ON-LINE DIAGNOSIS OF TURBINE-GENERATORS USING ARTIFICIAL INTELLIGENCE.

被引：0
|
作者：
Gonzalez, Avelino J. [1 ]
Osborne, Robert L. [1 ]
Kemper, Chris T. [1 ]
Lowenfeld, Simon [1 ]
机构：
[1] Westinghouse Electric Corp, Orlando,, FL, USA, Westinghouse Electric Corp, Orlando, FL, USA
来源：
IEEE Transactions on Energy Conversion | 1986年 / EC-1卷 / 02期
关键词：
ARTIFICIAL INTELLIGENCE - Expert Systems - ELECTRIC MACHINERY - Monitoring - SENSORS;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An artificial-intelligence-based, online turbine generator diagnostic expert system which is presently under development is described. Utilizing the inputs from a number of sensors, the diagnostic system evaluates the condition of the equipment and communicates appropriate action. This is different from present monitoring systems which simply apply alarm limits to the value of each sensed variable. The focus is on the design of the diagnostic system and its outstanding features, and the artificial intelligence rule base used to arrive at a diagnosis. Preliminary results of a rule-based online verification project are also described.
引用
收藏
页码：68 / 74
相关论文
共 50 条
  • [41] Epidemiological Surveillance of the Impact of the Covid-19 Pandemic on Stroke Care Using Artificial Intelligence.
    Nogueira, Raul
    Davies, Jason
    Gupta, Rishi
    Hassan, Ameer E.
    Devlin, Thomas G.
    Haussen, Diogo C.
    Mohammaden, Mahmoud
    Kellner, Christopher P.
    Arthur, Adam S.
    Elijovich, Lucas
    Owada, Kumiko
    Dina, Dina
    Narayan, Mukund
    Mordenfeld, Nadia
    Tekle, Wondwossen
    Nahab, Fadi B.
    Jovin, Tudor G.
    Don Frei, Don Frei
    Siddiqui, Adnan
    Frankel, Michael R.
    Mocco, J. D.
    STROKE, 2021, 52
  • [42] On-line estimation of quantities using artificial neural networks
    Zilková, Jaroslava
    Timko, Jaroslav
    Acta Technica CSAV (Ceskoslovensk Akademie Ved), 2002, 47 (03): : 305 - 315
  • [43] Multicenter ALADIN: Automated Large Artery Occlusion Detection in Stroke Imaging Using Artificial Intelligence.
    Rodrigues, Gabriel M.
    Barreira, Clara
    Froehler, Michael
    Baxter, Blaise
    Devlin, Thomas
    Lim, Jaims
    Al-Bayati, Alhamza R.
    Bouslama, Mehdi
    Haussen, Diogo C.
    Nogueira, Raul G.
    STROKE, 2019, 50
  • [44] Review of Artificial Intelligence Methods for Faults Monitoring, Diagnosis, and Prognosis in Hydroelectric Synchronous Generators
    Bechara, Helene
    Ibrahim, Rony
    Zemouri, Ryad
    Kedjar, Bachir
    Merkhouf, Arezki
    Tahan, Antoine
    Al-Haddad, Kamal
    IEEE ACCESS, 2024, 12 : 173599 - 173617
  • [45] The application of artificial intelligence technology in the fault diagnosis of floating wind turbine generator
    Han Hui
    Liu Xiu-wen
    Bian Jing-yu
    2020 5TH INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION (ICECTT 2020), 2020, : 305 - 307
  • [46] Fundamental study on vibration diagnosis for turbine generators using wavelet transform
    Kawada, M
    Yamada, K
    Yamashita, K
    Isaka, K
    2004 IEEE PES POWER SYSTEMS CONFERENCE & EXPOSITION, VOLS 1 - 3, 2004, : 1215 - 1220
  • [47] Fault Prediction and Diagnosis of Wind Turbine Generators Using SCADA Data
    Zhao, Yingying
    Li, Dongsheng
    Dong, Ao
    Kang, Dahai
    Lv, Qin
    Shang, Li
    ENERGIES, 2017, 10 (08)
  • [48] In service turbine generators stator windings failure risks minimization on the base of discharge events on-line monitoring
    Aksenov, YP
    ELECTRICAL INSULATION CONFERENCE AND ELECTRICAL MANUFACTURING & COIL WINDING CONFERENCE, PROCEEDINGS, 2001, : 429 - 436
  • [49] Autonomous Line Maze Solver Using Artificial Intelligence
    Norbert-Brendon, Kovacs
    Marius, Tiurbe Cristian
    2019 15TH INTERNATIONAL CONFERENCE ON ENGINEERING OF MODERN ELECTRIC SYSTEMS (EMES), 2019, : 133 - 136
  • [50] On-line automated analytical signal diagnosis in sequential injection analysis systems using artificial neural networks
    Ruisanchez, I
    Lozano, J
    Larrechi, MS
    Rius, FX
    Zupan, J
    ANALYTICA CHIMICA ACTA, 1997, 348 (1-3) : 113 - 127
12345