Vibration Fault Diagnosis for Steam Turbine Based on Fruit Fly Optimization Algorithm Support Vector Machine

PDF(1600 KB)

Journal of Vibration and Shock ›› 2014, Vol. 33 ›› Issue (22) : 111-114.

论文

Vibration Fault Diagnosis for Steam Turbine Based on Fruit Fly Optimization Algorithm Support Vector Machine

Shi Zhi-biao，Miao-Ying

Author information +

History +

Abstract

In order to solve the problem that the selection of the kernel function parameters and penalty factor parameters in the support vector machine(SVM)algorithm is blindfold，we use the fruit fly optimization algorithm(FOA)to optimize the parameters in SVM．A fault diagnosis algorithm of SVM based on FOA is put forward，and then we use it to execute the pattern recognition of the turbine failure experimental data．This algorithm could optimize the SVM parameters automatically，and achieve ideal global optimal solution．Comparing with the SVM which optimized by the common used methods of the particle swarm optimization(PSO) and the Genetic Algorithm (GA) currently，the results demonstrate that FOA-SVM has the fastest recognition speed and the highest recognition rate．

Key words

support vector machine / turbine / vibration diagnosis / fruit fly optimization algorithm

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Shi Zhi-biao;Miao-Ying. Vibration Fault Diagnosis for Steam Turbine Based on Fruit Fly Optimization Algorithm Support Vector Machine[J]. Journal of Vibration and Shock, 2014, 33(22): 111-114