【摘要】：針對(duì)當(dāng)前制造業(yè)生產(chǎn)線設(shè)備的故障檢測(cè)效率以及檢測(cè)方法通用性不高的問(wèn)題,提出了一種云端融合的動(dòng)態(tài)嵌套滑動(dòng)窗口故障信號(hào)在線檢測(cè)算法。該算法采用云服務(wù)與智能終端在線檢測(cè)相結(jié)合的架構(gòu),利用云服務(wù)大存儲(chǔ)量和高計(jì)算速度、精度的優(yōu)勢(shì),解決了終端設(shè)備對(duì)故障信號(hào)處理能力不足以及僅能對(duì)線上數(shù)據(jù)進(jìn)行單次掃描的問(wèn)題。云計(jì)算中心根據(jù)數(shù)據(jù)流的波動(dòng)情況初步確定滑動(dòng)窗口大小,再根據(jù)對(duì)異常信號(hào)的判斷,向智能終端反饋故障信號(hào)的大小和相對(duì)位置,通過(guò)動(dòng)態(tài)嵌套滑動(dòng)窗口對(duì)其進(jìn)行定位。理論分析和實(shí)驗(yàn)結(jié)果表明,該方法對(duì)周期信號(hào)有較好的通用性,而且有效提高了故障檢測(cè)的效率。
[Abstract]:In order to solve the problem that the fault detection efficiency of manufacturing line equipment is not high and the detection method is not universal, a dynamic nested sliding window fault signal on-line detection algorithm based on cloud fusion is proposed. The algorithm adopts the framework of cloud service and intelligent terminal on-line detection, and makes use of the advantages of large storage capacity, high computing speed and precision of cloud service. It solves the problem that the terminal equipment has insufficient ability to deal with the fault signal and can only scan the data on the line at a single time. Cloud computing center preliminarily determines the size of sliding window according to the fluctuation of data flow, then according to the judgement of abnormal signal, feedback the size and relative position of fault signal to intelligent terminal, and locate it by dynamically nested sliding window. The theoretical analysis and experimental results show that the proposed method has good generality for periodic signals and effectively improves the efficiency of fault detection.
【作者單位】： 貴州大學(xué)現(xiàn)代制造技術(shù)教育部重點(diǎn)實(shí)驗(yàn)室;貴州大學(xué)機(jī)械工程學(xué)院;貴州省公共大數(shù)據(jù)重點(diǎn)實(shí)驗(yàn)室;
【基金】：貴州省重大科技專項(xiàng)資助項(xiàng)目(黔科合重大專項(xiàng)字[2013]6019,黔科合重大專項(xiàng)字[2012]6018) 貴州大學(xué)研究生創(chuàng)新基金資助項(xiàng)目(研理工2017039);貴州大學(xué)面向智能裝備領(lǐng)域的“技術(shù)眾籌”研究生創(chuàng)新基地資助項(xiàng)目(JSZC[2016]004)
【分類號(hào)】：TP274;TP393.09

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