Title :
Prediction of wear for wood planing tool based on genetic-SVM classifier
Author :
Xu, Yunjie ; Xiu, Shudong
Author_Institution :
Coll. of Eng., Zhejiang Forestry Univ., LinAn, China
Abstract :
Wear prediction of wood planing tool is very complex, so it is difficult to use the mathematical model to describe their wear. In this study, an intelligent forecasting method based on genetic-support vector machine (GSVM) approach is presented of wood planing tool wear. An new way provides wear prediction of wood planing tool. The test results show that this GSVM model is effective to prediction wear of wood planing tool.
Keywords :
genetic algorithms; pattern classification; production engineering computing; support vector machines; woodworking machines; genetic SVM classifier; genetic-support vector machine; intelligent forecasting method; wear prediction; wood planing tool; Application software; Diagnostic expert systems; Educational institutions; Fault diagnosis; Forestry; Machinery; Planing; Support vector machine classification; Support vector machines; Testing; genetic-support vector machine; kernel function parameter; wear prediction; wood planing tool;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
DOI :
10.1109/MACE.2010.5535902
