in this paper, a fault diagnosis system based on discrete wavelet transform (dwt) and artificial neural networks (anns) is designed to diagnose different types of fault in gears. dwt is an advanced signal-processing technique for fault detection and identification. five features of wavelet transform rms, crest factor, kurtosis, standard deviation and skewness of discrete wavelet coefficients of...

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...

We derive a Kalman filter based on data from a sliding window. This is used for a new approach to fault detection and diagnosis, where the state estimate from past data is compared to the state estimate of some of the future data. We suggest a method to judge the quality of diagnosis in a simple way. For fault estimation in the diagnosis, the general concept of stochastic observability in linea...

Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These inputs are disturbance inputs, reference inputs and auxiliary inputs. The diagnosis of the system is...

This paper reviews the use of set-membership methods in fault diagnosis (FD) and fault tolerant control (FTC). Setmembership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims at checking the consistency between observed and predicted behaviour by using simple sets to approximate the exact set of possible behavio...

-The paper reviews the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and presents some new results. It outlines the principles and most important techniques of model-based residual generation using parameter identification and state estimation methods with emphasis upon the latest attempts to achieve robustness with respect to modelling er...

To improve safety, reliability, and efficiency of automotive vehicles and other technical applications, embedded systems commonly use fault diagnosis consisting of fault detection and isolation. Since many systems are constructed as distributed embedded systems including multiple control units, it is necessary to perform global fault isolation using for example a central unit. However, the draw...

Fault detection and isolation are very important elements in the design of faulttolerant decision support systems for ship operator guidance. This study outlines remedies that can be applied for fault diagnosis, when the ship responses are assumed to be linear in the wave excitation. A novel numerical procedure is described for the calculation of residuals using the ship’s transfer functions wh...

This paper investigates the fault detection of a micro parallel plate capacitor subjected to nonlinear electrostatic force. For this end Thau observer, which has good ability in fault detection of nonlinear system has been presented and governing nonlinear dynamic equation of the capacitor has been presented. Upper and lower threshold for fault detection have been obtained. The robustness of th...