A Spectral Optimization Method to Enhance Handheld LIBS for T91 Aging Grade Classification Using Lorentzian Profile and Kalman Filter
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    Abstract:

    The handheld laser-induced breakdown spectroscopy (LIBS) device has been developed to evaluate the aging grade of T91 heat-resistant steel. However, the reduced size of the device could potentially affect the accuracy of the measurement. To overcome this challenge, a novel spectral preprocessing approach that combines Lorentzian fitting correction and extended Kalman filter with support vector machine (SVM) is proposed in this work to enable the reliable evaluation of T91 aging grade by a handheld LIBS. The spectral features of T91 samples were measured and revealed that the obtained spectral line broadening is mainly due to Stark broadening. Consequently, the independent spectral peaks in the spectra can be corrected with Lorentzian function to obtain more comprehensive spectral information. Afterwards, the extended Kalman filter is introduced to further correct the measured spectral data, diminishing the fluctuation in the spectral signal and the device noise during the measurement. The results show that the accuracy of the T91 aging grade classification model based on the new preprocessing method can achieve 94 %. This surpasses the accuracy of the models developed with standard normal variation (SNV) and multi-scatter calibration (MSC) preprocessing methods. The proposed method improves the accuracy of handheld LIBS for T91 aging grade classification and provides a new insight into improving the quality of LIBS spectral data.

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  • Online: January 26,2024
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