代表性论文专著
在Cell子刊iScience, Mechanical Systems and Signal Processing, Knowledge-Based Systems, Automation in Construction, Journal of Intelligent Manufacturing, Science China Technological Sciences, IEEE Trans.等国内外期刊上发表SCI论文56篇(1篇入选ESI热点论文,4篇入选ESI高被引论文,中科院1区top18篇,中科院1/2区39篇,JCR Q1/2区52篇,*为通讯作者), 在Google Scholar上被引用近1100次, h-index=21。
2022
[78] Qin C., Shi G., Tao J., Yu H., Jin Y., Xiao D., Zhang Z., Liu C., An adaptive hierarchical decomposition-based method for multi-step cutterhead torque forecast of shield machine. Mechanical Systems and Signal Processing, 2022, 175:109148. (SCI, IF: 8.934)
[77] Liu Y., Qin C.*,et al, Diagnosis for MHCD with deep learning. iScience, 2022, Uuder Revision. (SCI, IF: 6.107)
[76] Qin C., Xiao D.,Tao J., Yu H., Jin Y., Sun Y., Liu C., Concentrated velocity synchronous linear chirplet transform with application to robotic drilling chatter monitoring. Measurement, 2022, 194:111090. https://doi.org/10.1016/j.measurement.2022.111090. (SCI, IF: 5.131)
[75] Qin C., Shi G., et al, RCLSTMNet: A Residual-Convolutional-LSTM Neural Network for Forecasting Cutterhead Torque in Shield Machine, International Journal of Control, Automation and Systems, 2022, Uuder Revision. (SCI, IF: 2.964)
[74] Liu Y., Qin C.*,et al, An efficient neural network-based method for patient-specific information involved arrhythmia detection. Knowledge-Based System, 2022, 250:109021. https://doi.org/10.1016/j.knosys.2022.109021. (SCI, IF: 8.139)
[73] Jin Y., Qin C.*, ,et al, A multi-scale CNN with anti-strong-noise and noise-domain adaptation for bearing compound fault diagnosis. Science China Technological Sciences, 2022, https://doi.org/10.1007/s11431-022-2109-4. (SCI, IF: 3.903)
[72] Fu X., Tao J., Qin C., ,et al, , A roller state-based fault diagnosis method for TBM main bearing using two-stream CNN with multi-channel detrending inputs. IEEE Transactions on Instrumentation & Measurement, 2022, Uuder Revision. (SCI, IF:5.332)
[71] Jin Y., Li Z., Qin C.*, et al, A novel interpretable method based on attentional deep neural network for actual ECG quality assessment. Biomedical Signal Processing and Control, 2022, https://doi.org/10.1016/j.bspc.2022.104064. (SCI, IF: 5.076)
[70] Jin Y., Li Z., Liu Y., Liu J., Qin C.*, Zhao L., Liu C*, Multi-class 12-lead ECG Automatic Diagnosis based on a novel Subdomain Adaptive Deep Network. Science China Technological Sciences, 2022, https://doi.org/10.1007/s11431-022-2080-6. (SCI, IF: 3.903)
[69] Tao J., Yu H., Qin C., Sun H., Liu C., A gene expression programming-based method for real-time wear estimation of disc cutter on TBM cutterhead". Neural Computing and Applications, 2022, https://doi.org/10.1007/s00521-022-07597-4. (SCI, IF: 5.102)
[68] Liu C., Ma X. Shi X., Han Y., Qin C., Hu S., A Novel NSCNN for Domain Generalization DiagnosisTasks Across Different Transducers and Different Bearings Specifications. Measurement, 2022, Uuder Revision. (SCI, IF: 5.131)
[67] Liu J., Jin Y., Liu Y, Li Z., Qin C., Chen X, Zhao L; Liu C., A novel P-QRS-T wave localization method in ECG Signals based on HNN. Computers in Biology and Medicine, 2022, Uuder Revision. (SCI, IF: 6.698)
[66] 刘明阳, 陶建峰, 覃程锦, 余宏淦, 刘成良. 基于随机森林与粒子群算法的隧道掘进机操作参数地质类型自适应决策.中南大学学报,2022,录用.
[65] 陶治同,陶建峰,覃程锦,刘成良. 基于时间冲击最优的TBM换刀机器人轨迹规划. 浙江大学学报(工学版),2022,录用.
