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秦毅
（重慶大學機械與運載工程學院教授）
鎖定
秦毅，男，四川宜賓人，博士，重慶大學機械與運載工程學院和高端裝備機械傳動全國重點實驗室教授，博士生導師，國家級青年人才，首批重慶英才·青年拔尖人才，重慶大學科研後備拔尖人才，連續入選全球前2%頂尖科學家“終身科學影響力排行榜”。主要從事智能故障診斷與預測、智能無人系統、大數據處理與人工智能、智能製造、動力學建模與數字孿生等領域的研究。現作為項目負責人承擔了國家自然科學基金、國家重點研發計劃子課題、重慶市基礎科學與前沿技術研究項目等多項國家和省部級項目。在國內外著名雜誌和會議上發表論文180餘篇，其中，SCI檢索139篇（被引用4700餘次，其中他引4000餘次），EI檢索34篇，ISTP檢索1篇；在科學出版社出版學術專著1部，參編高等教育出版社出版教材1部；獲授權發明專利30項、實用新型2項；獲計算機軟件著作權7件；獲省部級科技獎勵一等獎5項。
- 職 業
- 教師
- 專業方向
- 機械狀態監測與故障診斷、智能製造、大數據處理與人工智能等
- 職 務
- 重慶大學機械電子工程系支部書記
- 主要成就
- 教育部科技進步一等獎、重慶市科技進步一等獎 [1]
秦毅研究方向
秦毅人物經歷
2000年至2004年在重慶大學機械工程及自動化專業學習，獲學士學位，並推免到重慶大學機械電子工程系攻讀碩士學位；
2004年至2008在重慶大學機械電子工程專業碩博連讀，獲工學博士學位，其博士論文獲重慶市優秀博士論文；
2013年1月至2014年1月在密西根大學安娜堡校區作訪問學者；
2012年1月至2017年3月在四川大學從事博士後研究工作；
秦毅獲獎記錄
獲授權國家發明專利29項，美國發明實用新型1項；獲計算機軟件著作權7件；獲重慶市科技進步一等獎2項、教育部科技進步一等獎2項、重慶產學研創新成果獎一等獎1項；榮獲英國物理學會（IOP）出版社2019高被引作者獎、IEEE Reliability Society Chongqing Chapter傑出青年科學家、科學中國人(2018)年度人物
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秦毅兼任職務
擔任了80餘種國內外期刊的的常任審稿人，並多次榮獲傑出審稿人稱號。IEEE Senior Member、中國機械工程學會/振動工程學會高級會員、IEEE可靠性學會重慶分會副主席、中國振動工程學會動態測試專業委員會常務理事、中國振動工程學會轉子動力學專業委員會常務理事、中國振動工程學會故障診斷專業委員會理事、中國自動化學會技術過程的故障診斷與安全性專業委員會專委、中國機械工程學會設備智能運維分會委員、CCF工業控制計算機專委會專委。
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秦毅學術成果
秦毅科研項目
- 高速滾動軸承的無監督多尺度精細分層壽命預測方法研究 國家自然科學基金面上項目
- 水下機器人故障預測與容錯控制研究 國家自然科學基金重點項目
- 面向動軸齒輪傳動故障診斷的振動模型驅動稀疏表徵理論研究 國家自然科學基金面上項目
- 高性能齒輪疲勞試驗檢測新技術 國家重點研發計劃重點專項子課題
秦毅主要專利
秦毅，郭磊，趙月，湯寶平，多方向寬頻帶壓電振動發電裝置，2016.6.20，中國，ZL201610442193.5
秦毅，毛永芳，任兵，周廣武，一種迭代Teager能量算子解調方法與系統，2011.12.21，中國， ZL201110430480.1
秦毅，陳定糧，項盛，閻昊冉，基於GAU神經網絡的軸承剩餘壽命的預測方法，2020.05.29，中國，ZL202010478274.7
秦毅，吉浩天，張馨雨，王朝淯，向勇，葉子，陳夢然，一種小型齒輪箱觀察窗內壁除污裝置，2021.02.09，中國，ZL202011036035.2
秦毅發表論文
[1]Yi Qin*.A new family of model-based impulsive wavelets and their sparse representation for rolling bearing fault diagnosis. IEEE Transactions on Industrial Electronics, 2018, 65(3): 2716-2726.
[2]Yi Qin*,Xin Wang,Jingqiang Zou. The optimized deep belief networks with improved logistic Sigmoid units and their application in fault diagnosis for planetary gearboxes of wind turbines. IEEE Transactions on Industrial Electronics, 2019, 66(5): 3814-3824.
[3]Yi Qin*, Jingqiang Zou, Baoping Tang, Yi Wang, Haizhou Chen. Transient feature extraction by the improved orthogonal matching pursuit and K-SVD algorithm with adaptive transient dictionary, IEEE Transactions on Industrial Informatics, 2020, 16(1): 215-227.
[4] Sheng Xiang, JianghongZhou, Jun Luo, Fuqiang Liu, Yi Qin*.Cocktail LSTM and its application into machine remaining useful life prediction. IEEE/ASME Transactions on Mechatronics, 2023, 28(5): 2425-2436.
[5]Yi Qin, Jiahong YangJianghong Zhou, Huayan Pu, Xiangfeng Zhang, Yongfang Mao*. Dynamic weighted federated remaining useful life predictionapproach for rotating machinery. Mechanical Systems and Signal Processing, 2023, 202: 110688.
