A weighted PCA based denosing for the spectrum signal in laser induced breakdown spectroscopy

Based on laser induced breakdown spectroscopy (LIBS) technique, the content of the main elements in the liquid steel of carbon steel alloy can be detected in real time during melting process. In order to detect the liquid alloy steel and forecast the content of the main elements in the alloy steel more accurately, we use the method of weighted principal component analysis (PCA) to reduce noise in the spectral data which were collected in the detecting process. The experimental results show that the weighted PCA method can effectively improve the accuracy and precision of the spectral data.