本文選題：精密工程測(cè)量 + 總體局部均值分解　； 參考：《武漢大學(xué)學(xué)報(bào)(信息科學(xué)版)》2017年10期

【摘要】：時(shí)頻分解方法局部均值分解(local mean decomposition,LMD)在沉降監(jiān)測(cè)中已經(jīng)得到了應(yīng)用,但在使用中會(huì)出現(xiàn)模態(tài)混疊現(xiàn)象�？傮w局部均值分解(ensemble local mean decomposition,ELMD)通過(guò)添加輔助噪聲可以抑制局部均值分解過(guò)程中出現(xiàn)的模態(tài)混疊現(xiàn)象。提出了一種基于ELMD的并聯(lián)式組合沉降預(yù)測(cè)方法,結(jié)合高速鐵路某橋梁實(shí)際監(jiān)測(cè)數(shù)據(jù),在對(duì)ELMD模型進(jìn)行仿真分析的基礎(chǔ)上,分別使用ELMD和LMD將一組離散非線性信號(hào)分解為3個(gè)PF分量和1個(gè)剩余分量,并利用支持向量機(jī)和卡爾曼濾波進(jìn)行預(yù)測(cè)驗(yàn)證。結(jié)果表明:使用ELMD進(jìn)行分解的過(guò)程中能夠很好地抑制LMD方法中出現(xiàn)的模態(tài)混疊問(wèn)題。在預(yù)報(bào)精度方面,基于ELMD的并聯(lián)式組合模型的平均相對(duì)誤差可以達(dá)到8.3%,可為沉降監(jiān)測(cè)的預(yù)報(bào)工作提供參考和借鑒。
[Abstract]:Local mean decompositionLMD (local mean decomposition method) has been applied in settlement monitoring, but modal aliasing will occur in use. Total local mean decomposition (LMS) can suppress modal aliasing in the process of local mean decomposition by adding auxiliary noise. A parallel combined settlement prediction method based on ELMD is proposed. Based on the actual monitoring data of a bridge in high-speed railway, the ELMD model is simulated and analyzed. A set of discrete nonlinear signals are decomposed into three PF components and one residual component using ELMD and LMD respectively. The prediction is verified by support vector machine and Kalman filter. The results show that the modal aliasing problem in LMD method can be well suppressed by using ELMD in the process of decomposition. In the aspect of prediction accuracy, the average relative error of parallel combined model based on ELMD can reach 8.3, which can provide reference and reference for the prediction of settlement monitoring.
【作者單位】： 四川省第三測(cè)繪工程院;西南交通大學(xué)地球科學(xué)與環(huán)境工程學(xué)院;四川隧唐科技股份有限公司;株洲中車(chē)時(shí)代電氣股份有限公司;
【基金】：國(guó)家自然科學(xué)基金(41374002) 四川省科技計(jì)劃項(xiàng)目(2015JQ0046) 長(zhǎng)江學(xué)者和創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃項(xiàng)目(IRT13092)~~
【分類(lèi)號(hào)】：TU433
，

本文編號(hào)：2013442