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My bibliography Save this articleMore realistic degradation trend prediction for gas turbine based on factor analysis and multiple penalty mechanism loss function
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DOI: 10.1016/j.ress.2024.110097
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- Gong, Linjuan & Hou, Guolian & Li, Jun & Gao, Haidong & Gao, Lin & Wang, Lin & Gao, Yaokui & Zhou, Junbo & Wang, Mingkun, 2023. "Intelligent fuzzy modeling of heavy-duty gas turbine for smart power generation," Energy, Elsevier, vol. 277(C).
- Guandalini, Giulio & Campanari, Stefano & Romano, Matteo C., 2015. "Power-to-gas plants and gas turbines for improved wind energy dispatchability: Energy and economic assessment," Applied Energy, Elsevier, vol. 147(C), pages 117-130.
- Li, Yasong & Zhou, Zheng & Sun, Chuang & Peng, Jun & Nandi, Asoke K. & Yan, Ruqiang, 2023. "Life-cycle modeling driven by coupling competition degradation for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
- Daghi, Majid & Sedghi, Mahdi & Ahmadian, Ali & Aliakbar-Golkar, Masoud, 2016. "Factor analysis based optimal storage planning in active distribution network considering different battery technologies," Applied Energy, Elsevier, vol. 183(C), pages 456-469.
- Xiong, Zhanhang & Yao, Jianjiang & Huang, Yongmin & Yu, Zhaoxu & Liu, Yalei, 2024. "A wind speed forecasting method based on EMD-MGM with switching QR loss function and novel subsequence superposition," Applied Energy, Elsevier, vol. 353(PB).
- Deng, Zhongwei & Yang, Lin & Cai, Yishan & Deng, Hao & Sun, Liu, 2016. "Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery," Energy, Elsevier, vol. 112(C), pages 469-480.
- Shi, Jiayu & Zhong, Jingshu & Zhang, Yuxuan & Xiao, Bin & Xiao, Lei & Zheng, Yu, 2024. "A dual attention LSTM lightweight model based on exponential smoothing for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
- Arias Chao, Manuel & Kulkarni, Chetan & Goebel, Kai & Fink, Olga, 2022. "Fusing physics-based and deep learning models for prognostics," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
- Zhou, Liang & Wang, Huawei & Xu, Shanshan, 2023. "Aero-engine prognosis strategy based on multi-scale feature fusion and multi-task parallel learning," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Zhang, Yadong & Zhang, Chao & Wang, Shaoping & Dui, Hongyan & Chen, Rentong, 2024. "Health indicators for remaining useful life prediction of complex systems based on long short-term memory network and improved particle filter," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
- Wei, Meng & Balaya, Palani & Ye, Min & Song, Ziyou, 2022. "Remaining useful life prediction for 18650 sodium-ion batteries based on incremental capacity analysis," Energy, Elsevier, vol. 261(PA).
- Long, Zhenhua & Bai, Mingliang & Ren, Minghao & Liu, Jinfu & Yu, Daren, 2023. "Fault detection and isolation of aeroengine combustion chamber based on unscented Kalman filter method fusing artificial neural network," Energy, Elsevier, vol. 272(C).
- Fatemi, Seyyed A. & Kuh, Anthony & Fripp, Matthias, 2016. "Online and batch methods for solar radiation forecast under asymmetric cost functions," Renewable Energy, Elsevier, vol. 91(C), pages 397-408.
- Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
- Pan, Rui & Liu, Tongshen & Huang, Wei & Wang, Yuxin & Yang, Duo & Chen, Jie, 2023. "State of health estimation for lithium-ion batteries based on two-stage features extraction and gradient boosting decision tree," Energy, Elsevier, vol. 285(C).
- Tahan, Mohammadreza & Tsoutsanis, Elias & Muhammad, Masdi & Abdul Karim, Z.A., 2017. "Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review," Applied Energy, Elsevier, vol. 198(C), pages 122-144.
- Wang, Hongfei & Li, Xiang & Zhang, Zhuo & Deng, Xinyang & Jiang, Wen, 2024. "A deep learning based health index construction method with contrastive learning," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Song, Houde & Liu, Xiaojing & Song, Meiqi, 2023. "Comparative study of data-driven and model-driven approaches in prediction of nuclear power plants operating parameters," Applied Energy, Elsevier, vol. 341(C).
- Xiang, Sheng & Qin, Yi & Luo, Jun & Pu, Huayan & Tang, Baoping, 2021. "Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
- Bai, Rui & Noman, Khandaker & Feng, Ke & Peng, Zhike & Li, Yongbo, 2023. "A two-phase-based deep neural network for simultaneous health monitoring and prediction of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
- Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
- Wei, Yupeng & Wu, Dazhong & Terpenny, Janis, 2021. "Learning the health index of complex systems using dynamic conditional variational autoencoders," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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Keywords
Health index; Degradation trend prediction; Factor analysis; Improved loss function; Gas turbine;All these keywords.
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