【摘要】：隨著風電的廣泛應用，其安全性越來越受到重視。為了保證風力發(fā)電機組安全、可靠的運行，對其故障信息的研究具有重要的現(xiàn)實意義。風力發(fā)電機組在運行過程中，其振動信號往往包含大量的故障信息，通常表現(xiàn)為多分量的非平穩(wěn)信號的形式。目前常見的分析方法，例如傅里葉變換、短時傅里葉變換、Winger分布、小波變換等具有一定的局限性。針對以上問題，本文采用了局域均值分解(Local mean decomposition, LMD)和階比分析(Order Analysis)相結(jié)合的方法對風力發(fā)電機組的振動信號進行分析。主要研究內(nèi)容安排如下： 研究LMD的算法，針對滑動步長的選取對LMD的分解的影響，提出了一種自適應選取滑動步長的分解方法；并結(jié)合風力發(fā)電機在運行過程中會摻入噪聲這一問題，對振動信號進行降噪處理。利用改進后的LMD方法對風機的振動信號進行分解。所得到的單分量信號就包含風力發(fā)電機組振動信號的特征量。 根據(jù)直接法、能量算子解調(diào)方法和Hilbert變換法方法的特點，確定提取瞬時頻率這一特征量采用直接法，并驗證了直接法是提取風力發(fā)電機組的旋轉(zhuǎn)機械瞬時頻率的有效方法。 通過仿真驗證基于瞬時頻率估計的階比分析方法是振動分析的有效方法。并利用LMD算法和直接法獲取的瞬時頻率，根據(jù)瞬時頻率確定恒增量角度采樣時刻和恒角度增量采樣值，，最后進行階比分析。 利用軸承的振動數(shù)據(jù)驗證基于LMD瞬時頻率估計的階比分析方法是振動信號分析的有效方法。
[Abstract]:With the wide application of wind power, more and more attention has been paid to its safety. In order to ensure the safe and reliable operation of wind turbine, it is of great practical significance to study the fault information of wind turbine. During the operation of wind turbine, the vibration signal of wind turbine often contains a lot of fault information, usually in the form of multi-component non-stationary signal. Some common analytical methods, such as Fourier transform, short time Fourier transform, Winger distribution, wavelet transform and so on, have some limitations. To solve the above problems, the method of local mean decomposition (Local mean decomposition, LMD) and order ratio analysis (Order Analysis) is used to analyze the vibration signal of wind turbine. The main research contents are as follows: the algorithm of LMD is studied, and an adaptive decomposition method of sliding step size is proposed for the influence of the selection of sliding step size on the decomposition of LMD. Combined with the problem that wind turbine will be mixed with noise during operation, the noise reduction of vibration signal is carried out. The improved LMD method is used to decompose the vibration signal of the fan. The obtained single component signal contains the characteristic quantity of the wind turbine vibration signal. According to the characteristics of direct method, energy operator demodulation method and Hilbert transform method, the direct method is adopted to extract the instantaneous frequency, and the direct method is proved to be an effective method for extracting the instantaneous frequency of rotating machinery of wind turbine. Simulation results show that the order analysis method based on instantaneous frequency estimation is an effective method for vibration analysis. The instantaneous frequency obtained by LMD algorithm and direct method is used to determine the sampling time of constant increment angle and the sampling value of constant angle increment according to the instantaneous frequency. Finally, the order analysis is carried out. The order analysis method based on LMD instantaneous frequency estimation is proved to be an effective method for vibration signal analysis by using bearing vibration data.
【學位授予單位】：哈爾濱理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM315

【引證文獻】

相關碩士學位論文 前1條

1 王亞超;基于局部均值分解的旋轉(zhuǎn)機械故障診斷技術研究[D];燕山大學;2015年

本文編號：2367792