Fault Diagnosis of RC-coupled Amplifier Using Slope Fault Feature and Comparision with Different Neural Networks
This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault dictionary for RC-Coupled amplifier. This fault dictionary used to generate different fault diagnosis model for analog circuit using artificial n...
Uloženo v:
| Vydáno v: | 2015 Fifth International Conference on Communication Systems and Network Technologies s. 1163 - 1166 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.04.2015
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault dictionary for RC-Coupled amplifier. This fault dictionary used to generate different fault diagnosis model for analog circuit using artificial neural network technique. For generate the fault model three different type neural networks utilized. These neural networks are radial basis function neural network, perceptron neural network and feed forward back propagation algorithm neural network. In theses network radial basis function neural network shows 100 percentage efficiency, perceptron neural network shows 87.5 percentage efficiency and feed forward back propagation algorithm shows 99.31 percentage efficiency in the training and testing for fault dictionary. |
|---|---|
| AbstractList | This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault dictionary for RC-Coupled amplifier. This fault dictionary used to generate different fault diagnosis model for analog circuit using artificial neural network technique. For generate the fault model three different type neural networks utilized. These neural networks are radial basis function neural network, perceptron neural network and feed forward back propagation algorithm neural network. In theses network radial basis function neural network shows 100 percentage efficiency, perceptron neural network shows 87.5 percentage efficiency and feed forward back propagation algorithm shows 99.31 percentage efficiency in the training and testing for fault dictionary. |
| Author | Ayub, Shahanaz Saini, J. P. Gupta, Shashank Kumar |
| Author_xml | – sequence: 1 givenname: Shashank Kumar surname: Gupta fullname: Gupta, Shashank Kumar email: hariomtech25@gmail.com organization: Dept. of Electron. & Commun. Eng., Bundelkhand Inst. of Eng. & Technol., Jhansi, India – sequence: 2 givenname: Shahanaz surname: Ayub fullname: Ayub, Shahanaz email: shahanaz_ayub@rediffmail.com organization: Dept. of Electron. & Commun. Eng., Bundelkhand Inst. of Eng. & Technol., Jhansi, India – sequence: 3 givenname: J. P. surname: Saini fullname: Saini, J. P. email: jps_uptu@rediffmail.com organization: Dept. of Electron. & Commun. Eng., Bundelkhand Inst. of Eng. & Technol., Jhansi, India |
| BookMark | eNotzLtOwzAYQGEjwQClGxuLXyDBl_g2VoEAUlUkGubKSX4Xi8SOnEQVb0-lMn3TOXfoOsQACD1QklNKzFO539U5I1TkSlyhtVGaFsoYqow0t2is7NLP-NnbY4iTn3B0-LPM2riMPXR4M4y9dx4S_pp8OOJ9H0fAl6YCOy8JsA0dLuMw2uQnHwM--fn7PHQOEoQZ72BJtj8zn2L6me7RjbP9BOt_V6iuXuryLdt-vL6Xm23mGdFzZhsoREGJ5GA4s6LQspESmkaQDqzhDbGat9TJrmu5bpUQnBGQXIEU0jm-Qo-XrQeAw5j8YNPvQTFNKGH8D3V0VrU |
| CODEN | IEEPAD |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/CSNT.2015.75 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9781479917969 1479917974 1479917966 9781479917976 |
| EndPage | 1166 |
| ExternalDocumentID | 7280102 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i208t-abe4541063e932a5486b66ebb50dea93b0a83c1f6ddc38c755320e637e656ff3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000380431700234&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Thu Jun 29 18:36:45 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i208t-abe4541063e932a5486b66ebb50dea93b0a83c1f6ddc38c755320e637e656ff3 |
| PageCount | 4 |
| ParticipantIDs | ieee_primary_7280102 |
| PublicationCentury | 2000 |
| PublicationDate | 20150401 |
| PublicationDateYYYYMMDD | 2015-04-01 |
| PublicationDate_xml | – month: 04 year: 2015 text: 20150401 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | 2015 Fifth International Conference on Communication Systems and Network Technologies |
| PublicationTitleAbbrev | CSNT |
| PublicationYear | 2015 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.5652164 |
| Snippet | This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1163 |
| SubjectTerms | Analog circuits Circuit faults Dictionaries Fault diagnosis feed forward backpropagation algorithm Feeds Neural networks perceptron neural network radial basis function neural network RC-Coupled amplifier Resistance slope fault feature voltage relation function |
| Title | Fault Diagnosis of RC-coupled Amplifier Using Slope Fault Feature and Comparision with Different Neural Networks |
| URI | https://ieeexplore.ieee.org/document/7280102 |
| WOSCitedRecordID | wos000380431700234&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV09a8MwEBVp6NCpLUnpNxo6Vokd2ZI8FrehQwmhCSVb0McJAsY2id3fH0kOaYcunSQEkkA33LvTu3sIPZmYSm1SIDJSjCQaDMm4tETEkFDNqYxDlevXB5_NxGqVzXvo-VgLAwCBfAYjPw1_-abSrU-Vjb2UUuw7R55wzrparSOXPRvni9nSc7XSkScN_tJKCa5iev6_Sy7Q8KfmDs-P3uQS9aAcoHoq26LBrx0fbrPDlcWfOdFVWxdg8Iung1vn2HD4-ceLoqoBd3s8tmu3gGVpcH4QG3Q2wD7x6g7sZFEa7JtzyMINgQ2-G6Ll9G2Zv5ODRgLZTCLREKkgSRMX11FwSEy6-IMpxkCpNDIgM6oiKaiOLTNGU6F56oUggFEODshZS69Qv6xKuEbYAbFkwrmDVDp2NrPZJDYqs8IK58CsETdo4B9rXXddMNaHd7r9e_kOnXlTdByXe9Rvti08oFP93Wx228dguj2fRZ60 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA5jCnpS2cTf5uDRbG3TNulRqmPiLMMV2W2kyQsMSlu21r_fpB3TgxdPCYEkkHd433v53vsQelAuFVIFQISThcSXoEjEhCbcBZ9KRoXbVrl-zliS8OUymvfQ474WBgBa8hmM7LT9y1elbGyqbGyllFzbOfIg8H3P6aq19mz2aBwvktSytYKRpQ3-UktpncXk5H_XnKLhT9Udnu_9yRnqQTFA1UQ0eY2fO0bceotLjT9iIsumykHhJ0sI18a14fbvHy_ysgLc7bHortkAFoXC8U5u0FgB29SrObATRqmxbc8hcjO0fPDtEKWTlzSekp1KAll7Dq-JyMAPfBPZUTBYTJgIJMzCELIscBSIiGaO4FS6OlRKUi5ZYKUgIKQMDJTTmp6jflEWcIGwgWK-x5gBVdI1VtOR56os0lxz48K04pdoYB9rVXV9MFa7d7r6e_keHU3T99lq9pq8XaNja5aO8XKD-vWmgVt0KL_q9XZz15rxGwxfofs |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2015+Fifth+International+Conference+on+Communication+Systems+and+Network+Technologies&rft.atitle=Fault+Diagnosis+of+RC-coupled+Amplifier+Using+Slope+Fault+Feature+and+Comparision+with+Different+Neural+Networks&rft.au=Gupta%2C+Shashank+Kumar&rft.au=Ayub%2C+Shahanaz&rft.au=Saini%2C+J.+P.&rft.date=2015-04-01&rft.pub=IEEE&rft.spage=1163&rft.epage=1166&rft_id=info:doi/10.1109%2FCSNT.2015.75&rft.externalDocID=7280102 |