本文關(guān)鍵詞：一種采用相空間重構(gòu)的多源數(shù)據(jù)融合方法　出處：《西安交通大學(xué)學(xué)報(bào)》2016年08期 　論文類型：期刊論文

  更多相關(guān)文章： 相空間重構(gòu) 數(shù)據(jù)融合 自適應(yīng)加權(quán)融合估計(jì) 信息熵

【摘要】：針對(duì)化工生產(chǎn)系統(tǒng)中狀態(tài)監(jiān)控變量數(shù)量龐大、冗余度高等問(wèn)題,提出了一種采用相空間重構(gòu)的多源數(shù)據(jù)融合方法。該方法首先根據(jù)互信息法和Cao方法分別求取相空間重構(gòu)參數(shù)延遲時(shí)間和嵌入維數(shù);然后,基于信息熵對(duì)自適應(yīng)加權(quán)融合估計(jì)方法的融合目標(biāo)函數(shù)進(jìn)行改進(jìn),并利用社會(huì)認(rèn)知優(yōu)化算法確定各信息源的權(quán)重系數(shù),實(shí)現(xiàn)多源數(shù)據(jù)融合;最后,通過(guò)實(shí)際化工生產(chǎn)系統(tǒng)的數(shù)據(jù)分析對(duì)所提方法進(jìn)行有效性驗(yàn)證。實(shí)驗(yàn)結(jié)果表明,相比于傳統(tǒng)方法,由該方法得到的重構(gòu)相空間的信息更加完備,其信息量和平均峰值信噪比分別平均提高135.6%和40.6%。該方法為解決多源異類傳感器數(shù)據(jù)融合問(wèn)題提供了一種新思路。
[Abstract]:According to the number of state variables in the monitoring of chemical production system is huge, high redundancy problem, proposed a multi-source data fusion method by using phase space reconstruction. Firstly, according to the mutual information method and Cao method respectively to calculate the phase space reconstruction parameters of delay time and embedding dimension; then, information entropy fusion estimation fusion target function method to improve the adaptive weighting based on using social cognitive optimization algorithm to determine the weights of each information source, multi-source data fusion; finally, through the actual chemical production data analysis system to verify the validity of the proposed method. The experimental results show that compared with the traditional method, the reconstruction obtained by the method of phase space information more complete than the average increase of 135.6%, respectively, and the 40.6%. method to solve the multi-source heterogeneous sensor data fusion problem of the information quantity and average peak signal-to-noise A new way of thinking is provided.

【作者單位】： 西安交通大學(xué)機(jī)械制造系統(tǒng)工程國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(51375375)
【分類號(hào)】：TP202
【正文快照】： 化工生產(chǎn)系統(tǒng)是典型的耗散系統(tǒng),其中包含數(shù)百甚至更多的監(jiān)測(cè)變量對(duì)其狀態(tài)進(jìn)行監(jiān)測(cè),產(chǎn)生了海量的監(jiān)測(cè)時(shí)間序列,但同時(shí)也帶來(lái)了大量的冗余信息。多傳感器數(shù)據(jù)融合技術(shù)能夠?qū)?lái)自多個(gè)傳感器的信息和數(shù)據(jù)進(jìn)行綜合分析與處理,在實(shí)現(xiàn)多源信息互補(bǔ)的同時(shí)能有效降低冗余程度。數(shù)據(jù)級(jí)融

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1 馬東玲;;相空間重構(gòu)中時(shí)間延遲的確定方法[J];硅谷;2013年19期

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本文編號(hào)：1418503