Fault predicting and diagnosing method suitable for dynamic complex system

Abstract

The invention provides a fault predicting and diagnosing method suitable for a dynamic complex system. The method can be applied in the field of fault prediction and diagnosis of dynamic complex systems of spacecrafts and the like. The method comprises the following steps of: performing failure mode and effect analysis (FMEA) on the dynamic complex system to obtain a main fault mode and corresponding performance detection parameters, dividing the performance detection parameters into slowly variable data and fast variable data, pre-processing the performance detection parameters, establishingan autoregressive moving average model (ARMA) aiming at the slowly variable data to perform time sequence prediction, establishing a multi-resolution wavelet neural network aiming at the fast variable data to perform time sequence prediction, performing fault early warning on the time sequence prediction results by establishing a prediction interval model, and performing fault diagnosis by establishing a D-S (Dempster-Shafer) evidence theory-based multi-signal fusion model. The method can be used for predicting and diagnosing the faults of the dynamic complex system with high precision, and has strong universality.

Description

technical field [0001] The invention belongs to the field of fault prediction and diagnosis of dynamic complex systems such as spacecraft, and provides a set of fault prediction and diagnosis methods for systems in the field with complex structures and a large amount of performance monitoring parameter data. Background technique [0002] Fault prediction refers to predicting the time and type of failure of the system in the future time period based on the past and present state of the system, aiming at uncertain events, using existing knowledge, and using predictive reasoning methods to find out the cause and occurrence of failure. Faulty parts, providing theoretical basis for planned repair and maintenance. [0003] Failure prediction techniques were originally developed for mechanical applications and are used in helicopters and complex mechanical systems and HUMS subsystems. For fault prediction technology, it can be divided into four categories from the perspective of t...

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Problems solved by technology

[0012] In order to solve the problem that it is difficult to establish a high-precision fault prediction model caused by factors such as system composition structure and operating environment, and the existing methods cannot directly and accurately solve the problem of fault prediction and diagnosis of dynamic and complex systems, the present invention provides an applicable Fault Prediction and Diagnosis Methods for Dynamic Complex Systems

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