20240052810. BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM simplified abstract (BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.)
Contents
BLADE FAULT DIAGNOSIS METHOD, APPARATUS AND SYSTEM, AND STORAGE MEDIUM
Organization Name
BEIJING GOLDWIND SCIENCE & CREATION WINDPOWER EQUIPMENT CO., LTD.
Inventor(s)
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.
