Quality Reliability Evaluation of the Miner Lamp Power Supply with Principal Component Analysis and Support Vector Machine

Abstract:

The quality of the miner lamp power supply (MLPS) affects the performance of the miner lamp, while the safety performance and quality of the miner lamp are closely related to the safety production in coal mines. The factors, which affect the quality of power supply, are screened through the principal component analysis (PCA). After training the principal extracted component by PCA, the measurement model for the MLPS is set up based on support vector machine (SVM), meanwhile, the Gaussian function, which functions as the kernel function of SVM are selected to simulate, the test results indicate that the measurement model based on PCA-SVM could be used as the detection of the MLPS, which can better ensures the quality reliability of the MLPS.

• Periodical: Key Engineering Materials (Volumes 460-461)
• Pages: 716-723
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.460-461.716
• Online since: January 2011
• Authors: Dan Ma, Zhan Qing Chen, Ji Da Huang, Hao Jin Lv
• Keywords: Kernel Function, Miner Lamp Safety, Principal Component Analysis (PCA), Quality Reliability, Support Vector Machine (SVM)

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