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Updated: Apr 23, 2026

Measurement and Analysis of Atomic Hydrogen and Diatomic Molecular AlO, C2, CN, and TiO Spectra Following Laser-induced Optical Breakdown

Measurement and Analysis of Atomic Hydrogen and Diatomic Molecular AlO, C2, CN, and TiO Spectra Following Laser-induced Optical Breakdown

Published on: February 14, 2014

[An automatic peak detection method for LIBS spectrum based on continuous wavelet transform].

Peng-Fei Chen, Di Tian, Shu-Jun Qiao

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu

|October 2, 2014

Summary

This summary is machine-generated.

This study introduces an improved continuous wavelet transform ridge detection method for laser-induced breakdown spectroscopy (LIBS) peak analysis. The new technique enhances overlapping peak detection and accuracy in noisy LIBS spectra.

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Measurement and Analysis of Atomic Hydrogen and Diatomic Molecular AlO, C2, CN, and TiO Spectra Following Laser-induced Optical Breakdown

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Area of Science:

Spectroscopy
Signal Processing
Data Analysis

Context:

Accurate spectrum peak detection is crucial for laser-induced breakdown spectroscopy (LIBS).
Background noise and overlapping peaks in LIBS spectra challenge traditional peak detection methods.
Existing methods like direct comparison, derivative, and basic ridge search have limitations in precision and adaptability.

Purpose:

To develop an advanced automatic peak detection method for LIBS spectra.
To improve the capability of identifying and analyzing overlapping spectral peaks.
To enhance the precision and adaptivity of peak detection in the presence of noise and background.

Summary:

A novel ridge peak detection method based on continuous wavelet transform (CWT) was applied to LIBS.
The method was optimized by selecting the mother wavelet and tuning scale and shift factors.
A correcting ridge technique was incorporated to further refine the ridge peak detection.

Impact:

The proposed method significantly outperforms direct comparison, derivative, and basic ridge search methods.
Demonstrates superior ability in distinguishing overlapping peaks within LIBS spectra.
Offers enhanced precision for peak position determination, improving overall LIBS data processing and analysis.