Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Fault early warning method for double-fed fan main shaft

A fault warning and main shaft technology, which is applied in the monitoring of wind turbines, wind turbines, prediction, etc., can solve the problem that the constant threshold warning cannot meet the warning requirements, and achieve the goal of ensuring the accuracy of fault prediction, occupying less memory, and improving the accuracy of prediction Effect

Active Publication Date: 2021-04-30
HEBEI UNIV OF TECH
View PDF5 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Traditional wind turbine fault early warning is generally realized by setting a single constant early warning threshold. This invention aims at the problem that the constant threshold early warning cannot meet the early warning requirements under complex working conditions, and proposes a wind turbine main shaft fault early warning method based on the improved whale algorithm to optimize LightGBM

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
  • Fault early warning method for double-fed fan main shaft
  • Fault early warning method for double-fed fan main shaft
  • Fault early warning method for double-fed fan main shaft

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] In order to illustrate the technical solutions of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and examples. The embodiments of the present invention and their descriptions are only for explaining the present invention, and are not intended to limit the present invention.

[0050] The flow chart of a fan shaft failure early warning method based on the improved LightGBM described in the embodiment of the present invention is as follows figure 1 As shown, the specific implementation steps are as follows:

[0051] S1: Select the main shaft temperature and its related data from the fan equipment, and perform data preprocessing to form the original data set: the specific steps include:

[0052] S1.1: The data related to the main shaft temperature comes from a doubly-fed fan;

[0053] S1.2: For the missing data in the original data set, an artificial experience value within ...

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 relates to a fault early warning method for a double-fed fan main shaft. The method comprises the following steps: selecting main shaft temperature and temperature related data of main shaft related parts from fan equipment; selecting features with high correlation with the spindle temperature from the original data set by adopting a Pearson correlation coefficient; optimizing parameters in the LightGBM prediction model by using a whale algorithm to obtain an optimized LightGBM normal main shaft temperature prediction model; inputting the test set data into the optimized LightGBM normal main shaft temperature prediction model to obtain a corresponding main shaft temperature prediction value, and performing residual analysis to obtain a main shaft temperature early warning threshold; and selecting characteristic data with relatively high correlation with the spindle temperature from the fan data to be early warned, inputting the characteristic data into the optimized LightGBM normal spindle temperature prediction model to obtain a current fan spindle temperature prediction value to be early warned, and performing residual analysis to judge a spindle temperature state so as to achieve early warning of a fan spindle fault.

Description

technical field [0001] The invention relates to a fault early warning method, in particular to a double-fed fan main shaft fault early warning method, especially a fan main shaft fault early warning method based on an improved whale algorithm to optimize LightGBM. Background technique [0002] As wind energy, as a renewable clean energy, is widely developed and utilized by various countries, the installed capacity of wind turbines continues to increase. Because wind turbines usually work in harsh environments and complex wind changes, resulting in frequent failures of wind turbines, effective early warning of key component failures in wind turbines has gradually attracted attention. As one of the important components of the wind turbine, the main shaft is also a part of the unit that frequently fails. A failure of the main shaft may even cause the entire wind turbine to fail to operate normally. Therefore, effective fault warning before the main shaft fault is of great sign...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/00G06Q50/06G06N3/00G06N5/00G06N20/20F03D17/00
CPCG06Q10/04G06Q10/20G06Q50/06G06N3/006G06N20/20F03D17/00G06N5/01
Inventor 林涛严寒李波函左逸琳王瑞祥石琳张哲程淑伟
Owner HEBEI UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products