Diagnostics of continuous dynamic systems using structure sensitivity functions

Abstract

The paper considers an algorithm for searching for single defects of structural blocks of a diagnostic object in the form of an arbitrary change in the parameters of one dynamic block as part of a continuous dynamic system. This approach corresponds to the real picture of the manifestation of a specific structural defect in the unit and its influence on the dynamics of the system. The use of known algorithms of this kind is complicated by the need to use models with trial deviations of parameters, or by the need to analyze the signs of signal transmissions. The algorithm based on trial deviations of model parameters uses the specification of these changes in the model, which is a laborious task. The algorithm for analyzing transmission signs using a normalized diagnostic feature, as well as using a binary diagnostic feature, requires additional calculations of the signs of signal transmissions from block outputs to checkpoints. An algorithm for searching for single defects in the form of changes in the parameters of dynamic blocks is considered, based on the use of a model of the structural sensitivity of integral estimates of the output signals of an object to changes in the dynamic properties of a block. The algorithm allows you to move from the analysis of time functions to the analysis of the numerical values of their integral estimates. This approach allows you to identify a faulty dynamic unit without determining the actual parameters of its transfer function. The procedure for obtaining normalized diagnostic features and calculating a quantitative measure of the distinguishability of defects has been determined. The results of the implementation of the algorithm for the gas pressure stabilization system at a straight-tube furnace for heating oil products of an oil refinery are presented. The implementation of the algorithm shows that the considered algorithm gives acceptable values of the distinguishability of all single defects.