Study on Design of Intelligent Decision Support System of Engineering Equipment Repair

Ming Zhang; Jiang Yu; Min Hua Wang; Chun Ying Qi

doi:10.4028/www.scientific.net/AMM.127.36

Paper Titles

A Rotor Time Constant Identification Method with Compensation Algorithm
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Design of the Real-Time Autofocusing System for Collimator with Long Focus Length and Large Aperture
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The Study of Image Reconstruction Based on Compressed Sensing Theory
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Study on Design of Intelligent Decision Support System of Engineering Equipment Repair
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Design and Implementation of Auto Parts Data Management System Based on BOM
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A Design of Pulse-Wave Data Collection System
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Prediction of Networks Security Situation Based on Wavelet Kernel Function Network
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Research on the Repetitive Control Technique in Gird-Side Converter of the Double-Fed Wind Power System
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 127Study on Design of Intelligent Decision Support...

Study on Design of Intelligent Decision Support System of Engineering Equipment Repair

Abstract:

By introducing ES (Expert System) of AI (Artificial Intelligence) and KP (Knowledge Processing), etc. into DSS (Decision Support system), the study on design of IDSS_EER (Intelligent Decision Support System of Engineering Equipment Repair) is discussed in detail combined with the characteristics of EER (Engineering Equipment Repair).To start with, the research status quo and analysis of IDSS problems are analyzed and the traditional design problem of IDSS is improved in the system structure and system function of IDSS with a clear aim. Finally, the design and development of IDSS_EER are given a particular description. The system design embodies the strong points of the qualitative and quantitative analyses and can be achieved theatrically and technically. Simultaneously, the system provides the man-in-the-loop support and avoids the intelligent blindness.

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Periodical:

Applied Mechanics and Materials (Volume 127)

Pages:

36-41

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.127.36

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Online since:

October 2011

Authors:

Ming Zhang, Jiang Yu, Min Hua Wang, Chun Ying Qi

Keywords:

Design, Engineering Equipment, Intelligent Decision Support System

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References

[1] S.Y. Li, W.R. Li, X.F. Xiao and X.Q. Yang: Machinery, Vol. 35 (2008) No. 7, pp.75-76.

Google Scholar

[2] A. Liu: Engineering Equipment (PLA Publicatoins, China 2002).

Google Scholar

[3] Y.H. Wang: General Survey of Engineering Equipment Support (Military Science Publicatoins, China 2003).

Google Scholar

[4] P.Z. Teng, L.L. Si and X. Chen: Industrial Control Computer, Vol. 23 (2010) No. 6, p.46.

Google Scholar

[5] X.L. Chen, M.Q. Xiao and Z.Q. Wu: Computer Engineering and Applications, Vol. 43 (2007) No. 17, pp.236-237.

Google Scholar

[6] S.F. Fang and W.Y. Lu: Systems Engineering Theory and Practice, (2001) No. 12, p.54.

Google Scholar

[7] Q. Gao and Y.J. Zhao: National Defence Science and Technology, Vol. 29 (2008) No. 4, pp.6-7.

Google Scholar

[8] Q. Gao, Y.J. Zhao and H. Wang: Software Development and Applications, Vol. 27 (2008) No. 8, pp.92-93.

Google Scholar

[9] Z.H. Qi and X.Y. Ren: Microcomputer Development, Vol. 14 (2004) No. 9, pp.15-16.

Google Scholar

[10] X.D. Wen and T.F. Gao: Radio Engineering, Vol. 36 (2006) No. 12, pp.4-5.

Google Scholar