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Wind turbine generator transmission chain fault early warning method based on big data analysis

A technology for wind turbines and fault warning, applied in wind turbines, machines/engines, electrical digital data processing, etc., can solve problems such as affecting the service life of the transmission chain, and achieve the effects of reducing losses, facilitating maintenance, and accurate warning results.

Pending Publication Date: 2022-04-08
XIAN THERMAL POWER RES INST CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, in the actual application process of the current wind turbines, the transmission chain on the wind turbines will break down after a long time, and because it cannot be found in time, it will affect the service life of the transmission chain, and it cannot be a good early warning.

Method used

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  • Wind turbine generator transmission chain fault early warning method based on big data analysis
  • Wind turbine generator transmission chain fault early warning method based on big data analysis

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Embodiment 1

[0039] The present invention provides a wind turbine transmission chain fault warning method based on big data analysis, comprising the following steps:

[0040] S1. Numerical simulation: establish a flexible multi-body system dynamic model, and simplify the complex wind turbine transmission system model into an equivalent dynamic model; specifically: use the dynamic topology diagram, and input the wind turbine transmission in the dynamic topology diagram After inputting the parameters of each component of the chain, connect each component through the force element to complete the system model;

[0041] S2. Regional analysis: based on the flexible multi-body system dynamic model obtained in step S1, the modal calculation is carried out to obtain the natural frequency value and mode shape of the fan drive chain system. Specifically: firstly, the cut-in, cut-out and The modes of the transmission chain system in the stud state are calculated separately, and then according to the ...

Embodiment 2

[0058] The present invention provides a wind turbine transmission chain fault warning method based on big data analysis, comprising the following steps:

[0059] S1. Numerical simulation: establish a flexible multi-body system dynamic model, simplify the complex wind turbine transmission system model into an equivalent dynamic model, use the dynamic topology diagram, and input the various components of the wind turbine transmission chain in the dynamic topology diagram After inputting the parameters, each component is connected through the force element to complete the system model;

[0060] S2. Regional analysis: Carry out modal calculation on the basis of the system model in step S1 to obtain the natural frequency value and mode shape of the fan transmission chain system. Carry out separate calculations, and then draw the Campbell diagram of the natural frequencies within the operating speed of the transmission chain according to the selected natural frequencies;

[0061] S...

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Abstract

The invention provides a wind turbine generator transmission chain fault early warning method based on big data analysis. The wind turbine generator transmission chain fault early warning method comprises the following steps: step 1, establishing a flexible multi-body system dynamic model corresponding to a wind turbine generator transmission chain; step 2, obtaining a resonance point corresponding to the wind turbine generator transmission chain according to the obtained flexible multi-body system dynamic model, and determining an element with abnormal vibration in the wind turbine generator transmission chain according to the obtained resonance point; step 3, setting a test point of the wind turbine generator transmission chain in actual operation, and performing vibration benchmark test on abnormal vibration elements in the wind turbine generator transmission chain at the test point to obtain benchmark test data corresponding to each abnormal vibration element; step 4, judging the working condition of the transmission chain of the wind turbine generator according to the obtained benchmark test data, and if the transmission chain of the wind turbine generator is abnormal, entering step 5; 5, judging the fault position of the transmission chain of the wind turbine generator by using a preset network algorithm; according to the invention, multiple monitoring and early warning work can be carried out on the transmission chain of the wind turbine generator, so that the early warning result is more accurate, workers can find the early warning result in time, and unnecessary loss is reduced.

Description

technical field [0001] The invention belongs to the technical field of wind turbines, and specifically relates to a fault warning method for transmission chains of wind turbines based on big data analysis. Background technique [0002] The wind turbine includes a wind rotor and a generator; the wind rotor consists of blades, hubs, reinforcements, etc.; it has functions such as the blades are rotated by the wind to generate electricity, and the head of the generator rotates. Wind speed selection: low wind speed wind turbines can effectively increase wind power For the utilization of wind energy by generators in low wind speed areas, the transmission chain is an important part of the wind turbine, which is used to drive the rotation of the blades. [0003] However, in the actual application process of the current wind turbines, the transmission chain on the wind turbines will break down after a long time, and because it cannot be found in time, it will affect the service life ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/17G06F30/27F03D17/00G06F111/10G06F113/06
Inventor 王忠杰王昭刘瑞李嘉麟高平亮黄泷
Owner XIAN THERMAL POWER RES INST CO LTD
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