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Application of signal processing tools and artificial neural network in diagnosis of power system faults (Record no. 565506)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01624nam a22001937a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 241024b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780367431136 |
| Paper back/Hardbound | hbk. |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | Eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.310285632 |
| Item number | ROY |
| 110 ## - MAIN ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Roy, Nabamita Banerjee ; Bhattacharya, Kesab |
| 245 ## - TITLE STATEMENT | |
| Title | Application of signal processing tools and artificial neural network in diagnosis of power system faults |
| Statement of responsibility, etc | / Nabamita Banerjee Roy ; Kesab Bhattacharya |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Boca Raton |
| Name of publisher | CRC Press |
| Year of publication | c2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xx, 123 p. |
| Other physical details | : ill. |
| Dimensions | ; 24 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes index |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Accurate, fast, and reliable fault classification techniques are an important operational requirement in modern-day power transmission systems. Application of Signal Processing Tools and Neural Network in Diagnosis of Power System Faults examines power system faults and conventional techniques of fault analysis. The authors provide insight into artificial neural networks and their applications, with illustrations, for identifying power system faults. Wavelet transform and its application are discussed as well as an elaborate method of Stockwell transform. The authors also employ probabilistic neural networks (PNN) and back propagation neural networks (BPNN) to identify the different types of faults and determine their corresponding locations, respectively. Both PNN and BPNN are presented in detail, and their applications are illustrated through simple programming in MATLAB®. Furthermore, their applications in fault diagnosis are discussed through multiple case studies. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Nuclear Engineering |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Reference |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Full call number | Accession Number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Anna Centenary Library | Anna Centenary Library | 6TH FLOOR, A WING | 24.08.2024 | 621.310285632 ROY | 698214 | 24.10.2024 | English Books |