【摘要】：磁懸浮軸承作為新型支承部件，具有傳統(tǒng)軸承無法比擬的優(yōu)勢(shì)，現(xiàn)已應(yīng)用到諸多領(lǐng)域中。由于其剛度、阻尼參數(shù)具有在線可調(diào)性，磁懸浮軸承支承特性對(duì)系統(tǒng)的動(dòng)態(tài)特性具有更為重要的影響，因此，磁懸浮軸承支承參數(shù)的識(shí)別是磁懸浮技術(shù)研究的重要組成。而多數(shù)辨識(shí)方法是建立在頻域計(jì)算過程上的，因此，本文進(jìn)行了基于時(shí)域計(jì)算過程的擴(kuò)展卡爾曼濾波算法辨識(shí)支承參數(shù)的研究，分別針對(duì)不平衡激勵(lì)、沖擊激勵(lì)下的磁懸浮軸承-轉(zhuǎn)子系統(tǒng)進(jìn)行分析，識(shí)別出磁懸浮軸承剛度與阻尼參數(shù)。 通過分析利用擴(kuò)展卡爾曼濾波算法識(shí)別非線性系統(tǒng)的狀態(tài)參數(shù)的原理，結(jié)合本實(shí)驗(yàn)所使用的轉(zhuǎn)子系統(tǒng)結(jié)構(gòu)，將磁懸浮軸承剛度阻尼系數(shù)定為系統(tǒng)的狀態(tài)參數(shù)，確定利用擴(kuò)展卡爾曼濾波算法辨識(shí)磁懸浮軸承支承參數(shù)的過程，編制Matlab程序，分別在仿真與實(shí)驗(yàn)中，獲取轉(zhuǎn)子穩(wěn)態(tài)運(yùn)轉(zhuǎn)時(shí)不平衡質(zhì)量激勵(lì)下的轉(zhuǎn)子位移響應(yīng)，，實(shí)現(xiàn)對(duì)磁懸浮軸承支承參數(shù)的辨識(shí)。同時(shí)將辨識(shí)結(jié)果與邊界元辨識(shí)方法進(jìn)行對(duì)比分析。 將系統(tǒng)的激勵(lì)方式改為瞬態(tài)激勵(lì)，修改擴(kuò)展卡爾曼濾波算法中系統(tǒng)輸入項(xiàng)，分別運(yùn)用Samcef仿真及搭建的基于沖擊激勵(lì)的磁懸浮軸承轉(zhuǎn)子剛度阻尼測試與辨識(shí)試驗(yàn)平臺(tái)進(jìn)行實(shí)驗(yàn)，通過采集信號(hào)及數(shù)據(jù)處理獲得了系統(tǒng)在沖擊激勵(lì)下的軸承處位移響應(yīng)，并分別通過擴(kuò)展卡爾曼濾波和傳遞矩陣方法辨識(shí)了磁懸浮軸承的剛度阻尼。
[Abstract]:Magnetic levitation bearing (AMB), as a new supporting component, has many advantages compared with traditional bearing, and has been applied in many fields. Because its stiffness and damping parameters are on-line adjustable, the bearing characteristics of magnetic levitation bearing have more important influence on the dynamic characteristics of the system. Therefore, the identification of bearing parameters of magnetic levitation bearing is an important part of magnetic levitation technology research. Most of the identification methods are based on the frequency domain calculation process. Therefore, the extended Kalman filter algorithm based on the time domain calculation process is studied to identify the support parameters, respectively, aiming at the unbalanced excitation. The magnetic suspension bearing-rotor system under impact excitation is analyzed and the stiffness and damping parameters of the magnetic suspension bearing are identified. By analyzing the principle of identifying the state parameters of the nonlinear system by using the extended Kalman filter algorithm and combining with the rotor system structure used in this experiment, the stiffness and damping coefficient of the magnetic levitation bearing is determined as the state parameter of the system. The process of using extended Kalman filter algorithm to identify the bearing parameters of magnetic levitation bearing is determined, and the Matlab program is compiled to obtain the rotor displacement response under unbalanced mass excitation in steady-state operation in simulation and experiment, respectively. The identification of bearing parameters of magnetic levitation bearing is realized. At the same time, the identification results are compared with the boundary element identification method. The excitation mode of the system is changed to transient excitation, and the system input in the extended Kalman filter algorithm is modified. The test platform of stiffness and damping test and identification of magnetic suspension bearing rotor based on impact excitation is simulated by Samcef and the experiment platform is built to test the rotor stiffness and damping of maglev bearing. The displacement response of the system under impact excitation is obtained by collecting the signal and processing the data. The stiffness and damping of the magnetic bearing are identified by the extended Kalman filter and the transfer matrix method respectively.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TH133.3

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