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20th Annual American Control Conference (ACC)

作者： Liu, SL Zhang, JZ Shi, WG Huang, WH Daqing Petr Inst Dept Engn Mech Anda 151400 Heilongjiang Peoples R China

ISBN: (纸本)0780372980

The main task of the immune system is to detect and eliminate the non-self materials called antigens such as virus and cancer cells which come from inside and outside of the living system. The negative-selection algorithm proposed which is inspired by the negative-selection mechanism of the immune system is able to detect any change. In this paper, the algorithm is improved to make it suitable for the fault diagnosis of mechanical equipment. Moreover, based on the improved algorithm a new approach of fault diagnosis of rotary machinery is proposed and its feasibility is demonstrated by the on-line fault diagnosis of rotary machinery successfully. In addition, the approach of the novel fault diagnosis can also be applied to other fields.

关键词： immune system negative-selection algorithm improved algorithm rotary machinery fault diagnosis

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An Artificial Immune algorithm Based Intelligent Monitoring System in Grinding Process

An Artificial Immune Algorithm Based Intelligent Monitoring ...

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2nd International Conference on Manufacturing Science and Engineering

作者： Lv, Zhijun Xiang, Qian Pang, Jingzhu Donghua Univ Key Lab Text Sci & Technol Minist Educ Shanghai 201620 Peoples R China Donghua Univ Coll Mech Engn Shanghai 201620 Peoples R China

ISBN: (纸本)9783037850312

Grinding is widely used as a precision process for machining difficult-to-cut materials. Grinding productivity is still greatly dependent on the experience and skill of human operators. Focusing on the indirect method, an attempt was made to build up an intelligent system to monitor the condition of grinding wheels with force signals and the acoustic emission (AE) signals. An artificial immune algorithm based multi-signals processing method was presented in this paper. The intelligent system is capable of incremental supervised learning of grinding conditions and quickly pattern recognition, and can continually improve the monitoring precision. The experiment indicates that the accuracy of condition identification is about 87%, and able to meet the industrial need on the whole.

关键词： negative-selection algorithm Artificial Immune Intelligent Monitoring Model Multi-Sensor System Grinding Process

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An Application Case Study on Multi-sensor Data fusion System for Intelligent Process Monitoring

An Application Case Study on Multi-sensor Data fusion System...

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47th CIRP Conference on Manufacturing Systems

作者： Lu, Zhi-Jun Xiang, Qian Xu, Lan Engineering Research Center of Advanced Textile Machinery Ministry of Education China College of Mechanical Engineering Donghua University China

Multi-sensor data fusion is a technology to enable combining information from several sources in order to form a unified picture. Focusing on the indirect method, an attempt was made to build up a multi-sensor data fusion system to monitor the condition of grinding wheels with force signals and the acoustic emission (AE) signals. An artificial immune algorithm based multi-signals processing method was presented in this paper. The intelligent monitoring system is capable of incremental supervised learning of grinding conditions and quickly pattern recognition, and can continually improve the monitoring precision. The application case indicates that the accuracy of condition identification is about 87%, and able to meet the industrial need on the whole. (C) 2014 Elsevier B.V.

关键词： Multi-sensor Data Fusion negative-selection algorithm Artificial immune Process Monitoring Grinding

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ADC FUNCTIONAL TESTING USING ARTIFICIAL IMMUNE SYSTEM

ADC FUNCTIONAL TESTING USING ARTIFICIAL IMMUNE SYSTEM

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19th IMEKO World Congress

作者： de Souza, Cleonilson Protasio Torres, Claudio Leao Freire, Raimundo C. S. de Assis, Francisco M. Fed Inst Maranhao Sao Luis Brazil Univ Fed Campina Grande Campina Grande Brazil

ISBN: (纸本)9789638841001

Artificial immune systems have been considered one of the most promising nature-inspired technique used for novelty detection systems, optimization, identification, etc. One of the main tools of these systems is the negative-selection algorithm that is based on the natural self-nonself discrimination which has made possible the body distinguish any foreign cell from the body's self cell. In this work, it is used the negative-selection algorithm to perform functional testing of analog-to-digital converter. In this way, the evaluation of the converter is performed by a set of immune-based detectors which can detect faulty output responses. Using the immune-based detector set, experimental results have been shown the effectiveness of the proposed method.