2021
[64] Qin C., Shi G., Tao J., Yu H., Jin Y., Lei J., Liu C., Precise cutterhead torque prediction for shield tunneling machines using a novel hybrid deep neural network. Mechanical Systems and Signal Processing, 2021, 151: 107386. (SCI, IF: 8.934, 入选ESI高被引论文)
[63] Qin C., Zeng H., Tao J., Xiao D., Yu H., Sun Y., Liu C., A chatter recognition approach for robotic drilling operations based on SCT. Mechanical Systems and Signal Processing, 2021, Revision submitted. (SCI, IF: 8.934)
[62] Qin C., Jin Y., Tao J., Xiao D.,Yu H., Liu C., Shi G.,Lei J., Liu C., DTCNNMI: A deep twin convolutional neural networks with multi-domain inputs for strongly noisy diesel engine misfire detection. Measurement, 2021, 180: 109548. (SCI, IF: 5.131, 入选ESI热点论文和高被引论文)
[61] Jin Y., Qin C.*, Tao J., Liu C., An accurate and adaptative cutterhead torque prediction method for shield tunneling machines via adaptative residual long-short term memory network. Mechanical Systems and Signal Processing, 2021. https://doi.org/10.1016/j.ymssp.2021.108312. (SCI, IF: 8.934)
[60] Yu H., Tao J.*, Qin C.*, Liu M., Xiao D., Sun H., Liu C., A novel constrained dense convolutional autoencoder and DNN-based semi-supervised method for shield machine tunnel geological formation recognition. Mechanical Systems and Signal Processing, 2021. https://doi.org/10.1016/j.ymssp.2021.108353. (SCI, IF: 8.934)
[59] Shi G., Qin C.*, Tao J., Liu C., A VMD-EWT-LSTM-based multi-step prediction approach for shield tunneling machine cutterhead torque. Knowledge-Based System, 2021, 228:107213. (SCI, IF: 8.139)
[58] Xiao D., Qin C., Ge J., Xia P., Huang Y.*, Liu C., Self-attention-based Adaptive RUL Prediction for IGBT with MCD. Knowledge-Based System, 2022, 239:107902. https://doi.org/10.1016/j.knosys.2021.107902. (SCI, IF: 8.139)
[57] Xiao D., Qin C., Xia P., Jin Y., Huang Y.*,Liu C., Unsupervised DA RUL Prediction for IGBTs under DWC. IEEE Transactions on Power Electronics, 2021, Under Revision. (SCI, IF: 6.153)
[56] Jin Y., Qin C.*, Liu J., Li Z., Shi H., Lin K., Liu Y., Liu C.*, A novel incremental and interactive method for actual heartbeat classification with limited additional labeled samples. IEEE Transactions on Instrumentation & Measurement, 2021, 70: 2507212. (SCI, IF:5.332)
[55] Yu H., Tao J.*, Huang S., Qin C.*, Xiao D., Liu C., A field parameters-based method for real-time wear estimation of disc cutter on TBM cutterhead. Automation in Construction, 2021, 124:103603. (SCI, IF: 10.517)
[54] Jin Y., Liu J., Liu Y., Qin C.*, Li Z., Xiao D., Zhao L., Liu C.*, A novel interpretable method based on dual-Level attentional deep neural network for actual Multi-label Arrhythmia detection. IEEE Transactions on Instrumentation & Measurement, 2022, 71:2500311. https://doi.org/10.1109/TIM.2021.3135330. (SCI, IF:5.332)
[53] Tao J., Qin C.*, Xiong Z., Gao X., Liu C., Optimization and control of cable tensions for hyper-redundant snake arm robots. International Journal of Control, Automation and Systems, 2021, 19: 3764–3775. (SCI, IF: 3.314)
[52] Xiao D., Qin C.*, Yu H., Huang Y.*, Liu C., Zhang J., Unsupervised Machine Fault Diagnosis for Noisy Domain Adaptation using marginal Denoising Autoencoder. Measurement, 2021, 176:109186. (SCI, IF: 5.131)
[51] Jin Y., Qin C.*, Huang Y.*, Liu C., Actual Bearing Compound Fault Diagnosis based on Active Learning and Decoupling Attentional Residual Network. Measurement, 2021, 173: 108500. (SCI, IF: 5.131, 入选ESI高被引论文)
[50] Yu H., Tao J.*, Qin C.*, Xiao D., Sun H., Liu C.,Rock mass type prediction for tunnel boring machine using a novel semi-supervised method. Measurement, 2021, 179: 10954. (SCI, IF: 5.131)
[49] Liu Y., Jin Y., Liu J., Qin C.*, Lin K., Shi H., Tao J., Zhao L., Liu C.*, Precise and efficient heartbeat classification using a novel lightweight-modified method. Biomedical Signal Processing and Control, 2021, 68:102771. (SCI, IF: 5.076)
[48] Xiao D., Qin C.*, Yu H., Huang Y.*,Liu C., Unsupervised deep representation learning for motor fault diagnosis by mutual information maximization. Journal of Intelligent Manufacturing, 2021, 32(2): 377–391. (SCI, IF:7.136)
[47] Liu C., Qin C., Shi X., Wang Z., Zhang G., Han Y., TScatNet: An interpretable cross-domain intelligent diagnosis model with anti-noise and few-shot learning capability. IEEE Transactions on Instrumentation & Measurement, 2021, 70:9279302. (SCI, IF:5.332)
[46] Sun H., Tao J., Qin C., Yu H., Liu C., Dynamics modeling and bifurcation analysis for valve-controlled hydraulic cylinder system containing counterbalance valves. Journal of Vibration Engineering & Technologies, 2021, https://doi.org/10.1007/s42417-021-00342-6. (SCI)
[45] Yu H., Tao J.*, Qin C., Sun H., Liu C., A Novel A-CNN Method for TBM Utilization Factor Estimation. Journal of Physics Conference Series, 2021. https://doi.org/10.1088/1742-6596/2002/1/012049.
