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题目 基于复杂网络Newman快速算法的船舶柴油机故障诊断 作者 张爱萍； 任光； 林叶锦； 曹辉； 贾宝柱 期刊 内燃机工程 |
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得意忘形21
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Accession number: 20152100877317 |
2楼2015-06-16 15:28:31
Paulwolf
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Accession number: 20152100877317 Title: Fault diagnosis for marine diesel engine based on newman fast algorithm in complex network Authors: Zhang, Ai-Ping1 Email author zhangaiping.07@163.com; Ren, Guang1 Email author reng@dlmu.edu.cn; Lin, Ye-Jin1; Cao, Hui1; Jia, Bao-Zhu1 Author affiliation: 1 College of Marine Engineering, Dalian Maritime University, Dalian, China Corresponding author: Ren, Guang Source title: Neiranji Gongcheng/Chinese Internal Combustion Engine Engineering Abbreviated source title: Neiranji Gongcheng Volume: 36 Issue: 2 Issue date: April 15, 2015 Publication year: 2015 Pages: 61-67 Language: Chinese ISSN: 10000925 CODEN: NEGOEB Document type: Journal article (JA) Publisher: Chinese Society for Internal Combustion Engines Abstract: Fault classification and diagnosis process of marine diesel engine was transformed into process of the data sample cluster. Defining functions of linear similarity, inverse similarity, exponential similarity and ellipse similarity and taking similarity as the weighted edge and each sample point as the node, a weighted and undirected network model was constructed. A fault diagnosis method using criterion function of Newman fast algorithm as clustering criterion function to detect gradually the community structure of the network was proposed.Using the fault data of a self-developed marine engine simulator as an example of fault diagnosis, fault analysis and diagnosis were conducted to verify the method and analyze impacts of thresholds and similarity coefficient on the performance of the algorithm. Results show that this method has advantages of effectiveness, computation time short, and satisfying online diagnosis requirements. Moreover, it can recognize unknown fault patterns, solving the problem to find the cluster in cluster analysis. ©, 2015, Chinese Society for Internal Combustion Engines. All right reserved. Number of references: 14 Main heading: Fault detection Controlled terms: Algorithms - Cluster analysis - Clustering algorithms - Complex networks - Computer aided diagnosis - Diesel engines - Engines - Failure analysis - Internal combustion engines - Inverse problems - Marine engines Uncontrolled terms: Community structures - Fast algorithms - Fault classification - Fault diagnosis method - IC engines - Marine Diesel Engines - Marine engine simulators - Similarity coefficients Classification code: 422 Strength of Building Materials; Test Equipment and Methods - 612 Engines - 721 Computer Circuits and Logic Elements - 722 Computer Systems and Equipment - 723 Computer Software, Data Handling and Applications - 723.5 Computer Applications - 921 Mathematics - 922 Statistical Methods DOI: 10.13949/j.cnki.nrjgc.2015.02.011 Database: Compendex Compilation and indexing terms, © 2015 Elsevier Inc. |
3楼2015-06-16 15:29:09
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4楼2015-06-16 15:35:18
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5楼2015-06-16 15:41:40
