Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the a...

Full description

Saved in:
Bibliographic Details
Main Authors: Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.
Other Authors: 58701334000
Format: Article
Published: Frontier Scientific Publishing 2024
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-34465
record_format dspace
spelling my.uniten.dspace-344652024-10-14T11:19:58Z Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment Al-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. 58701334000 14030355800 55057479600 58765817900 58168727000 Artificial Intelligent Algorithms Big Data Cloud Computing Power Systems Smart Grid Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the actual details of developing a Power Plant Fault Diagnosis Management System. Furthermore, cloud computing technology and association rule mining as the core technology based on analysis of domestic and foreign research. In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. The functions of private cloud computing clusters for power extensive data management and analysis are realised through MapReduce computing framework and Hbase database. The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. Through analysing the functional requirements of the system in the project, using MySQL database and Enhancer platform, the intelligent fault diagnosis management system of cloud computing power plant is designed and developed, which realises the functions of system modules such as system authority management, electronic equipment account, technical supervision, expert database, data centre. The result shows that the proposed method improves the security problem of the system, the message-digest algorithm (MD5) is used to encrypt the user password, and a strict role authorisation system is designed to realise the access and manage the system�s security. � 2023 by author(s). Journal of Autonomous Intelligence is published by Frontier Scientific Publishing. Final 2024-10-14T03:19:58Z 2024-10-14T03:19:58Z 2023 Article 10.32629/jai.v6i1.640 2-s2.0-85175471600 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175471600&doi=10.32629%2fjai.v6i1.640&partnerID=40&md5=d9c3533f78ddb88331236ecaed878229 https://irepository.uniten.edu.my/handle/123456789/34465 6 1 All Open Access Gold Open Access Frontier Scientific Publishing Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Artificial Intelligent Algorithms
Big Data
Cloud Computing
Power Systems
Smart Grid
spellingShingle Artificial Intelligent Algorithms
Big Data
Cloud Computing
Power Systems
Smart Grid
Al-Jumaili A.H.A.
Muniyandi R.C.
Hasan M.K.
Singh M.J.
Paw J.K.S.
Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
description Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the actual details of developing a Power Plant Fault Diagnosis Management System. Furthermore, cloud computing technology and association rule mining as the core technology based on analysis of domestic and foreign research. In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. The functions of private cloud computing clusters for power extensive data management and analysis are realised through MapReduce computing framework and Hbase database. The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. Through analysing the functional requirements of the system in the project, using MySQL database and Enhancer platform, the intelligent fault diagnosis management system of cloud computing power plant is designed and developed, which realises the functions of system modules such as system authority management, electronic equipment account, technical supervision, expert database, data centre. The result shows that the proposed method improves the security problem of the system, the message-digest algorithm (MD5) is used to encrypt the user password, and a strict role authorisation system is designed to realise the access and manage the system�s security. � 2023 by author(s). Journal of Autonomous Intelligence is published by Frontier Scientific Publishing.
author2 58701334000
author_facet 58701334000
Al-Jumaili A.H.A.
Muniyandi R.C.
Hasan M.K.
Singh M.J.
Paw J.K.S.
format Article
author Al-Jumaili A.H.A.
Muniyandi R.C.
Hasan M.K.
Singh M.J.
Paw J.K.S.
author_sort Al-Jumaili A.H.A.
title Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_short Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_full Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_fullStr Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_full_unstemmed Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_sort intelligent transmission line fault diagnosis using the apriori associated rule algorithm under cloud computing environment
publisher Frontier Scientific Publishing
publishDate 2024
_version_ 1814061181458972672
score 13.214268