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Volume 32 Issue 5
May  2010
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Liu Sheng, Zhang Lan-yong, Zhang Li-jun. The Study of Electromagnetic Interference Measurement Technique Based on Wavelet Analysis[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1229-1233. doi: 10.3724/SP.J.1146.2009.00631
Citation: Liu Sheng, Zhang Lan-yong, Zhang Li-jun. The Study of Electromagnetic Interference Measurement Technique Based on Wavelet Analysis[J]. Journal of Electronics & Information Technology, 2010, 32(5): 1229-1233. doi: 10.3724/SP.J.1146.2009.00631

The Study of Electromagnetic Interference Measurement Technique Based on Wavelet Analysis

doi: 10.3724/SP.J.1146.2009.00631
  • Received Date: 2009-04-28
  • Rev Recd Date: 2009-11-25
  • Publish Date: 2010-05-19
  • A innovative digital signal processing technique for fast measurements of ElectroMagnetic Interference(EMI) from devices under test in the time-domain at open area test sites is presented. Suppressing ambient noise by using the wavelet analysis, the EMI measurements of an Equipment Under Test(EUT) can be performed at a test site polluted with electromagnetic ambient noise. Frequency-domain threshold funtion filtering using the wavelet analysis method is applied. The coherence of ambient noise is computed by using the wavelet analysis in time domain and frequency domain. With the characteristic of ambient noise, it can be suppressed by the threshold function in the wavelet domain, and the pure electromagnetic radiation can be obtained readily. The EMI measurement can be performed without the anechoic chamber. It is seen that it is convenient to perform the EMI measurements while the total cost can be reduced greatly. Measurement results show that the successful cancelation of ambient noise can be obtained in the frequency range of 30 Hz to 1000 MHz.
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  • Shinuzuka T and Sugiura A. Reduction of ambient noise in EMI measurement [C]. IEEE International Symposium On Electromagnetic Compatibility Digest, Nagoya, Japan, 1989, September 8-10: 24-28.[2]Parhami P, Marino M, Watkins S, and Nakauchi E. Innovative precompliance test methodology using ambient cancellation and coherence detection techniques[C]. IEEE International Symposium On Electromagnetic Compatibility, Seattle, USA, 1999: 1022-1025.[3]Braun S, Al-Qedra M, and Russer P. A novel realtime time-domain measurement system based on field programmable gate arrays[C]. 17th International Zurich Symposium On Electromagnetic Compatibility, Singapore, 2006: 501-504.[4]Braun S, Krug F, and Russer P. A novel automatic digital quasipeak detector for a time-domain measurement system[C]. 2004 IEEE International Symposium On Electromagnetic Compatibility Digest, Santa Clara, USA, 2004: 832-837.[5]Frech A.[J].Zakaria A, Braun S, and Russer P. Ambient noise cancelation with a time-domain EMI measurement system using adaptive filtering[C]. 2008 Asia-Pacific Sympsoium on Electromagnetic Compatibility 19th International Zurich Symposium on Electromagnetic Compatibility, Singapore.2008,:-[6]Klein A, Sauer T, Jedynak A, and Skrandies W. Conventional and wavelet coherence applied to sensory-evoked electrical brain activity [J].IEEE Transactions on Biomedical Engineering.2006, 53(2):266-272[7]Payandehjoo K. Suppression of unwanted harmonics using integrated complementary split-ring resonators in nonlinear transmission line frequency multipliers[J].IEEE Transactions on Microwave Theory and Techniques.2008, 56(4):931-941[8]Yue Zhao and Niu Wen-cheng. The application of wavelet analysis in ultrasonic sensor system characteristic signal pretreament[J]. Acta Scientiarun Naturaltium Universitatis Nankaiensis, 2005, 38(2): 5-9.[9]Zhang Hao, Blackburn T R, Phung B T, and Sen D. A novel wavelet transform technique for nn-line partial discharge measurements, IEEE Transactions on Dielectrics and Electrical Insulation. 2007, 14(1): 3-14.[10]Huang Juan, Qian Xin, and Wang Cheng-lin. The construction of a wavelet filter and its application in environmental research[J]. Journal of Nanjing University (Natural Sciences), 2007, 43(4): 389-396.[11]Ren Shou-xin and Gao Ling. Application of a wavelet packet transform based radial basis function neural network to analyze overlapping spectral[C]. 2008 Congress on Image and Signal Processing. China, 2008: 874-878.
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