【摘要】：針對(duì)內(nèi)燃機(jī)故障診斷中振動(dòng)響應(yīng)信號(hào)強(qiáng)耦合、弱故障特征的問題,提出一種基于內(nèi)燃機(jī)振動(dòng)譜圖紋理特征提取的故障診斷方法。首先,為了清晰地刻畫內(nèi)燃機(jī)振動(dòng)信號(hào)時(shí)頻聯(lián)合分布中的非平穩(wěn)時(shí)變分量,將變分模態(tài)分解(VMD)與Rihaczek復(fù)能量密度分布方法有效結(jié)合,得到了時(shí)頻聚集性好、無交叉項(xiàng)干擾的內(nèi)燃機(jī)振動(dòng)譜圖像;針對(duì)VMD分解過程中的參數(shù)選取問題,提出將功率譜熵作為目標(biāo)函數(shù),對(duì)VMD的分解參數(shù)進(jìn)行網(wǎng)格尋優(yōu),提高了VMD分解的自適應(yīng)性。為了實(shí)現(xiàn)對(duì)內(nèi)燃機(jī)振動(dòng)譜圖像的自動(dòng)識(shí)別及故障診斷,提出了改進(jìn)的局部二值模式(ILBP)方法,用來對(duì)振動(dòng)譜圖中蘊(yùn)含的紋理信息進(jìn)行分析,提取低維特征參量并采用最近鄰分類器對(duì)內(nèi)燃機(jī)不同工況的振動(dòng)譜圖像進(jìn)行模式識(shí)別。將該方法應(yīng)用于內(nèi)燃機(jī)故障診斷實(shí)例中,結(jié)果表明該方法能有效提取內(nèi)燃機(jī)振動(dòng)信號(hào)中的微弱故障特征,實(shí)現(xiàn)內(nèi)燃機(jī)故障的自動(dòng)診斷。
[Abstract]:Aiming at the problem of strong coupling and weak fault characteristics of vibration response signals in internal combustion engine fault diagnosis, a fault diagnosis method based on texture feature extraction of internal combustion engine vibration spectrum is proposed. Firstly, in order to describe clearly the nonstationary time-varying components in the time-frequency joint distribution of internal combustion engine vibration signals, the variational mode decomposition (VMD) method and the Rihaczek complex energy density distribution method are effectively combined to obtain good time-frequency aggregation. In view of the problem of parameter selection in the process of VMD decomposition, the power spectrum entropy is used as the objective function to optimize the decomposition parameters of VMD in order to improve the self-adaptability of VMD decomposition. In order to realize the automatic identification and fault diagnosis of internal combustion engine vibration spectrum image, an improved local binary mode (ILBP) method is proposed to analyze the texture information contained in the vibration spectrum image. The low dimensional characteristic parameters are extracted and the nearest neighbor classifier is used to recognize the vibration spectrum images of internal combustion engines under different working conditions. The method is applied to the fault diagnosis of internal combustion engine. The results show that the method can effectively extract the weak fault characteristics from the vibration signal of internal combustion engine and realize the automatic fault diagnosis of internal combustion engine.
【作者單位】： 火箭軍工程大學(xué)理學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(51405498) 中國(guó)博士后基金(2015M582642)項(xiàng)目資助
【分類號(hào)】：TK407;TP391.41

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