Paper
20 May 2009 Application of wavelet analysis on thin-film wideband monitoring system
Jun Han, Song Wang, Xiaoyan Shang, Yuying An
Author Affiliations +
Abstract
In the thin-film thickness wideband monitoring system, an accurate measurement of the spectral intensity signal is critical to improving precision of coating. Because of electron gun, ion source and baking, vacuum chamber is a complex environment with background light. Together with the inherent noise of linear CCD and quantization noise of A/D conversion, which are main factors affecting accurate measurement of spectrum intensity. This paper uses time and frequency multi-resolution properties of wavelet transform, adaptive threshold adjustment method is designed. According to the different characteristics of signal and the random noise processed by wavelet transform in different scales, the fine adjustment factor is added when the threshold is determined, on the hand, which makes the adaptive threshold of wavelet coefficient with positive Lipschitz index decrease, this is beneficial to preserve real signals of wavelet coefficient; on the other hand, which makes the one with negative Lipschitz index increase, this is favorable to filter out noise signal. By this method, both rejecting true probability and false declaration probability are reduced, the random noise is suppressed effectively, a very good filtering result is achieved, and finally the analysis accuracy of spectrum signal and the precision of systematic decision pause are improved.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Han, Song Wang, Xiaoyan Shang, and Yuying An "Application of wavelet analysis on thin-film wideband monitoring system", Proc. SPIE 7283, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 72831L (20 May 2009); https://doi.org/10.1117/12.828671
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Cited by 1 scholarly publication.
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KEYWORDS
Interference (communication)

Wavelets

Signal to noise ratio

Thin films

Signal processing

Coating

Wavelet transforms

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