基于改进YOLOX的继电保护压板状态校核方法*

Verification Method of Relay Protection Platen State Based on the Improved YOLOX

  • 摘要: 继电保护压板状态校核是变电站巡检的重要业务,然而现有校核方法多为人工读取和复诵核对,存在费力耗时以及安全风险的不足。为此,提出一种基于改进YOLOX的智能化校核方法。首先,该方法采用以注意力机制改进主干特征提取模块的YOLOX模型,实现压板状态识别和压板标签定位。其次,针对标签边界框标定的图像区域进行倾斜角矫正,并基于光学字符引擎和压板双重名称专业语料库实现文本识别,获得压板状态和双重名称的映射关系。最后,采用实际变电站的压板图像进行试验验证。结果表明,对于压板状态识别,所提方法具有更高的识别精度和鲁棒性,并且对于文本识别、倾斜角矫正和专业语料库的构建,可以显著提高压板双重名称的识别准确率。所提方法为巡检机器人实现智能化压板状态校核提供了一种新思路。

     

    Abstract: Verifying the state of relay protection plate is an important part of the substation inspection, but the existing verification methods are mostly manual reading and repetition checking, which is inefficiency and error-prone. Therefore, an intelligent verification method of protection plate state based on the improved YOLOX is proposed. Firstly, the method recognizes the platen state and locates platen label position based on YOLOX model which is improved by attention mechanism in the backbone feature extraction network. Secondly, the angle of the image area calibrated by the bounding box is corrected, and then text recognition is realized based on the optical character engine and professional corpus of the plate dual name in order to obtain the mapping relationship between the state and the dual name. Finally, images collected in actual substation is used for experiment. The results show that, for the recognition of the platen state, this proposed method has higher recognition accuracy and robustness, and for text recognition, skew angle correction and the construction of professional corpus can significantly improve the recognition accuracy of platen dual names. This proposed method provides a new idea for the smart inspection robot to realize the intelligent platen state check.

     

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