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 centrifugal pump

A fault diagnosis and information entropy technology, applied in pump control, non-variable pumps, machines/engines, etc., can solve problems such as non-stationary, poor repeatability, and large amount of vibration signal information of centrifugal pumps, and achieve diagnosis High precision, suppression of modal aliasing, and good robustness

Active Publication Date: 2016-01-27
北京恒兴易康科技有限公司
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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-sta

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  • 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 centrifugal pump
  • 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 centrifugal pump
  • 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 centrifugal pump

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Embodiment Construction

[0026] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0027] 1. Introduction to the embodiment of the centrifugal pump fault diagnosis method based on CEEMD-STFT time-frequency information entropy and multi-SVM

[0028] 1.1 The flow of centrifugal pump fault diagnosis method based on CEEMD-STFT time-frequency information entropy and multi-SVM

[0029] The fault diagnosis process proposed by this method is as follows: figure 1 As shown, there are five main parts including data preprocessing, feature extraction, dimension reduction and pattern recognition, as follows:

[0030] The first step is data preprocessing. In order to improve the quality and efficiency of subsequent data processing, abnormal data in the original data were removed and normalized.

[0031] The second step is fault feature extraction. First, use the CEEMD decomposition method to adaptively decompose the preprocessed signal ...

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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...

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Application Information

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IPC IPC(8): F04D15/00
Inventor 刘红梅李连峰吕琛赵万琳王洋
Owner 北京恒兴易康科技有限公司
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