Harris角点检测在电力设备状态监测中的应用
|
摘要
人们对电力设备的要求逐渐提高,电力设备的带电检测、在线监测、巡检和试验、运行工况、环境等是电力设备状态监测和评估发展的必然趋势;由于一些大型电力设备长期工作在户外恶劣的环境下,随着时间的推移,其性能会下降并逐渐降低用电可靠性;为了更好地实现对电力设备的监测并保证电力系统的正常运行,针对常见电力设备运行中出现故障的特点,该文采用Harris角点检测监控电力设备状态的方法来对电力系统中的运行设备进行监测;该方法将摄像头搜集的实时图像和正常运行的电力设备状态进行比较,根据比对采集到的图像焦点特征来判断正在运行的电力设备是否发生故障,以便于电力设备监测的工作人员及时采取合理的处理措施对已故障的设备进行保养和维护;该方法不仅减轻了维修人员的工作负担,还减少了因设备故障导致的用电事故,从而大幅度提高了电力系统的安全性和稳定性。
The demand for electric power equipment is increasing gradually.The electrification detection,on-line monitoring,inspection and test,operating condition and environment are the inevitable trend of the state monitoring and evaluation of the power equipment.Because some large power equipments work in the outdoor environment for a long time,their performance will decrease with time,and gradually reduce the reliability of electricity.In order to better realize the monitoring of the power equipment and ensure the normal operation of the power system,in view of the characteristics of the fault in the operation of the common power equipment,this paper uses the Harris corner detection to monitor the state of the power equipment to monitor the operating equipment in the power system.This method compares the real-time image collected by the camera with the state of the normal running power equipment.According to the comparison of the focus features of the captured image,it can judge whether the power equipment in operation is malfunction,so that the staff of the power equipment monitoring will take reasonable measures to ensure the equipment that has been broken down in time.To be praperly maintained and repaired,this method not only reduces the work burden of the maintenance personnel,but also reduces the electrical accidents caused by the equipment failure,thus greatly improving the security and stability of the power system.
The demand for electric power equipment is increasing gradually.The electrification detection,on-line monitoring,inspection and test,operating condition and environment are the inevitable trend of the state monitoring and evaluation of the power equipment.Because some large power equipments work in the outdoor environment for a long time,their performance will decrease with time,and gradually reduce the reliability of electricity.In order to better realize the monitoring of the power equipment and ensure the normal operation of the power system,in view of the characteristics of the fault in the operation of the common power equipment,this paper uses the Harris corner detection to monitor the state of the power equipment to monitor the operating equipment in the power system.This method compares the real-time image collected by the camera with the state of the normal running power equipment.According to the comparison of the focus features of the captured image,it can judge whether the power equipment in operation is malfunction,so that the staff of the power equipment monitoring will take reasonable measures to ensure the equipment that has been broken down in time.To be praperly maintained and repaired,this method not only reduces the work burden of the maintenance personnel,but also reduces the electrical accidents caused by the equipment failure,thus greatly improving the security and stability of the power system.
引文
[1]潘峥嵘,张增涛,朱翔,等.Harris角点检测在列车滑动监测系统中的应用[J].微计算机信息,2012(10):139-140.
[2]郭晓旭,刘志刚,张桂南,等.角点配准与图像差分的接触网绝缘子故障检测[J].电力系统及其自动化学报,2015,27(2):8-14.
[3]王崴,唐一平,任娟莉,等.一种改进的Harris角点提取算法[J].光学精密工程,2008,10(16):1997-2001.
[4]张冬亚.电力设备图像的特征提取和分类方法的研究[D].保定:华北电力大学,2014.
[5]张浩,王玮,徐丽杰,等.图像识别技术在电力设备监测中的应用[J].电力系统保护与控制,2010,38(6):88-91.
[6]Gualtieri I.Wind resource extrapolating Tools for modern multiMW wind turbines:comparison of the deaves and Harris model VS.the power law[J].Journal of Wind Engineering&Industrial Aerodynamics,2017,170.
[7]赵小川.MATLAB图像处理[M].北京:北京航空航天大学出版社,2014.
[8]李祥,崔昊杨,皮凯云,等.基于改进遗传算法的电力设备红外图像分割研究[J].现代电子技术,2017,40(21):56-58.
[9]岳彩兵,张国华,马军勇.基于图像分块的Harris-SIFT特征匹配算法[J].现代电子技术,2013(22):73-75.
