{"title":"利用时变模型补偿残余能量对时域介电响应的影响","authors":"Chandra Madhab Banerjee;Deepak Mishra;Arijit Baral;Sivaji Chakravorti","doi":"10.1109/JSEN.2025.3552516","DOIUrl":null,"url":null,"abstract":"Analysis of polarization and depolarization current (PDC) is a widely accepted method for diagnosing power transformer insulation. The accuracy of such techniques depends significantly on the premise that measurement of insulation response has been done correctly. During field measurement, equipment sometimes fails to record proper current, even after applying dc charging voltage. In such cases, the polarization current profile gets affected by residual energy. Recently, a conventional Debye model (CDM) based approach has been reported to solve the issue. The CDM-based approach relies on identifying the correct time-invariant branch parameters, by minimizing the deviation between measured and estimated value of several performance parameters, through an iterative technique. This coupled with the presence of multiple branches in CDM makes the overall method time consuming and computationally intensive. This article proposes a non-iterative methodology, based on a model with time-varying parameters that is capable of achieving the same result. This not only saves time but also reduces overall data post processing and computation burden required for diagnosis. Performance of the proposed method is tested on data obtained from the oil-paper sample and several real-life power transformers. The proposed method is observed to be capable of estimating paper-moisture (using affected data) with more than 95% accuracy for in-service units. The time required for achieving this is found to be approximately 1/third of that required by CDM-based technique (which could provide results with maximum 90% accuracy).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15184-15193"},"PeriodicalIF":4.3000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Compensating the Impact of Residual Energy on Time Domain Dielectric Response Using Time-Varying Model\",\"authors\":\"Chandra Madhab Banerjee;Deepak Mishra;Arijit Baral;Sivaji Chakravorti\",\"doi\":\"10.1109/JSEN.2025.3552516\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analysis of polarization and depolarization current (PDC) is a widely accepted method for diagnosing power transformer insulation. The accuracy of such techniques depends significantly on the premise that measurement of insulation response has been done correctly. During field measurement, equipment sometimes fails to record proper current, even after applying dc charging voltage. In such cases, the polarization current profile gets affected by residual energy. Recently, a conventional Debye model (CDM) based approach has been reported to solve the issue. The CDM-based approach relies on identifying the correct time-invariant branch parameters, by minimizing the deviation between measured and estimated value of several performance parameters, through an iterative technique. This coupled with the presence of multiple branches in CDM makes the overall method time consuming and computationally intensive. This article proposes a non-iterative methodology, based on a model with time-varying parameters that is capable of achieving the same result. This not only saves time but also reduces overall data post processing and computation burden required for diagnosis. Performance of the proposed method is tested on data obtained from the oil-paper sample and several real-life power transformers. The proposed method is observed to be capable of estimating paper-moisture (using affected data) with more than 95% accuracy for in-service units. The time required for achieving this is found to be approximately 1/third of that required by CDM-based technique (which could provide results with maximum 90% accuracy).\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 9\",\"pages\":\"15184-15193\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10938140/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10938140/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Compensating the Impact of Residual Energy on Time Domain Dielectric Response Using Time-Varying Model
Analysis of polarization and depolarization current (PDC) is a widely accepted method for diagnosing power transformer insulation. The accuracy of such techniques depends significantly on the premise that measurement of insulation response has been done correctly. During field measurement, equipment sometimes fails to record proper current, even after applying dc charging voltage. In such cases, the polarization current profile gets affected by residual energy. Recently, a conventional Debye model (CDM) based approach has been reported to solve the issue. The CDM-based approach relies on identifying the correct time-invariant branch parameters, by minimizing the deviation between measured and estimated value of several performance parameters, through an iterative technique. This coupled with the presence of multiple branches in CDM makes the overall method time consuming and computationally intensive. This article proposes a non-iterative methodology, based on a model with time-varying parameters that is capable of achieving the same result. This not only saves time but also reduces overall data post processing and computation burden required for diagnosis. Performance of the proposed method is tested on data obtained from the oil-paper sample and several real-life power transformers. The proposed method is observed to be capable of estimating paper-moisture (using affected data) with more than 95% accuracy for in-service units. The time required for achieving this is found to be approximately 1/third of that required by CDM-based technique (which could provide results with maximum 90% accuracy).
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
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-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
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-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice