紫外成像检测技术在高压电力设备带电检测中的应用
发布时间:2018-12-17 02:30
【摘要】:结合近年来获得的大量紫外成像检测诊断的数据资料,探讨了紫外成像检测技术在电力系统故障诊断应用中的特点。基于此,从紫外成像检测技术的基本原理出发,分析影响紫外成像检测结果的主要因素,并阐述了利用紫外成像检测技术检测高压电力设备电晕放电缺陷的操作方法;结合输变电电力设备紫外成像检测的实际案例,分析了引起设备电晕放电的主要原因,并给出相应的检修建议。实际应用案例表明该方法可有效地对高压电力设备进行带电检测。
[Abstract]:Based on a large number of data obtained in recent years, the characteristics of the application of ultraviolet imaging in fault diagnosis of power system are discussed. Based on this, the main factors influencing the detection results of ultraviolet imaging are analyzed based on the basic principle of ultraviolet imaging detection technology, and the operating method of detecting corona discharge defects of high-voltage power equipment by using ultraviolet imaging detection technology is described. Combined with the actual cases of ultraviolet imaging detection of transmission and transformer power equipment, the main causes of corona discharge are analyzed, and the corresponding repair suggestions are given. The practical application shows that this method can effectively detect high voltage power equipment.
【作者单位】: 广东电网有限责任公司电力科学研究院;上海日夜光电技术有限公司;
【基金】:广东电网有限责任公司科技项目(K-GD2014-0622)
【分类号】:TM507;TN23
[Abstract]:Based on a large number of data obtained in recent years, the characteristics of the application of ultraviolet imaging in fault diagnosis of power system are discussed. Based on this, the main factors influencing the detection results of ultraviolet imaging are analyzed based on the basic principle of ultraviolet imaging detection technology, and the operating method of detecting corona discharge defects of high-voltage power equipment by using ultraviolet imaging detection technology is described. Combined with the actual cases of ultraviolet imaging detection of transmission and transformer power equipment, the main causes of corona discharge are analyzed, and the corresponding repair suggestions are given. The practical application shows that this method can effectively detect high voltage power equipment.
【作者单位】: 广东电网有限责任公司电力科学研究院;上海日夜光电技术有限公司;
【基金】:广东电网有限责任公司科技项目(K-GD2014-0622)
【分类号】:TM507;TN23
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