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Research on information technology of state monitoring and fault prediction for mechatronics system

仪器仪表学报 2016年第S1期37卷 139-145页

作者： Xu Xiaoli Zuo Yunbo Meng Lingxia Zhao Xiwei Liu Xiuli Beijing Information Science & Technology University Beijing Institute of Technology

The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and *** on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring *** technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.

关键词： mechatronics system information technology state monitoring fault prediction

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Recognition of Pump state by RBF Neural Network

Recognition of Pump State by RBF Neural Network

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2007国际机械工程与力学会议

作者： Jimei WU Qiumin WU Institute of Printing and Packaging Engineering Xi’an University of Technology

On the basis of the traditional BP and RBF neural network, a new algorithm--user-defined step radial basis function was developed to monitor and recognize the three state (normal, wear and abnormal state) of vacuum air press pump ZYB03-60, then diagnosed the fault of it. The feature was extracted by sorting, learning and discriminating of the vibration signal. The frequency factor was taken into account in the new method. Therefore, the entire initial central node was adjusted and moved to the data area. This avoided the "dead center" which came from the traditional method with the principle of the nearest distance. In addition, the algorithm punished the competitor of the winning node and realized the choice of node automatically. Results indicate that the three states are presented in different area. The node reaches steady state with training 400 times and this is much faster than the traditional (1000 times of traditional).

关键词： Mode recognition Neural network Radial basis function state monitoring

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Study on Quantitative Analysis Method of Methanol Raman Spectra in Oil By Extraction Technology

Study on Quantitative Analysis Method of Methanol Raman Spec...

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第二十届全国光散射学术会议（CNCLS20）

作者： WANG Cong ZHANG Jiayi SONG Shijie GAO Junying SU Bing state Grid Shandong Electric Power Company Dezhou Power Supply Company state Key Laboratory of Power Transmission Equipment ＆ System Security and New Technology Chongqing University

Accurately detecting the concentration of methanol dissolved in transformer oil is of great importance for diagnosing the aging degradation of insulating *** this paper,acetonitrile were selected as extractants,and mixed with transformer oil samples containing different concentrations of methanol to complete the sample pretreatment *** concentration of methanol in transformer oil samples was determined by Raman *** quantitative analysis method based on the principal component analysis of peak intensity of Raman spectra and the quantitative analysis method based on principal component analysis of peak area of Raman spectra were *** results show that the accuracy of fitting and error calculation using Raman spectral peak area as quantitative analysis parameter is higher,especially in the low concentration case concerned,it is helpful for us to detect trace methanol dissolved in transformer oil.

关键词： state monitoring Methanol quantitative analysis Extraction Raman spectroscopy

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D-S Data Fusion and Efficiency Evaluation for Drilling Process

D-S Data Fusion and Efficiency Evaluation for Drilling Proce...

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第37届中国控制会议

作者： Haipeng Fan Xuzhi Lai Min Wu School of Automation China University of Geosciences Hubei Key Labortory of Advanced Control and Intelligent Automation for Complex System

Due to the unknown complexity of geological conditions, drilling operations are difficult to carry out. It is of great value to implement drilling measurement while drilling. However, due to the poor working conditions underground, information transmission for the drilling process may be affected, which leads to the loss and conflicts of the data. It is necessary to use effective method to deal with the data and to make evaluation for the drilling process. In this paper, we present a D-S data fusion method and use fused data to form a framework to evaluate efficiency for the drilling process. We can efficiently analyze the entire drilling process and optimize the drilling parameters based on this framework.

关键词： state monitoring Wireless Sensor Network Data fusion Efficiency evaluation Drilling process

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