Xing Qi;Tingting Qiu;Lassi Aarniovuori;Qian Zhang;Jiazi Xu;Wenping Cao
{"title":"基于正交锁相自编码器和圆谐波分解的无模型多相交流信号降阶方法","authors":"Xing Qi;Tingting Qiu;Lassi Aarniovuori;Qian Zhang;Jiazi Xu;Wenping Cao","doi":"10.1109/TIE.2024.3503603","DOIUrl":null,"url":null,"abstract":"Reference frame transformation methods are generally introduced in multiphase ac systems, so as to simplify system's high dimensional ac signals into low dimensional dc ones. Classical methods, such as Clark/Park transformations, are used in balanced systems whose models are known, but not suitable for model-unknown systems which may contain unbalanced components. To address this issue, this article proposes a model-free method, that can downscale both balanced and unbalanced multiphase ac signals into dc ones, without any access to prior model knowledge. The proposed method follows the principles of low rank and sparsity, and consists of two components: 1) a phase-lock orthogonal autoencoder is designed, to transform multiphase ac signals into two-phase orthogonal ac signals; 2) a circular harmonic decomposition is introduced, to further simplify two-phase orthogonal ac signals into some dc constant values. The effectiveness of the proposed method is validated on a real-world model-unknown system, and the experimental results also indicate that the proposed method benefits of discovering some potential patterns of the system, which is helpful for an in-depth study of model-unknown systems. Comparative studies show that the proposed method is superior to classical methods in terms of interpretability, information integrity and scalability in model-unknown scenarios.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 7","pages":"6573-6582"},"PeriodicalIF":7.2000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model-Free Multiphase AC Signals Downscaling Method Using Orthogonal Phase-Lock Autoencoder and Circular Harmonic Decomposition\",\"authors\":\"Xing Qi;Tingting Qiu;Lassi Aarniovuori;Qian Zhang;Jiazi Xu;Wenping Cao\",\"doi\":\"10.1109/TIE.2024.3503603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reference frame transformation methods are generally introduced in multiphase ac systems, so as to simplify system's high dimensional ac signals into low dimensional dc ones. Classical methods, such as Clark/Park transformations, are used in balanced systems whose models are known, but not suitable for model-unknown systems which may contain unbalanced components. To address this issue, this article proposes a model-free method, that can downscale both balanced and unbalanced multiphase ac signals into dc ones, without any access to prior model knowledge. The proposed method follows the principles of low rank and sparsity, and consists of two components: 1) a phase-lock orthogonal autoencoder is designed, to transform multiphase ac signals into two-phase orthogonal ac signals; 2) a circular harmonic decomposition is introduced, to further simplify two-phase orthogonal ac signals into some dc constant values. The effectiveness of the proposed method is validated on a real-world model-unknown system, and the experimental results also indicate that the proposed method benefits of discovering some potential patterns of the system, which is helpful for an in-depth study of model-unknown systems. Comparative studies show that the proposed method is superior to classical methods in terms of interpretability, information integrity and scalability in model-unknown scenarios.\",\"PeriodicalId\":13402,\"journal\":{\"name\":\"IEEE Transactions on Industrial Electronics\",\"volume\":\"72 7\",\"pages\":\"6573-6582\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2024-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Industrial Electronics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10791297/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10791297/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Model-Free Multiphase AC Signals Downscaling Method Using Orthogonal Phase-Lock Autoencoder and Circular Harmonic Decomposition
Reference frame transformation methods are generally introduced in multiphase ac systems, so as to simplify system's high dimensional ac signals into low dimensional dc ones. Classical methods, such as Clark/Park transformations, are used in balanced systems whose models are known, but not suitable for model-unknown systems which may contain unbalanced components. To address this issue, this article proposes a model-free method, that can downscale both balanced and unbalanced multiphase ac signals into dc ones, without any access to prior model knowledge. The proposed method follows the principles of low rank and sparsity, and consists of two components: 1) a phase-lock orthogonal autoencoder is designed, to transform multiphase ac signals into two-phase orthogonal ac signals; 2) a circular harmonic decomposition is introduced, to further simplify two-phase orthogonal ac signals into some dc constant values. The effectiveness of the proposed method is validated on a real-world model-unknown system, and the experimental results also indicate that the proposed method benefits of discovering some potential patterns of the system, which is helpful for an in-depth study of model-unknown systems. Comparative studies show that the proposed method is superior to classical methods in terms of interpretability, information integrity and scalability in model-unknown scenarios.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.