| 1 | Prognostic for fuel cell based on particle filter and recurrent neural network fusion structure显示文摘Fuel cells are considered as one of the most promising candidates for future power source due to its high energy density and environmentally friendly properties,whereas the short lifespan blocks its large-scale commercializa-tion.In order to enhance the reliability and durability of proton exchange membrane fuel cell,a fusion prog-nostic approach based on particle filter(model-based)and long-short term memory recurrent neural network(data-driven)is proposed in this paper.Both the remaining useful life estimation and the short-term degradation prediction can be achieved based on the prognostic method.For remaining useful life estimation,the particle filter method is used to identify the model parameters in the training phase and the long-short term memory recurrent neural network is used to update the parameters in the prediction phase.As for short-term degradation prediction,the particle filter and long-short term memory recurrent neural network are firstly trained individually in the training phase and then be fused to make predictions in the prediction phase.The proposed fusion structure is validated by the fuel cell experimental tests data,and results indicate that better prognostic performance can be obtained compared with the individual model-based or data-driven method. | Renyou Xie Rui Ma Sicheng Pu Liangcai Xu Dongdong Zhao Yigeng Huangfu | 2020 | Energy and AI2020，2，2： | 1 |
| 2 | Improved Fatigue and Damage Tolerant Material Design for Aerospace Industry显示文摘Various micro-mechanical and micro-structural influences on fatigue crack growth resistance of the material havebeen investigated over the years. It is widely recognized that resistance to fatigue crack growth can be differentiatedinto ’intrinsic’ and ’extrinsic’. The separation of intrinsic and extrinsic crack growth resistance has constituted amajor theme of fatigue research in the last 30 years, with the concept of crack closure or crack tip shielding beingused to rationalize a wide range of micro-structural and mechanical influences on fatigue crack growth behavior. Anaccurately quantitative understanding of intrinsic and extrinsic effects on crack growth is essential to directed alloydesign for improved fatigue resistance, and/or improved structural service life. This paper presents a compliance-basedcrack closure measurement method and a multi-mechanism based analytical model for the separation of intrinsic andextrinsic material fatigue resistance, with application in characterizing the fatigue performance of two high strengthdamage tolerant airframe Al alloys. | Yigeng XU Jiang CHEN Jianmin LI Zefei ZHU | 2005 | Journal of Materials Science & Technology2005，21，6： | 1 |
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