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For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, Willsky and Jones. have developed the Generalized Likelihood Ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system...
The problem of model-based fault detection is studied with application of the Kalman filter for residual generation. The filter has two important incoming parameters, the state noise and the output noise covariance matrices, which tuning is analyzed in order to optimize the fault detection performance. The problem is formulated through an appropriate optimization criteria and applied to the oscillatory...
Significant research has been carried out over the past three decades in the area of fault tolerant control. Most methods available in the chemical engineering literature are capable of detecting, identifying, estimating and accommodating faults for nonlinear processes with continuous states without state dependent and controlled switching. This work is aimed at developing a method for diagnosing...
In this paper, we present a multiple-model based method of analyzing for the longitudinal controller performance loss caused by actuator faults in the aircraft elevator system. More specifically, we consider the effects of the failure-induced elevator actuator bandwidth reduction integrated with the longitudinal flight dynamics. Results of the proposed multiple-model based fault detection, isolation,...
Forecasting the condition of the equipment is becoming an important ingredient of the advanced maintenance and asset management systems. In this paper a probabilistic approach to the prognosis of damage progression in gearboxes is presented. It is based on a stochastic nonlinear grey-box model of the underlying wear phenomena. Model parameters are estimated from the available vibration records by...
In this work, a new fault tolerant control (FTC) methodology is proposed to deal with the potential problems due to possible fault scenarios. For this purpose, a state estimation scheme has been developed using an adaptive unscented Kalman filter (AUKF) approach. A fuzzy-based decision making (FDM) algorithm is introduced to diagnose sensor and/or actuator faults. The proposed fault detection and...
In this paper, a new approach for state filtering of dynamic stochastic discrete-time systems affected by unknown inputs is presented. The proposed state filtering scheme includes a restricted diagonal detection filter generating a set of minimum variance white detection signals, each of them sensitive to a particular component of the unknown input vector. After having tested the statistical effect...
A new methodology is presented in this paper which incorporates the marginalized likelihood ratio (MLR) test for online fault detection and isolation. The proposed methodology reduces the number of optimization problems required for isolating the fault by means of a simple integration scheme. Moreover, the dependency on the accuracy of the statistical fault detection and confirmation tests is relaxed...
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