本文選題：混沌系統(tǒng)　切入點：微弱信號檢測　出處：《西安建筑科技大學》2014年碩士論文　論文類型：學位論文

【摘要】：在工程應用中，回轉支承是大型低速重載設備的關鍵部件，極易受損，其原因是這類設備承受載荷大、轉速低，容易造成滾珠和滾道的點蝕和塑性變形等疲勞損傷。當回轉支承存在潛在微小故障時，長期運行可能導致事故發(fā)生，輕則影響機器正常工作，重則導致惡性事故發(fā)生造成巨大的經濟損失。由于回轉支承不便拆裝維修且工期長，其內部磨損或其它缺陷的檢測就顯得十分困難，而且存在不確定外界因素，易造成危險或較多的資源浪費，因此回轉支承的故障識別及診斷技術具有重大的研究與實際應用價值。為了提前發(fā)現(xiàn)早期的微弱故障信號，本課題主要研究了如何利用Duffing振子間歇混沌現(xiàn)象來檢測小型挖掘機回轉支承早期微弱故障信號頻率。 本課題所做的工作主要包括以下幾個方面： (1)研究幾種典型的混沌動力學模型（Duffing系統(tǒng)、Lorenz系統(tǒng)、Logistic系統(tǒng)和變形Rossler系統(tǒng)等）。研究阻尼、周期攝動力幅值、初始條件等參數(shù)對混沌系統(tǒng)的影響。 (2)研究混沌的判據。利用Poincare截面法、Lyapunov指數(shù)法從不同的角度判定變形Rossler系統(tǒng)的臨界狀態(tài)。 (3)變形Rossler系統(tǒng)對含有噪音的微弱信號進行幅值檢測，通過分析比較，擬選擇變形Rossler混沌系統(tǒng)應用于弱信號參量的檢測。此外介紹了未知任意頻率信號的檢測方法。 (4)由于傳統(tǒng)故障診斷方法對檢測回轉支承等工程機械出現(xiàn)早期微弱信號存在弊端。為了更好的檢測出故障特征信號，采用混沌系統(tǒng)利用其對微弱信號的敏感性以及對噪音的免疫力，，結合小波分析進行微弱信號的檢測，將此方法用于工程實際中可以有效的檢測微弱故障信號。
[Abstract]:In engineering application, slewing bearing is the key part of large low speed heavy load equipment, and it is easy to be damaged because of the heavy load and low speed of this kind of equipment. It is easy to cause fatigue damage such as pitting and plastic deformation of ball and raceway. When there is a potential minor fault in the slewing bearing, the long-term operation may lead to an accident, and the light will affect the normal operation of the machine. Heavy accidents lead to huge economic losses. Because of the inconvenience of disassembly and repair of slewing bearings and the long construction period, it is very difficult to detect internal wear or other defects, and there are uncertain external factors. It is easy to cause danger or waste more resources, so the fault identification and diagnosis technology of slewing bearing has great research and practical application value. In this paper, we mainly study how to use the intermittent chaos of Duffing oscillator to detect the frequency of weak fault signal in the early stage of rotary support of small excavator. The work of this topic mainly includes the following aspects:. 1) several typical chaotic dynamics models, such as Logistic system and Rossler system, are studied. The effects of damping, amplitude of periodic perturbation force and initial conditions on the chaotic system are studied. (2) the criterion of chaos is studied. The critical state of deformed Rossler system is determined from different angles by using Poincare section method and Lyapunov exponent method. The deformed Rossler system detects the amplitude of the weak signal with noise. Through analysis and comparison, the deformed Rossler chaotic system is chosen to be applied to the detection of weak signal parameters. In addition, the detection method of unknown arbitrary frequency signal is introduced. 4) because of the disadvantages of the traditional fault diagnosis method to detect the weak signal in the early stage of engineering machinery such as rotary support, in order to detect the fault characteristic signal better, The chaotic system is used to detect weak signals by using its sensitivity to weak signals and immunity to noise, and wavelet analysis is used to detect weak signals. This method can be used to detect weak fault signals effectively in engineering practice.
【學位授予單位】：西安建筑科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TU621;TN911.23

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本文編號：1588914