A Centrifugal Pump Fault Diagnosis Method Based on Ceemd-stft Time-Frequency Information Entropy and Multi-SVM

Abstract

The invention provides a CEEMD (Complementary Empirical Mode Decomposition)-STFT (Short-Time Fourier Transform) time-frequency information entropy and multi-SVM (Support Vector Machine) based fault diagnosis method for a centrifugal pump. The method comprises the following steps: 1, preprocessing the fault data of the centrifugal pump; 2, extracting fault features; 3, performing dimensionality reduction for the fault features; 4, automatically recognizing a fault mode through a multi-SVM classifier. Vibration signals of the centrifugal pump have the characteristics of being non-stable and low in repeatability and reproducibility, so that some traditional time domain or frequency domain based analysis methods cannot timely reflect the running conditions of a system. The CEEMD is a self-adaptive signal decomposition method and can decompose the signals into a series of intrinsic mode functions; the STFT is a time-frequency analysis method and can analyze non-stable signals; the time-frequency information entropy is a metric of the signal time-frequency distribution complexity and can reflect the fault information hidden in the signals. According to the method, the CEEMD, the STFT and the information entropy method are combined; the method is applied to the actual diagnosis experiment, and the data analysis result shows that the method is high in diagnosis accuracy.

Description

technical field [0001] The present invention relates to the technical field of fault diagnosis of centrifugal pumps, in particular to a CEEMD-STFT (Complete Integrated Empirical Mode Decomposition-Short Time Fourier Transform) time-frequency information entropy and multi-SVM (multi-class support vector machine) Centrifugal pump fault diagnosis method. Background technique [0002] In the past 20 years, with the rapid development of science and technology, equipment fault diagnosis technology has gradually matured. As a new marginal subject, it has flourished in the field of comprehensive engineering. As a basic measure to ensure the safe operation of equipment, fault diagnosis can effectively predict the early fault development level of equipment, determine the cause of fault formation, analyze the incentives and put forward countermeasures and suggestions, and deal with existing hidden dangers to avoid or reduce the risk of accidents. occur. After entering the 21st centur...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is: the vibration signal of the centrifugal pump has the characteristics of large amount of information, non-stationary, poor repeatability, etc., so that some analysis methods based on the traditional time domain or frequency domain cannot reflect the operating status of the system in time

Images