Alarm system for detecting abnormal operation of wind power generator

Abstract

The invention provides an alarm system for detecting abnormal operation of a wind power generator. The wind power generator is provided with a sound collection module, and the alarm system comprises asound collection module, an acoustic signal processing module, a fault diagnosis module and an early warning module; the sound collection module, the sound signal processing module, the fault diagnosis module and the early warning module are in turn connected, the early warning module is used for detecting the working state of the wind power generator, and if the wind power generator is found tobe abnormal, the early warning module sends an early warning message to remind maintenance personnel to perform maintenance. The system provides a simple, efficient and low-cost non-contact in-situ fault diagnosis method for wind power generator abnormality detection, and gives guiding suggestions for normal operation and maintenance of the wind power generator.

Description

technical field [0001] The invention relates to the field of detection of power generation systems, in particular to an alarm system for detecting abnormal operation of wind power generators. Background technique [0002] Wind turbine blades are an important component that absorbs wind energy and provides unit operation, and its cost accounts for about 15%-20% of the total cost of wind turbines. The harsh environment and complex climatic conditions suffered by the blades in all-weather operation cause impact or fatigue damage and destruction. Statistical analysis of global wind turbine accidents in the past 30 years shows that blade failures account for the largest number and are increasing year by year. Blade failures often occur during high wind periods, during which maintenance not only brings huge economic losses, but blade breakage is also an important factor that causes other equipment failures of wind turbines. Regular maintenance and repair of blades and shutdown i...

AI Technical Summary

Problems solved by technology

Blade failures often occur during high wind periods, during which maintenance not only brings huge economic losses, but blade breakage is also an important factor that causes other equipment failures in wind turbines

Regular maintenance and repair of blades and shutdown inspections after abnormal conditions cannot meet the actual needs of wind power plants. In particular, the internal damage of the composite material that constitutes the main body of the blade is concealed, which can easily lead to a sudden collapse of the overall structure, causing serious property losses and security threat

[0003] In the past ten years, my country's wind power industry has experienced explosive growth. However, the condition monitoring and fault identification technology is backward, and the wind turbines lack supporting condition monitoring devices, which highlights the importance of wind turbine condition monitoring and fault identification.

Wind turbine blades are composed of a variety of materials with a hollow overall structure. They operate under complex variable conditions (pitch and yaw motion), and the manufacturing standards of different blades are not uniform. Great difficulties and challenges

Most of the existing blade condition monitoring technologies rely on contact strain measurement and Lamb wave measurement. The sensors need to be pasted on the blade surface or embedded in the interior in advance. The number and arrangement of sensors in monitoring have a great influence on the measurement results, and the diagnostic effect is not stable enough.

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