Machine pump fault diagnosis method and device based on random forest classification

A random forest classification and fault diagnosis technology, applied in the measurement device, random CAD, testing of mechanical parts, etc., can solve problems such as the inability to achieve rapid and accurate diagnosis of machine and pump faults, and achieve overcoming uncertainty, good robustness, The effect of efficient training

Inactive Publication Date: 2021-09-17
ZHEJIANG UNIV
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Problems solved by technology

[0007] The purpose of the embodiments of the present invention is to provide a machine pump diagnosis method and device based on random forest classification to solve the technical problem in the related art that it is impossible to quickly and accurately diagnose machine pump failures

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  • Machine pump fault diagnosis method and device based on random forest classification
  • Machine pump fault diagnosis method and device based on random forest classification
  • Machine pump fault diagnosis method and device based on random forest classification

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[0037] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0038] The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term...

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Abstract

The embodiment of the invention discloses a machine pump fault diagnosis method and device based on random forest classification. The method comprises the steps: acquiring Z-axis vibration signal components in a machine pump fault state and a normal state; preprocessing the Z-axis vibration component to obtain the frequency domain signal; then training the frequency domain signal by adopting a random forest method, and establishing a relationship between the frequency domain signal and a fault state to obtain a fault diagnosis model; and inputting a to-be-diagnosed pump frequency domain signal into the fault diagnosis model, and judging the fault state of the pump. According to the method, by using random forest classification, calculation is convenient, the diagnosis speed is high, and the real-time performance and accuracy of fault diagnosis are improved; therefore, the method reduces the cost of fault diagnosis, and has a good practical value.

Description

technical field [0001] The invention relates to machine pump maintenance technology, in particular to a random forest classification machine pump fault diagnosis method and device. Background technique [0002] Equipment condition monitoring and fault diagnosis technology originated in the 1960s. Under the background of industrial production becoming modernized and automated, the research and development of fault diagnosis technology for rotating machinery is extremely active and developing rapidly. [0003] In the process industry, the general equipment investment is large, the continuous production process is long, and the loss caused by mechanical equipment failure is large. It depends on fault diagnosis to carry out effective, fast and accurate state assessment of faulty equipment, so that equipment abnormalities can be detected early. And timely and effectively deal with equipment abnormalities or failures. [0004] The existing industrial water pump fault diagnosis t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/17G06F30/27G06K9/62G01M13/00G01M13/022G01M13/028G01M13/045G06F111/08
CPCG06F30/17G06F30/27G01M13/00G01M13/022G01M13/028G01M13/045G06F2111/08G06F18/24323G06F18/214
Inventor 项子鑫孙琦铭黄磊杨春节
Owner ZHEJIANG UNIV
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