Configurable Fault Diagnosis Model in Induction Motor

Abstract

Abstract:

Abstract： Based on the research on typical fault diagnosis model, a configurable diagnosis model of induction motor was proposed to resolve the problem of complexity of network and difficulty of training. This model contains multiple sub RBF neural networks which have multiple inputs and single output, and one type of fault can be recognized by a specific sub-model. The sub-models can be any combination based on the demands of the system, and various faults can be identified. The model is trained using the samples with feature extracted, and the effectiveness of fault diagnosis model is verified through test samples. It is shown that one sub-model can be used to recognize one specific state of motor in the configured fault diagnosis model, the structure is simple, the difficulty of model training is reduced, the fault identification capability of model and flexibility of application are improved, providing a new method for the induction motor fault diagnosis.

Key words: induction motor, fault diagnosis model, configuration, radial basis function (RBF) neural network, structure

CLC Number:

TM 307

NIE Binga,ZHAO Huimina,DING Mingyanb,LI Wena. Configurable Fault Diagnosis Model in Induction Motor[J]. Journal of Shanghai Jiaotong University, 2015, 49(03): 402-405.

References

［1］Martins J F, Piers V F, Pires A J. Unsupervised neuralnetworkbased algorithm for an online diagnosis of treephase induction motor stator fault ［J］. IEEE Transaction on Industrial Electronics, 2007，54(1)：259264.

［2］Dubey P, Sujatha C. Motor fault classification using wavelet energy and artificial neural network ［J］. International Journal of COMADEM, 2009, 12(3)：2431.

［3］杨存祥, 朱琛, 解豪杰. 基于RPROP神经网络算法的异步电动机故障诊断［J］. 电力自动化设备, 2012，32(1)：8083.

YANG Cunxiang, ZHU Chen, XIE Haojie. Fault diagnosis based on RPROP neural network for asynchronous motor ［J］. Electric Power Automation Equipment，2012，32(1)：8083.

［4］朱博，胡燕，赵永标. 人工神经网络在故障诊断系统中的应用［J］. 舰船电子工程，2005，25(1)：9195.

ZHU Bo, HU Yan, Zhao Yongbiao. Application of artificial neural networks in fault diagnose system ［J］. Ship Electronic Engineering，2005，25(1)：9195.

［5］HechtNielsen R. Theory of backpropagation neural network ［J］. Neural Networks，1989(1)：593605.

［6］邱阿瑞，孙健. 牵引电机故障模式识别与诊断［J］.清华大学学报:自然科学版，1999，39(3)：7274.

QIU Arui, SUN Jian. Pattern recognition and diagnosis of faults in electrical machines ［J］. Journal of Tsinghua University: Science and Technology, 1999，39(3)：7274.

［7］魏海坤. 神经网络结构设计的理论与方法［M］. 北京：国防工业出版社, 2005.

［8］PonsLlinares J, AntoninoDaviu J A, RieraGuasp M，et al. Induction motor diagnosis based on a transient current analytic wavelet transform via frequency BSplines ［J］. IEEE Transactions on Industrial Electronics，2011，58(5)：15301544.

［9］WANG Zhenzhou, HAN Ming, LIU Peng，et al. Fault detection of motor’s interturn short circuit based on BP neural network ［J］. International Journal of Modelling, Identification and Control, 2012，16(3)：234239.

[1]	WANG Yanlin, GUO Qi, SUN Shanshan, WEI Sihao, XU Ning. Discrete Element Simulation and Analysis of Ice-Inclined Structure Interaction [J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1168-1175.
[2]	LU Linhai, WU Chaojun, SUN Jiecheng, CAI Hao, YE Guanlin. Micropore Characteristics and CT Seepage Test of Jinan Red Clay with a Strong Vertical Permeability [J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1218-1226.
[3]	NI Yangfan, YANG Yuanyuan, XIE Zhe, ZHENG Dezhong, WANG Weidong. Multi-Feature Extraction of Pulmonary Nodules Based on LSTM and Attention Structure [J]. Journal of Shanghai Jiao Tong University, 2022, 56(8): 1078-1088.
[4]	LI Jianjun, ZHU Wenfeng, SUN Haitao, LI Yuanhui, WANG Shunchao. Method of Curing Deformation Prediction and Surface Reconstruction Compensation for Roller-Hemming Structures with Dissimilar Materials [J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 965-976.
[5]	CAI Shuyu∗ (蔡舒妤), SHI Lizhong (师利中). Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 757-767.
[6]	HUANG Yinghao1,2 (黄颖浩), WU Yi3 (吴怡), YAO Lixiu2 (姚莉秀), CAI Yunze1,2∗ (蔡云泽). A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 671-679.
[7]	LIN Zhangpeng, YU Haidong, YUAN Ke. Model of Assembly Deviation of Irregular Large Thin-Walled Structures Based on Higher-Order Composite Shell Element [J]. Journal of Shanghai Jiao Tong University, 2022, 56(5): 584-593.
[8]	YANG Pufan (杨朴凡), HUANG Hongxin (黄洪鑫) WEI Siji (卫思霁), YAO Yuan (姚远), ZHANG Zhinan∗ (张执南). Design of a Low Respiratory Resistance Mask for COVID-19 [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(4): 543-551.
[9]	HUANG Chengjun, ZHU Tianyi, SONG Xiaobing. In-Plane Yield Criterion of Steel-Concrete-Steel Unit Panel [J]. Journal of Shanghai Jiao Tong University, 2022, 56(4): 422-430.
[10]	QIN Han, WU Bin, SONG Yuhui, LIU Jin, CHEN Lan. Numerical Analysis of Support Interference for a Slender Configuration at Super Large Angles of Attack in High Speed Wind Tunnel [J]. Air & Space Defense, 2022, 5(3): 44-51.
[11]	LI Yu, YANG Daoyong, LIU Lingya, WANG Yiyin. Underwater Image Enhancement Based on Generative Adversarial Networks [J]. Journal of Shanghai Jiao Tong University, 2022, 56(2): 134-142.
[12]	WANG Yecheng, LI Yang, ZHANG Di, YANG Yue, LUO Zhen. Resistance Element Welding of Carbon Fiber Reinforced Thermoplastic Composites to High-Strength Steel [J]. Journal of Shanghai Jiao Tong University, 2022, 56(10): 1349-1358.
[13]	WANG Zheng (王正), XU Hui (许辉), L v Na (吕娜), TAO Wei∗ (陶卫), CHEN Guodong (陈国栋), CHI Wenzheng (迟文正), SUN Lining (孙立宁). Dynamic Obstacle Avoidance for Application of Human-Robot Cooperative Dispensing Medicines [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(1): 24-35.
[14]	WANG Zhaolong,LIU Lijiao. Future City: How Can Urban Problems Be Solved by Nature System? [J]. Journal of Shanghai Jiao Tong University, 2021, 55(Sup.1): 79-81.
[15]	WANG Lipo. Quantification of Spatial Structures of Complex Systems [J]. Journal of Shanghai Jiao Tong University, 2021, 55(Sup.1): 104-105.