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Large semi-direct drive unit health status assessment method

A healthy state, semi-direct drive technology, applied in the direction of complex mathematical operations, etc., can solve the problems of lack of technical support and difficulty in finding early defects of wind turbines, etc.

Inactive Publication Date: 2018-11-23
GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Even if the fan does not fail, it is difficult to find the early defects of the fan through ordinary fan operation and maintenance
There are many difficulties in realizing preventive maintenance, and there is a lack of necessary technical support

Method used

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  • Large semi-direct drive unit health status assessment method
  • Large semi-direct drive unit health status assessment method
  • Large semi-direct drive unit health status assessment method

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0050] The present invention will be further described below in conjunction with specific examples.

[0051] Such as figure 1 As shown, the method for evaluating the health status of large-scale semi-direct drive units provided by this embodiment is as follows:

[0052] 1) The second-level data of each fan in the wind farm is collected through the wind farm SCADA system or the centralized control system of the big data platform. The time for fan second-level data collection is in days and the unit of measurement of the collection tag points is consistent.

[0053] 2) Preprocess the data, clean the outliers and missing data; then divide the second-level data into time intervals, and calculate the average values ​​of 10 minutes, 1 minute and 10 seconds respectively.

[0054] 3) Determine the state evaluation grades of the wind turbine health state evaluation model as good (A), qualified (B), attention (C), serious (D), and shutdown (E).

[0055] 4) Determine the factor set of ...

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Abstract

The invention discloses a large semi-direct drive unit health status assessment method. The insufficiency of the prior art and the passive operation and maintenance are remedied. The method comprisesthe following steps: selecting related variables influencing the status operations of the complete fan and various key parts; establishing a fan operation health status assessment model by using a variable weight theory and the fuzzy comprehensive evaluation algorithm, and performing real-time assessment on the operation statuses of the whole fan and various key parts. On a bit data platform, thedata transmitted in real time is operated through the health status assessment model, the output statuses of the whole fan and various key parts comprise five different levels: good, qualified, attention, serious, and halt; the real-time monitoring and assessment on the operation statuses of the whole fan and various key pars are realized. The field staff of the wind power plant adopts the corresponding operation and maintenance measures through the judgement on the result analysis of the health status assessment model, thereby realizing preventive maintenance.

Description

technical field [0001] The invention relates to the technical field of wind power intelligent operation and maintenance, in particular to a method for evaluating the health status of a large semi-direct drive unit. Background technique [0002] Wind turbines are the key equipment of wind farms, and their operational reliability is closely related to the economic benefits of wind farms. A wind turbine is an extremely complex system consisting of a variety of mechanical, electrical and control components. Any failure of any component may cause the unit to shut down, and serious failures may even affect the stable operation of the power system. [0003] The downtime of wind turbines and the decline in power generation performance of wind turbines are the biggest reasons for the loss of power generation. If the failure of wind turbines can be avoided in advance or measures can be taken before the performance of wind power generation declines, the loss of power generation will be...

Claims

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Application Information

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IPC IPC(8): G06F17/10
CPCG06F17/10
Inventor 柴飞飞葛婧孙安平王起昆李永战
Owner GUANGDONG MINGYANG WIND POWER IND GRP CO LTD
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