Mechanical fault monitoring and diagnosis system establishment method based on SDAE-RCmvMSE

A diagnostic system and mechanical failure technology, which is applied in the establishment of SDAE-RCmvMSE-based mechanical failure monitoring and diagnosis system, can solve the problems of large signal noise, difficulty in extraction, poor stability of vibration signals, etc.

Active Publication Date: 2020-12-29
HUBEI UNIV OF TECH
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem of poor stability of mechanical equipment vibration signals and the difficulty of extracting signal features d

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  • Mechanical fault monitoring and diagnosis system establishment method based on SDAE-RCmvMSE
  • Mechanical fault monitoring and diagnosis system establishment method based on SDAE-RCmvMSE
  • Mechanical fault monitoring and diagnosis system establishment method based on SDAE-RCmvMSE

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Embodiment Construction

[0062] Embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but should not be used to limit the scope of the present invention.

[0063] 1. System composition

[0064] This project uses a mechanical fault monitoring and diagnosis system based on SDAE-RCmvMSE, which includes an acceleration sensor unit, an embedded industrial control machine and an audible and visual alarm device. The embedded industrial control all-in-one machine is composed of industrial computer, data acquisition module, diagnostic model, display screen and other functional modules. The system composition is as follows: figure 1 shown.

[0065] 2. System workflow

[0066] Install the acceleration sensor in the appropriate position of the mechanical equipment to be monitored. After the system is started, the embedded industrial control all-in-one machine...

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Abstract

The invention discloses a mechanical fault monitoring and diagnosis system establishment method based on SDAE-RCmvMSE. The method comprises the following steps of: firstly, acquiring vibration signalsof equipment through n vibration sensors, training an SDAE model in a diagnosis model through acquired digital signals under different working conditions, and obtaining optimal parameters of the SDAEmodel; extracting an RCmvMSE value of the acquired digital signal to train an SVM classifier, and obtaining an optimal parameter of the SVM; and deploying the SDAE, the RCmvMSE and the SVM into an embedded industrial control all-in-one machine to complete fault diagnosis model deployment, and putting the fault diagnosis model into use on site. The diagnosis model established through the method ishigh in fault recognition accuracy and good in fault tolerance performance.

Description

technical field [0001] The invention belongs to the field of mechanical fault detection, and relates to a fault detection system based on deep learning, in particular to a method for establishing a mechanical fault monitoring and diagnosis system based on SDAE-RCmvMSE. Background technique [0002] Rotating machinery parts are the most widely used in mechanical equipment, and their failures are also relatively common. It is of great significance to monitor and accurately diagnose the faults of mechanical equipment to ensure the normal operation of the equipment. Due to the complex fault types of mechanical equipment in the actual environment, its vibration signals often have unsteady and nonlinear characteristics. It is difficult to accurately diagnose faults by traditional time-frequency analysis methods. [0003] Commonly used non-time-frequency analysis methods include fractal method, sample entropy, permutation entropy, multi-scale permutation entropy, compound multi-s...

Claims

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Application Information

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IPC IPC(8): G01M13/00G01M13/045G06K9/00G06K9/62
CPCG01M13/00G01M13/045G06F2218/12G06F18/214G06F18/241
Inventor 杨光友习晨博刘浪陈学海马志艳姜帆姜洪远刘威宏
Owner HUBEI UNIV OF TECH
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