基于定子匝间故障的感应电机故障估计

B. L. Widjiantoro, Syahrul Munir, K. Indriawati
{"title":"基于定子匝间故障的感应电机故障估计","authors":"B. L. Widjiantoro, Syahrul Munir, K. Indriawati","doi":"10.12962/j23546026.y2020i6.11148","DOIUrl":null,"url":null,"abstract":"― Since the 19th century, the use of electric motors continues to grow. Nowadays electric motors have been widely used in various fields of industry. One type of electric motor that is often used is an induction motor. Induction motors work in the presence of induced currents due to the relative difference in rotor rotation with rotating magnetic fields. Induction motors are preferred for industrial purposes because of low cost, easy to maintain, and high efficiency. Induction motors that are used continuously can experience several types of fault. The existence of fault can affect the performance of the induction motor. One of the fault that often occurs in induction motor is the result of stator inter-turn fault. This fault is caused by the gradual deterioration of insulation in the stator winding which cause a short-circuit. Sooner or later, this fault can cause damage to the induction motor in a short time if left unchecked. So, it is very important to monitor the fault in real-time. Therefore, this research proposes a fault estimation method on induction motor. The design of fault estimation based on particle filtering and extended state space equations is used to estimate the stator inter-turn fault. The effectiveness of this approach is validated by use of a computer simulation with using two fault signal represented by 𝛈 𝐜𝐜 ramp and step signal. The performances of this fault estimation are measured by RMSE and with using 500 particles has smallest RMSE value, which are 0.0112 and 0.0124 for dq current fault when using 𝛈 𝐜𝐜 ramp signal and 0.2373 and 0.2367 for dq current fault when using 𝛈 𝐜𝐜 step signal.","PeriodicalId":14533,"journal":{"name":"IPTEK Journal of Proceedings Series","volume":"114 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fault Estimation on Induction Motor Based on Stator Inter-Turn Fault\",\"authors\":\"B. L. Widjiantoro, Syahrul Munir, K. Indriawati\",\"doi\":\"10.12962/j23546026.y2020i6.11148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"― Since the 19th century, the use of electric motors continues to grow. Nowadays electric motors have been widely used in various fields of industry. One type of electric motor that is often used is an induction motor. Induction motors work in the presence of induced currents due to the relative difference in rotor rotation with rotating magnetic fields. Induction motors are preferred for industrial purposes because of low cost, easy to maintain, and high efficiency. Induction motors that are used continuously can experience several types of fault. The existence of fault can affect the performance of the induction motor. One of the fault that often occurs in induction motor is the result of stator inter-turn fault. This fault is caused by the gradual deterioration of insulation in the stator winding which cause a short-circuit. Sooner or later, this fault can cause damage to the induction motor in a short time if left unchecked. So, it is very important to monitor the fault in real-time. Therefore, this research proposes a fault estimation method on induction motor. The design of fault estimation based on particle filtering and extended state space equations is used to estimate the stator inter-turn fault. The effectiveness of this approach is validated by use of a computer simulation with using two fault signal represented by 𝛈 𝐜𝐜 ramp and step signal. The performances of this fault estimation are measured by RMSE and with using 500 particles has smallest RMSE value, which are 0.0112 and 0.0124 for dq current fault when using 𝛈 𝐜𝐜 ramp signal and 0.2373 and 0.2367 for dq current fault when using 𝛈 𝐜𝐜 step signal.\",\"PeriodicalId\":14533,\"journal\":{\"name\":\"IPTEK Journal of Proceedings Series\",\"volume\":\"114 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IPTEK Journal of Proceedings Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12962/j23546026.y2020i6.11148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPTEK Journal of Proceedings Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12962/j23546026.y2020i6.11148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

-自19世纪以来,电动机的使用不断增长。如今,电动机已广泛应用于工业的各个领域。一种常用的电动机是感应电动机。感应电动机在感应电流的存在下工作,这是由于转子旋转与旋转磁场的相对差异。由于成本低,易于维护和效率高,感应电机是工业用途的首选。连续使用的感应电动机可能会出现几种故障。故障的存在会影响异步电动机的性能。定子匝间故障是感应电动机常见的故障之一。这种故障是由定子绕组绝缘逐渐劣化导致短路引起的。如果不加以检查,这种故障迟早会在短时间内对感应电动机造成损坏。因此,对故障进行实时监控显得尤为重要。因此,本研究提出了一种异步电动机故障估计方法。采用基于粒子滤波和扩展状态空间方程的故障估计设计,对定子匝间故障进行估计。利用𝛈𝐜𝐜斜坡信号和阶跃信号两种故障信号进行计算机仿真,验证了该方法的有效性。采用RMSE对故障估计的性能进行了测量,使用500个粒子的RMSE值最小,使用𝛈𝐜𝐜斜坡信号的dq电流故障RMSE值分别为0.0112和0.0124,使用𝛈𝐜𝐜阶跃信号的dq电流故障RMSE值分别为0.2373和0.2367。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Fault Estimation on Induction Motor Based on Stator Inter-Turn Fault
― Since the 19th century, the use of electric motors continues to grow. Nowadays electric motors have been widely used in various fields of industry. One type of electric motor that is often used is an induction motor. Induction motors work in the presence of induced currents due to the relative difference in rotor rotation with rotating magnetic fields. Induction motors are preferred for industrial purposes because of low cost, easy to maintain, and high efficiency. Induction motors that are used continuously can experience several types of fault. The existence of fault can affect the performance of the induction motor. One of the fault that often occurs in induction motor is the result of stator inter-turn fault. This fault is caused by the gradual deterioration of insulation in the stator winding which cause a short-circuit. Sooner or later, this fault can cause damage to the induction motor in a short time if left unchecked. So, it is very important to monitor the fault in real-time. Therefore, this research proposes a fault estimation method on induction motor. The design of fault estimation based on particle filtering and extended state space equations is used to estimate the stator inter-turn fault. The effectiveness of this approach is validated by use of a computer simulation with using two fault signal represented by 𝛈 𝐜𝐜 ramp and step signal. The performances of this fault estimation are measured by RMSE and with using 500 particles has smallest RMSE value, which are 0.0112 and 0.0124 for dq current fault when using 𝛈 𝐜𝐜 ramp signal and 0.2373 and 0.2367 for dq current fault when using 𝛈 𝐜𝐜 step signal.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Increasing The Quality and Quantity of Marine Processed Production in Fisherman Villages Assistance of Handicraft Small Business in Increasing Capacity Greenhouse Potential based on Ecotourism and Education for Sustainable Village Economic Resilience Developing New Indonesia Circular Economy Indicators: A Lesson Learnt from European Union A Review of Circular Economy Index from Many Perspective
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1