New PDF release: Auxiliary Signal Design in Fault Detection and Diagnosis

By Xue J. Zhang

ISBN-10: 3540466436

ISBN-13: 9783540466437

ISBN-10: 3540515593

ISBN-13: 9783540515593

The item of this booklet is to give a scientific technique for auxiliary sign layout in fault detection and analysis. It covers platforms that may be represented by way of linear or linearised multiple-input, multiple-output stochastic types. it's very illustrative due to the fact that each one new notion is established with easy examples and plots. a few primary difficulties in swap detection were investigated. A uncomplicated wisdom of likelihood thought, statistical inference, matrix and keep watch over concept is needed. Postgraduates and researchers will locate it an attractive connection with fault detection and attempt sign layout. The e-book is additionally used as an instructional fabric for ultimate yr undergraduates, specially those that paintings on a undertaking relating to try out sign designs, fault detection or modeling.

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Extra resources for Auxiliary Signal Design in Fault Detection and Diagnosis

Example text

1 Design constraints The auxiliary signal design must take account of the constraints on the allowable operating conditions. For example, the auxiliary signal should be zero mean in order to avoid introducing any bias into the system. The other constraints could be on the amplitude or power of the inputs, outputs or internal variables of the system. ,r where u,~j is the maximum allowable magnitude of the j~a auxiliary signal uj(t) and a symmetric constraint is applied to ui(t ) so that the auxiliary signal can be 53 zero mean.

Fig. 8 shows the S P R T sequence when i n p u t - o u t p u t models are used. It is easy to see that the two S P R T cumulative sum behaviours are very similar except at the initial period. 66) H, - ~(t) = 0 . 606 × 10 -4 r e s p c c t i v e l y . T h e p a r a m e t e r s co a n d cl h a v e the following values: Co = - 0 . 3 1 3 9 , cl = - 0 . 3 8 3 7 . 1. It s h o u l d b e p o i n t e d o u t here t h a t lower b o u n d s a r e set for t h e p r o b a b i l i t y and t h e S P R T c u m u l a t i v e sums.

It is known that in system identification, optimal experiment design can assist in providing the 'best' system model according to selected criteria ([74], [23]). Roughly~ the key problem is how to select those experimeptM factors which are open to choice so as to maximize the sensitivity of the observed data to the parameters of interest. Keviczky (1972) has developed initial work for on-line input signal synthesis ([35]). A theoretical investigation into off-line test signal design is carried out by Zarrop (1979) [74], in the case of SISO systems.

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Auxiliary Signal Design in Fault Detection and Diagnosis by Xue J. Zhang

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