Motor fault detection and diagnosis involves processing a large amount of information of the motor system. With the combined synergy of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault detection/diagnosis process and successful fault detection/diagnosis schemes can be achieved. This paper presents two neural fuzzy (NN/FZ) inference systems, na...

The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated in a standard setup and a synthesis method for the fault detector is given. Further, fault detectio...

This paper considers robust fault detection for nonlinear systems with full state information. We propose and solve a multi-objective fault detection criterion by maximizing the smallest singular value of the transformation from faults to fault detection residuals while decoupling/or minimizing the largest singular value of the transformation from disturbance to the fault detection residuals.

Numerical magnetic field analysis is used for predicting the performance of an induction motor and a slip-ring generator having different faults implemented in their structure. Virtual measurement data provided by the numerical magnetic field analysis are analysed using modern signal processing techniques to get a reliable indication of the fault. Support vector machine based classification is ...

this paper presents a method for diagnosis of eccentricity fault in a switched-reluctance motor (srm) during offline and standstill modes. in this method, the fault signature is differential induced voltage (div) achieved by injecting diagnostic pulses to the motor windings. it will be demonstrated by means of results that there is a correlation between differential induced voltage and eccentri...

A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred senso...

This paper deals with a fault detection for a magnetic suspension system by using Generalized Internal Model Control (GIMC) structure. To design robust fault detection filters, two fault detection design problems are formulated as multiple objective optimization problems by minimizing the effects of disturbances and maximizing the fault sensitivity involving an LTI system with disturbance and f...

This paper presents a methodology that designs a fault detection Artificial Immune System (AIS) based on immune theory. The fault detection is a challenging problem due to increasing complexity of processes and agility necessary to avoid malfunction or accidents. The key fault detection challenge is determining the difference between normal and potential harmful activities. A promising solution...