A weighted PCA based denosing for the spectrum signal in laser induced breakdown spectroscopy
- Resource Type
- Conference
- Authors
- Niu, Zhixing; Yang, Peng; Sun, Junqing
- Source
- 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), International Congress on. :848-853 Oct, 2016
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Principal component analysis
Surface emitting lasers
Steel
Spectroscopy
Plasmas
Electric breakdown
Liquids
LIBS
PCA
Weighted PCA
Denosing
- Language
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.