发电机状态辨识的空间排序熵模型研究  

Research on spatial permutation entropy model for generator state identification

作　　者：罗睿 王毅[1] 仇璐珂[1] 王智微[1] 何新[1] 孙叶柱 LUO Rui;WANG Yi;QIU Luke;WANG Zhiwei;HE Xin;SUN Yezhu(Xi’an Thermal Power Research Institute Co.,Ltd.,Xi’an 710054,China;Huaneng Power International Inc.,Beijing 100031,China)

机构地区：[1]西安热工研究院有限公司,陕西西安710054 [2]华能国际电力股份有限公司,北京100031

出　　处：《热力发电》2022年第6期159-166,共8页Thermal Power Generation

基　　金：中国华能集团有限公司科技项目(HNKJ19-H34,HNKJ20-H74);西安热工研究院研发基金项目(TS-20-TYK44)。

摘　　要：排序熵是一种计算数据相邻大小关系混乱度的模型。采用空间排序熵的构建方法,建立了发电机的状态诊断模型。首先根据发电机的定子线圈温度测点群构建原始向量,然后通过向量维度和空间延迟参数将该序列重构为排序向量矩阵,接着计算定子线圈温度的空间排序熵,作为发电机状态辨识的特征值。最后,通过对不同发电机的历史状态及运行数据分析,发现定子线圈温度的空间排序熵随发电负荷增大,绝对均值变大且标准差降低。并且,通过合适的向量维度和延迟参数计算得到的空间排序熵,能够准确诊断发电机定子线圈的5种温度异常状态,可为发电机的大量温度测点群的状态辨识和故障报警提供精准判据。Permutation entropy is a kind of model which calculating the turbidity of data adjacent size relation.The construction method of spatial permutation entropy is employed to establish the state diagnosis model for generator.The original vector is constructed through multiple measurement points of stator coil temperature,and the ordering vector space is reconstructed through the vector dimension and spatial delay parameter.The permutation entropy of original vector is calculated to indicate the generator state.It is found that the permutation entropy value calculated from historical monitoring data of stator coil temperature can indicate different load conditions of different classes of generators.With the increase of power generation load,the mean value of permutation entropy increases and the standard deviation of ranking entropy decreases.The spatial permutation entropy formed by appropriate vector dimension and spatial delay parameter can diagnose the five abnormal conditions of generator stator coil temperature.It can provide accurate signal for state identification and fault alarm of a large number of temperature measuring point groups of generators.

关 键 词：发电机 状态辨识 排序熵 向量重构 故障诊断 

分 类 号：TK311[动力工程及工程热物理—热能工程] TP306.3[自动化与计算机技术—计算机系统结构]