| 引用本文: | 张露江,张利,杨要伟,等.基于改进贝叶斯网络的风机齿轮箱自动诊断策略研究[J].电力系统保护与控制,2019,47(19):145-151.[点击复制] |
| ZHANG Lujiang,ZHANG Li,YANG Yaowei,et al.Research on automatic diagnosis strategy of wind turbine gearbox based on improved Bayesian network[J].Power System Protection and Control,2019,47(19):145-151[点击复制] |
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| 摘要: |
| 为实现风机运行状态的监测功能，并完成监测数据智能诊断任务，开发了风机智能监测系统。首先，基于振动理论建立了齿轮箱动态模型，并分析了不同故障类型的数据特征，为智能诊断提供了辨识依据。然后，利用贝叶斯网络理论，分析了贝叶斯网络的全概率公式；并在此基础上进行研究，提出了简化广义逆矩阵的智能诊断实现方法。最后，搭建了以广义逆矩阵的智能诊断方法为核心的智能监测系统实现结构。系统在现场进行了运行检测，结果表明，智能监测系统输出结果和人工诊断结果相符。系统已在风场取得初步的工程应用。 |
| 关键词: 贝叶斯网络 振动理论 风力发电机 智能诊断 |
| DOI：10.19783/j.cnki.pspc.181282 |
| 投稿时间：2018-10-16修订日期：2019-01-03 |
| 基金项目:国家重点研发计划项目资助(2018YFB0904000)“智能电网技术与装备”专项“大容量风电机组电网友好型控制技术” |
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| Research on automatic diagnosis strategy of wind turbine gearbox based on improved Bayesian network |
| ZHANG Lujiang,ZHANG Li,YANG Yaowei,LU Xiaoguang |
| (State Grid Henan Electric Power Corporation Maintenance Company, Zhengzhou 450007, China;Zhengzhou Public Utility Investment Development Group Co., Ltd., Zhengzhou 450007, China;XJ-Wind Power Technology Company, Xuchang 461000, China) |
| Abstract: |
| In order to obtain the functions of monitoring wind turbine’s working state and the task of intelligent diagnosis of these state data, an intelligent monitoring system for wind turbines is developed. Firstly, based on the vibration theory, the dynamic model of gearbox is established, and the data characteristics in condition of various fault types are analyzed, which provides identification basis for intelligent diagnosis. Then, the full probability formula of Bayesian network is analyzed by using Bayesian network theory, and on this basis, the research is carried out and an intelligent diagnosis way is proposed which consists of simplifying generalized inverse matrix. Finally, the intelligent monitoring system based on generalized inverse matrix is constructed. The system is tested on the spot. The results show that the output of the intelligent monitoring system is consistent with the results of artificial diagnosis. The system has been preliminarily applied successfully in the wind field. This work is supported by National Key Research and Development Program of China Grid-friendly Control Technology for Large-Capacity Wind Turbines Project (No. 2018YFB0904000). |
| Key words: Bayesian network vibration theory wind turbine intelligent diagnosis |
