基于LCD和谱峭度的共振解调方法在齿轮箱故障诊断中的应用

发布时间：2018-05-17 04:05

  本文选题：齿轮箱故障诊断 + LCD　； 参考：《东北石油大学》2017年硕士论文

【摘要】：齿轮由于拥有稳定的传动比、大的传动扭矩和紧凑的结构等优点,在改变设备转速以及传递动力发面起着必不可少的作用,被广泛的应用于社会各领域的现代化机械设备中。虽然齿轮在机械设备的组成中无法代替,但故障发生率也非常的高,其运行状态会严重影响整机的工作性能。因此,对齿轮箱进行故障诊断具有重要意义。论文的主要内容如下:(1)介绍齿轮箱故障诊断的基本方法,研究了齿轮箱的故障类型、振动机理、信号特征。对局部特征尺度分解方法(Local characteristic-scale decomposition,简称LCD)及其他三种时频分解方法的均值曲线优劣、分解效果进行仿真分析。(2)建立齿轮箱故障实验方案,分别测取在不同转速下正常齿轮箱以及三种典型齿轮箱故障数据,包括断齿、裂纹及磨损故障数据。对实验数据进行时域、频域分析,发现单纯的时域、频域分析不能有效的识别齿轮箱故障特征。(3)齿轮箱振动信号具有调频调幅的特点,故障诊断的关键是对齿轮箱振动调制信号进行解调,从而提取出齿轮箱故障特征。此外,实际工况下的齿轮箱信号还包含了大量噪声信号。针对此情况,本文提出了基于LCD和谱峭度的共振解调方法,对齿轮箱进行故障诊断。该方法采用LCD将信号分解为一系列调幅调频的单分量信号,通过计算各分量和原信号的相关系数和相对熵选取合适的分量进行信号重构,再计算出重构信号的谱峭度,根据谱峭度最大原则选出用于提取故障性冲击成分的带通滤波器的最佳参数,最后对滤波后的信号进行共振解调分析。通过对齿轮箱仿真信号和实验信号的分析结果表明,该方法能有效的提取出齿轮箱故障特征。(4)实际工况下齿轮箱振动信号的调制边频带往往交叉在一起,形成非对称边带结构,一般的频域分析方法很难识别出来。针对此情况,将局部特征尺度分解方法和倒频谱方法相结合应用于齿轮箱故障诊断。首先利用LCD方法对信号进行分解,再采用倒频谱方法对单分量信号进行分析。通过对齿轮箱仿真信号和实验信号的分析结果表明,该方法能提取出齿轮箱故障特征,但是分析效果会受到故障程度的影响。
[Abstract]:Because of the advantages of stable transmission ratio, large transmission torque and compact structure, gear plays an essential role in changing the speed of equipment and transmitting power. It is widely used in modern machinery and equipment in various fields of society. Although the gear can not be replaced in the composition of mechanical equipment, but the rate of failure is also very high, its running state will seriously affect the performance of the whole machine. Therefore, the gearbox fault diagnosis is of great significance. The main contents of this paper are as follows: (1) the basic method of gearbox fault diagnosis is introduced, and the fault types, vibration mechanism and signal characteristics of gearbox are studied. The local characteristic scale decomposition method (LCD) and three other time-frequency decomposition methods are simulated and analyzed to establish the gearbox fault test scheme. The fault data of normal gearbox and three typical gearboxes were measured at different rotational speeds, including broken teeth, cracks and wear faults. By analyzing the experimental data in the time domain and the frequency domain, it is found that the simple time domain and frequency domain analysis can not effectively identify the gearbox fault characteristics. (3) the vibration signal of the gear box has the characteristics of frequency modulation and amplitude modulation. The key of fault diagnosis is to demodulate the vibration modulation signal of gearbox and extract the fault feature of gearbox. In addition, a large number of noise signals are also included in the gearbox signals under actual working conditions. In this paper, a method of resonance demodulation based on LCD and spectral kurtosis is proposed to diagnose the gearbox fault. In this method, the signal is decomposed into a series of single-component signals with amplitude modulation and frequency modulation by LCD. The spectral kurtosis of the reconstructed signal is calculated by calculating the correlation coefficient and relative entropy of each component and the original signal to select the appropriate components for signal reconstruction. According to the principle of maximum spectral kurtosis, the optimal parameters of the band-pass filter used to extract the fault impulse components are selected. Finally, the resonance demodulation analysis of the filtered signal is carried out. Through the analysis of the simulation signal and the experimental signal of the gearbox, the results show that the method can effectively extract the gearbox fault characteristics. 4) under the actual working conditions, the modulated frequency bands of the vibration signals of the gearbox are often crossed together to form an asymmetric sideband structure. General frequency domain analysis methods are difficult to identify. In this case, the local characteristic scale decomposition method and the cepstrum method are applied to the gearbox fault diagnosis. Firstly, the signal is decomposed by LCD method, and then the single component signal is analyzed by cepstrum method. Through the analysis of the simulation and experimental signals of the gearbox, it is shown that the method can extract the fault characteristics of the gearbox, but the effect of the analysis will be affected by the degree of the fault.
【学位授予单位】：东北石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH132.41
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本文编号：1899818