Technique to improve quality of LIBS spectrum signal based on multiple data processing methods

Based on multiple signal process methods, such as segmented spectral feature extraction and wavelet transform algorithm, the pre- spectrum signal treatment technique was investigated to decrease the difference of segmented spectral baseline and lower the spectral noise, and thus the signal quality in laser-induced breakdown spectroscopy(LIBS) was improved. Based on extracting the characteristic value in different spectral bands of multi-channel spectrometers, a simple method was presented to connect the characteristic value in different segmented data and effectively flats the signal baseline. Through analyzing the experimental data, the wavelet transform was used to lower the noise and obtain the optimum parameters. On the basis of the above work, artificial neural network based error back propagation was adopted to identify spectral line of the copper and stainless steel sample successfully. All the results illustrate that the utilization of multiple data processing method for spectral signal processing in LIBS technique can improve the quality of line's analysis and recognition.