The invention provides a slide block anomaly detection method, which comprises the following steps: acquiring a real-time video stream, performing real-time frame extraction on the real-time video stream to obtain a target picture, and determining a target picture set; wherein the target picture set comprises a plurality of target pictures shot within a preset time period from the current moment; inputting the target picture set into a preset detection model to obtain an anomaly detection result; wherein the detection model is used for determining a sliding block area in each target picture in the target picture set, extracting geometric features of the sliding block areas, and performing classification based on a random forest classification method and the geometric features to obtain an anomaly detection result; and performing exception notification based on the exception detection result. By means of the mode, the requirement for calculation power in the sliding block anomaly detection process is lowered, the calculation speed is higher, and the real-time performance of detection is guaranteed.

    本发明提供一种滑块异常检测方法,包括:获取实时视频流,对所述实时视频流进行实时抽帧得到目标图片,确定目标图片集;其中,所述目标图片集包括距离当前时刻预设时间段内拍摄的多张目标图片;将所述目标图片集输入预设的检测模型,得到异常检测结果;其中,所述检测模型用于确定所述目标图片集中各个目标图片中的滑块区域,提取滑块区域的几何特征,基于随机森林分类方法和所述几何特征进行分类,得到异常检测结果;基于所述异常检测结果进行异常通报。通过上述方式,降低滑块异常检测过程中对算力的要求,使得计算速度更快,以保证检测的实时性。


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    Titel :

    Slide block anomaly detection method and device and crane


    Weitere Titelangaben:

    滑块异常检测方法、装置和起重机


    Beteiligte:
    YUAN PENGWEI (Autor:in) / SHEN FEI (Autor:in) / ZHAO XIAOWEI (Autor:in)

    Erscheinungsdatum :

    25.03.2022


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    B66C Krane , CRANES



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