研究方向
機(jī)械狀態(tài)監(jiān)測(cè)與故障診斷、智能制造、大數(shù)據(jù)處理與人工智能、智能結(jié)構(gòu)。
人物經(jīng)歷
2000年至2004年在重慶大學(xué)機(jī)械工程及自動(dòng)化專業(yè)學(xué)習(xí)，獲學(xué)士學(xué)位，并推免到重慶大學(xué)機(jī)械電子工程系攻讀碩士學(xué)位；
2004年至2008在重慶大學(xué)機(jī)械電子工程專業(yè)碩博連讀，獲工學(xué)博士學(xué)位，其博士論文獲重慶市優(yōu)秀博士論文；
2013年1月至2014年1月在密西根大學(xué)安娜堡校區(qū)作訪問學(xué)者；
2012年1月至2017年3月在四川大學(xué)從事博士后研究工作；
2009年1月至今在重慶大學(xué)從事教學(xué)科研工作。
榮譽(yù)記錄
獲授權(quán)國(guó)家發(fā)明專利7項(xiàng)，實(shí)用新型1項(xiàng)；獲教育部科技進(jìn)步一等獎(jiǎng)2項(xiàng)、“重慶產(chǎn)學(xué)研創(chuàng)新成果獎(jiǎng)”一等獎(jiǎng)1項(xiàng)；獲計(jì)算機(jī)軟件著作權(quán)2件；榮獲科學(xué)中國(guó)人（2018）年度人物。兼任職務(wù)
擔(dān)任了三十余種期刊的的常任審稿人，并多次榮獲杰出審稿人稱號(hào)。IEEE Member、SPIE Member、中國(guó)機(jī)械工程學(xué)會(huì)高級(jí)會(huì)員、中國(guó)振動(dòng)工程學(xué)會(huì)高級(jí)會(huì)員、中國(guó)力學(xué)學(xué)會(huì)高級(jí)會(huì)員、IEEE可靠性學(xué)會(huì)重慶分會(huì)副主席、中國(guó)振動(dòng)工程學(xué)會(huì)故障診斷專業(yè)委員會(huì)理事、中國(guó)振動(dòng)工程學(xué)會(huì)轉(zhuǎn)子動(dòng)力學(xué)專業(yè)委員會(huì)理事、全國(guó)高校機(jī)械工程測(cè)試技術(shù)研究會(huì)理事和西南分會(huì)秘書長(zhǎng)。
學(xué)術(shù)成果
科研項(xiàng)目
面向動(dòng)軸齒輪傳動(dòng)故障診斷的振動(dòng)模型驅(qū)動(dòng)稀疏表征理論研究國(guó)家自然科學(xué)基金面上項(xiàng)目
齒輪傳動(dòng)基礎(chǔ)數(shù)據(jù)與可靠性分析機(jī)械傳動(dòng)國(guó)家重點(diǎn)實(shí)驗(yàn)室特色研究項(xiàng)目
基于耦合壓電阻抗的轉(zhuǎn)子復(fù)合損傷定量診斷方法研究 重慶市基礎(chǔ)科學(xué)與前沿技術(shù)研究項(xiàng)目
陸航十三五預(yù)研項(xiàng)目
數(shù)據(jù)驅(qū)動(dòng)航空發(fā)動(dòng)機(jī)主軸軸承故障預(yù)測(cè)研究重慶大學(xué)中央高校基本科研業(yè)務(wù)費(fèi)前沿交叉研究專項(xiàng)項(xiàng)目
主要專利
多方向?qū)掝l帶壓電振動(dòng)發(fā)電裝置秦毅, 郭磊, 趙月, 湯寶平 發(fā)明 2018.5.22ZL201610442193.5
一種迭代Teager能量算子解調(diào)方法與系統(tǒng) 秦毅, 毛永芳, 任兵, 周廣武 發(fā)明 2011.12.21 ZL201110430480.1
高性能機(jī)械基礎(chǔ)件精密成形智能制造系統(tǒng) 王家序, 秦毅, 韓彥峰, 崔洪斌 發(fā)明2 011.12.16 ZL201110420431.x
滾動(dòng)軸承摩擦力矩試驗(yàn)臺(tái) 王家序，秦毅，趙慧，蒲偉, 李俊陽(yáng) 發(fā)明 2012.04.16ZL201210108207.1
水潤(rùn)滑軸承及傳動(dòng)系統(tǒng)綜合性能實(shí)驗(yàn)平臺(tái) 王家序, 周廣武, 秦毅, 王戰(zhàn)江, 韓彥峰, 李敏, 李俊陽(yáng), 肖科 發(fā)明 2011.05.10 ZL2011101197668
發(fā)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, 2019, DOI 10.1109/TII.2019.2909305
[4] Siliang Lu,Yi Qin*, Jun Hang, Baohua Zhang, Qunjing Wang. Adaptively Estimating Rotation Speed from DC Motor Current Ripple for Order Tracking and Fault Diagnosis.IEEE Transactions on Instrumentation and Measurement,2019,68（3）: 741-753.
