automotive elect...

This paper proposes a weak signal detection strategy for rolling element bearing fault diagnosis by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods–Saxon (WS) potential. The WS potential has the distinct structure with smooth potential bottom and steep potential wall, which guarantees a stable particle motion within the potential and avoids the unexpected n...

The failure of rotating machinery sometimes involves several faulty components. Existence of both bearing fault and gearbox fault is widely observed and in this situation the vibration feature of the bearing fault can be masked by the faulty gearbox vibration signals. In this research, a method is proposed based on wavelet packet transform and envelope analysis to extract fault features of the ...

Current spectrum analysis is a proven technique for fault diagnosis in electrical machines. Current spectral estimation is usually performed using classical techniques such as periodogram (FFT) or its extensions. However, these techniques have several drawbacks since their frequency resolution is limited and additional post-processing algorithms are required to extract a relevant fault detectio...