View source for 20240052810. BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM simplified abstract (BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.)

=BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM=


==Organization Name==

[[:Category:BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.|BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.]]


[[Category:BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.]]

==Inventor(s)==

[[:Category:Yong Zhao of Beijing (CN)|Yong Zhao of Beijing (CN)]][[Category:Yong Zhao of Beijing (CN)]]

[[:Category:Xinle Li of Beijing (CN)|Xinle Li of Beijing (CN)]][[Category:Xinle Li of Beijing (CN)]]

[[:Category:Xinyuan Niu of Beijing (CN)|Xinyuan Niu of Beijing (CN)]][[Category:Xinyuan Niu of Beijing (CN)]]

==BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240052810 titled 'BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM

==Simplified Explanation==

The present application discloses a method, apparatus, and system for diagnosing blade faults in a wind turbine generator system. It also includes a storage medium for storing the necessary data. 

The method involves the following steps:
* Acquiring the audio of blade rotation collected by an audio collection device during the operation of the wind turbine generator system.
* Preprocessing the audio by applying a wind noise filtering algorithm to filter out the wind noise and obtain a filtered blade rotation audio.
* Dividing the filtered blade rotation audio into audio segments corresponding to the blades of the wind turbine generator system.
* Diagnosing the blades based on the audio segments to determine if they are faulty.

Potential applications of this technology:
* Wind turbine maintenance: The method can be used to detect faulty blades in a wind turbine generator system, allowing for timely maintenance and repair.
* Blade performance optimization: By diagnosing the blades, the method can identify any performance issues or abnormalities, enabling optimization of the wind turbine system.

Problems solved by this technology:
* Accurate blade fault diagnosis: The method improves the accuracy of diagnosing faulty blades by analyzing the audio segments of different blades individually.
* Early detection of blade faults: By continuously monitoring the audio of blade rotation, the method can detect blade faults at an early stage, preventing further damage and potential accidents.

Benefits of this technology:
* Improved maintenance efficiency: The method allows for targeted maintenance and repair of faulty blades, reducing downtime and increasing the overall efficiency of the wind turbine system.
* Enhanced safety: Early detection of blade faults helps prevent accidents and ensures the safe operation of the wind turbine generator system.
* Cost savings: By identifying and addressing blade faults promptly, the method helps minimize repair costs and prolong the lifespan of the wind turbine system.


==Original Abstract Submitted==

the present application discloses a blade fault diagnosis method, apparatus and system, and a storage medium. the method includes: acquiring a blade rotation audio collected by an audio collection device during operation of a wind turbine generator system; preprocessing the blade rotation audio based on a wind noise filtering algorithm to obtain a blade rotation audio filtered out of wind noise; dividing the blade rotation audio filtered out of wind noise to obtain audio segments corresponding to blades of the wind turbine generator system respectively; diagnosing, based on the audio segments, whether the blades each corresponding to one of the audio segments are faulty. the present application can diagnose whether a corresponding blade is faulty respectively according to the audio segments of different blades, which improves the accuracy of the diagnosis results.



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