基于c．RIO的阶次跟踪分析在风力发电中的应用

针对风力发电机组齿轮箱变速过程中振动信号非平稳的特点，将阶次跟踪和信号包络提取技术相结合，提出了一种针对齿轮点蚀故障的诊断方法。首先利用Compact RIO对齿轮箱的振动信号进行了时域数据采集，然后对时域信号进行了包络提取，进而对时域包络信号进行等角域重采样得到等角域包络信号，最后对等角域包络信号进行了阶次跟踪分析；通过对比正常齿轮和点蚀故障齿轮的包络阶次谱，进而找到了点蚀故障齿轮的故障频率特征。模拟仿真结果表明，阶次跟踪分析可以解决传统傅里叶变换在处理非平稳信号时的“频谱模糊”现象。通过齿轮点蚀故障试验的分析，结果表明包络阶次谱能够用于有效地分析出点蚀故障齿轮的特征频率，阶次跟踪分析在风力发电机组齿轮箱的故障诊断中具有广阔的应用前景。

Application of order tracking analysis based on c-RIO in wind power

Aiming at the characteristic of the non-stationary vibration signal from gearboxes of wind power generators, an analysis method on fault diagnosis of gears with pitting corrosion was explored by the combination of order tracking analysis and envelope extraction. Firstly, vibration signal on gearboxes was acquired with Compact RIO（C-RIO）. Then the signal was processed by means of envelope extraction and the processed signal was converted to even-angle signal. Order tracking analysis for even-angle signal was achieved in the next step. According to the comparison with frequency characteristics of normal gears, that on gears with pitting corrosion can be found. The results indicate that fuzzy frequency can be solved by order tracking analysis in simulation, and fault frequency characteristics can be analyzed effectively in the experiment about gears with pitting corrosion. Therefore, order tracking analysis has a broad application prospect in the fault diagnosis of gearboxes of the wind power generators.