| 引用本文: | 陈佳,王建华,张冰,朱志宇.船舶电站故障诊断中的数据融合算法[J].电力自动化设备,2006,(3):28-31 |
| .Data fusion algorithm for ship power station fault diagnosis system[J].Electric Power Automation Equipment,2006,(3):28-31 |
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| 摘要: |
| 将数据融合技术应用于船舶电站故障诊断系统中,在数据处理的检测层、特征层及决策层上分别提出不同的数据融合算法:在检测层提出自适应加权数据融合算法,在特征层提出基于灰色优势分析的数据融合算法,在决策层提出基于D-S证据理论的数据融合算法。这些算法解决了传统故障诊断中存在的大量采集数据如何有效处理的问题。所提出的算法针对船舶电站故障诊断的特殊性,有较强的适应性,提高了实际诊断的准确性和可靠性。 |
| 关键词: 船舶电站,故障诊断,数据融合,自适应加权,优势分析,D-S证据理论 |
| DOI： |
| 分类号:TM76 TP206.3 |
| 基金项目: |
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| Data fusion algorithm for ship power station fault diagnosis system |
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CHEN Jia WANG Jian-hua ZHANG Bing ZHU Zhi-yu
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| Abstract: |
| The data fusion technology is applied in ship power station fault diagnosis system. Diffe-rent data fusion algorithms are brought forward for different layers of data processing,in which adap-tive weighting data fusion algorithm is for the detection layer,grey superiority analysis - based data fusion algorithm for the character layer,and D-S theory-based data fusion algorithm for the decision-making layer. Thus the collected data can be processed more efficiently. Having considered the particula -rity of the ship power statiom fault diagnosis, the proposed algorithms have good adaptability and im-prove the accuracy and reliability of diagnosis. |
| Key words: ship power station,fault diagnosis,data fusion,adaptive weighting,superiority analysis,Dempster-Shafer theory |
