【摘要】：近年我國(guó)風(fēng)電行業(yè)飛速發(fā)展,至2012年全國(guó)累計(jì)風(fēng)電裝機(jī)容量已達(dá)75.32GW,在全球風(fēng)電裝機(jī)容量中占據(jù)了第一的位置。但風(fēng)電機(jī)組故障頻繁發(fā)生,導(dǎo)致運(yùn)行維護(hù)費(fèi)用增加。而風(fēng)電機(jī)組齒輪箱又是風(fēng)電機(jī)組中故障率較高的部件,且維修、更換困難,因此,對(duì)于風(fēng)電機(jī)組齒輪箱故障診斷分析方法、故障特征值提取方面的研究具有較大的經(jīng)濟(jì)價(jià)值和現(xiàn)實(shí)意義。 小波分析方法是近年來(lái)一門迅速發(fā)展的技術(shù),廣泛應(yīng)用于信號(hào)分析、圖像處理和通信等工程領(lǐng)域,本文以風(fēng)電機(jī)組齒輪箱為研究對(duì)象,采用小波分析為工具對(duì)其故障特征值提取方面進(jìn)行了理論研究和實(shí)例分析。 本文首先對(duì)小波理論包括連續(xù)小波變換、離散小波變換和小波包進(jìn)行了總結(jié),并給出仿真分析案例；其次,對(duì)小波降噪的各種方法和小波包能量法進(jìn)行了研究,并通過(guò)實(shí)際信號(hào)的分析對(duì)該方法的有效性進(jìn)行了驗(yàn)證；第三,探討了一種較為新穎的小波分析方法,即復(fù)數(shù)小波多尺度包絡(luò)譜分析方法,該方法能多尺度分解信號(hào),利用不同的頻率覆蓋范圍提取和分離機(jī)械故障信號(hào)的包絡(luò)譜,克服了傳統(tǒng)包絡(luò)譜分析方法中必需預(yù)知故障頻帶的缺點(diǎn),將帶通濾波和包絡(luò)分析一步完成,提高了信號(hào)分析的魯棒性,并用風(fēng)電機(jī)組實(shí)測(cè)信號(hào)進(jìn)行了測(cè)試,證實(shí)了復(fù)數(shù)小波多尺度包絡(luò)譜分析方法的有效性；最后,針對(duì)第一代小波變換的局限性,探討了第二代小波的構(gòu)造方法,并通過(guò)Matlab軟件編寫程序構(gòu)造第二代小波,應(yīng)用于風(fēng)電機(jī)組實(shí)際信號(hào)的分析,證明了第二代小波在信號(hào)分析中的可行性。 小波分析作為近年快速發(fā)展的新興領(lǐng)域,理論深刻且應(yīng)用廣泛,在風(fēng)電機(jī)組齒輪箱的故障特征值提取中得到了較好的應(yīng)用,并且在其它機(jī)械故障診斷領(lǐng)域具有很好的應(yīng)用前景,是一項(xiàng)非常值得推廣的技術(shù)。
[Abstract]:In recent years, the wind power industry in China has developed rapidly, and the total installed wind power capacity has reached 75.32 GW in 2012, which occupies the first position in the global wind power installed capacity. However, wind turbine failures frequently occur, resulting in increased operating and maintenance costs. The gearbox of wind turbine is the part with high failure rate, and it is difficult to repair and replace. Therefore, the method of fault diagnosis and analysis for the gearbox of wind turbine, The study of fault eigenvalue extraction is of great economic value and practical significance. Wavelet analysis is a rapidly developing technology in recent years. It is widely used in signal analysis, image processing, communication and other engineering fields. Wavelet analysis is used to extract the fault eigenvalue. In this paper, the wavelet theory including continuous wavelet transform, discrete wavelet transform and wavelet packet is summarized, and a simulation case is given. Secondly, various methods of wavelet noise reduction and wavelet packet energy method are studied. The validity of the method is verified by the analysis of actual signals. Thirdly, a novel wavelet analysis method, complex wavelet multi-scale envelope spectrum analysis method, is discussed, which can decompose signals at multiple scales. By using different frequency coverage to extract and separate the envelope spectrum of mechanical fault signal, this paper overcomes the shortcoming of the traditional envelope spectrum analysis method which must predict the fault frequency band, and completes the band-pass filter and envelope analysis in one step. The robustness of signal analysis is improved, and the validity of complex wavelet multi-scale envelope spectrum analysis method is verified by testing the measured signal of wind turbine. Finally, aiming at the limitation of the first generation wavelet transform, The construction method of the second generation wavelet is discussed, and the second generation wavelet is constructed by the Matlab software, which is applied to the analysis of the actual signal of the wind turbine, and proves the feasibility of the second generation wavelet in the signal analysis. Wavelet analysis, as a new field of rapid development in recent years, has deep theory and wide application. It has been applied in the extraction of fault eigenvalue of wind turbine gearbox, and has a good application prospect in other fields of mechanical fault diagnosis. It is a technique worth popularizing.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM315

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