直驱式风电机组轴承振动监测与故障诊断

发布时间：2018-05-02 02:24

本文选题：直驱式风电机组 + 主轴轴承　；参考：《太原理工大学》2014年硕士论文

【摘要】：由化石燃料消耗引起的重度雾霾天气,给全国人民的生活带来了严重的灾难。在此情况下,风能作为新的可再生能源受到各国政府前所未有的重视。而目前大型风力发电机组制造技术已经趋向成熟,特别是直驱式风电机组作为近年来风电机组发展的最新趋势,得到了广泛的应用。然而风电机组受到运行环境的制约,导致其故障率较高,影响其可靠性。风电机组中的轴承作为风电机组传动系统的关键部件,其故障有各自的特点。主轴轴承由于其长时间受力不均匀而形成疲劳破坏；偏航和变桨轴承直接暴露在空气环境中,容易受到恶劣环境气流的影响,通常会在机舱和叶片上形成巨大的倾覆力矩,导致偏航和变桨轴承内外圈和滚动体上承受巨大的接触应力,造成轴承内部变形,以及风沙、尘土、潮湿等恶劣环境容易造成轴承磨损和锈蚀等故障。因此,对于风电机组轴承的故障特点进行监测诊断,对于了解轴承故障产生的机理,对轴承进行维护保养,预防轴承的故障产生,减少引轴承故障引起的经济损失等都具有重要的实际意义。本文从以下几方面对风电机组轴承进行深入的研究： (1)通过风电机组的运行状况和受力情况,分析了风电机组轴承的结构特征、工作状况、故障类型及故障产生的原因。针对轴承故障的振动机理、频率特性和信号特征等,由此为基础搭建了风电轴承故障的振动测试系统。 (2)针对风电机组轴承的故障特征进行诊断,其结论是：倒频谱方法对于风电轴承故障的主要特征频率产生的调制边频成分具有明显的识别作用。广义倒频谱对风电轴承在强噪声干扰情况下的故障特征能够进行有效的诊断。包络谱方法通过解调分析来提取轴承故障的调制信息,对风电轴承故障的特征频率、谐波频率和调制边频成分具有一定的辨识作用。 (3)通过对风电机组主轴和偏航轴承的正常及故障两种情况进行对比分析,验证了上述分析方法的有效性。针对正常和故障轴承的运行特性、振动特点、信号特征、故障部位等情况进行对比,得出了如下结论：倒频谱方法和包络谱方法在主轴和偏航轴承故障诊断中都具有一定的局限性,在主轴轴承故障诊断中倒频谱方法比包络谱方法显示结果更加清晰和准确；在偏航轴承故障诊断中包络谱方法比倒频谱方法的功能更加强大。
[Abstract]:The severe fog weather caused by fossil fuel consumption brings a serious disaster to the life of the people in the whole country . In this case , wind energy has been paid more and more attention by governments as a new renewable energy source . At present , the manufacturing technology of large wind generating set has become mature , especially direct drive wind turbine set as the latest trend of the development of wind power unit in recent years , and has been widely used . However , wind turbine unit is restricted by operating environment , which causes its failure rate to be high and its reliability is affected .

As the key parts of the transmission system of wind turbine , the bearings in the wind turbine unit have their own characteristics .
The yawing and pitch bearing are directly exposed in the air environment and can be easily influenced by the adverse environmental air flow . Generally , huge overturning moment is formed on the nacelle and the blade , which causes great contact stress on the inner and outer races and rolling bodies of the yaw and pitch bearing , which causes the bearing to wear and rust . Therefore , the bearing is maintained and maintained , the failure of the bearing is prevented , and the economic loss caused by the bearing failure is reduced .

In this paper , we study the bearing of wind turbine unit in the following aspects :

( 1 ) The structural characteristics , working conditions , fault types and the cause of failure of the bearing of wind turbine are analyzed through the operating conditions and stress conditions of the wind turbine unit . The vibration mechanism , frequency characteristic and signal characteristics of the bearing fault are analyzed , and the vibration test system for the fault of the wind power bearing is built on the basis of the analysis .

( 2 ) The fault characteristic of wind turbine bearing is diagnosed . The conclusion is that the cepstrum method has obvious recognition effect on the main characteristic frequency of wind power bearing fault . The generalized cepstrum method can diagnose the fault characteristic of wind power bearing under the condition of strong noise interference . The envelope spectrum method extracts the modulation information of bearing fault by demodulation analysis , and has certain identification effect on the characteristic frequency , harmonic frequency and modulation edge frequency component of the wind power bearing fault .

( 3 ) By comparing and analyzing the normal and fault conditions of the main shaft and the yaw bearing of the wind turbine unit , the effectiveness of the analysis method is verified . According to the operating characteristics , the vibration characteristics , the signal characteristics and the fault location of the normal and fault bearings , the following conclusions are obtained : the cepstrum method and the envelope spectrum method have certain limitations in the fault diagnosis of the main shaft and the yaw bearing , and the cepstrum method in the fault diagnosis of the main shaft bearing is clearer and more accurate than the envelope spectrum method .
The envelope spectrum method is more powerful than cepstrum method in the fault diagnosis of yaw bearing .

【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM315

【参考文献】