A method for improving wavelet threshold denoising in laser-induced breakdown spectroscopy

Zhang, Bo; Sun, Lanxiang; Yu, Haibin; Xin, Yong; Cong, Zhaotong

doi:10.1016/j.sab.2015.02.015

Cited by 54 publications

(26 citation statements)

References 47 publications

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“…The commonly used wavelet threshold function consists of soft threshold function, hard threshold function and half-soft threshold function. 26 The soft threshold function is to ensure the continuity of the threshold function. The threshold function curve is moved down and connected to the threshold, causing the effective signal components in the wavelet coefficients larger than the threshold are compressed, which is an influential factor for the noise reduction effect.…”

Section: Simulation Verificationmentioning

confidence: 99%

An improved denoise method based on EEMD and optimal wavelet threshold for model building of OPAX

Chen

Zhang

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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To improve the accuracy of Operational Path Analysis with Exogeneous Inputs (OPAX) model by excluding the noise interference sufficiently in the vehicle operating condition data (time-domain vibration signal), the combined noise reduction method of Ensemble Empirical Mode Decomposition (EEMD) and wavelet threshold was used. Since the noise content of each noisy intrinsic mode functions (IMFs) decomposed by EEMD is uncertain, the effective signal element in the less noisy IMFs affects the accuracy of the first-layer wavelet coefficients to estimate the noise variance, the EEMD and wavelet particle swarm optimization sample entropy threshold denoising (EEMD-WPSE) method is presented in terms of information entropy. In this method, the sample entropy of the eliminated noise is used as the information cost function, together with the particle swarm optimization algorithm to find the optimal wavelet threshold of each high-frequency noisy IMFs. After denoising the simulation signal, it is found that the combination of EEMD-WPSE threshold with hard threshold function, soft threshold function and half-soft threshold function identifying higher SNR and lower RMSE, are given to demonstrate the higher universality of the proposed method. The method is applied to the noise reduction processing of the automobile operating condition data for constructing the OPAX model, and the degree of similarity between the synthesized responses of the care-target point obtained by the OPAX model and the measured responses under the second order operational condition are observed, as it turned out, the calculation results of SNR and RMSE indicated that EEMD-WPSE can better promote the accuracy of OPAX model in terms of noise reduction.

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Section: Simulation Verificationmentioning

confidence: 99%

An improved denoise method based on EEMD and optimal wavelet threshold for model building of OPAX

Chen

Zhang

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Therefore, it is necessary to determine the optimal DL. Zhang et al proposed a method to select the optimal DL based on entropy analysis of a noisy LIBS signal and noise; they verified the denoising performance by analyzing some synthetic signals. The optimal DL improved the performance of the denoising results obtained by WTD with nonoptimal wavelet functions.…”

Section: Spectral Data Preprocessingmentioning

confidence: 99%

Chemometrics in laser‐induced breakdown spectroscopy

Zhang

Tang

2018

Journal of Chemometrics

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Laser-induced breakdown spectroscopy (LIBS) is a new type of elemental analytical technology with the advantages of real-time, online, and noncontact as well as enabling the simultaneous analysis of multiple elements. It has become a frontier analytical technique in spectral analysis. However, the issue of how to improve the accuracy of qualitative and quantitative analyses by extracting useful information from a large amount of complex LIBS data remains the main problem for the LIBS technique. Chemometrics is a chemical subdiscipline of multi-interdisciplinary methods; it offers advantages in data processing, signal analysis, and pattern recognition. It can solve some complicated problems that are difficult for traditional chemical methods. In this paper, we reviewed the research progress of chemometrics methods in LIBS for spectral data preprocessing as well as for qualitative and quantitative analyses in the most recent 5 years (2012-2016). KEYWORDSchemometrics, data preprocessing, laser-induced breakdown spectroscopy, qualitative analysis, quantitative analysis | INTRODUCTIONAs one of the most promising analytical tools in the 21st century, laser-induced breakdown spectroscopy (LIBS) is a novel analytical technique for materials and elements; it is based on atomic emission spectroscopy and a laser as an excitation source. 1-4 In LIBS, a low-energy pulse laser (typically tens to hundreds of millijoules per pulse) generated from a laser device is reflected by a plane mirror and focused by a plano-convex lens onto the sample surface; a laser-induced plasma with high temperature is then generated. The light with different frequencies is radiated during the plasma cooling process, and it is collected by an optical fiber coupled to a spectrometer. The qualitative and quantitative analyses by the LIBS technique can be performed using the wavelength and integrated intensity of the spectral line. A schematic diagram of the LIBS instrument is presented in Figure 1. It consists of Nd:YAG laser, optical part, X-Y-Z manual micrometric stage, optical fiber, spectrometer, Charge coupled device (CCD) camera, and computer.The LIBS technology has benefited from the invention of the ruby crystal laser 5 and was first reported by Brech and Cross. 6 It has become a research focus in the spectral field with the development of laser and optical detection techniques. Compared with conventional analytical tools, LIBS demonstrates some substantial advantages with regards to being rapid, real-time, on-site, and nondestructive while allowing remote detection without complicated sample preparation procedures as well as simultaneous multicomponent analysis. 7-9 Because of these advantages, LIBS technology has been widely used in process analysis and in the control of industrial manufacturing, food supervision, environmental monitoring, historical relic identification, and space exploration. [10][11][12][13] The National Aeronautics and

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“…Obviously, the key to determine the threshold is the noise standard deviation ˆn  [33]. HH is the high frequency sub-band wavelet coefficient in the first level.…”

Section: The Proposed Filtermentioning

confidence: 99%

SAR Interferogram Filtering of Shearlet Domain Based on Interferometric Phase Statistics

Zhu

et al. 2017

Applied Sciences

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This paper presents a new filtering approach for Synthetic Aperture Radar (SAR) interferometric phase noise reduction in the shearlet domain, depending on the coherent statistical characteristics. Shearlets provide a multidirectional and multiscale decomposition that have advantages over wavelet filtering methods when dealing with noisy phase fringes. Phase noise in SAR interferograms is directly related to the interferometric coherence and the look number of the interferogram. Therefore, an optimal interferogram filter should incorporate information from both of them. The proposed method combines the phase noise standard deviation with the shearlet transform. Experimental results show that the proposed method can reduce the interferogram noise while maintaining the spatial resolution, especially in areas with low coherence.

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A method for improving wavelet threshold denoising in laser-induced breakdown spectroscopy

Cited by 54 publications

References 47 publications

An improved denoise method based on EEMD and optimal wavelet threshold for model building of OPAX

An improved denoise method based on EEMD and optimal wavelet threshold for model building of OPAX

Chemometrics in laser‐induced breakdown spectroscopy

SAR Interferogram Filtering of Shearlet Domain Based on Interferometric Phase Statistics

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