Fault diagnosis method for gear case of wind turbine generator system

A technology for fault diagnosis of wind power generators, applied in the field of wind power, can solve problems such as heavy motor weight, multiple background noises, and unsatisfactory application effect of rotating machinery fault monitoring methods in wind power generators, so as to reduce time and cost and improve reliability The effect of the noise ratio

Inactive Publication Date: 2015-07-22
ZHONGSHAN FLASHLIGHT POLYTECHNIC
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AI Technical Summary

Problems solved by technology

The direct drive model does not have a gearbox, which avoids the high failure rate and the reduction of maintenance costs due to the gearbox, but the direct drive model also has its inevitable disadvantages: the rare earth resources required by the permanent magnet generator type The large motor weight of the direct drive unit makes transportation and assembly very difficult. ENERCON’s 6WM model in Hamburg took as long as 3 months to hoist
Since wind turbines are mostly located in the field, they have to withstand various factors such as severe weather, impact loads caused by erratic wind speed and direction, and changing working conditions. The collected vibration signals contain a lot of background noise. Therefore, conventional rotating machinery fault monitoring The application effect of the method on the wind turbine is not ideal

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  • Fault diagnosis method for gear case of wind turbine generator system
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  • Fault diagnosis method for gear case of wind turbine generator system

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Embodiment Construction

[0032] The scheme of this application is further described in conjunction with the accompanying drawings as follows:

[0033] Firstly, the specific implementation steps of the present invention are described in detail by analyzing the vibration data collected from the test bench, and then the vibration data collected from the actual wind farm test prototype are analyzed to further verify the effectiveness and application value of the fault diagnosis method proposed by the present invention .

[0034] The test data used in this patent all come from the rolling bearing failure simulation test bench of the Electrical Engineering Laboratory of Case Western Reserve University in the United States. The test bench includes a 2-horsepower electric motor, a torque sensor and a power tester. The bearings to be tested are located at both ends of the motor. The drive end bearing model is SKF6205, and the fan end bearing model is SKF6203. The bearing fault points are machined by EDM, and t...

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Abstract

The invention provides a fault diagnosis method for a gear case of a wind turbine generator system. According to the fault diagnosis method based on LMD (local mean decomposition) and an optimized K mean value clustering algorithm, important factors such as non-stable characteristics, fault degree recognition and fault position diagnosis of vibration signals of the gear case of the wind turbine generator system are considered. The method includes collecting original vibration acceleration signals of measurement points of the gear case of the wind turbine generator system, decomposing the original vibration acceleration signals according to an LMD method into a plurality of PF (product function) components, selecting the PF components according to a principle that correlation coefficients are biggest to perform signal reconstruction, performing Hilbert envelope spectrum analysis on reconstructed signals to further extract fault characteristic quantity, and finally, classifying fault positions and fault degrees by the optimized K mean value clustering algorithm.

Description

technical field [0001] The invention belongs to the technical field of wind power, and in particular relates to a fault diagnosis method for a gearbox of a wind power generating set. The fault diagnosis method is based on LMD and an optimized K-means clustering algorithm. Background technique [0002] As a renewable and non-polluting new green energy, wind energy has been widely regarded as a new energy utilization method with great development and utilization prospects at home and abroad. In the current situation of increasingly severe energy shortage in the world, vigorously developing wind power technology is an effective way and one of the inevitable trends to solve the problems of energy shortage and environmental pollution. In 2013, in China (excluding Taiwan), the new installed capacity was 16088.7MW, a year-on-year increase of 24.1%; the cumulative installed capacity was 91412.89MW, a year-on-year increase of 21.4%. Both new installed capacity and cumulative install...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/02
Inventor 郭艳平熊宇晏华成宋国翠张远海左红英
Owner ZHONGSHAN FLASHLIGHT POLYTECHNIC
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