[44] Li B., Wang S., Qin C., Gong L, Simulation of Aircraft Anti-skiding Braking System Considering Dynamic Contact Force between Road and Wheels. Journal of Physics Conference Series, 2021, 1905(1):012012.
[43] 刘明阳, 余宏淦,陶建峰, 覃程锦, 刘成良. 基于盾构机运行参数的局部切空间排列与Xgboost融合的岩土类型识别[J].中南大学学报,2022, 53(6): 2080−2091. https://doi.org/10.11817/j.issn.1672-7207.2022.06.010.
2020
[42] Qin C., Tao J., Shi H., Xiao D., Li B., Liu C., A novel Chebyshev-wavelet-based approach for accurate and fast prediction of milling stability. Precision Engineering, 2020, 62:244–255. (SCI, IF:3.315, 入选ESI高被引论文)
[41] Tao J., Qin C.*, Xiao D., Shi H., Ling X., Li B., Liu C., Timely chatter identification for robotic drilling using a local maximum synchrosqueezing-based method. Journal of Intelligent Manufacturing, 2020, 31: 1243–1255. (SCI, IF:7.136)
[40] Jin Y., Qin C.*, Liu J., Lin K., Shi H., Huang Y., Liu C.*, A novel Domain Adaptive Residual Network for automatic Atrial Fibrillation Detection. Knowledge-Based System, 2020, 203:106122. (SCI, IF: 8.139)
[39] Qin C., Tao J., Xiao D., Shi H., Ling X., Liu C., Accurate and efficient stability prediction for milling operations using a Legendre-Chebyshev-based method. International Journal of Advanced Manufacturing Technology, 2020, 107(1–2): 247–258. (SCI, IF:3.563)
[38] Qin C., Tao J., Xiao D., Shi H., Li B., Liu C.. A Legendre wavelet–based stability prediction method for high-speed milling processes. International Journal of Advanced Manufacturing Technology, 2020, 108(7-8): 2397-2408. (SCI, IF:3.563)
[37] Jin Y., Qin C., Huang Y., Zhao W., Liu C., Multi-domain modeling of atrial fibrillation detection with twin attentional convolutional long short-term memory neural networks. Knowledge-Based System, 2020, 193:105460. (SCI, IF: 8.139)
[36] Shi H., Qin C., Xiao D., Zhao L., Liu C., Automated heartbeat classification based on deep neural network with multiple input layers. Knowledge-Based System, 2020, 188:10503. (SCI, IF: 8.139)
[35] Wang H., Shi H., Lin K., Qin C.*, Zhao L., Huang Y., Liu C.*, A high-precision arrhythmia classification method based on dual fully connected neural network. Biomedical Signal Processing and Control, 2020, 58:101874. (SCI, IF: 5.076)
[34] Shi H., Wang H., Qin C., Zhao L., Liu C.. An incremental learning system for atrial fibrillation detection based on transfer learning and active learning. Computer Methods and Programs in Biomedicine, 2020, 187:105219. (SCI, IF: 7.027)
[33] Xiao, D., Tao, Z., Qin C., ...Huang, Y., Liu, C.,Fast Machine Fault Diagnosis Using Marginalized Denoising Autoencoders Based on Acoustic Signal. 2020 Prognostics and Health Management Conference, PHM-Besancon 2020, 2020, pp. 229–234, 9115517.
[32] 蔡道清, 周洪宇, 覃程锦, 李彦明, 刘成良. 基于小波变换的农田图像光照不变特征提取算法[J].农业机械学报,2020,51(02):15-20.
