基于双曲S变换算法的电能检测状态辨识及故障诊断研究  

Research on State Identification and Fault Diagnosis of ElectricEnergy Detection Based on Hyperbolic S-transform Algorithm

作　　者：厉建宾 潘阳 闫亚俊 赵光辉 高建莉 刘曼 LI Jianbin;PAN Yang;YAN Yajun;ZHAO Guanghui;GAO Jianli;LIU Man(Marketing Service Center of State Grid Hebei Electric Power Co.,Ltd.,Shijiazhuang 050035,China)

机构地区：[1]国网河北省电力有限公司营销服务中心,河北石家庄050035

出　　处：《无线电工程》2023年第10期2424-2430,共7页Radio Engineering

基　　金：河北省自然科学基金(E2021412002)。

摘　　要：为了提高电能运行状态检测能力、增强电能检测过程中的数据辨识度、提高电能检测设备故障诊断精度,引入改进双曲S变换算法模型,建立电能状态分析系统,设计了电能检测状态辨识系统,根据电能运行过程电能变换频率进行分析,利用图模交互技术对辨识图像和模型进行融合,完成电能数据的图像显示。利用一体化组态网络统一图模交互数据与故障诊断数据,完成电能状态检测的一体化。利用改进双曲S变换算法总结电能数据规律,以双曲S函数的形式进行显示,提高了电能检测状态辨识及故障诊断能力。该系统通过Proteus软件仿真得到电能检测最佳辨识度为93.2%,诊断误差最高为1.4%,表明系统对电能运行状态的检测研究具有明显效果。In order to improve the detection ability of electric energy operation state,enhance the data identification degree in the process of electric energy detection,and improve the fault diagnosis accuracy of electric energy detection equipment,an improved hyperbolic S-transform algorithm model is introduced,an electric energy state analysis system is established,and an electric energy detection state identification system is designed.The analysis is carried out according to the electric energy transformation frequency in the process of electric energy operation,and the identification image and model are fused by using the image and model interaction technology,and the image display of electric energy data is completed.The integrated configuration network is used to unify the interactive data of image and model and the fault diagnosis data to complete the integration of energy state detection.The improved hyperbolic S-transform algorithm is used to summarize the law of electric energy data and display it in the form of hyperbolic S function.The result shows that the ability of electric energy detection state identification and fault diagnosis is improved.The system is simulated by Proteus software,and the best identification degree of electric energy detection is 93.2%,and the maximum diagnostic error is 1.4%,which indicates the effectiveness of the design in electric energy operation state detection.

关 键 词：电能状态分析 图像融合 故障诊断 状态辨识 状态检测 一体化组态网络 

分 类 号：TM930[电气工程—电力电子与电力传动]