[6] Quan Qian, Jianghong Zhou, Yi Qin*. Relationship transfer domain generalization network for rotating machinery fault diagnosisunder different working conditions. IEEE Transactions on Industrial Informatics, 2023, 19(9): 9898-9908.
[7]Yi Qin, Yongfang Mao, Baoping Tang, Yi Wang, Haizhou Chen. M-band flexible wavelet transform and its application into planetary gear transmission fault diagnosis.Mechanical Systems and Signal Processing, 2019
[8]Jianghong Zhou, Yi Qin*, JunLuo, Shilong Wang, Tao Zhu. Dual-thread gated recurrent unit for gear remaininguseful life prediction. IEEE Transactions on Industrial Informatics, 2023, 19(7): 8307-8318.
[9]Yi Qin*, Quan Qian, Jun Luo,Huayan Pu. Deep joint distribution alignment: a novelenhanced domain adaptation mechanism for fault transfer diagnosis. IEEE Transactions on Cybernetics, 2023, 53(5): 3128-3138.
[10]Quan Qian, Yi Qin*, Jun Luo*, Yi Wang, Fei Wu. Deep discriminative transfer learningnetwork for cross-machine fault diagnosis. Mechanical Systems and Signal Processing, 2023, 186: 109884.
[11]Yi Qin. Multicomponent AM–FM demodulation based on energyseparation and adaptive filtering. Mechanical Systems and Signal Processing, 2013, 38(2): 440-459.
[12]Jianghong Zhou, Yi Qin*, Jun Luo, Tao Zhu. Remaining useful lifeprediction by distribution contact ratio health indicator and consolidated memoryGRU. IEEE Transactions on Industrial Informatics, 2023, 19(7): 8472-8483.
[13]Yi Qin, JiaxuWang,Yongfang Mao.Dense framelets with two generators and their application in mechanical fault diagnosis. Mechanical Systems and Signal Processing, 2013,40(2): 483-498.
[14]Yi Qin, Yongfang Mao, Baoping Tang. Multicomponent decomposition by wavelet modulus maximaand synchronous detection. Mechanical Systems and Signal Processing, 2017, 91: 57-80.
[15]Yi Qin, Yi Tao, Ye He, Baoping Tang. Adaptive bistable stochastic resonance and its application in mechanical fault feature extraction. Journal of Sound and Vibration, 2014,333(26): 7386-7400.
[16] Yi Qin*, Quan Qian*, Yi Wang, Jianghong Zhou. Intermediate distribution alignment andits application into mechanical fault transfer diagnosis. IEEE Transactions on Industrial Informatics,2022, 18(10): 7305-7315.
[17] Sheng Xiang, Yi Qin*, Jun Luo, Huayan Pu. Spatiotemporally multidifferential processing deep neural network and its application toequipment remaining useful life prediction. IEEE Transactions on Industrial Informatics, 2022, 18(10): 7230-7239.
[18] Dingliang Chen, Yi Qin*, Jun Luo, ShengXiang. Gated adaptive hierarchical attention unit neural networks for the lifeprediction of servo motors. IEEE Transactions on Industrial Electronics, 2022, 69(9): 9451-9461.
[19] Yi Qin*, Jianghong Zhou, Dingliang Chen. Unsupervised health indicatorconstruction by a novel degradation-trend-constrained variational autoencoderand its applications. IEEE/ASME Transactions on Mechatronics, 2022, 27(3): 1447-1456.
[20] Yi Qin∗, Xingguo Wu, Jun Luo. Data-model combined drivendigital twin of life-cycle rolling bearing. IEEE Transactions on IndustrialInformatics, 2022, 18(3): 1530-1540
[21] Yi Qin∗, Dingliang Chen, Sheng Xiang, Caichao Zhu. Gated dual attention unit neural networks for remaining useful lifeprediction of rolling bearings. IEEE Transactions on Industrial Informatics,2021, 17(9): 6438-6447.
[22] Yi Qin∗, Sheng Xiang, Yi Chai, Haizhou Chen. Macroscopic-microscopic attention in LSTM networks based on fusion features forgear remaining life prediction. IEEE Transactions on Industrial Electronics,2020, 67(12): 10865-10875.
[23] Yi Qin∗, Chengcheng Li, Folin Cao, Haizhou Chen. A fault dynamic model of high-speed angular contact ball bearings. Mechanism and Machine Theory, 2020, 143: 103627.
[24] Quan Qian, Yi Qin*, Jun Luo,Dengyu Xiao. Cross-machine transfer fault diagnosis by ensemble weighting subdomain adaptation network. IEEE Transactions on Industrial Electronics, 2023, 70(12): 12773-12783.
[25] Yi Qin*, Qirui Li, Shuo Wang, Peiyu Cao. Dynamics modeling of faulty planetary gearboxes bytime-varying mesh stiffness excitation of spherical overlapping pittings. Mechanical Systems and Signal Processing, 2024, 210:111162.
[26] Sheng Xiang, Penghua Li, Jun Luo, Yi Qin*. Micro transfer learning mechanism for cross-domain equipment RUL prediction.IEEE Transactions on Automation Science and Engineering,2024, DOI: 10.1109/TASE.2024.3366288.
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- 參考資料
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- 1. 重慶大學主頁平台管理系統 秦毅 ．首頁．2024-03-15[引用日期2024-03-14]
