{"title":"基于稀疏阵列的超高压换能阀绝缘板局部放电快速到达方向估计方法","authors":"Yunpeng Liu, Jiashuo Liu, Tingyu Lai, Xiaoguang Wei, Shaotong Pei","doi":"10.1049/smt2.12095","DOIUrl":null,"url":null,"abstract":"<p>An insulation board is an important insulator used between damping capacitors in a converter valve. The potential creeping discharge phenomenon on the insulation board will affect the insulation between the damping capacitors and even the safe operation of the converter valve; therefore, a modified chaos particle swarm optimization multiple signal classification (MCSPO-MUSIC) localization algorithm based on a sparse array was proposed. The performance of the localization algorithm and the sparse array was analyzed by MATLAB simulation, and a test platform was established to detect the insulation board discharge position localization. The simulation results showed that the calculation time of this algorithm is about 1.5 s, which is an order of magnitude less than traditional MUSIC algorithm, and it is found that when the sparsity of the 4 × 4 array is 4 (the sparse array elements are 5, 9, 14 and 15), the localization accuracy remains high. Ten groups of experimental data were put into the MCSPO-MUSIC algorithm; the root mean square errors (RMSE) of the localization errors are 1.91° (non-sparse array) and 3.12° (sparse array), respectively. Finally, the blind source separation algorithm was used to remove the field noise, which verifies the algorithm and sparse concept accurate and economical in practical application.</p>","PeriodicalId":54999,"journal":{"name":"Iet Science Measurement & Technology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smt2.12095","citationCount":"0","resultStr":"{\"title\":\"Fast direction of arrival estimation method for ultra-high voltage converter valve insulation board partial discharge based on a sparse array\",\"authors\":\"Yunpeng Liu, Jiashuo Liu, Tingyu Lai, Xiaoguang Wei, Shaotong Pei\",\"doi\":\"10.1049/smt2.12095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>An insulation board is an important insulator used between damping capacitors in a converter valve. The potential creeping discharge phenomenon on the insulation board will affect the insulation between the damping capacitors and even the safe operation of the converter valve; therefore, a modified chaos particle swarm optimization multiple signal classification (MCSPO-MUSIC) localization algorithm based on a sparse array was proposed. The performance of the localization algorithm and the sparse array was analyzed by MATLAB simulation, and a test platform was established to detect the insulation board discharge position localization. The simulation results showed that the calculation time of this algorithm is about 1.5 s, which is an order of magnitude less than traditional MUSIC algorithm, and it is found that when the sparsity of the 4 × 4 array is 4 (the sparse array elements are 5, 9, 14 and 15), the localization accuracy remains high. Ten groups of experimental data were put into the MCSPO-MUSIC algorithm; the root mean square errors (RMSE) of the localization errors are 1.91° (non-sparse array) and 3.12° (sparse array), respectively. Finally, the blind source separation algorithm was used to remove the field noise, which verifies the algorithm and sparse concept accurate and economical in practical application.</p>\",\"PeriodicalId\":54999,\"journal\":{\"name\":\"Iet Science Measurement & Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2021-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smt2.12095\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iet Science Measurement & Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/smt2.12095\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iet Science Measurement & Technology","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/smt2.12095","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Fast direction of arrival estimation method for ultra-high voltage converter valve insulation board partial discharge based on a sparse array
An insulation board is an important insulator used between damping capacitors in a converter valve. The potential creeping discharge phenomenon on the insulation board will affect the insulation between the damping capacitors and even the safe operation of the converter valve; therefore, a modified chaos particle swarm optimization multiple signal classification (MCSPO-MUSIC) localization algorithm based on a sparse array was proposed. The performance of the localization algorithm and the sparse array was analyzed by MATLAB simulation, and a test platform was established to detect the insulation board discharge position localization. The simulation results showed that the calculation time of this algorithm is about 1.5 s, which is an order of magnitude less than traditional MUSIC algorithm, and it is found that when the sparsity of the 4 × 4 array is 4 (the sparse array elements are 5, 9, 14 and 15), the localization accuracy remains high. Ten groups of experimental data were put into the MCSPO-MUSIC algorithm; the root mean square errors (RMSE) of the localization errors are 1.91° (non-sparse array) and 3.12° (sparse array), respectively. Finally, the blind source separation algorithm was used to remove the field noise, which verifies the algorithm and sparse concept accurate and economical in practical application.
期刊介绍:
IET Science, Measurement & Technology publishes papers in science, engineering and technology underpinning electronic and electrical engineering, nanotechnology and medical instrumentation.The emphasis of the journal is on theory, simulation methodologies and measurement techniques.
The major themes of the journal are:
- electromagnetism including electromagnetic theory, computational electromagnetics and EMC
- properties and applications of dielectric, magnetic, magneto-optic, piezoelectric materials down to the nanometre scale
- measurement and instrumentation including sensors, actuators, medical instrumentation, fundamentals of measurement including measurement standards, uncertainty, dissemination and calibration
Applications are welcome for illustrative purposes but the novelty and originality should focus on the proposed new methods.