A Fault Classification Method Based on Big Data Fusion Cluster Analysis with Correlation Parameters

Abstract

The present invention provides a method for classification of associated parameter faults based on big data fusion clustering analysis. The fault classification method of the present invention selects fault data according to the interpretation rules from the massive data of equipment operation, and performs supervised machine autonomous clustering , to form the automatic classification results of associated parameter faults, which can solve the problem that the current equipment fault diagnosis is overly dependent on the expert knowledge base, while ignoring the correlation between the parameters of the deep nonlinear coupling between subsystems, and the massive effective The problem that the data has not been well mined and utilized; at the same time, because the implementation of the fault classification method of the present invention does not need to rely on the accurate physical modeling of the object equipment, it avoids the difficulty of traditional complex systems that are difficult to model, and realizes the problem based on massive The intelligent classification of faults and the analysis of associated parameters by data mining have the ability to classify faults with controllable accuracy.

Description

technical field [0001] The invention relates to the field of equipment failure prediction and health management (PHM), in particular to a method for classification of associated parameter failures based on big data fusion cluster analysis. Background technique [0002] Fault prediction and health management have developed into an important supporting technology and foundation for system logistics support, maintenance and autonomous health management in the aerospace field. In the "National Medium- and Long-Term Science and Technology Development "Life prediction technology" is proposed as a cutting-edge technology. In the development reports of aerospace and aviation science and technology disciplines in recent years, PHM technology is listed as a key and supporting technology. [0003] PHM technology has become an interdisciplinary and popular research direction covering basic materials, mechanical structures, energy, electronics, automatic testing, reliability, information...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the technical problem that the existing data-driven PHM method has difficulty in obtaining fault data. The status quo that equipment operation data containing massive information has not been effectively mined and utilized

Images