基于粗糙集的智能数据挖掘算法在风机监测中的应用

An Application of Intelligent Data Mining Algorithm Based on Rough Set in WTIG Monitoring

为了对风力发电机监测诊断过程中冗繁属性进行约简,提高监测诊断的效率和自动化、智能化水平。在运用自组织神经网络处理数据的基础上,运用改进粗糙集理论的属性约简算法及关联规则的数据挖掘方法,在风力发电机状态监测参数的优选和智能诊断中进行分析。这种方法不仅大大减少了特定属性信息提取的工作量,更在数据分析中发挥了自主式学习和决策的优越性。

In order to improve the efficiency and automatic measurement of the WTIG （wind turbine induction generators） ,the method based on RS （Rough Set） and GA （Genetic Algorithm） has been adopted. In the thesis, RS is ameliorated dealing with the flocks of data which is predigested in the Neural Networks, and then the correlative information could be disinterred as using integrated formula of GA and data mining. The composite algorithm exerting the preponderance in decision-making and impregnability has expansive application domain.