摘要
为解决现有的盲元检测算法效率低、不适用于电力设备监测系统和缺乏对块状盲元的适应性等问题,提出了一种基于聚类算法的盲元快速检测算法。通过选择合适的死像元和过热像元参照中心,并计算选出合适的灰度差阈值。以各像元点的灰度值和参照点的灰度差是否超过阈值作为判断依据。由于每个像元点只需和参照点比较两次,有效减少了算法运算时间,并引入相对误差Q来验证算法的检测精度。实验仿真也表明,所提方法有较好的检测精度。
In order to solve the problems of the existing blind element detection algorithm,low efficiency,not suitable for the power equipment monitoring system,and lack of adaptability to the block blind element,a fast blind detection algorithm based on clustering algorithm is proposed. The appropriate gray scale difference threshold is selected by selecting the appropriate dead pixel and superheated pixel reference center. Whether or not the gradation value of each pixel point and the gradation difference of the reference point exceed the threshold value is used as a judgment basis. Since each pixel point only needs to be compared with the reference point twice,the algorithm operation time is effectively reduced,and the relative error Q is introduced to verify the detection precision of the algorithm. The experimental simulation also shows that the proposed method has better detection precision.
作者
李兵
许浩文
琚天公
曾文波
赵锋
LI Bing;XU Haowen;JU Tiangong;ZENG Wenbo;ZHAO Feng(School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 230009,China)
出处
《传感器与微系统》
CSCD
2020年第11期158-160,共3页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(51777050,51637004)
装备预先研究项目(41402040301)
国家重大科学仪器设备开发资助项目(2016YFF0102200)
湖南省自然科学基金面上资助项目(2017JJ2080,2018JJ5029)。
关键词
电力设备红外监测系统
盲元块
聚类算法
相对误差
infrared monitoring system for power equipment
blind element block
clustering algorithm
relative error
