基于机电混合数据驱动的风力发电机故障诊断与预测方法研究

项目名称： 基于机电混合数据驱动的风力发电机故障诊断与预测方法研究

项目编号： No.51505424

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 金晓航

作者单位： 浙江工业大学

项目金额： 20万元

中文摘要： 随着风力发电机装机容量的迅猛发展，维护问题突出，迫切需要研发有效的风力机健康监测和故障诊断与预测系统。本项目提出综合利用振动和电流信号，通过EWT和VMD等时频分析方法，提取风力机故障特征，揭示振动与电流信号之间的耦合特性。针对风力机复杂的运行条件，提出同步采样分析，将非稳态信号转换成稳态信号，进而实现变工况下的风力机故障诊断。考虑到获取风力机各种状况下的完整数据成本昂贵，通过对现有的有限数据的学习和建模，提出基于半监督模式识别技术的故障诊断方法。拟合分析风力机性能退化数据，构建非线性状态空间模型，提出基于贝叶斯滤波算法的故障预测方法，实现在线性能评估和剩余寿命预测。项目将通过搭建风力机故障仿真试验平台和设计性能退化实验，获取实验数据，验证基于机电混合数据驱动的风力机故障诊断与预测方法的有效性。本项目研究工作源于学科前沿和工程实际需求，对风力机的故障诊断与预测技术提供理论指导具有重要意义。

中文关键词： 风力发电机；振动和电流；数据驱动；健康监测；故障诊断与预测

英文摘要： As the number of wind turbines continues to grow and the high cost of maintenance, the need for online health monitoring and fault diagnosis and prognosis system becomes increasingly important. This project proposes a vibration and current-based data driven approaches for wind turbine fault diagnosis and prognosis. New time-frequency analysis methods, such as empirical wavelet transform and variational mode decomposition, will be used to analyze the signals to extract the fault-related features. It also aims to reveal the correlations between vibration and current signals. Synchronously sampling technique, which resamples the non-stationary signal such that the varying characteristic features of the wind turbine become constant values, is proposed to be used to diagnose wind turbine faults under the dynamic operational conditions. Since there’ve limited healthy and faulty data, a semi-supervised pattern recognition based approach is then proposed for wind turbine fault diagnosis. Considering the degradation of wind turbine is a dynamic and nonlinear process, a nonlinear degradation model will be built, and Bayesian filter based approach will be developed for updating the model parameters and predicting the remaining useful life of wind turbine. Finally, experimental studies will be carried out to demonstrate the effectiveness of the proposed vibration and current-based data driven approaches for fault diagnosis and prognosis of wind turbines operating in variable-speed conditions. This project is from the frontier of engineering, meets the demand of practical engineering, and has the significance to provide theoretical guidance and technique support to fault diagnosis and prognosis of wind turbines.

英文关键词： Wind Turbine;vibration and current;data driven;health monitoring;fault diagnosis and prognosis