基于能量解耦的风力发电旋转机械故障趋势预示方法研究

项目名称： 基于能量解耦的风力发电旋转机械故障趋势预示方法研究

项目编号： No.51275052

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 机械、仪表工业

项目作者： 徐小力

作者单位： 北京信息科技大学

项目金额： 80万元

中文摘要： 在复杂变工况的风力发电旋转机械故障趋势信息中，不仅包含故障发展趋势信息，也包含载荷变化、噪声等非故障信息，这些信息具有能量耦合特征，传统的基于能量变化的趋势预示方法不一定反映故障趋势，同时基于单一故障征兆的预示方法难以全面、准确预示故障发展趋势，为此研究基于能量解耦的故障趋势预示新方法。提出趋势预示能量解耦的三维轴心轨迹流形图特征提取方法，构建三维轴心轨迹，通过非线性流形映射获取二维流形图像，提取用于描述流形图像形状的图形特征量，实现旋转机械的图形形式故障信息获取；提出趋势预示能量解耦的非线性独立成分分析方法，通过非线性盲信号分离，提纯能量形式故障信息，有效抑制风况信息、噪声信息等干扰；提出对多类预示信息加权融合方法，综合反映各类信息在空间与时间上对预示结果的影响程度，提高故障趋势预示信息的准确性和有效性。本研究能够为变工况风力发电机械故障预报提供新方法，有利于提高安全运行及科学维护水平。

中文关键词： 旋转机械；故障趋势；预示方法；能量解耦；

英文摘要： The fault trend information of wind-power rotating machinery under complicated varying working conditions not only includes fault trend information but also includes non-fault information such as varying loads, noise and so on. The information has the feature of energy decoupling. So the traditional prediction methods based on energy varying information can not reflect fault trend accurately,meanwhile,prediction methods utilizing single fault symptom information can not forecast fault development trend. To solve these problems, new prediction methods of fault trend based on energy decoupling were studied. In the research, a manifold feature extracting method of three-dimensional axis orbit for trend predicting and energy decoupling was presented, which constructed three-dimensional axis orbit, and mapped it into two-dimensional graphic by using nonlinear manifold analysis method. The graphic characteristic parameters extracting from graphic were used to represent fault information about rotating machinery; An independent component analysis method for trend predicting and energy decoupling was presented, which could extract fault information from energy monitoring information of wind-power rotating machinery by nonlinear blind signal separation and suppress the disturbance of wind information, noise information a

英文关键词： rotating machinery；fault trend；prediction method；energy decoupling；