本文選題：風(fēng)力發(fā)電機(jī) + 齒輪箱��； 參考：《湖南大學(xué)》2011年碩士論文

【摘要】：當(dāng)前,環(huán)境污染和能源問題日益突出,風(fēng)力發(fā)電己成為世界各國更加重視和重點(diǎn)開發(fā)的能源之一。隨著大型風(fēng)力發(fā)電機(jī)組裝機(jī)容量的增加,其系統(tǒng)結(jié)構(gòu)也日趨復(fù)雜,當(dāng)機(jī)組發(fā)生故障時(shí),不僅會(huì)造成停電,而且會(huì)產(chǎn)生嚴(yán)重的安全事故,造成巨大的經(jīng)濟(jì)損失。 風(fēng)力發(fā)電機(jī)的電氣故障信號(hào)信噪比較大,采用常規(guī)的方法就能較好地識(shí)別故障。而其機(jī)械系統(tǒng)是一個(gè)復(fù)雜的時(shí)變非線性系統(tǒng),且受到風(fēng)場(chǎng)不穩(wěn)定氣流等因素的影響,其故障振動(dòng)信號(hào)是非平穩(wěn)的,使用常規(guī)方法難以有效提取故障特征。研究使用先進(jìn)的診斷技術(shù)對(duì)其進(jìn)行故障診斷,具有縮短維修時(shí)間、降低維修成本,避免發(fā)生嚴(yán)重事故的重要意義。 多尺度線調(diào)頻基稀疏信號(hào)分解是一種新的信號(hào)處理方法,經(jīng)驗(yàn)證在時(shí)頻分析方面效果優(yōu)越;廣義解調(diào)可以將時(shí)頻分布呈曲線變化的多分量非平穩(wěn)信號(hào)轉(zhuǎn)化為時(shí)頻分布平行于時(shí)間軸的平穩(wěn)信號(hào),因此非平穩(wěn)信號(hào)經(jīng)廣義解調(diào)后滿足傅里葉分析對(duì)平穩(wěn)性的要求;包絡(luò)階次譜方法采用等角度采樣,采樣信號(hào)具有角度域的平穩(wěn)性,因此也適用于變轉(zhuǎn)速工況下的風(fēng)力發(fā)電機(jī)旋轉(zhuǎn)部件故障振動(dòng)信號(hào)分析。本文在國家高技術(shù)研究發(fā)展計(jì)劃(863計(jì)劃)課題“大型風(fēng)力發(fā)電機(jī)組狀態(tài)監(jiān)控與故障診斷技術(shù)研究(項(xiàng)目批準(zhǔn)號(hào):2009AA04Z414)”和國家自然科學(xué)基金項(xiàng)目“多尺度線調(diào)頻基稀疏信號(hào)分解方法及其在機(jī)械故障診斷中的應(yīng)用(項(xiàng)目批準(zhǔn)號(hào):50875078)”資助下,圍繞多尺度線調(diào)頻基稀疏信號(hào)分解方法及其在風(fēng)力發(fā)電機(jī)齒輪箱故障診斷中的應(yīng)用進(jìn)行了理論研究和實(shí)驗(yàn)分析。 論文主要研究工作和創(chuàng)新性研究成果有: (1)根據(jù)風(fēng)力發(fā)電機(jī)的結(jié)構(gòu)以及風(fēng)場(chǎng)的環(huán)境特點(diǎn),研究了風(fēng)力發(fā)電機(jī)齒輪箱的故障產(chǎn)生機(jī)理�；陲L(fēng)力發(fā)電機(jī)組的變轉(zhuǎn)速運(yùn)行特點(diǎn),建立了風(fēng)力發(fā)電機(jī)故障模擬實(shí)驗(yàn)系統(tǒng),并通過數(shù)據(jù)分析表明,準(zhǔn)確的提取、識(shí)別振動(dòng)信號(hào)的調(diào)制特征是對(duì)風(fēng)力發(fā)電機(jī)的齒輪箱進(jìn)行故障診斷的關(guān)鍵。 (2)針對(duì)變轉(zhuǎn)速工況下風(fēng)力發(fā)電機(jī)齒輪箱振動(dòng)信號(hào)的瞬時(shí)頻率提取困難問題,將基于多尺度線調(diào)頻基的稀疏信號(hào)分解方法引入到風(fēng)力發(fā)電機(jī)齒輪箱振動(dòng)信號(hào)分析。介紹了基于多尺度線調(diào)頻基的稀疏信號(hào)分解原理,并通過仿真算例和實(shí)驗(yàn)信號(hào)分析證明了該方法在處理瞬時(shí)頻率連續(xù)變化的信號(hào)時(shí)具有較強(qiáng)的抗噪能力和時(shí)頻聚集性,非常適合于變轉(zhuǎn)速工況下風(fēng)力發(fā)電機(jī)齒輪箱振動(dòng)信號(hào)的分析處理。 (3)針對(duì)廣義解調(diào)時(shí)頻分析方法中對(duì)頻率呈曲線變化的多分量非平穩(wěn)信號(hào)相位函數(shù)提取困難的問題,將基于多尺度線調(diào)頻基稀疏信號(hào)分解方法引入廣義解調(diào),有效解決了相位函數(shù)提取問題。仿真算例和應(yīng)用實(shí)例表明,該方法能準(zhǔn)確提取相位函數(shù),將多分量非平穩(wěn)信號(hào)解調(diào)為平穩(wěn)信號(hào),適用于風(fēng)力發(fā)電機(jī)變轉(zhuǎn)速工況下的齒輪箱故障診斷。 (4)針對(duì)包絡(luò)階次分析中轉(zhuǎn)速提取困難和基于瞬時(shí)頻率的轉(zhuǎn)速估計(jì)方法精度不理想問題,采用基于多尺度線調(diào)頻基的稀疏信號(hào)分解方法來獲取轉(zhuǎn)速信號(hào),在此基礎(chǔ)上再對(duì)風(fēng)力發(fā)電機(jī)齒輪箱振動(dòng)信號(hào)進(jìn)行包絡(luò)階次分析。仿真算例和應(yīng)用實(shí)例表明,該方法能準(zhǔn)確提取瞬時(shí)轉(zhuǎn)頻,解決了傳統(tǒng)階次分析方法中轉(zhuǎn)速測(cè)量設(shè)備安裝困難問題,節(jié)約了診斷成本。 多尺度線調(diào)頻基稀疏信號(hào)分解算法在分解瞬時(shí)頻率呈曲線變化的多分量非平穩(wěn)信號(hào)方面效果明顯,本文將其引入非平穩(wěn)振動(dòng)信號(hào)的廣義解調(diào)分析、包絡(luò)階次分析能有效應(yīng)用于風(fēng)力發(fā)電機(jī)齒輪箱系統(tǒng)的故障診斷。
[Abstract]:At present, the problem of environmental pollution and energy is becoming more and more prominent. Wind power has become one of the more important energy sources in the world. With the increase of the capacity of the large wind turbine assembly machine, its system structure is becoming more and more complex. When the unit fails, it will not only make a power outage, but also cause serious safety accidents, causing huge accidents. Big economic losses.
The signal to noise of the electrical fault signal of the wind turbine is relatively large, and the fault is well recognized by the conventional method, and its mechanical system is a complex time-varying nonlinear system, which is influenced by the unstable air flow of the wind field and other factors. The fault vibration signal is nonstationary, and it is difficult to extract the fault features effectively by the conventional method. The use of advanced diagnostic technology for fault diagnosis has the important significance of shortening maintenance time, reducing maintenance cost and avoiding serious accidents.
