DYNAMIC RELIABILITY RESEARCH OF FLEXIBLE MECHANISM BASED ON SUPPORT VECTOR MACHINE REGRESSION

In order to improve computational accuracy and efficiency in Flexibility Mechanism (FM) dynamic reliability analysis, a novel SVM Regression Extremum Method (SREM) is proposed based on the combination of Monte Carlo method (MC) and Support Vector Machine (SVM) regression theory. By means of ADAMS software, a small amount of samples for FM dynamic response extremum were generated. Based on these samples, the surrogate model of FM dynamic response extremum was established by SVM regression theory. Reliability of FM dynamic response can be assessed by the surrogate model. Finally, the reliability of rocker maximum angle in crank-rocker FM was analyzed by MC, SREM and other two methods. The results show that, in the case of small samples, the computational precision of SREM is almost the same as that of MC, and is obviously better than that of other two methods; the computational efficiency of SREM is significantly higher than that of MC, and is slightly higher than that of other two methods. It is proved that SREM is of high-precision and high-efficiency in FM dynamic reliability analysis in the case of a small amount of samples.