Gas turbine hot sections condition monitoring based on operational thermal dataset

被引:0
|
作者
Khoshghiafehgan, Masoud [1 ]
Akhlaghi, Amir [1 ]
Ranji, Abbas [1 ]
Mazhar, Majid Yeganeh [1 ]
机构
[1] TUGA Co, MAPNA Grp, Tehran, Iran
来源
DATA IN BRIEF | 2024年 / 55卷
关键词
Gas turbine; Failure; Standard deviation; Skewness; Fluctuation; Statistical analysis;
D O I
10.1016/j.dib.2024.110624
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper aimed to monitor the exhaust gas temperature (EGT) from the end of the low-pressure turbine (LPT) of a gas turbine for period of 6 months. To achieve this, 16 thermocouples were strategically placed to gather data at different points in the exhaust system. This comprehensive approach allowed for a detailed analysis of the exhaust gas temperature, which is a critical factor in the health of hot section of gas turbines. The results of this study provide valuable insights that can be used to optimize the periodic inspections of gas turbines and improve their decisions. The investigation of thermal fluctuations that can cause damage to hot components has been carried out using two statistical methods - Standard deviation and Skewness. By analyzing the standard deviation, the degree to which the temperature values vary from the mean and relative normal condition of each unit can be determined. Skewness helps to identify whether the temperature data is skewed towards the high or low values, indicating the presence of potential anomalies. The application of these statistical methods is aimed at understanding the impact of temperature fluctuations on hot components and developing maintenance strategies to mitigate their effects. In order to verify the accuracy of the statistical results, a thorough borescope inspection of the gas turbine is carried out in accordance with the maintenance manual. These inspections were conducted at three distinct intervals to ensure a comprehensive evaluation of the gas turbine condition per- formance and condition. The results of this inspection serve as a critical component in determining the optimal mainte- nance and repair plan for the gas turbine. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY -NC license (http://creativecommons.org/licenses/by-nc/4.0/)
引用
收藏
页数:10
相关论文
共 50 条
  • [11] Gaussian Process Operational Curves for Wind Turbine Condition Monitoring
    Pandit, Ravi
    Infield, David
    ENERGIES, 2018, 11 (07):
  • [12] A guide to condition assessment of gas turbine hot gas path components
    Smillie, M. J.
    Cole, D. G.
    Knowles, D. M.
    MATERIALS AT HIGH TEMPERATURES, 2007, 24 (03) : 139 - 147
  • [13] OPERATIONAL STATE MONITORING OF WIND TURBINE MAIN TRANSMISSION SYSTEM BASED ON WORKING CONDITION RECOGNITION
    Chen J.
    Chen H.
    Xiao Z.
    Xie C.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (02): : 77 - 85
  • [14] On gas turbine engine and control system condition monitoring
    Breikin, T
    Arkov, V
    Kulikov, G
    Kadirkamanathan, V
    Patel, V
    (SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3, 1998, : 67 - 71
  • [15] Condition monitoring Rx for gas turbine equipment health
    Stambler, Irwin
    Gas Turbine World, 2002, 32 (03): : 30 - 33
  • [16] An Agent-Based Implementation of Hidden Markov Models for Gas Turbine Condition Monitoring
    Kenyon, Andrew D.
    Catterson, Victoria M.
    McArthur, Stephen D. J.
    Twiddle, John
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2014, 44 (02): : 186 - 195
  • [17] PowerGen Gas Turbine Losses and Condition Monitoring: A Loss Data-Based Study
    Zhou, Bin
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 2016, 2 (02):
  • [18] Gas-turbine condition monitoring using qualitative model-based diagnosis
    TraveMassuyes, L
    Milne, R
    IEEE EXPERT-INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1997, 12 (03): : 22 - 31
  • [19] POWERGEN GAS TURBINE LOSSES AND CONDITION MONITORING-A LOSS DATA BASED STUDY
    Zhou, Bin
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2014, VOL 14, 2015,
  • [20] Condition Based Monitoring of Small Wind Turbine
    Luczak, M.
    Franssen, P.
    Potok, D.
    Rozycki, M.
    Vivolo, M.
    Peeters, B.
    STRUCTURAL HEALTH MONITORING 2010, 2010, : 955 - 960