Multiscale linear frequency modulation based sparse signal decomposition is a new signal processing method. It is proved to be superior in time-frequency analysis. The generalized demodulation can transform the time-frequency distribution multicomponent nonstationary signal into a stationary signal parallel to the time axis, which satisfies Fu Li after the nonstationary signal is demodulated by the generalized demodulation. The blade analysis is required for stability, and the envelope order spectrum method adopts equal angle sampling, and the sampling signal has the stability of the angle domain. Therefore, it is also suitable for the analysis of the fault vibration signal of the rotating parts of the wind generator under the variable speed condition. This paper is in the state high technology research and development plan (863 plan) "large wind turbine state". Research on monitoring and Fault Diagnosis Technology (project approval number: 2009AA04Z414) and National Natural Science Fund Project "multi scale linear frequency modulation based sparse signal decomposition method and its application in mechanical fault diagnosis (project approval number: 50875078)" supported by multi scale linear frequency modulation based sparse signal decomposition method and its wind power generation The application of machine gearbox fault diagnosis is studied theoretically and experimentally.
The main research work and innovative research results are as follows:
(1) according to the structure of the wind turbine and the environment characteristics of the wind field, the mechanism of the fault generation of the gear box of the wind generator is studied. Based on the variable speed running characteristics of the wind turbine, the fault simulation experiment system of the wind turbine is set up, and the accurate extraction and identification of the modulation characteristics of the vibration signal are shown by the data analysis. The key of fault diagnosis is the gearbox of wind turbine.
(2) in view of the difficulty in extracting the instantaneous frequency of the vibration signals of the gearbox in the wind generator, the sparse signal decomposition method based on the multi scale linear frequency modulation (FM) base is introduced to the analysis of the vibration signal of the gear box of the wind turbine. The analysis of signal analysis shows that the method has strong anti noise ability and time frequency aggregation when dealing with continuous change of instantaneous frequency. It is very suitable for the analysis and processing of the vibration signal of the gear box of wind generator in variable speed condition.
(3) aiming at the difficulty of extracting the phase function of the multicomponent nonstationary signal with varying frequency in the generalized demodulation time frequency analysis method, the multi scale linear frequency modulation based sparse signal decomposition method is introduced into the generalized demodulation, which effectively solves the problem of phase function extraction. The simulation calculation example and the application example show that the method can be extracted accurately. The phase function demodulates multi-component non-stationary signals into stationary signals, which is suitable for gearbox fault diagnosis of wind turbines under variable speed conditions.
(4) aiming at the difficulty of speed extraction and the accuracy of speed estimation based on instantaneous frequency in the envelope order analysis, the sparse signal decomposition method based on multi scale linear frequency modulation (FM) base is used to obtain the speed signal. On this basis, the envelope order analysis of the vibration signals of the gear box of the wind turbine is analyzed. The simulation example and Application The example shows that the method can accurately extract instantaneous frequency conversion, and solves the difficulty of installation of rotating speed measuring equipment in traditional order analysis method, and saves the cost of diagnosis.
The multiscale linear frequency modulation (FM) sparse signal decomposition algorithm is effective in decomposing the multi component nonstationary signal with a curve changing instantaneous frequency. This paper introduces it to the generalized demodulation analysis of the non-stationary vibration signal. The envelope order analysis can be used in the fault diagnosis of the gear box system of the wind turbine.

【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH165.3;TM315

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