Fan gear box fault diagnosis model establishing method and device

A technology for fault diagnosis model and establishment method, which is applied in the direction of machine gear/transmission mechanism testing, measuring device, neural learning method, etc., which can solve the problems of low diagnosis efficiency and poor accuracy of fan gearboxes

Inactive Publication Date: 2017-07-07
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF4 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Therefore, the technical problem to be solved by the present invention lies in the def

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fan gear box fault diagnosis model establishing method and device
  • Fan gear box fault diagnosis model establishing method and device
  • Fan gear box fault diagnosis model establishing method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] This embodiment provides a method for establishing a fault diagnosis model of a wind turbine gearbox, which is used to establish a fault diagnosis model of a wind direction gearbox, and the model is used for fault diagnosis of a wind turbine gearbox. The flow chart of the method is as figure 1 mentioned, including:

[0053] S1. Obtain the vibration signal of the fan gearbox. The vibration signal of the fan gearbox under normal and typical fault conditions is collected by the vibration sensor. The vibration signal can include normal vibration signal, vibration signal when the inner ring of the gearbox bearing is faulty, vibration signal when the outer ring of the gearbox bearing is faulty, and vibration signal when the tooth is broken. some or all of the .

[0054] In this embodiment, the vibration signal of the wind turbine gearbox is obtained through the vibration sensor installed on the wind turbine gearbox, which includes four kinds of vibration signals under four ...

Embodiment 2

[0089] A device for establishing a fault diagnosis model of a wind turbine gearbox, the structural block diagram is as follows figure 2 As shown, used to build a diagnostic model, which includes

[0090] The signal acquisition unit 01 is used to acquire the vibration signal of the fan gearbox;

[0091] A preprocessing unit 02, configured to perform smoothing and noise reduction processing on the vibration signal;

[0092] The feature vector extraction unit 03 is used to decompose the processed vibration signal and extract the feature vector of the vibration signal;

[0093] The data set setting unit 04 is used to divide the feature vector of the vibration signal into a training data set and a test data set;

[0094] The model generation unit 05 is used to optimize the parameters of the radial basis neural network model by using the fruit fly algorithm, input the eigenvector of the vibration signal in the training data set to obtain the optimal value of the parameters, and g...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a fan gear box fault diagnosis model establishing method used for establishing a fan gear box fault diagnosis model. The method comprises a step of obtaining a vibration signal of a fan gear box and then carrying out smoothing and denoising processing on the vibration signal, a step of decomposing the processed vibration signal and extracting the characteristic vector of the vibration signal, a step of dividing the characteristic vector of the vibration signal into a training data set and a testing data set, and a step of using a Drosophila algorithm to optimize a parameter of a radial basis function (RBF) neural network model, inputting the characteristic vector of the vibration signal in the training data set to obtain the optimal value of the parameter, generating the fan gear box fault diagnosis model based on a radial basis function neural network and carrying out test. In the scheme, the optimization algorithm is introduced for the characteristic of the RBF neural network, through introducing the artificial intelligence analysis technology, the extracted characteristic value is processed further, thus the efficiency of fault diagnosis is improved, and stop losses caused by faults are reduced.

Description

technical field [0001] The invention relates to the field of fault diagnosis, in particular to a method for establishing a fault diagnosis model of a fan gearbox. Background technique [0002] The global energy problem is becoming more and more prominent. The non-renewability of fossil fuels and the adverse impact on the global climate have led countries to introduce policies to alleviate the crisis caused by energy shortages. Developing new energy and renewable energy and gradually reducing the use of fossil energy are strategic and important measures for protecting the ecological environment and sustainable social and economic development. With the development of economy, renewable energy represented by wind power is developing rapidly all over the world. my country is also a big country in the development of the wind power industry. By the end of 2015, the cumulative number of installed wind turbines and cumulative installed capacity in China ranked first in the world. ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01M13/02G06N3/08
CPCG01M13/021G01M13/028G06N3/08
Inventor 黄从智李岩朱红路
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap