A Method of Pump Health Diagnosis Based on Support Vector Machine

Abstract

The invention relates to machine pump maintenance technology, and aims to provide a machine pump health diagnosis method based on a support vector machine. Including: collecting real-time vibration signal data during the operation of the machine pump, and analyzing the vibration signal in the time-frequency domain; extracting the time-frequency domain characteristic signal from the frequency-domain waveform diagram obtained by the time-frequency domain analysis; extracting the time-frequency domain characteristic signal Substitute into the trained support vector machine health diagnosis model for diagnosis, and obtain the fault conditions of the pump's operating status. The present invention uses a plurality of second-class support vector machines, which has simple structure and convenient calculation, and improves the speed and accuracy of fault diagnosis; greatly reduces the number of support vector machines, and avoids classification overlapping and unclassifiable phenomena; support vector machines The diagnostic model can be updated in real time as the actual samples change; the requirements on the structure and quantity of data samples are reduced, the difficulty of the problem is greatly simplified, and it has good practical value.

Description

technical field [0001] The invention relates to machine pump maintenance technology, in particular to a support vector machine-based machine pump health diagnosis method, which is the application of statistical analysis technology and machine learning technology in machine pump health diagnosis. Background technique [0002] After the support vector machine was officially published in 1995, due to its excellent performance in text classification tasks, it quickly became the mainstream technology of machine learning, and directly set off a learning climax of "statistical learning". Support vector machine is a new nonlinear pattern recognition method, which has better classification accuracy and generalization ability than traditional neural network and Bayesian network algorithm. In addition, the support vector machine is a typical binary classifier, which has low requirements on the number of sample data and is easy to implement. At the same time, with the development of var...

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Problems solved by technology

[0003] Mechanical and pump equipment such as fans, water pumps, and air compressors are key equipment in modern enterprises such as petrochemical, metallurgy, steel, and electric power. Its fault diagnosis and health monitoring have always been difficult, and there is no specific implementation using support vector machines. Method of pump health diagnosis

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