【摘要】：針對傳統(tǒng)方法難以實現(xiàn)對海量數(shù)據(jù)環(huán)境下的設(shè)備狀態(tài)評價的問題,提出了一種基于海量數(shù)據(jù)融合的設(shè)備狀態(tài)評價方法。首先,利用擅長處理海量數(shù)據(jù)的分布式聚類算法K-means對海量狀態(tài)數(shù)據(jù)進(jìn)行預(yù)處理為多個簇,并求出各個簇的質(zhì)心作為該簇的代表信息;然后對代表信息進(jìn)行加權(quán)處理;最后利用證據(jù)理論對加權(quán)的代表信息進(jìn)行融合,從而決斷出設(shè)備的狀態(tài)。通過仿真實驗結(jié)果表明,該方法能對海量信息進(jìn)行有效融合,并能更合理地決斷出設(shè)備的狀態(tài)信息。
[Abstract]:Aiming at the problem that traditional methods are difficult to evaluate the equipment status in mass data environment, a method of equipment status evaluation based on mass data fusion is proposed. Firstly, the distributed clustering algorithm K-means which is good at processing mass data is used to preprocess mass state data into multiple clusters, and the centroid of each cluster is obtained. Finally, the weighted representative information is fused with the evidence theory to determine the state of the device. The simulation results show that the method can effectively fuse the massive information and reasonably determine the state information of the device.
【作者單位】： 貴州大學(xué)現(xiàn)代制造技術(shù)教育部重點實驗室;貴州大學(xué)機(jī)械工程學(xué)院;
【基金】：國家自然科學(xué)基金資助項目(51475097) 貴州省基礎(chǔ)研究重大項目(黔科合JZ字[2014]2001)
【分類號】：TH17

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