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
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[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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