【摘要】：風(fēng)力機(jī)葉片的故障已經(jīng)成為現(xiàn)有風(fēng)場中的隱患，本文旨在研究風(fēng)力機(jī)葉片承受隨機(jī)載荷和交變載荷共同作用時的裂紋萌生、生長和擴(kuò)展信號特征，分析不同的初始裂紋的辨識方法，了解裂紋動態(tài)生存狀態(tài)與葉片疲勞損傷程度之間的因果關(guān)系，識別風(fēng)力機(jī)葉片的損傷程度和類型，由此研制具有自主知識產(chǎn)權(quán)的大型風(fēng)力機(jī)葉片疲勞損傷辨識系統(tǒng)，從而解決難以實時監(jiān)測大型風(fēng)力機(jī)葉片的問題，在故障尚輕微時盡早地準(zhǔn)確識別其位置和程度，提前對葉片故障預(yù)警，保障風(fēng)力機(jī)高效安全地運行，大大降低風(fēng)力機(jī)后期維修成本。 本文建立了初始裂紋及裂紋生長擴(kuò)展的診斷模型，通過試驗設(shè)計，搭建試驗平臺采集不同裂紋類型、不同裂紋階段對應(yīng)的故障信號，為有效地監(jiān)測葉片狀態(tài)優(yōu)化聲發(fā)射傳感器安裝位置，同時確定葉片裂紋故障信號的采樣頻率、采樣長度、濾波頻率等信號采集和檢測的技術(shù)參數(shù)。分析風(fēng)力機(jī)葉片承受循環(huán)載荷作用下的裂紋變化特征，明確瞬時聲發(fā)射導(dǎo)波傳遞對裂紋生存狀態(tài)關(guān)聯(lián)機(jī)制，研究局部集中應(yīng)力導(dǎo)致裂紋生長的葉片疲勞損傷特征，確定裂紋的形變特點、增長率以及葉片疲勞損壞程度之間的因果關(guān)系，由此及時準(zhǔn)確地評估風(fēng)力機(jī)葉片疲勞狀態(tài)。 本文結(jié)合試驗?zāi)M的方法進(jìn)一步分析風(fēng)力機(jī)葉片裂紋萌生和擴(kuò)展機(jī)理，了解動態(tài)應(yīng)力對葉片疲勞破壞的影響，根據(jù)裂紋類型和狀態(tài)判定風(fēng)力機(jī)葉片的疲勞損傷程度，構(gòu)建一個以聲發(fā)射信號為監(jiān)測參量、基于自適應(yīng)小波分析提取微細(xì)裂紋故障特征的機(jī)制。首先結(jié)合Shannon熵方法實現(xiàn)小波基函數(shù)的自適應(yīng)選取，實現(xiàn)消除背景噪聲、分離有用信息，提取裂紋故障信號中的微細(xì)特征，在此算法基礎(chǔ)上將采集到的風(fēng)力機(jī)葉片裂紋聲發(fā)射信號進(jìn)行特征提取，再使用到小波尺度譜及重分配尺度譜中，通過對比得到不同類型裂紋的特征信號，，完成對初始裂紋的萌生擴(kuò)展?fàn)顟B(tài)的特征提取。風(fēng)力機(jī)的玻璃鋼葉片材料不存在明確的疲勞極限，當(dāng)葉片出現(xiàn)裂紋導(dǎo)致葉片固有頻率下降時，不同部位裂紋對固有頻率的影響不同，裂紋深度擴(kuò)展后振型將發(fā)生變化，而且產(chǎn)生裂紋的原因多樣，由此引發(fā)的裂紋生存狀態(tài)不同，因此提取葉片疲勞裂紋特征的分析機(jī)制是非常復(fù)雜的。從多分辨率角度入手來提取裂紋特征，分析采集數(shù)據(jù)中的敏感參數(shù)，挖掘葉片微細(xì)裂紋故障的特征參數(shù)，建立初始裂紋的診斷形式，展現(xiàn)葉片疲勞裂紋在不同頻率段的特征，成為解決此問題的關(guān)鍵。本文使用多分辨率的奇異值分解并重構(gòu)信號從而得到噪聲干擾更少的信號；再進(jìn)行重分配尺度譜的多分辨率計算使得在每一分辨率上的信號更加準(zhǔn)確且更具有實際操作性，同時結(jié)合能量表達(dá)方法，得到可以指導(dǎo)實踐的特征向量。 針對風(fēng)力機(jī)葉片疲勞短裂紋從萌生，生長及擴(kuò)展，到多裂紋以及長裂紋的出現(xiàn)直到葉片斷裂的這一裂紋群體性行為。使用實時的聲發(fā)射信號采集裂紋的特征就會出現(xiàn)時間跨度長，外界因素不好控制且損傷狀態(tài)不好界定的問題。故采用分形理論來分析經(jīng)過疲勞加速試驗得到的葉片縮尺模型的不同裂紋階段的裂紋幾何特征。極大的排除了外界因素的限制和干擾，從而展現(xiàn)了從裂紋萌生到葉片斷裂的全過程，并用分形維數(shù)這一參量表達(dá)了損傷變化程度。
[Abstract]:The fault of the wind turbine blade has become a hidden danger in the existing wind field. The purpose of this paper is to study the crack initiation, growth and extension signal characteristics of the wind turbine blade under the mutual action of the random load and the alternating load, and to analyze the identification methods of different initial cracks. To understand the causal relationship between the dynamic life state of the crack and the fatigue damage degree of the blade, the damage degree and the type of the wind turbine blade are identified, and the fatigue damage identification system of the large wind turbine blade with the independent intellectual property is developed. so as to solve the problem that the large-scale wind turbine blade is difficult to be monitored in real time, the position and the degree of the blade can be accurately identified as early as the fault is still slight, the early warning of the blade fault is advanced, the high-efficiency and safe operation of the wind turbine is guaranteed, and the later maintenance cost of the wind turbine is greatly reduced. In this paper, the diagnosis model of initial crack and crack growth expansion is established, and the test platform is designed to collect the fault signals corresponding to different crack types and different crack stages, so as to effectively monitor the blade state and optimize the installation of the acoustic emission sensor. the technology of signal acquisition and detection of the sampling frequency, the sampling length, the filtering frequency and the like of the blade crack fault signal at the same time In this paper, the characteristics of crack change under the action of the wind turbine blade under the action of cyclic loading are analyzed, and the related mechanism of the transient acoustic emission guided wave to the crack survival state is determined, and the fatigue damage characteristics of the blade caused by the local