傳統(tǒng)的同步數(shù)據(jù)融合算法不能在計(jì)算量和估計(jì)精確度上達(dá)到整體“優(yōu)”，而現(xiàn)有的異步融合算法大都存在時(shí)間延遲以及計(jì)算量大等問題。本文針對(duì)傳統(tǒng)融合算法研究存在的問題，致力于新的融合算法的設(shè)計(jì)，本文將(多尺度)數(shù)據(jù)融合理論與故障監(jiān)控相結(jié)合，提出一種基于(多尺度)數(shù)據(jù)融合理論的故障監(jiān)控策略。最后給出了具體應(yīng)用實(shí)例。
關(guān)鍵詞：數(shù)據(jù)融合；多尺度；故障監(jiān)控

Abstract: The traditional data fusion algorithms based on synchronous data can’t get the
holistic ’Best’ in the computation and estimation accuracy. And the existing asynchronous fusion algorithms have been mostly several questions, for instance time delay, the large computation and so forth. According to the existing questions of traditional algorithms, we take up with the design of the new fusion algorithm. Combing Multi-scale data fusion theory with process monitoring, we present a new process monitoring method based on(Multi-scale)data fusion, and finally present a application example.
Key words：Data Fusion; Multi-scale; Fault Monitoring