Feature-processing-based complex equipment fault diagnosis method

Abstract

The invention provides a feature-processing-based complex equipment fault diagnosis method. The method comprises the following steps: step one, collecting an action current signal in real time; step two, carrying out segment division on the action current curve; step three, carrying out segment division on an action curve; step four, constructing a high-dimensional feature representation data setof an equipment action current curve; step five, carrying out feature selection on the high-dimensional feature representation data set; step six, carrying out feature extraction on the high-dimensional feature representation data set; step seven, carrying out division on the feature representation data set; step eight, carrying out optimizing solution on parameters of an SVM; step nine, carryingout SVM supervision learning to obtain a fault diagnosis model; and step ten, verifying the diagnosis accuracy rate of the fault diagnosis model by using testing set data. Therefore, the feature-processing-based complex equipment fault diagnosis method is realized; and the fault diagnosis classifier is realized by the parameter-optimized SVM method and thus the fault identification and analysis ofthe feature number of the working current curve of the equipment are completed.

Description

technical field [0001] The invention provides a complex equipment fault diagnosis method based on feature processing, which relates to the realization of a complex equipment fault diagnosis method based on feature processing, and belongs to the field of complex equipment reliability and complex equipment fault diagnosis. Background technique [0002] Fault diagnosis is a comprehensive emerging science that finds fault sources based on equipment operating status information and determines corresponding decisions. Fault diagnosis technology began in the 1960s, and after more than 50 years of development, it has made great progress. Its connotation has developed from the fault diagnosis of simple equipment to the fault diagnosis of complex systems. Today, fault diagnosis technology has been widely used in various industrial sectors. At present, the fault diagnosis of complex equipment mainly involves two problems: one is the feature description corresponding to the complex equ...

AI Technical Summary

Problems solved by technology

At present, the fault diagnosis of complex equipment mainly involves two problems: one is the feature description corresponding to complex equipment under different working modes, the difficulty lies in how to combine the features of the working state of the equipment concisely and efficiently; the other is the fault diagnosis model The difficulty lies in how to design the adaptability and fault tolerance of the diagnostic model, so that the model can make intelligent decisions according to the different working states of complex equipment, and accurately judge and identify faults

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