A Terahertz Spectroscopy Nondestructive Identification Method for Rubber Based on CS-SVM

• Main Authors: Xianhua Yin, Wei Mo, Qiang Wang, Binyi Qin
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: Advances in Condensed Matter Physics
• Online Access: http://dx.doi.org/10.1155/2018/1618750

A method is proposed for rubber identification based on terahertz time-domain spectroscopy (THz-TDS) and support vector machine (SVM). In order to improve the accuracy, the cuckoo search algorithm (CS) is used to optimize the penalty factor C and kernel function parameter g of SVM. The SVM model optimized by the cuckoo search algorithm is abbreviated as CS-SVM. Principal component analysis (PCA) is applied to decrease the dimension of the spectral data. The top ten principal component factors, whose accumulated variance contribution rate reaches 93.93%, are extracted from the original spectra data and then are applied to CS-SVM. The identification rate of testing sets for CS-SVM is 100%, which is significantly higher than 96.67% identification rate of testing sets for PSO-SVM and Grid search. Experimental results show that CS-SVM can accomplish nondestructive identification for different rubber. This method lays a theoretical foundation for the application of terahertz spectroscopy in rubber classification and identification.