基于图像分析的电力设备故障检测技术研究

发布时间：2018-05-19 06:30

本文选题：红外图像 + 电力设备　；参考：《现代电子技术》2015年24期

【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。
[Abstract]:The overheating fault of power equipment can be identified by infrared image. Therefore, the thermal fault detection technology of power equipment based on infrared thermal image analysis is proposed. The thermal fault detection system of power equipment is composed of image acquisition module and infrared image detection module. The infrared image registration method is used to ensure that the acquisition position of infrared image of power equipment is the same as the original position, and the accuracy of overall thermal fault detection is improved. According to the position of power equipment image feature point which has been set up in the database, the temperature information of the infrared image registration area is collected. Based on the results obtained by comparing the temperature information with each other, the thermal fault detection of power equipment is realized, and the alarm is issued. The key code of Laplacian sharpening algorithm is given in order to sharpen the infrared image of power equipment and improve the clarity of the image. The experimental results show that the proposed technique has high detection accuracy and robustness in the process of detecting thermal faults of power equipment.
【作者单位】：国网重庆市电力公司长寿供电分公司;
【基金】：2014年国家自然科学基金(面上项目)(61472268)
【分类号】：TP391.41;TM507

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