Under the complex condition of nuclear power plant, all kinds of influence factors may cause distortion
of on-line monitoring data. It is essential that on-line monitoring data should be de-noised in order to ensure the
accuracy of diagnosis. Based on the research of wavelet analysis and threshold de-noising, a new threshold denoising
method based on Mallat transform is proposed. This method adopts factor weighing method for threshold
quantization. Through the specific case of nuclear power plant, it is verified that the algorithm is of validity and
superiority.
CUI Yan* (崔妍), CHEN Shijun (陈世均), QU Meng (瞿勐), HE Shanhong (何善红)
. Research and Application of New Threshold De-noising Algorithm for Monitoring Data Analysis in Nuclear Power Plant[J]. Journal of Shanghai Jiaotong University(Science), 2017
, 22(3)
: 355
-360
.
DOI: 10.1007/s12204-017-1843-3
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