关键词： ADC Functional testing Artificial immune systems negative-selection algorithm

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A Process Monitoring System Based on Multi-sensor Data fusion: An Experiment Study

A Process Monitoring System Based on Multi-sensor Data fusio...

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2nd International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE)

作者： Xiang, Qian Lu, Zhi-Jun Li, Bei-Zhi Yang, Jiang-guo Minist Educ Engn Res Ctr Adv Text Machinery Shanghai 201620 Peoples R China Donghua Univ Shanghai 201620 Peoples R China

ISBN: (纸本)9781467314602

Multi-sensor data fusion is a technology to enable combining information from several sources in order to form a unified picture. Focusing on the indirect method, an attempt was made to build up a multi-sensor data fusion system to monitor the condition of grinding wheels with force signals and the acoustic emission (AE) signals. An artificial immune algorithm based multi-signals processing method was presented in this paper. The intelligent monitoring system is capable of incremental supervised learning of grinding conditions and quickly pattern recognition, and can continually improve the monitoring precision. The experiment indicates that the accuracy of condition identification is about 87%, and able to meet the industrial need on the whole.

关键词： Multi-sensor Data Fusion negative-selection algorithm Artificial immune Process Monitoring Grinding

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Study of fault diagnosis in brushless machines based on artificial immune algorithm

Study of fault diagnosis in brushless machines based on arti...

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IEEE International Symposium on Industrial Electronics

作者： Wang Tao Liu Nian Xie Chi Sun Kejin Sichuan Univ Dept Elect Engn Chengdu Sichuan Peoples R China Sichuan Univ Dept Measurement & Control Sichuan Peoples R China

ISBN: (纸本)9781424404964

It is describes a kind of artificial immune algorithm (AIA), which is based on the nature immune system in this paper, and the basic principle of the immune system is presented. And the negative-selection algorithm is inspired by the negative-selection mechanism of the nature immune system, and it is can detect any tiny change in an actual system, so it can be used in the state monitoring and fault diagnosis. In order to increase effectively the operation reliability of the brushless machines, a new detection method has been presented to the faults diagnosis of rotating rotor rectifiers in generators with brushless excitation systems, which is based on the negative-selection algorithm. When any rotating rotor rectifier has some faults, such as one bridge arm breaking, then the rectifiers are under abnormal operating mode, and the current waveform is changed, so the signal waveform monitored is unusual. Different fault has different signal waveform, and the signal waveform can be also analyzed by taking: advantage of the negative-selection algorithm, then the fault type can be identified The development trends of the application of the negative-selection algorithm for fault diagnosis are also introduced.

关键词： brushless machines fault diagnosis optimisation rectifying circuits reliability rotors artificial immune algorithm brushless excitation systems immune system negative-selection algorithm operation reliability rotating r

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An Application Case Study on Multi-sensor Data fusion System for Intelligent Process Monitoring

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Procedia CIRP 2014年 17卷 721-725页

作者： Zhi-Jun Lu Qian Xiang Lan Xu Engineering Research Center of Advanced Textile Machinery Ministry of Education College of Mechanical Engineering Donghua University

关键词： Multi-sensor Data Fusion negative-selection algorithm Artificial immune Process Monitoring Grinding

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An Intelligent Monitoring System for Grinding Process

An Intelligent Monitoring System for Grinding Process

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2007国际机械工程与力学会议

作者： Beizhi LEE Jianguo YANG Zhijun Lü Jingzhu PANG College of Mechanical Engineering Donghua University

Grinding is widely used as a precision process for machining difficult-to-cut materials. However, the inherent complexities of grinding process make mathematical modelling difficult. Therefore, grinding productivity is still greatly dependent on the experience and skill of human operators. Focusing on the indirect method, an attempt was made to build up an intelligent system to monitor the condition of grinding wheels with force signals and the acoustic emission (AE) signals. The novel multi-signals processing method---negative-selection algorithm (NSA) based on artificial immune mechanism was presented in this paper. The intelligent system is capable of incremental supervised learning of grinding conditions and quickly pattern recognition, and can continually improve the monitoring precision. The experiment indicates that the accuracy of condition identification is about 87%, and able to meet the industrial need on the whole.

关键词： negative-selection algorithm Artificial immune Intelligent monitoring model Multi-sensor System Grinding process

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