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题目：Fault Diagnosis for Marine Engine System Based on Complex Network Cluster Method 作者：Aiping Zhang, Guang Ren, and Baozhu Jia 论文集CA：Advanced Materials Research Vols. 655-657 (2013) pp 801-805 多谢多谢！ |
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微型控制器: 金币+2, ★★★★★最佳答案, 太感谢了！！ 2013-03-08 09:44:57
静安jingan: 金币+1, 鼓励应助！ 2013-03-08 10:09:07
微型控制器: 金币+2, ★★★★★最佳答案, 太感谢了！！ 2013-03-08 09:44:57
静安jingan: 金币+1, 鼓励应助！ 2013-03-08 10:09:07
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Accession number: 20130916061971 Title: Fault diagnosis for marine engine system based on complex network cluster method Authors: Zhang, Aiping1 ; Ren, Guang1 ; Jia, Baozhu1 Author affiliation: 1 College of Marine Engineering, Dalian Maritime University, Dalian, China Corresponding author: Zhang, A. (zhangaiping_86@yahoo.com.cn) Source title: Advanced Materials Research Abbreviated source title: Adv. Mater. Res. Volume: 655-657 Monograph title: Engineering Solutions for Manufacturing Processes Issue date: 2013 Publication year: 2013 Pages: 801-805 Language: English ISSN: 10226680 ISBN-13: 9783037856482 Document type: Conference article (CA) Conference name: 2012 3rd International Conference on Advances in Materials and Manufacturing Processes, ICAMMP 2012 Conference date: December 22, 2012 - December 23, 2012 Conference location: Beihai, China Conference code: 95671 Sponsor: University of Wollongong, Australia; Northeastern University, China; University of Science and Technology Beijing; Hong Kong Industrial Technology Research Centre Publisher: Trans Tech Publications, P.O. Box 1254, Clausthal-Zellerfeld, D-38670, Germany Abstract: Fault diagnosis can be achieved by the cluster analysis process. We give a complete similarity measurement method and a cluster criterion function defined by modularity increment in complex network community detection. An agglomerative cluster method is proposed and the diagnosis rules are extracted to fault diagnosis for the marine engine system. Using the samples collected from self-manufactured marine engine room simulator, fault diagnosis simulation experiment is carried out to verify the algorithm performance. The results show that the method is accurate and less time-consuming, and is able to recognize the fault pattern which does not exist in the fault history data. © (2013) Trans Tech Publications, Switzerland. Number of references: 8 Main heading: Marine engines Controlled terms: Cluster analysis - Complex networks - Failure analysis - Industrial engineering - Production engineering Uncontrolled terms: Algorithm performance - Cluster - Cluster method - Criterion functions - Fault patterns - History data - Marine engine room simulators - Network cluster - Network communities - Similarity measurements Classification code: 921 Mathematics - 913.1 Production Engineering - 912.1 Industrial Engineering - 922 Statistical Methods - 723 Computer Software, Data Handling and Applications - 612 Engines - 421 Strength of Building Materials; Mechanical Properties - 722 Computer Systems and Equipment DOI: 10.4028/www.scientific.net/AMR.655-657.801 Database: Compendex Compilation and indexing terms, © 2013 Elsevier Inc. |
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