本文關(guān)鍵詞：基于粒子群優(yōu)化的改進(jìn)EMD算法在軸承故障特征提取中的應(yīng)用　出處：《振動(dòng)與沖擊》2017年16期 　論文類型：期刊論文

  更多相關(guān)文章： EMD 有理Hermite插值 PSO 軸承 故障特征提取

【摘要】：經(jīng)驗(yàn)?zāi)B(tài)分解(Empirical Mode Decomposition,EMD)作為一種數(shù)據(jù)驅(qū)動(dòng)的自適應(yīng)信號(hào)分解方法,在軸承故障特征提取中有著廣泛應(yīng)用。針對(duì)EMD自身存在的模態(tài)混疊、端點(diǎn)效應(yīng)以及三次樣條插值帶來的過沖/欠沖問題,同時(shí)考慮到有理Hermite插值方法具有一個(gè)形狀控制參數(shù),為選擇最優(yōu)的插值曲線提供了可能,基于此,提出了一種基于粒子群優(yōu)化(Particle Swarm Optimization,PSO)的改進(jìn)EMD算法,選定頻率帶寬作為IMF優(yōu)劣評(píng)判準(zhǔn)則,并以此作為PSO的評(píng)價(jià)函數(shù);在篩分過程中,從眾多不同形狀控制參數(shù)對(duì)應(yīng)的分解結(jié)果中尋找最優(yōu)IMF從而確定最優(yōu)形狀控制參數(shù);在每階分解結(jié)果中都能保證所得IMF是最優(yōu)的,從而達(dá)到更好的自適應(yīng)性及更高精度。為驗(yàn)證所提出方法的有效性,采用傳統(tǒng)EMD、EEMD與該算法對(duì)仿真信號(hào)進(jìn)行處理、對(duì)比,并通過計(jì)算相關(guān)技術(shù)指標(biāo)進(jìn)行了驗(yàn)證。最優(yōu)將其應(yīng)用于滾動(dòng)軸承故障特征提取,并與傳統(tǒng)EMD算法、EEMD進(jìn)行對(duì)比,包絡(luò)譜結(jié)果顯示,改進(jìn)后的EMD算法具有更好的分解效果,抑制干擾并能提取出更多故障信息。
[Abstract]:The empirical mode decomposition (Empirical Mode Decomposition, EMD) adaptive signal decomposition method as a data driven, there is extensive application in bearing fault feature extraction. For the existence of EMD modal aliasing, the end effect and three spline interpolation to bring the overshoot or undershoot problem, taking into account the rational Hermite interpolation the method has a shape parameter control, to select the optimal interpolation curve may be provided, based on this, puts forward a method based on particle swarm optimization (Particle Swarm Optimization, PSO) of the improved EMD algorithm, the selected frequency bandwidth of IMF as evaluation criteria, and as a PSO evaluation function; in the process of screening. To find the optimal IMF to determine the optimal shape control parameters from the decomposition results of many different shapes corresponding control parameters; in each step of decomposition results can ensure the IMF is optimal, so as To better adaptability and higher accuracy. In order to validate the proposed method, compared with traditional EMD, and the EEMD algorithm, the simulation signal, and verified by calculating the related technical index. The optimal applied in rolling bearing fault feature extraction, and compared with the traditional EMD algorithm, EEMD comparison of envelope spectrum results show that the improved EMD algorithm has better decomposition, inhibition of interference and can extract more fault information.

【作者單位】： 北京航空航天大學(xué)宇航學(xué)院;中國民航大學(xué)電子信息與自動(dòng)化學(xué)院;
【基金】：國家自然科學(xué)基金(10972019)
【分類號(hào)】：TH133.3
【正文快照】： 軸承作為旋轉(zhuǎn)機(jī)械中運(yùn)用最為廣泛且關(guān)鍵的部件,眾多故障皆來源于此[1],同時(shí),它的運(yùn)行狀態(tài)也直接影響了整臺(tái)設(shè)備的產(chǎn)能以及精度。在實(shí)際運(yùn)行環(huán)境下,軸承通常有以下幾種故障形式:外圈故障、內(nèi)圈故障、球故障以及幾種復(fù)合情形。而這些故障原因多由于滑油污染、過載[2]、脈沖寬度

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1 曹鵬舉;魏文斌;李曉峰;劉昕暉;;一種運(yùn)用EMD算法的裝載機(jī)動(dòng)態(tài)稱重系統(tǒng)[J];工程機(jī)械;2007年05期

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本文編號(hào)：1412334