concentrated stress are studied, and the deformation of the crack is determined. The causal relationship between the characteristics, the growth rate and the degree of fatigue damage of the blade is assessed and the fatigue of the wind turbine blade is assessed in a timely and accurate manner. In this paper, the crack initiation and expansion mechanism of the wind turbine blade is further analyzed by the method of test simulation, and the effect of dynamic stress on the fatigue damage of the blade is studied. The fatigue damage degree of the wind turbine blade is determined according to the crack type and the state, and an acoustic emission signal is constructed. In order to monitor the parameters, the micro-crack fault is extracted based on the adaptive wavelet analysis The self-adaptive selection of the wavelet base function is first realized by combining the Shannon entropy method, the background noise is eliminated, the useful information is separated, the fine features in the crack fault signal are extracted, and the collected wind turbine blade crack sound emission signal is input on the basis of the algorithm. the characteristic signals of different types of cracks are obtained through comparison to obtain the characteristic signals of different types of cracks, and the initiation and expansion state of the initial crack is completed, The characteristic feature extraction is that the material of the glass fiber reinforced plastic blade of the wind turbine does not have a definite fatigue limit, and when the natural frequency of the blade is reduced due to the crack of the blade, the influence of the crack on the natural frequency of the different parts is different, the vibration mode of the crack is changed after the crack depth is expanded, and the crack is generated The causes of the fatigue crack of the extraction blade are different, and the analysis mechanism of the fatigue crack characteristics of the extraction blade is It is very complicated to extract the characteristics of the crack from the multi-resolution angle, to analyze the sensitive parameters in the data, to find the characteristic parameters of the fault of the micro-crack of the blade, to establish the diagnosis form of the initial crack, to show the characteristics of the fatigue crack of the blade in different frequency segments, and to solve the problem. The key of the problem is to use the singular value of the multi-resolution to decompose and reconstruct the signal so as to obtain the signal with less noise interference. The multi-resolution calculation of the rescaling scale spectrum makes the signal on each resolution more accurate and practical, and at the same time the binding energy The expression method can be used to guide the practice. A feature vector for the fatigue of a wind turbine blade from the initiation, the growth and the expansion, to the multi-crack and the occurrence of a long crack, until the blade is broken A crack group's sexual behavior. The characteristics of using the real-time acoustic emission signal to collect the crack will have a long time span, and the external factors are not well controlled and damaged. In this paper, the fractal theory is used to analyze the different crack steps of the blade scale model obtained by the fatigue acceleration test. The crack geometry of the segment is greatly eliminated. The limitation and interference of the external factors are greatly eliminated, and the whole process of the crack initiation to the failure of the blade is shown, and the parameter table of the fractal dimension number is used.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：TM315

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 陳雪峰;李繼猛;程航;李兵;何正嘉;;風(fēng)力發(fā)電機(jī)狀態(tài)監(jiān)測和故障診斷技術(shù)的研究與進(jìn)展[J];機(jī)械工程學(xué)報;2011年09期

本文編號：2355751