Li Lingjun,Zhang Zhousuo,He Zhengjia
(School of Mechanical Engineering,Xi'an Jiaotong University,Xi'an 710049,China)
Abstract: A new method of condition trend prediction of mechanical equipment based on support vector machine was presented and the support vector regression machine was constructed. Both simulation data and actual data were used to validate the performance of this regression machine.The support vector regression machine was applied to the trend prediction of the vibration signal from machine sets. The single-step prediction error for peak-peak value of the vibration signal is less than 2% and the 24 steps prediction error is less than 5% with radial basis function £¨RBF£© kernel function and proper parameters.These results show that the support vector regression machine has excellent performance of condition trend prediction for mechanical equipment£®
Keywords: support vector machine;regression;trend prediction