A wavelet de-nosing algorithm of XLPE cable partial discharge signals based on chaotic simulated annealing
- Resource Type
- Conference
- Authors
- Xiuqin, Lin; Jinfeng, Huang; Yongpeng, Xu; Ye, Yan; Yiming, Zhang; Xiaoxin, Chen
- Source
- 2015 IEEE 5th International Conference on Electronics Information and Emergency Communication Electronics Information and Emergency Communication (ICEIEC), 2015 5th International Conference on. :333-336 May, 2015
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Noise reduction
Partial discharges
Simulated annealing
Chaos
Signal processing algorithms
Wavelet coefficients
partial discharge
XLPE cable
wavelet de-noising
soft threshold value
GCV
chaotic simulated annealing
- Language
For the poor adaptive capability and de-nosing effect of wavelet de-nosing for partial discharge detection in XLPE cable, a wavelet de-nosing algorithm based on Chaotic simulated annealing was proposed to improve adaptive soft threshold value. And then we verify its validity. The algorithm combined Global Chaos rough search with local simulated annealing fine search. This algorithm employs generalized cross-validation criteria for selecting adaptive threshold and obtains optimal wavelet soft threshold after processing. Then the collected raw signalde-noised. Finally, we met the requirement of retaining useful information and effectively reducing noise. The results show that SNR increase of at least 13.3% by using this algorithm compared with other traditional threshold methods. It can be applied to the detection signal de-noising on site, which is beneficial for the assessment of XLPE cables running.