Wind turbine operating state fuzzy synthetic evaluation method based on Markov chain

A technology of fuzzy comprehensive evaluation and Markov chain, applied in the direction of instruments, data processing applications, calculations, etc., can solve the problems that it is difficult to accurately reflect the potential failure of the unit and prone to misjudgment

Inactive Publication Date: 2015-09-30
HUAQIAO UNIVERSITY
View PDF8 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Literature [12] and others [13、14] When calculating the degree of deterioration, only the current value of the index parameter is substituted, and it is difficult to accurately reflect the potential failure of the unit
Literature [15] aimed at

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
  • Wind turbine operating state fuzzy synthetic evaluation method based on Markov chain
  • Wind turbine operating state fuzzy synthetic evaluation method based on Markov chain
  • Wind turbine operating state fuzzy synthetic evaluation method based on Markov chain

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0076] Example 1

[0077] The present invention provides a fuzzy comprehensive evaluation method for wind turbine operating state based on Markov chain (also known as Markov chain) parameter prediction, including the following steps:

[0078] Step 1) Determine the evaluation level V of the operation state of the wind turbine; this embodiment takes the evaluation of the operation state of the wind turbine at a single moment as an example, and divides the operation state of the wind turbine into four evaluation levels, namely:

[0079] V = {Good, Passed, Attention, Serious} = {v 1 ,v 2 ,v 3 ,v 4}.

[0080]Step 2) Establish a hierarchical model of wind turbine operating status evaluation indicators: take the wind turbine operating status as the evaluation object, first divide the wind turbine into five sub-items, including the gearbox system, pitch system, generator system, control system and parallel Then, according to the principle of integrity, select the monitoring param...

Example Embodiment

[0177] Example 2

[0178] In this embodiment, the evaluation of the operating state of the wind turbines at continuous time is taken as an example. Table 8 shows the evaluation results of the wind turbine operating status at time T2-T6. Judging from the evaluation results of continuous time, the evaluation results of the proposed model are more in line with the actual operating status of the wind turbine analyzed before. The evaluation results of the traditional FSE model are relatively conservative , in contrast, the evaluation results of the improved FSE model can better reflect the potential failure of the unit, and if maintenance measures are taken at T4 time, the "serious" operating state can be avoided.

[0179] Table 8 State evaluation results at continuous time

[0180]

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 wind turbine operating state fuzzy synthetic evaluation method based on the Markov chain. Aiming at defects in deterioration degree calculation of a traditional fuzzy synthetic evaluation model, a Markov chain model is built, the variation trend of evaluation index parameters is introduced into the deterioration degree calculation, so that the deterioration degree calculation is more reasonable, and an evaluation result of the overall operating states of wind turbines is more objective and more accurate than a result obtained with a traditional method.

Description

technical field [0001] The present invention relates to a system operation state evaluation technology, more specifically, to a fuzzy comprehensive evaluation method for wind turbine operation state based on Markov chain parameter prediction. Background technique [0002] With the large-scale development of wind power generation, the wind power industry has played an important role in coping with climate change and adjusting the energy structure. However, due to the harsh operating environment of wind turbines and other influencing factors, wind turbine failures occur frequently, and as high as 10%-15% of the operation and maintenance costs have become the biggest bottleneck in the development of the wind power industry [1] Therefore, how to ensure the safe and reliable operation of wind turbines and reduce operation and maintenance costs has attracted great attention from experts and scholars. Carrying out wind turbine operation status evaluation research can effectively p...

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): G06Q50/06
Inventor 方瑞明江顺辉
Owner HUAQIAO UNIVERSITY
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