Title :
HV Power Equipment Running State Detection Based on Image Processing and Recognition
Author :
Zhao, Shutao ; Li, Baoshu ; Zhu, Xiaohui
Author_Institution :
North China Electr. Power Univ., Baoding
Abstract :
Aimed at the necessary on the automatic detection level in unattended substation, a new method which monitoring and diagnosis the high-voltage (HV) power equipment running state based on image processing is put forward. Image processing techniques realize and strengthen the capability of the human vision. It is a non-contact measurement method, which can monitor the HV power equipment running state online. In recent years, it is widely applied in many fields and gets plentiful and substantial success. The HV power equipment running state detection process is introduced in this paper. After image preprocesses and feature extraction, the automatic target recognition algorithm based on the radial basis function neural network (RBFNN) is presented.
Keywords :
electric machine analysis computing; feature extraction; high-voltage techniques; image recognition; power apparatus; radial basis function networks; HV power equipment running state detection; feature extraction; image processing; image recognition; radial basis function neural network; unattended substation; Computerized monitoring; Digital cameras; Feature extraction; Image processing; Image recognition; Leak detection; Power systems; Power transformers; Substations; Videos; HV equipment; abnormal status; feature extracting; image detecting; recognition;
Conference_Titel :
Power System Technology, 2006. PowerCon 2006. International Conference on
Conference_Location :
Chongqing
Print_ISBN :
1-4244-0110-0
Electronic_ISBN :
1-4244-0111-9
DOI :
10.1109/ICPST.2006.321561