Research on Classification Optimization Algorithm of Rotor to Stator Rub-impact Fault Using FGSO-SVM - You, Lei; Wang, Jin; Han, Qiyi; Chen, Jing; Liang, Ying (2020 International Symposium on Computer Engineering and Intelligent Communications (ISCEIC), 2020)
Rotor to stator rub-impact fault (RSRIF) is a common fault in rotating machinery. In this paper, a FGSO-SVM algorithm is proposed for the classification and recognition of RSRIF. The algorithm, combining glowworm swarm optimization algorithm (GSO) and shuffled frog-leaping algorithm (SFLA), optimizes the support vector machine (SVM) parameters. Compared with traditional algorithms, FGSO-SVM improves the recognition rate of fault classification and overcomes the deficiencies of being easily trapped into local optimum and slow late convergence rate. Three algorithms herein, namely BPNN, AFSA-SVM and FGSO-SVM, are used for a comparative study under normal condition and RSRIF. The experimental results show that FGSO-SVM has the highest classification and recognition rate of RSRIF.