项目名称: 大型风电装备故障机理分析与诊断
项目编号: No.51335006
项目类型: 重点项目
立项/批准年度: 2014
项目学科: 机械、仪表工业
项目作者: 褚福磊
作者单位: 清华大学
项目金额: 320万元
中文摘要: 本项目针对大型风电装备故障率居高不下的现状,研究其故障机理及诊断的理论与方法。在动力学方面,研究大型风电装备在多源动载复合作用下的动力学特性,揭示柔性支承下大型风电装备的力流传递规律;研究含不确定参数的风电装备动力系统的稳定性,揭示不确定性参数与系统动态性能变化区间的映射规律。在失效机理和故障诊断方面,研究复杂外载作用下高副接触界面微观应力与界面能的分布及传递规律,探索界面能诱导的微点蚀产生机理;建立非连续非平稳运行条件下大型风电装备状态评估理论,提出早期损伤的定量识别和智能预示方法。本项目将在柔性支承下的风电装备分层次建模方法、不确定参数条件下的稳定机制、界面能诱导的关键接触界面失效机制和风电装备运行状态压缩感知与智能预测等方面取得重要突破。研究成果对于提高大型风电装备运行稳定性、保障其高可靠长寿命服役具有重要意义。
中文关键词: 大型风电装备;传动系统;动力学;故障诊断;
英文摘要: Due to the high failure rate of large scale wind turbines, the research project will mainly focus on the fault mechanism and theory and methods of diagnosis. In the dynamic analysis, the vibrational characteristics of large-scale wind turbines under multi-source dynamic loading are studied, and the force-energy flow law is investigated considering the influence of flexible supports. The dynamic stabilities of the wind turbine with uncertain parameters are analyzed utilizing the interval theory. The relations between the uncertain parameters and dynamic behaviors of the system are then pointed out. In the analysis of fault mechanism and diagnosis, the microscopic stress of the high contact interface and interfacial energy are studied for the distributions and transformations under complex external loading conditions. Based upon these, some typical micro faults, such as the micro-pitting in high-loaded gear teeth, are mainly discussed taking into account of the effect of interfacial energy. The condition monitoring and estimations for large-scale wind turbines under the non-continuous, non-stationary operating conditions are studied, and the methods of quantitative recognition and intelligent herald for early damages are presented. Four (even more) aspects of breakthrough will be achieve by this research project, including: the Hierarchical dynamic modeling of wind turbines under flexible supports, stability mechanism of the system with uncertain parameters, failure mechanism of key contact interface induced by interfacial energy, compressive sensing and intelligent prediction for the operating conditions. Research results are of great significance for improving the operational stability and protecting the high reliability and long life of service of large-scale wind turbines.
英文关键词: large-scale wind trubines;transmission system;dynamics;fault diagnosis