姓名：趙成英 職稱：講師
性別：女
出生日期：1992/04
所在專業(yè)：機(jī)械設(shè)計(jì)制造及其自動(dòng)化
碩士生指導(dǎo)教師：是
博士生指導(dǎo)教師：否
E-mail：zhaochengying0223@163.com
聯(lián)系電話：13840311401
研究方向：機(jī)械設(shè)備健康狀態(tài)監(jiān)測(cè),故障診斷,壽命預(yù)測(cè),深度學(xué)習(xí),機(jī)械動(dòng)力學(xué)
***********教育經(jīng)歷及工作經(jīng)歷*********
2023/07~至今， 沈陽(yáng)建筑大學(xué)， 講師
2018/09~2023/01，東北大學(xué)，機(jī)械設(shè)計(jì)及理論，博士
2016/09~2018/07，東北大學(xué)，機(jī)械設(shè)計(jì)及理論，碩士
2014/08~2016/08，哈爾濱固泰電子有限責(zé)任公司，標(biāo)準(zhǔn)化工程師
2010/09~2014/07，黑龍江工程學(xué)院，機(jī)械設(shè)計(jì)制造及其自動(dòng)化，學(xué)士
***********科研項(xiàng)目***********
(1) 遼寧省教育廳基礎(chǔ)科研項(xiàng)目，基于數(shù)字孿生的跨工況陶瓷軸承性能退化預(yù)測(cè)方法研究，2024/9-2027/8, 5萬(wàn)元，主持；
(2)遼寧省自然科學(xué)基金項(xiàng)目，物理信息引導(dǎo)下變工況非完備數(shù)據(jù)的軸承剩余壽命預(yù)測(cè)方法研究，2024/12-2026/12，5萬(wàn)，主持；
(3) 遼寧省教育廳基礎(chǔ)科研項(xiàng)目，空間大型桁架結(jié)構(gòu)動(dòng)力學(xué)相似分析與模型試驗(yàn)研究，2024/9-2027/8, 5萬(wàn)元，參與；
(4)遼寧省自然科學(xué)基金項(xiàng)目，基于模-數(shù)驅(qū)動(dòng)的航空薄壁件銑削顫振診斷與抑制系統(tǒng)研發(fā)，2024/12-2026/12，5萬(wàn)，參與；
(5)遼寧省自然科學(xué)基金項(xiàng)目，基于能量俘獲的滾動(dòng)軸承集成傳感器的自供電機(jī)理研究，2024/06-2026/08，5萬(wàn)，參與；
(6) 遼寧省教育廳基礎(chǔ)科研項(xiàng)目，基于數(shù)據(jù)驅(qū)動(dòng)的葉片類薄壁件銑削顫振識(shí)別與抑制研究，2023/11-2025/11, 3萬(wàn)元，參與；
(7) 橫向課題，旋轉(zhuǎn)機(jī)械零部件加工技術(shù)與服役性能研究，2024/05-2025/12，2萬(wàn)元，主持；
(8) 橫向課題，多功能復(fù)合涂層潤(rùn)滑、導(dǎo)熱及防腐性能研究，2024/05-2025/12，2萬(wàn)元，參與；
***********發(fā)表論文***********
(1) Chengying Zhao, Jiajun Wang, Fengxia He, et al., A fatigue life prediction method based on multi-signal fusion deep attention residual convolutional neural network [J]. Applied Acoustics, 2025, 235: 110646
(2) Chengying Zhao,Huaitao Shi, Xianzhen Huang, et al.，A temporal-spatial encoder convolutional network model for multitasking prediction [J]. Applied Intelligence, 2025, 55: 326.
(3) Chengying Zhao,Huaitao Shi, Xianzhen Huang, et al.，A multiple conditions dual inputs attention networkremaining useful life prediction method [J]. Engineering Applications of Artificial Intelligence, 2024, 133: 108160.
(4) Chengying Zhao, Xianzhen Huang, Yuxiong Li. A novel remaining useful life prediction method based on gated attention mechanism capsule neural network [J]. Measurement, 2022, 189: 110637.
(5) ChengyingZhao, XianzhenHuang, Yuxiong Li. A novel Cap-LSTM model for remaining useful life prediction [J]. IEEE Sensors Journal, 2021, 21(20): 23498-23509.
(6) Chengying Zhao,Xianzhen Huang, Huizhen Liu. A novel bootstrap ensemble learning convolutional simple recurrent unit method for remaining useful life interval prediction of turbofanengines [J]. Measurement Science and Technology. 2022, 33(12): 125004.
(7) Huizhen Liu, Chengying Zhao, Xianzhen Huang, et al. Data-driven modelingfor the dynamic behavior of nonlinear vibratory systems [J]. Nonlinear Dynamics. 2023, 111: 10809-10834.
(8) Liangshi Sun, Chengying Zhao, Xianzhen Huang, et al. Cutting toolremaining useful life prediction based on robust empirical mode decompositionand Capsule-BiLSTM network [J]. Proceedings of the Institution of MechanicalEngineers Part C-Journal of Mechanical Engineering Science. 2023, 237(14): 3308-3323.
(9) Yuxiong Li, Xianzhen Huang, Chengying Zhao. A novel remaining useful life prediction method based on multi-support vector regression fusion and adaptive weight updating[J]. ISA Transactions. 2022, 131: 444-459.
(10) Yuxiong Li, Xianzhen Huang, Chengying Zhao. Stochastic fractal search-optimizedmulti-support vector regression for remaining useful life prediction of bearings[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2021, 43(9).
(11) Pengfei Ding; Xianzhen Huang; Chengying Zhao. Online monitoring model of micro-milling force incorporating tool wear prediction process [J]. Expert Systems with Applications. 2023, 223: 119886.
