本文選題：故障診斷 + 軌邊聲學(xué)��； 參考：《中國(guó)科學(xué)技術(shù)大學(xué)》2017年博士論文

【摘要】：機(jī)械故障診斷技術(shù)的興起,給高速發(fā)展中的各新興制造業(yè)的安全保障提供了支持,減少和避免了重大事故的發(fā)生,表現(xiàn)出了巨大的經(jīng)濟(jì)和社會(huì)價(jià)值。高鐵作為我國(guó)新興裝備制造業(yè)的代名詞,其安全、舒適、高效一直受到國(guó)內(nèi)外的廣泛關(guān)注。因此,監(jiān)測(cè)和診斷列車運(yùn)行狀態(tài),預(yù)防列車事故的發(fā)生具有十分重大的意義。列車輪對(duì)軸承故障作為一種常見故障,與其相關(guān)的監(jiān)測(cè)與診斷研究一直為國(guó)內(nèi)外相關(guān)部門的熱點(diǎn)。其中,軌邊聲學(xué)診斷系統(tǒng)以非接觸式測(cè)量,可監(jiān)測(cè)早期故障的特點(diǎn)而廣受關(guān)注。然而,由于軌邊聲學(xué)診斷系統(tǒng)獲取信號(hào)的獨(dú)特方式,使其不可避免的存在一些測(cè)量問題。本文將以獲取軌邊聲學(xué)診斷系統(tǒng)中清晰可辨的故障聲譜為目標(biāo),以時(shí)變陣列分析為主要手段,針對(duì)系統(tǒng)測(cè)量所產(chǎn)生的聲譜微弱、聲譜畸變與聲譜混疊三個(gè)問題進(jìn)行探討和研究,以期獲取高速情況下可靠、準(zhǔn)確的列車軸承診斷結(jié)果。論文首先通過分析軌邊聲學(xué)診斷系統(tǒng)的幾何模型,公式化的揭示了該系統(tǒng)中聲譜微弱、畸變、混疊三個(gè)測(cè)量問題產(chǎn)生的原因。針對(duì)目前主要使用的列車軸承,建立了以軸承故障頻率為主要指標(biāo)的故障類型判別基礎(chǔ)。并以此分別設(shè)計(jì)了列車軸承靜態(tài)聲學(xué)獲取方案和麥克風(fēng)陣列的列車軸承動(dòng)態(tài)聲學(xué)獲取方案。通過對(duì)靜態(tài)和動(dòng)態(tài)實(shí)驗(yàn)信號(hào)的頻譜特征分析,驗(yàn)證了軌邊系統(tǒng)中畸變混疊問題的存在。針對(duì)單麥克風(fēng)分離矯正方法的局限性,以形態(tài)時(shí)頻濾波與時(shí)頻幅值匹配方法為例進(jìn)行了深層次的分析探討,指出了單麥克風(fēng)信號(hào)對(duì)空間聲源的欠定性描述是導(dǎo)致方法失效的本質(zhì)原因。其次,針對(duì)聲譜混疊問題,論文先后從遠(yuǎn)場(chǎng)條件下的陣列模型出發(fā),提出了一條基于麥克風(fēng)陣列的時(shí)變空域?yàn)V波重排的多源畸變混疊信號(hào)分離、矯正方案。該方法通過零角度空域?yàn)V波器獲取不同聲源的時(shí)間中心,并通過時(shí)變空域?yàn)V波重排最終實(shí)現(xiàn)不同畸變聲源的分離與矯正。由于時(shí)變空域?yàn)V波器的建立與信號(hào)能量幾乎無關(guān),因此該方法在微弱信號(hào)源分離與矯正方面相比于傳統(tǒng)單麥克風(fēng)方法具有明顯的優(yōu)勢(shì)。此外,實(shí)驗(yàn)表明所提方案對(duì)頻帶近似、時(shí)頻能量離散的多源信號(hào)分離表現(xiàn)也十分良好。隨后,針對(duì)聲譜畸變問題,論文又對(duì)基于陣列的聲譜畸變矯正方案進(jìn)行了進(jìn)一步的研究,并以單聲源為例提出了一種基于時(shí)變多信號(hào)分類和角插值重采樣的無參矯正方法。該方案通過時(shí)變多信號(hào)分類獲取聲源的實(shí)時(shí)位置,并通過聲源發(fā)射時(shí)間和接收時(shí)間的一一映射關(guān)系建立重采樣時(shí)間序列,實(shí)現(xiàn)對(duì)畸變信號(hào)的無參矯正。該方法相比于傳統(tǒng)方法具有無需先驗(yàn)知識(shí),計(jì)算量小,噪聲魯棒性強(qiáng),適用于變速聲源問題等諸多優(yōu)點(diǎn),在實(shí)際系統(tǒng)的應(yīng)用中具有較高的潛力。最后,針對(duì)聲譜特征微弱問題,論文以時(shí)變陣列分析思想為指導(dǎo),通過漢克矩陣構(gòu)建與陣列信號(hào)極其類似的偽陣列信號(hào),提出了一種基于時(shí)變奇異值分解的周期性暫態(tài)信號(hào)聲譜特征增強(qiáng)方法。重點(diǎn)研究了時(shí)變奇異值分解方法在處理周期暫態(tài)信號(hào)中所表現(xiàn)的基本性質(zhì),并以此及建立了一條基于時(shí)變奇異值分解的軸承故障頻譜特征增強(qiáng)與識(shí)別路線。研究表明,該路線不僅在各類噪聲,提高頻譜特征信噪比表現(xiàn)優(yōu)異,還在保留周期故障特征的諧波成分上具有較為顯著的優(yōu)勢(shì)。通過對(duì)列車軸承的故障聲學(xué)信號(hào)進(jìn)行分析,表明該方案在提升故障信號(hào)的聲譜特征方面作用明顯。全文以麥克風(fēng)陣列所采集的單、多聲源軌邊聲學(xué)軸承故障信號(hào)為處理對(duì)象,從軌邊聲學(xué)信號(hào)采集模型與軌邊信號(hào)的聲譜特征出發(fā),建立了一條完整的以時(shí)變陣列分析思路為主體的聲譜混疊分離、聲譜畸變矯正和聲譜特征增強(qiáng)的技術(shù)路線,為最終實(shí)現(xiàn)列車軸承軌邊聲學(xué)系統(tǒng)故障聲譜清晰識(shí)別提供了一定的研究基礎(chǔ)和解決思路。
[Abstract]:The rise of mechanical fault diagnosis technology has provided support to the safety guarantee of the emerging manufacturing industry in high speed development, reducing and avoiding the occurrence of major accidents, showing great economic and social value. As the pronoun of the new equipment manufacturing industry of our country, the high speed railway has been widely concerned at home and abroad. Therefore, it is of great significance to monitor and diagnose the running state of the train and prevent the occurrence of train accidents. The train wheelset bearing fault is a common fault, and its related monitoring and diagnosis research has always been a hot spot in the relevant departments at home and abroad. However, because of the unique way of obtaining signals from the acoustic diagnosis system on the rail side, it inevitably has some measurement problems. This paper aims at obtaining the clear and distinguishable sound spectrum in the track edge acoustic diagnosis system, with the time-varying array analysis as the main hand, and the sound spectrum produced by the system measurement is weak and sound. Three problems of spectral distortion and sound spectrum mixing are discussed and studied in order to obtain reliable and accurate diagnosis results of train bearing in high speed conditions. Firstly, the paper analyzes the geometric model of the track acoustic diagnosis system, and formulae the reasons for the weak, distortion and aliasing of three measurement problems in the system. In order to use the train bearing, a fault type criterion based on the bearing fault frequency is established, and the dynamic acoustic acquisition scheme of the static acoustics of the train bearing and the dynamic acoustic