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A method for fault diagnosis of wind turbine bearings

A fault diagnosis and wind turbine technology, applied in the direction of mechanical bearing testing, etc., can solve problems affecting the grid voltage stability, affecting the safe operation of the system, etc., to achieve a wide range of diagnostics, ensure safe operation, and convenient and fast diagnostic methods

Active Publication Date: 2021-06-08
SHANDONG UNIV OF SCI & TECH
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

[0002] The bearing failure rate of wind turbines accounts for more than 40% of all failures, and the bearing failures of wind turbines not only affect the safe operation of the system, but also affect the voltage stability of the grid

Method used

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  • A method for fault diagnosis of wind turbine bearings
  • A method for fault diagnosis of wind turbine bearings
  • A method for fault diagnosis of wind turbine bearings

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Embodiment 1

[0048] The present invention applies the negative / positive selection algorithm to four groups of sample data, thereby generating a detector, which can be used for fault detection and separation of test data. The flow chart is shown in figure 1 .

[0049] I. Description and steps of the negative / positive selection algorithm including data representation, matching rules and generation of detectors.

[0050] 1) Data representation: Data representation has a significant impact on matching rules and detector generation. There are four types of data including numeric data, categorical data, Boolean data and text data. The representation can be roughly divided into string, real-valued vector and matrix forms. In the present invention, data will be presented in the form of binary strings.

[0051] 2) Matching rules: matching rules, which are also the calculation method of affinity, describe the similarity between antibodies and antigens. The Hamming distance is defined as the sum ...

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Abstract

The invention discloses a method for wind turbine bearing fault diagnosis, comprising: bearing fault detection and bearing fault separation, the steps of bearing fault detection are: acquiring data to be detected, extracting characteristic values ​​from the data to be detected, and converting them into binary string; compare the binary string of the data to be detected with detector 1 according to the Hamming distance formula, if they do not match, the bearing is healthy, and if they match, the bearing is faulty. The step of separating the bearing fault is: obtain the data to be detected, extract the characteristic value from the data to be detected, and convert it into a binary string; compare the binary string of the data to be detected with the detector i+1 according to the Hamming distance formula, if If there is no match, fault i is not present, if there is a match, fault i is present, where i ≥ 1. The method provided by the invention is convenient and fast, has wide and accurate diagnosis range, can ensure the safe operation of the wind turbine, and has great significance to the field of wind power generation.

Description

technical field [0001] The invention belongs to the technical field of fault detection of wind power generators, and in particular relates to a method for fault diagnosis of wind power generator bearings. Background technique [0002] The bearing failure rate of wind turbines accounts for more than 40% of all failures, and the bearing failures of wind turbines not only affect the safe operation of the system, but also affect the voltage stability of the grid. Therefore, bearing fault diagnosis is very important for the safety and reliability of wind turbine systems. Artificial immune algorithm is a new fault diagnosis method inspired by biological immune recognition in recent years. [0003] The biological immune system is a highly complex, self-organizing and self-adaptive parallel distribution system that can distinguish self from non-self, resist the invasion and infection of foreign pathogens, and maintain the body's own stability and balanced physiological activities. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/04
CPCG01M13/04
Inventor 王向华任衍恒张春明
Owner SHANDONG UNIV OF SCI & TECH