本文關(guān)鍵詞：葉片—轉(zhuǎn)子系統(tǒng)振動(dòng)特性與參數(shù)辨識(shí)方法研究　出處：《大連理工大學(xué)》2013年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 葉片-轉(zhuǎn)子-軸承系統(tǒng) 葉盤(pán)失諧 差分進(jìn)化算法 Kriging代理模型 參數(shù)辨識(shí)

【摘要】：高速旋轉(zhuǎn)機(jī)械作為一類被廣泛使用的機(jī)械設(shè)備,在許多行業(yè)(如航空航天、電力、冶金等)中都發(fā)揮著重要的作用,轉(zhuǎn)子系統(tǒng)作為高速旋轉(zhuǎn)機(jī)械的重要組成部分,其研究一直受到廣泛關(guān)注,近年來(lái)由于轉(zhuǎn)子系統(tǒng)的故障產(chǎn)生的惡性事故給企業(yè)造成過(guò)極大的損失,因此對(duì)轉(zhuǎn)子系統(tǒng)進(jìn)行準(zhǔn)確的建模以及故障和參數(shù)的辨識(shí),逐漸受到關(guān)注。 本文以轉(zhuǎn)子系統(tǒng)為主要研究對(duì)象,建立了葉片-轉(zhuǎn)子-軸承耦合系統(tǒng)的非線性動(dòng)力學(xué)模型,并將改進(jìn)的差分進(jìn)化算法應(yīng)用到失諧葉盤(pán)系統(tǒng)的優(yōu)化排序以及轉(zhuǎn)子系統(tǒng)的結(jié)構(gòu)參數(shù)和故障參數(shù)的辨識(shí)中。為了進(jìn)一步提高運(yùn)算效率,提出了多點(diǎn)加點(diǎn)Kriging代理模型和改進(jìn)的差分進(jìn)化算法相結(jié)合的參數(shù)辨識(shí)方法,高效準(zhǔn)確的實(shí)現(xiàn)了線性和非線性轉(zhuǎn)子系統(tǒng)的參數(shù)辨識(shí)工作。本文的主要工作有以下幾個(gè)方面： 1、建立了能夠全面考慮葉片彎曲振動(dòng)的葉片-轉(zhuǎn)子-軸承系統(tǒng)的非線性動(dòng)力學(xué)模型。首先,利用集中質(zhì)量法將轉(zhuǎn)子系統(tǒng)離散。其次,為分析葉片對(duì)轉(zhuǎn)子系統(tǒng)的慣性效應(yīng)并考慮系統(tǒng)的時(shí)變性,將葉片模化為懸臂梁結(jié)構(gòu),利用假設(shè)模態(tài)法對(duì)葉片進(jìn)行離散分析,同時(shí)根據(jù)葉片的循環(huán)對(duì)稱性對(duì)系統(tǒng)的微分方程進(jìn)行簡(jiǎn)化降階。對(duì)于葉片數(shù)量較多的葉片-轉(zhuǎn)子-軸承系統(tǒng)可以實(shí)現(xiàn)明顯的維數(shù)降低的效果。利用數(shù)值方法對(duì)系統(tǒng)動(dòng)力學(xué)方程進(jìn)行求解,并通過(guò)分岔圖、最大Lyapunov指數(shù)曲線、相圖、Poincar6截面映射、時(shí)域波形、幅值譜圖等分析了該系統(tǒng)在非線性油膜力作用下的彎扭耦合振動(dòng)特性。最后,討論了葉片的存在以及葉片長(zhǎng)度對(duì)系統(tǒng)非線性演化過(guò)程的影響。 2、建立了葉片-圓盤(pán)系統(tǒng)的集中參數(shù)化模型,分析了葉盤(pán)系統(tǒng)自由振動(dòng)和受迫振動(dòng)下的振動(dòng)特性,并討論了失諧葉盤(pán)系統(tǒng)各階模態(tài)的局部化程度以及失諧葉盤(pán)系統(tǒng)響應(yīng)影響的一般規(guī)律。結(jié)合所得規(guī)律,提出了一種評(píng)價(jià)失諧葉盤(pán)系統(tǒng)振動(dòng)優(yōu)劣的新的評(píng)價(jià)參數(shù)。最終將差分進(jìn)化算法應(yīng)用到失諧葉盤(pán)系統(tǒng)葉片排序的優(yōu)化研究中。在兼顧降低振幅和平衡葉片間振幅大小的情況下,使各葉片較均勻的分擔(dān)系統(tǒng)的整體振動(dòng)能量,以達(dá)到降低疲勞、延長(zhǎng)壽命的目的。 3、在基本差分進(jìn)化算法的基礎(chǔ)上提出了適用于轉(zhuǎn)子系統(tǒng)參數(shù)辨識(shí)的遺傳-自適應(yīng)混合差分進(jìn)化算法。由于轉(zhuǎn)子系統(tǒng)待辨識(shí)參數(shù)過(guò)大或者過(guò)小同時(shí)待辨識(shí)區(qū)間范圍較大,因此首先引入具有全局搜索能力的遺傳算法以縮小問(wèn)題的尋優(yōu)區(qū)間,其次為了防止問(wèn)題陷入局部最優(yōu),提出了自適應(yīng)Cauchy變異和自適應(yīng)Caussian變異策略,用以修正差分進(jìn)化算法原有的變異策略。并以考慮不平衡量的線性轉(zhuǎn)子模型和考慮油膜力和碰摩力共同作用下的非線性轉(zhuǎn)子模型為對(duì)象進(jìn)行仿真分析,驗(yàn)證了所提出方法在轉(zhuǎn)子系統(tǒng)參數(shù)辨識(shí)中的可行性和準(zhǔn)確性。最后與基本差分進(jìn)化算法和遺傳算法進(jìn)行比較,結(jié)果顯示本文提出的GA-AHDE優(yōu)化算法能夠快速有效的逼近全局最優(yōu)解。 4、在原有Kriging代理模型的基礎(chǔ)上,結(jié)合改進(jìn)的自適應(yīng)混合差分進(jìn)化算法設(shè)計(jì)了新的轉(zhuǎn)子系統(tǒng)參數(shù)辨識(shí)方法,在每次更新Kriging代理模型時(shí),增加當(dāng)前由差分進(jìn)化算法得到的最優(yōu)設(shè)計(jì)點(diǎn),以提高模型的全局預(yù)測(cè)精度。通過(guò)數(shù)值算例和實(shí)驗(yàn),驗(yàn)證了該方法在轉(zhuǎn)子系統(tǒng)參數(shù)辨識(shí)中的高效性和準(zhǔn)確性。在此基礎(chǔ)上又將新的多點(diǎn)加點(diǎn)準(zhǔn)則引入到Kriging代理模型中,即在每次更新模型時(shí)除了增加當(dāng)前最優(yōu)設(shè)計(jì)點(diǎn)外,還根據(jù)搜索進(jìn)程加入相關(guān)度較大或較小的點(diǎn),從而進(jìn)一步提高了Kriging代理模型的精度,更大程度的提高了搜索效率。最后通過(guò)完成線性算例和非線性算例的辨識(shí)工作,討論了多點(diǎn)加點(diǎn)的Kriging代理模型與改進(jìn)的差分進(jìn)化算法相結(jié)合的參數(shù)辨識(shí)方法在不同情況下的的辨識(shí)結(jié)果,并分析了該方法的適用條件。
[Abstract]:High speed rotating machinery as a mechanical equipment widely used, in many industries (such as aerospace, electric power, metallurgy etc.) have played an important role, as an important part of the high-speed rotor system of rotating machinery, its research has been widespread concern, accidents in recent years due to the fault of rotor system to produce the enterprise had caused a great loss, so the accurate identification and fault modeling and parameters of the rotor system, has attracted increasing attention.
In this paper, the rotor system is the main research object, established the nonlinear dynamic model of blade rotor bearing system, the identification and the improved differential evolution algorithm is adopted to optimize the mistuned bladed disk system sort and structure parameters of rotor system and fault parameters. In order to further improve the computational efficiency, and puts forward the method of parameter identification of multi point sampling Kriging model and the improved differential evolution algorithm combining, realize the efficient work of parameter identification of linear and nonlinear rotor system. The main works of this paper are as follows:
