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  本文選題：內(nèi)燃機 + 噪聲源識別��； 參考：《吉林大學》2014年碩士論文

【摘要】：NVH(Noise Vibration and Harshness)水平是衡量機動車輛性能的重要指標之一，NVH直接反應機動車輛舒適性品質(zhì)，而機動車輛舒適性程度直接影響該車輛的市場競爭力。車輛的噪聲和振動特性的研究和控制重點在于對內(nèi)燃機噪聲進行控制，而噪聲源識別對內(nèi)燃機噪聲控制起重要的作用。要想合理的控制內(nèi)燃機噪聲，應該對內(nèi)燃機的振動噪聲產(chǎn)生原因進行研究，，即對振動噪聲的產(chǎn)生部位進行定位，準確測量和分析振源的特性，如振源的類型、頻率特性、聲壓級大小、變化和傳播規(guī)律等。然后根據(jù)振動噪聲源的分析結果，采取相應的措施，降低內(nèi)燃機的輻射聲壓級。近三十年來，內(nèi)燃機科技工作者通過不懈的努力，使其在低噪聲結構優(yōu)化設計、低噪聲燃燒系統(tǒng)開發(fā)、內(nèi)燃機噪聲分離以及阻尼降噪技術等領域均有多項技術突破，有關資料顯示，與三十年前噪聲整體輻射水平相對比，其總體噪聲輻射水平下降了12dB。 即便如此，內(nèi)燃機噪聲輻射水平仍有下降的空間和必要性。由于內(nèi)燃機屬于復雜機械系統(tǒng)，當內(nèi)燃機系統(tǒng)運行時，其內(nèi)部多個零部件在同時運轉，這使待分析的目標部件響應即使可以直接測量也受到非目標零部件振動信號的影響，在頻譜中多個振源信號往往存在重疊，再加上實驗手段也十分復雜，實驗成本高，這使得傳統(tǒng)的內(nèi)燃機噪聲源識別技術具有一定的局限性。隨著新理論的提出以及新技術的應用，采用現(xiàn)代信號處理方法對內(nèi)燃機的噪聲和振動特性的研究有著重要的理論意義和工程實用價值。 針對上述相關問題，本文開展了相應的研究工作： 首先，闡述了課題研究背景，介紹柴油機振聲特性的危害性，以及當前柴油機振動信號處理過程中存在的技術問題。詳盡介紹了盲分離算法發(fā)展過程以及研究現(xiàn)狀，內(nèi)燃機振動信號現(xiàn)代處理方法，并指出應用時域盲識別算法對內(nèi)燃機噪聲源識別理論意義及工程價值； 其次，利用連續(xù)小波變換對內(nèi)燃機表面振動信號進行時-頻分析，通過對內(nèi)燃機各個部位表面加速度振動信號的特征的分解，對內(nèi)燃機在運轉過程中的主要噪聲源進行識別，為內(nèi)燃機的噪聲源的識別研究提供一些方法和途徑； 再次，建立了源信號線性瞬時混合模型和源信號線性卷積混合模型，介紹了有關信息論的基本概念，介紹了線性瞬時盲分離問題的常用解混算法，并詳細的介紹了FastICA算法的流程，通過數(shù)值算例驗證了FastICA算法的高效性和魯棒性。同時，介紹線性卷積盲分離問題的常用解混算法，詳盡介紹了MBLMS算法流程，并通過數(shù)值算例驗證MBLMS算法的高效性和魯棒性。 最后，應用FastICA算法以及改進的MBLMS算法對柴油機表面混合信號進行分離，通過分離結果比較驗證了改進的MBLMS算法的高效性和可靠性，也進一步對內(nèi)燃機非平穩(wěn)振聲響應結構模型進行了驗證。
[Abstract]:The level of NVH noise Vibration and Harshnessis is one of the important indexes to measure the performance of motor vehicles, which directly reflects the comfort quality of motor vehicles, and the degree of comfort of motor vehicles directly affects the market competitiveness of motor vehicles. The research and control of vehicle noise and vibration characteristics is focused on the control of internal combustion engine noise, and noise source identification plays an important role in internal combustion engine noise control. In order to control the internal combustion engine noise reasonably, it is necessary to study the cause of the vibration noise, that is, to locate the position of the vibration noise, to measure and analyze the characteristics of the vibration source, such as the type of the vibration source and the frequency characteristic. Sound pressure level, variation and propagation law, etc. Then according to the analysis results of vibration and noise source, the corresponding measures are taken to reduce the sound pressure level of internal combustion engine. In the past 30 years, the scientific and technological workers of internal combustion engine have made many technical breakthroughs in the fields of low noise structure optimization design, low noise combustion system development, internal combustion engine noise separation and damping noise reduction technology through unremitting efforts. The relative data show that compared with the total noise radiation level of 30 years ago, the overall noise radiation level has decreased by 12 dB. Even so, the internal combustion engine noise radiation level still has the space and the necessity. Since the internal combustion engine belongs to a complex mechanical system, when the internal parts of the internal combustion engine system are running at the same time, the response of the target component to be analyzed is affected by the vibration signal of the non-target component even if it can be measured directly. There is often overlap in the spectrum of multiple vibration source signals, in addition, the experimental means are also very complex and the experimental cost is high, which makes the traditional identification technology of internal combustion engine noise source has some limitations. With the development of new theory and the application of new technology, it is of great theoretical significance and practical value to study the noise and vibration characteristics of internal combustion engine by using modern signal processing method. In view of the above related problems, this paper has carried out the corresponding research work: first, elaborated the research background, introduced the diesel engine vibration sound characteristic harmfulness, And the technical problems existing in the process of diesel engine vibration signal processing. The development and research status of blind separation algorithm and the modern processing method of internal combustion engine vibration signal are introduced in detail, and the theoretical significance and engineering value of using time domain blind recognition algorithm to identify internal combustion engine noise source are pointed out. The time-frequency analysis of internal combustion engine surface vibration signal is carried out by using continuous wavelet transform, and the main noise sources of internal combustion engine during operation are identified by decomposing the characteristics of the acceleration vibration signal on each part of the internal combustion engine. It provides some methods and approaches for the identification of internal combustion engine noise sources. Thirdly, a linear instantaneous mixing model of source signals and a mixed model of linear convolution of source signals are established, and the basic concepts of information theory are introduced. In this paper, the common unmixing algorithms for linear instantaneous blind separation are introduced, and the flow chart of FastICA algorithm is introduced in detail. The efficiency and robustness of FastICA algorithm are verified by numerical examples. At the same time, the common de-mixing algorithms for linear convolution blind separation problem are introduced, and the flow chart of MBLMS algorithm is introduced in detail, and the efficiency and robustness of MBLMS algorithm are verified by numerical examples. Finally, the FastICA algorithm and the improved MBLMS algorithm are used to separate the diesel engine surface mixed signals. The efficiency and reliability of the improved MBLMS algorithm are verified by comparing the separation results. The structural model of non-stationary vibration response of internal combustion engine is also verified.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TB535

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本文編號：2025407