[10]Wang L P,Zhang L P,Zhao M,et al.An algorithm for moving target detection in IR image based on grayscale distribution and Kernel function[J].Journal of Central South University,2014,21(11):4270-4278.
[11]李博,杨丹,张小洪.基于Harris多尺度角点检测的图像配准新算法[J].计算机工程与应用,2006,42(35):37-40.
[12]卢伟家,刘缠牢.一种基于Harris特征点检测的改进算法[J].仪表技术与传感器,2017(12):107-109.
[13]许丽娟.飞行器遥感图像的远程定位监控仿真研究[J].计算机仿真,2016,33(8):26-29.
[14]佟喆.基于视觉表达的工业设计合理性评估方法研究[J].现代电子技术,2017,40(14):154-157.
[15]赵万金,龚声蓉,刘纯平,等.一种自适应的Harris角点检测算法[J].计算机工程,2008,34(10):212-214.
[16]赵文君,李枭.基于Harris算法的无人机影像拼接技术[J].软件导刊,2018(4).
[17]汪立,蒋念平.基于改进Harris角点检测的视网膜图像配准[J].电子科技,2017,30(2):119-122.
[18]Ryu J B,Lee C G,Park H H.Formula for Harris corner detector[J].Electronics Letters,2011,47(3):180-181.
[19]Wang Z,Li R,Shao Z,et al.Adaptive Harris corner detection algorithm based on iterative threshold[J].Modern Physics Letters B,2017,31:175-181.
[20]陈白帆,蔡自兴.基于尺度空间理论的Harris角点检测[J].中南大学学报:自然科学版,2005,36(5):751-754.
[2]郭晓旭,刘志刚,张桂南,等.角点配准与图像差分的接触网绝缘子故障检测[J].电力系统及其自动化学报,2015,27(2):8-14.
[3]王崴,唐一平,任娟莉,等.一种改进的Harris角点提取算法[J].光学精密工程,2008,10(16):1997-2001.
[4]张冬亚.电力设备图像的特征提取和分类方法的研究[D].保定:华北电力大学,2014.
[5]张浩,王玮,徐丽杰,等.图像识别技术在电力设备监测中的应用[J].电力系统保护与控制,2010,38(6):88-91.
[6]Gualtieri I.Wind resource extrapolating Tools for modern multiMW wind turbines:comparison of the deaves and Harris model VS.the power law[J].Journal of Wind Engineering&Industrial Aerodynamics,2017,170.
[7]赵小川.MATLAB图像处理[M].北京:北京航空航天大学出版社,2014.
[8]李祥,崔昊杨,皮凯云,等.基于改进遗传算法的电力设备红外图像分割研究[J].现代电子技术,2017,40(21):56-58.
[9]岳彩兵,张国华,马军勇.基于图像分块的Harris-SIFT特征匹配算法[J].现代电子技术,2013(22):73-75.
[10]Wang L P,Zhang L P,Zhao M,et al.An algorithm for moving target detection in IR image based on grayscale distribution and Kernel function[J].Journal of Central South University,2014,21(11):4270-4278.
[11]李博,杨丹,张小洪.基于Harris多尺度角点检测的图像配准新算法[J].计算机工程与应用,2006,42(35):37-40.
[12]卢伟家,刘缠牢.一种基于Harris特征点检测的改进算法[J].仪表技术与传感器,2017(12):107-109.
[13]许丽娟.飞行器遥感图像的远程定位监控仿真研究[J].计算机仿真,2016,33(8):26-29.
[14]佟喆.基于视觉表达的工业设计合理性评估方法研究[J].现代电子技术,2017,40(14):154-157.
[15]赵万金,龚声蓉,刘纯平,等.一种自适应的Harris角点检测算法[J].计算机工程,2008,34(10):212-214.
[16]赵文君,李枭.基于Harris算法的无人机影像拼接技术[J].软件导刊,2018(4).
[17]汪立,蒋念平.基于改进Harris角点检测的视网膜图像配准[J].电子科技,2017,30(2):119-122.
[18]Ryu J B,Lee C G,Park H H.Formula for Harris corner detector[J].Electronics Letters,2011,47(3):180-181.
[19]Wang Z,Li R,Shao Z,et al.Adaptive Harris corner detection algorithm based on iterative threshold[J].Modern Physics Letters B,2017,31:175-181.
[20]陈白帆,蔡自兴.基于尺度空间理论的Harris角点检测[J].中南大学学报:自然科学版,2005,36(5):751-754.