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One-way valve fault diagnosis method based on total variation noise reduction and RQA

A fault diagnosis and total variation technology, applied in mechanical valve testing, pattern recognition in signals, instruments, etc., can solve the problem of difficulty in accurately extracting equipment operating state characteristics, harsh working environment of high-pressure diaphragm pumps, and background of check valve vibration signals. noise, etc.

Pending Publication Date: 2021-01-05
KUNMING UNIV OF SCI & TECH
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  • Application Information

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a check valve fault diagnosis method based on total variation noise reduction and RQA, which is used to solve the problem of check valve vibration signal due to the harsh working environment of the high-pressure diaphragm pump and the complex structure of the mechanical system. There is background noise, and it is difficult to accurately extract the characteristics of equipment operating status. We are committed to improving the accuracy of check valve fault diagnosis

Method used

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  • One-way valve fault diagnosis method based on total variation noise reduction and RQA
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  • One-way valve fault diagnosis method based on total variation noise reduction and RQA

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Embodiment 1

[0087] Embodiment 1: as figure 1 As shown, a check valve fault diagnosis method based on total variation noise reduction and RQA, the specific steps are:

[0088] Step1: Use the acceleration sensor to sample when the check valve is normal, the valve is stuck, and the wear is faulty, and the vibration data of the check valve in each state is obtained.

[0089] Step2: Use the total variation noise reduction algorithm to perform noise reduction processing on the data samples in the three states of the check valve.

[0090] Step3: Draw the recursive graphs for the denoised signals, and extract the characteristic parameters in the recursive graphs through recursive quantitative analysis to form a eigenvector matrix.

[0091] Step4: The feature matrix is ​​normalized, and the compensation distance evaluation technology is used for feature scoring to obtain the sensitivity evaluation of each feature, and the features with high sensitivity form a new feature set.

[0092] Step5: Ran...

Embodiment 2

[0108] Embodiment 2: In order to reflect the superiority of the processing method of the present invention, the necessity of denoising the signal and then extracting features and the superiority of RQA in fault feature extraction, the RQA feature is directly extracted from the non-noise-reduced signal to form a feature vector . After the signal is denoised, 12 traditional time-domain statistical features (peak-to-peak value, root mean square, variance and kurtosis indicators, etc.) are extracted to form a feature vector. Then, the above two groups of feature vectors are selected through the compensation distance evaluation technique to select two features with good fault representation and input them into the weighted KNN classifier for comparison. The settings of the weighted KNN classifier and the number of repeated experiments are consistent with those in this paper. Table 5 is the comparison of fault diagnosis results in different situations. The comprehensive results sh...

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Abstract

The invention relates to a one-way valve fault diagnosis method based on total variation noise reduction and RQA, and belongs to the technical field of mechanical fault diagnosis and signal processing. The method comprises the steps of firstly, using a total variation noise reduction method for reducing noise of vibration signals, and increasing the signal-to-noise ratio; then, drawing a recurrence plot for the signal after noise reduction, extracting nonlinear characteristic parameters in the recurrence plot through a recursive quantitative analysis (RQA) method, carrying out sensitivity analysis on the extracted characteristic parameters through a compensation distance evaluation technology, and finding out characteristic parameters with higher sensitivity to form a characteristic vector; and finally, inputting the obtained feature vector into a weighted K nearest neighbor classifier (KNN) to complete the identification of the fault type of the one-way valve. Compared with the priorart, the method mainly solves the problems of low signal-to-noise ratio and unobvious fault representation caused by the fact that the one-way valve vibration signal is submerged by strong backgroundnoise, effectively improves the accuracy of one-way valve fault diagnosis, and has a certain engineering application value.

Description

technical field [0001] The invention relates to a check valve fault diagnosis method based on total variation noise reduction and RQA, and belongs to the technical field of mechanical fault diagnosis and signal processing. Background technique [0002] Reciprocating high-pressure diaphragm pumps, as the main power equipment for slurry pipeline transportation, are widely used in the transportation of high-concentration and highly corrosive slurry materials. As the most frequently moving part of the high-pressure diaphragm pump, the check valve is the most prone to failure in actual work. Once the check valve breaks down and loses its tightness, it will cause the high-pressure diaphragm pump system to be paralyzed, affect the smelting process at the end of the transportation, and cause heavy losses and production accidents. Therefore, it is of great significance to carry out fault diagnosis on the check valve. However, due to the complexity of the mechanical system of the di...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G01M13/003
CPCG01M13/003G06F2218/10G06F2218/04G06F2218/12G06F18/24147
Inventor 黄国勇何冬
Owner KUNMING UNIV OF SCI & TECH
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