acquisition scheme of the train bearing of the microphone array are designed respectively. The analysis of the spectrum characteristics of the static and dynamic experimental signals is used to verify the track edge system. In view of the limitation of the single microphone separation and correction method, the deep analysis is carried out with the morphological time frequency filtering and the time frequency amplitude matching method. It is pointed out that the underqualitative description of the single microphone signal to the spatial sound source is the essential reason for the failure of the method. Secondly, the theory of the sound spectrum aliasing is discussed. In this paper, based on the array model under the far field condition, a multi source distorted aliasing signal separation and correction scheme based on the time-varying spatial domain filter rearrangement based on the microphone array is proposed. This method obtains the time center of different sound sources through the zero angle spatial domain filter, and finally realizes the different distortion sound sources through the time-varying spatial domain filter rearrangement. Separation and correction. Since the establishment of the time-varying space filter is almost independent of the signal energy, this method has obvious advantages compared with the traditional single microphone method in the separation and correction of weak signal source. In addition, the experiment shows that the proposed scheme is very good for the frequency band approximation and the time frequency energy discrete multisource signal separation. Then, in order to solve the problem of acoustic spectrum distortion, this paper further studies the array based correction scheme of acoustic spectrum distortion, and presents a non parametric correction method based on time-varying multi signal classification and angular interpolation resampling with single sound source as an example. The scheme obtains the real-time position of the sound source through the time-varying multi signal classification and sends through the sound source. The resampling time series is established by the one-to-one mapping relationship between the shooting time and the receiving time to realize the non parametric correction of the distorted signal. Compared with the traditional method, the method has many advantages, such as without prior knowledge, small calculation, strong noise robustness, suitable for the problem of variable speed sound source and so on, and has high potential in the application of the actual system. Finally, the needle Based on the time-varying array analysis idea, the paper constructs a pseudo array signal which is extremely similar to the array signal by the Hank matrix, and proposes a method for the characteristic enhancement of the periodic transient signal based on the time-varying singular value decomposition. The time variant singular value decomposition method is focused on the processing of the transient transient signal. Based on the basic properties of the signal, a frequency spectrum feature enhancement and recognition route based on time-varying singular value decomposition is established. The study shows that the route is not only excellent in all kinds of noise, but also in improving the spectrum characteristic signal to noise ratio. After analyzing the fault acoustic signal of the train bearing, it shows that the scheme plays an obvious role in improving the sound spectrum characteristics of the fault signal. The full text is based on the single, multi source track edge acoustic bearing fault signal collected by the microphone array, and sets out from the sound spectrum characteristics of the acoustic signal acquisition mode and the edge signal of the rail. The technical route of the sound spectrum aliasing separation, the correction of the sound spectrum distortion and the enhancement of the sound spectrum features by the time-varying array analysis idea provides a certain research basis and solution for the final realization of the clear recognition of the fault sonogram of the train bearing rail edge acoustic system.
【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：U279.323

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