본 발명은 풍력 발전기 결함 인식/분석 장치 및 방법을 개시한다. 본 발명의 일실시예에 따른 무인 비행장치(Unmanned Aerial Vehicle)의 촬영 이미지로부터 딥러닝을 이용하여 풍력 발전기의 결함 인식 및 분석 방법은, 상기 무인 비행장치로부터 촬영된 상기 풍력 발전기의 이미지를 수신하는 수신과정; 상기 풍력 발전기의 이미지로부터 상기 풍력 발전기의 블레이드(Blade) 영역이 포함된 이미지를 검출하는 블레이드 검출과정; 상기 검출된 블레이드 영역 이미지로부터 결함 존재 여부를 픽셀 단위로 판단하여 검출하는 결함 검출과정; 및 상기 블레이드 영역 이미지로부터 결함이 인식된 픽셀 단위의 검출 이미지의 결함의 성질을 분석하는 결함 분석과정을 포함하여 이루어진다.

    The present invention provides an apparatus and a method for recognizing/analyzing a defect of a blade of a wind power generator. According to an embodiment of the present invention, the method for recognizing and analyzing a defect of a wind power generator from a photographed image of an unmanned aerial vehicle by using deep learning comprises: a receiving process of receiving an image of the wind power generator photographed from the unmanned aerial vehicle; a blade detection process of detecting an image including a blade area of the wind power generator from the image of the wind power generator; a defect detection process of determining whether a defect exists in pixel units from the detected blade area image; and a defect analysis process of analyzing a property of a defect of a detection image in pixel units with a recognized defect from the blade area image.


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    Title :

    / Apparatus and Method for Detecting/Analyzing Defect of Windturbine Blade


    Additional title:

    풍력 발전기 블레이드 결함 인식/분석 장치 및 방법


    Publication date :

    2022-04-13


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G01N Untersuchen oder Analysieren von Stoffen durch Bestimmen ihrer chemischen oder physikalischen Eigenschaften , INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES / B64C AEROPLANES , Flugzeuge / F03D Windkraftmaschinen , WIND MOTORS



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