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基于图像分析的电力设备故障检测技术研究 被引量:6

Research on power equipment fault detection technology based on image analysis
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摘要 电力设备过热故障可以通过采集的红外图像进行识别。因此,提出基于红外热图像分析的电力设备热故障检测技术,该技术下的电力设备热故障检测系统由图像采集模块和红外图像检测模块构成。通过红外图像配准方法,确保电力设备红外图像的采集位置同原始位置一致,提高总体热故障检测的精度。依照数据库中已经完成设置的电力设备图像特征点位置,采集完成红外图像配准区域的温度信息。凭借温度信息相互对比获取的结果,实现电力设备热故障检测,并且发出警报。给出了拉普拉斯锐化算法的关键代码,以实现对电力设备红外图像的锐化处理,提高图像清晰度。实验结果说明,所提出的技术在检测电力设备热故障过程中,具有较高的检测精度和鲁棒性。 The overheat fault of power equipments can be recognized by the acquired infrared image. Therefore,the overheat fault detection technology based on the infrared thermal image analysis is proposed for the power equipments,by which the heat fault detection system of the power equipments is constituted of image acquisition module and infrared image detection module.The infrared image registration method can ensure the acquisition position of power equipment infrared image in accordance with original position,and improve the accuracy of the overall heat fault detection. According to the location of image feature points of the power equipment set in database,the temperature information in the infrared image registration area is collected. In combination with the results coming from the comparison among temperature information,the overheat fault detection of power equipments is achieved,and the alarm is raised. The key code of Laplace sharpening algorithm is provided to realize the sharpening processing of power equipment infrared image,and improve the image resolution. The experimental results indicate that the proposed technology has high detection accuracy and robustness in the process of detecting the overheat fault of power equipments.
作者 冯俊
出处 《现代电子技术》 北大核心 2015年第24期7-11,共5页 Modern Electronics Technique
基金 2014年国家自然科学基金(面上项目)(61472268)
关键词 红外图像 电力设备 热故障 拉普拉斯锐化算法 infrared image power equipment heat fault detection Laplace sharpening algorithm
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