1, established can comprehensively consider the nonlinear dynamics model of blade blade bending vibration of the rotor bearing system. Firstly, using the lumped mass method to discrete the rotor. Secondly, for the analysis of the inertial effect of blades on the rotor system considering time-varying system, Ye Pianmo as the cantilever beam structure, by using assumed mode method the discrete analysis on the blades, and according to the differential equation of circular symmetry of leaves on the system are simplified and reduced order. For the number of leaf blade rotor bearing system can achieve obvious dimension reduction effect. Using numerical method for system dynamics equations, and the bifurcation diagram, the largest Lyapunov exponent curve, phase diagram section Poincar6, mapping, time domain waveform, amplitude spectrum analysis of coupled bending and torsional vibration characteristics in the nonlinear oil film force of the system. Finally, discuss the blade The influence of the existence of the blade and the length of the blade on the nonlinear evolution of the system.
2, a concentrated parametric model of blade - disc system, analysis of the free vibration of bladed disk system and forced vibration vibration, and discusses the localization of mistuned bladed disk system modal and response of mistuned bladed disk system of general rules. Combined with the law, put forward a evaluation of mistuned bladed disk system vibration the merits of the new evaluation parameters. Finally the differential evolution algorithm is adopted to optimize system of vanes of mistuned bladed disk. The decrease amplitude and amplitude balance between the blades under the overall vibration energy makes the blade sharing system more uniform, in order to achieve reduce fatigue, prolong life.
3, based on the basic differential evolution algorithm for genetic parameter identification of rotor system - adaptive hybrid differential evolution algorithm is proposed. The rotor system parameters is too large or too small to be identified at the same time range is larger, so the genetic algorithm has the global search ability is first introduced to reduce the problem of optimization the second interval, in order to prevent problems fall into local optimum, we propose adaptive Cauchy mutation and adaptive Caussian mutation strategy is used to revise the differential mutation strategy evolutionary algorithm. The original nonlinear rotor model and to consider the balance of linear model and considering the amount of rotor oil film force and the interaction of rub impact force as the object for simulation analysis and verify the feasibility and accuracy of the proposed method in parameter identification of rotor system. And finally the basic differential evolution algorithm and genetic algorithm are compared, the results show The GA-AHDE optimization algorithm presented in this paper can quickly and effectively approach the global optimal solution.
4, based on the original Kriging model, combined with the improved adaptive hybrid differential evolution algorithm design method for parameter identification of rotor system, each update Kriging agent model, the optimal design point of the differential evolution algorithm is obtained, in order to improve the prediction accuracy of the global model. Through the numerical example and experimental validation of the method in parameter identification of rotor system in high efficiency and accuracy. On the basis of the multi-point sampling criterion is introduced into the new Kriging model, namely each update model in addition to the optimal design point, according to the search process added to a greater or lesser degree. Thus, the Kriging model accuracy is further improved, to a greater extent to improve the search efficiency. Finally, complete the identification work is linear and nonlinear case examples, discussed the multi point plus point K The identification results of different parameter identification methods based on riging surrogate model and improved differential evolution algorithm are applied in different cases, and the applicable conditions of the method are analyzed.

【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：TH113.1

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相關(guān)期刊論文 前10條

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本文編號(hào)：1355882