A STUDY OF NEGATIVE SELECTION ALGORITHM-BASED MOTOR FAULT DETECTION AND DIAGNOSIS

Xiao-Zhi Gao; He Xu; Xiaolei Wang; Kai Zenger

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A STUDY OF NEGATIVE SELECTION ALGORITHM-BASED MOTOR FAULT DETECTION AND DIAGNOSIS

机译：基于负选择算法的电机故障检测与诊断研究

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摘要

In this paper, we present a comprehensive study of the Negative Selection Algorithm (NSA)-based motor fault detection and diagnosis. The NSA only needs the feature signals of the healthy motors for generating the motor fault detectors. Different from the conventional fault detection approaches, no prior knowledge of the motor fault types is assumed to be known beforehand. Based on the motor fault detection results, the NSA can be further applied for the fault diagnosis. The applicability of our motor fault detection and diagnosis method is examined using the Fisher's iris data classification and three real-world motor fault detection and diagnosis problems in computer simulations.

机译：在本文中，我们对基于负选择算法（NSA）的电动机故障检测和诊断进行了全面的研究。 NSA仅需要正常电动机的特征信号即可生成电动机故障检测器。与常规的故障检测方法不同，假定没有事先知道电机故障类型的先验知识。根据电机故障检测结果，可以将NSA进一步用于故障诊断。我们使用Fisher虹膜数据分类和计算机仿真中的三个现实世界中的电机故障检测和诊断问题，检验了我们的电机故障检测和诊断方法的适用性。

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来源
《International Journal of Innovative Computing Information and Control》 |2013年第2期|875-901|共27页
作者
Xiao-Zhi Gao; He Xu; Xiaolei Wang; Kai Zenger;
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作者单位

Department of Automation and Systems Technology School of Electrical Engineering Aalto University Aalto 00076, Finland;

College of Mechanical and Electrical Engineering Harbin Engineering University No. 145, Nantong Street, Nangang District, Harbin 150001, P. R. China;

Department of Automation and Systems Technology School of Electrical Engineering Aalto University Aalto 00076, Finland;

Department of Automation and Systems Technology School of Electrical Engineering Aalto University Aalto 00076, Finland;

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正文语种 eng
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关键词
artificial immune systems (AIS); negative selection algorithm (NSA); fault detection; fault diagnosis; motors; electrical machines; mobile robots;

机译：人工免疫系统（AIS）;否定选择算法（NSA）;故障检测;故障诊断;马达;电机;移动机器人;

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1. Improvement of induction motor fault diagnosis performance by using genetic algorithm-based feature selection [J] . N-T Nguyen H-H Lee Proceedings of the Institution of Mechanical Engineers . 2008,第C8期

机译：通过基于遗传算法的特征选择提高感应电动机故障诊断性能
2. Improvement of induction motor fault diagnosis performance by using genetic algorithm-based feature selection [J] . N.-T. Nguyen, H.-H. Lee Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science . 2008,第8期

机译：通过基于遗传算法的特征选择提高感应电动机故障诊断性能
3. Diagnosis of Stator-Winding-Turn Faults of Induction Motor by Direct Detection of Negative Sequence Currents [J] . TOSHIJI KATO, KAORU INOUE, KEISUKE YOSHIDA Electrical engineering in Japan . 2014,第3期

机译：直接检测负序电流诊断异步电动机定子绕组旋转故障
4. Negative Selection Algorithm-Based Motor Fault Diagnosis [C] . Xiao-Zhi Gao, Xiaolei Wang, Kai Zenger, Practical applications of intelligent systems . 2011

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5. Robust fault detection and diagnosis for permanent magnet synchronous motors. [D] . Liu, Li. 2006

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6. Big Data Approach to Batch Process Monitoring: Simultaneous Fault Detection and Diagnosis Using Nonlinear Support Vector Machine-based Feature Selection [O] . Melis Onel, Chris A. Kieslich, Yannis A. Guzman, -1

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7. Current Based Fault Detection and Diagnosis of Induction Motors. Adaptive Mixed-Residual Approach for Fault Detection and Diagnosis of Rotor, Stator, Bearing and Air-Gap Faults in Induction Motors Using a Fuzzy Logic Classifier with Voltage and Current Measurement only. [O] . Bradley William John 2013

机译：基于电流的感应电动机故障检测和诊断。仅使用电压和电流测量的模糊逻辑分类器的自适应混合残差方法对异步电动机的转子，定子，轴承和气隙故障进行故障检测和诊断。

A STUDY OF NEGATIVE SELECTION ALGORITHM-BASED MOTOR FAULT DETECTION AND DIAGNOSIS

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