[5]Yi Qin, Tiantian Wei, Yue Zhao, Haizhou Chen. Simulation and experiment on bridge-shaped nonlinear piezoelectric vibration energy harvester. Smart Materials and Structures, 2019, 28: 045015.
[6]Yi Qin, Folin Cao, Yi Wang, Weiwei Chen, Haizhou Chen. Dynamics modelling for deep groove ball bearings with local faults based on coupled and segmented displacement excitation. Journal of Sound and Vibration, 2019, 447: 1-19.
[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]Yi Qin, Shuren Qin, Yongfang Mao.Research on iterated Hilbert transform and its application in mechanical fault diagnosis. Mechanical Systems and Signal Processing, 2008, 22（8）: 1967-1980.
[9]Yi Qin, Baoping Tang, Jiaxu Wang. Higher density dyadic wavelet transform and its application. Mechanical Systems and Signal Processing, 2010, 24（3）: 823-834.
[10]Yi Qin, Jiaxu Wang, Baoping Tang, Yongfang Mao.Higher density wavelet frames with symmetric low-pass and band-pass filters. Signal Processing, 2010, 90（12）: 3219-3231.
[11]Yi Qin. Multicomponent AMu2013FM demodulation based on energyseparation and adaptive filtering. Mechanical Systems and Signal Processing, 2013, 38（2）: 440-459.
[12]Yi Qin, YongfangMao, BaopingTang.Vibration signal component separation by iteratively using basis pursuit and its application in mechanical fault detection. JournalofSoundandVibration, 2013, 332（20）: 5217-5235.
[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. JournalofSoundandVibration, 2014,333（26）: 7386-7400.
[16]Yi Qin, Yi Tao, Yongfang Mao, Baoping Tang. Quantitative rotor damage detection basedon piezoelectric impedance . Measurement Science and Technology, 2015, 26: 125012.
[17]Yi Qin, Baoping Tang, Yongfang Mao. Adaptive signal decomposition based on wavelet ridge and its application. Signal Processing, 2016, 120: 480-494.
[18]Yi Qin, Baoping Tang, Jiaxu Wang, Ke Xiao. A new method for multicomponent signal decomposition based on self-adaptive filtering.Measurement, 2011, 44（7）: 1312-1327.
[19]Yi Qin, Jianfeng Xing, and Yongfang Mao. Weak transient fault feature extraction based on an optimized Morlet wavelet and kurtosis. Measurement Science and Technology, 2016, 27: 085003.
[20]Yi Qin, Qingliang Zhang, Yongfang Mao, Baoping Tang.Vibration component separation by iteratively using stochastic resonance with different frequency-scale ratios. Measurement, 2016, 94: 538-553.
[21]Yi Qin, Shuren Qin, Yongfang Mao. Fast implementation of orthogonal empirical mode decomposition and its application into harmonic detection. Chinese Journal of Mechanical Engineering, 2008, 21（2）: 93-98.
[22]Xin Wang,Yi Qin*,and Aibing Zhang. An intelligent fault diagnosis approach for planetary gearboxes based on deep belief networks and uniformed features. Journal of Intelligent & Fuzzy Systems, 2018, 3.
[23]Yonghua Jiang,Baoping Tang,Yi Qin, Wenyi Liu.Feature extraction method of wind turbine based on adaptive Monet wavelet and SVD. Renewable Energy, 2011, 36（8）: 2146-2153.
[24]Zuqiang Su, Baoping Tang, Ziran Liu,Yi Qin.Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine. Neurocomputing, 2015, 157: 208-222
[25]Yongfang Mao, Shuren Qin,Yi Qin.Demodulation based on harmonic wavelet and its application into rotary machinery fault diagnosis. Chinese Journal of Mechanical Engineering, 2009, 22（3）: 419-425.
[26]Baoping Tang, Feng Li,Yi Qin. Fault diagnosis model based on feature compression with orthogonal locality preserving projection. Chinese Journal of Mechanical Engineering, 2011, 24（5）: 891-898.