[31] 杨泰春, 陶建峰, 覃程锦, 刘成良. 采用支持向量机的非对称阀控液压缸模型预测控制[J].西安交通大学学报,2020,54(01):93-100+107.
2019
[30] Qin C., Tao J., Liu C., A novel stability prediction method for milling operations using the holistic-interpolation scheme. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2019, 233(13):4463–4475. (SCI)
[29] Tao J., Qin C.*, Xiao D., Shi H., Liu C., A pre-generated matrix-based method for real-time robotic drilling chatter monitoring. Chinese Journal of Aeronautics, 2019, 32(12): 2755–2764. (SCI, IF: 4.061)
[28] Tao J., Qin C.*, Liu C., A synchroextracting-based method for early chatter identification of robotic drilling process. International Journal of Advanced Manufacturing Technology, 2019, 100(1–4):273–285. (SCI, IF:3.563)
[27] Tao J., Zeng H., Qin C.*, Liu C., Chatter detection in robotic drilling operations combining multi-synchrosqueezing transform and energy entropy. International Journal of Advanced Manufacturing Technology, 2019, 105(7–8): 2879–2890. (SCI, IF:3.563)
[26] Tao J., Qin C.*, Li W., Liu C., Intelligent fault diagnosis of diesel engines via extreme gradient boosting and high-accuracy time–frequency information of vibration signals. Sensors, 2019, 19:3280. (SCI, IF: 3.576)
[25] Xiao D., Huang Y., Zhao L., Qin C., Shi H., Liu C., Domain adaptive motor fault diagnosis using deep transfer learning. IEEE Access, 2019, 7:80937-80949. (SCI, IF: 3.367)
[24] Xiao D., Huang Y., Qin C., Liu Z., Li Y., Liu C., Transfer learning with convolutional neural networks for small sample size problem in machinery fault diagnosis. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2019, 233(14):5131-5143. (SCI)
[23] Ling X., Tao J., Li B., Qin C., Liu C.. A Multi-physics modeling-based vibration prediction method for switched reluctance motors. Applied Sciences, 2019, 9(21):4544. (SCI, IF: 2.679)
[22] Xiao, D., Huang, Y., Qin C., ...Liu, C., Shan, Z., Health Assessment for Crane Pumps based on Vehicle Tests using Deep Autoencoder and Metric Learning. 2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019, 2019, 8819387.
[21] Xiao D., Huang Y., Qin C., Shi H., Li Y., Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN. Shock and Vibration, 2019, 2019:8325218. (SCI)
[20] Shi H., Wang H., Huang Y., Zhao L., Qin C., Liu C., A hierarchical method based on weighted extreme gradient boosting in ECG heartbeat classification. Computer Methods and Programs in Biomedicine, 2019, 171:1-1. (SCI, IF: 5.428)
[19] 段贤强, 陶建峰, 覃程锦, 蔡道清, 李彦明, 刘成良. 变速条件下农业机械路径跟踪稳定控制方法[J].农业机械学报,2019,50(09):18-24+32.
[18] 齐文超, 李彦明, 张锦辉, 覃程锦, 刘成良, 殷月朋. 丘陵山地拖拉机车身调平双闭环模糊PID控制方法[J].农业机械学报,2019,50(10):17-23+34.
[17] 薛雷, 曾宏伟, 覃程锦, 陶建峰, 刘成良等. 采用同步压缩变换和能量熵的机器人加工颤振监测方法[J].西安交通大学学报,2019,53(08):24-30+89.
[16] 张康, 陶建峰, 覃程锦, 李卫星, 刘成良. 随机丢弃和批标准化的深度卷积神经网络柴油机失火故障诊断[J].西安交通大学学报,2019,53(08):159-166.
[15] 齐文超, 李彦明, 陶建峰, 覃程锦, 刘成良, 种昆. 丘陵山地拖拉机姿态主动调整系统设计与实验[J].农业机械学报,2019,50(07):381-388.
[14] 蔡道清, 李彦明, 覃程锦, 刘成良. 水田田埂边界支持向量机检测方法[J].农业机械学报,2019,50(06):22-27+109.
[13] 陈建国, 李彦明, 覃程锦, 刘成良. 小麦精量播种机排种高精度检测系统设计与试验[J].农业机械学报,2019,50(01):66-74.
[12] 李卫星, 陶建峰, 覃程锦, 刘成良. 同步压缩小波与极限梯度提升树融合的柴油机失火故障诊断[J].西安交通大学学报,2019,53(02):47-54+169.
[11] 张伟, 杨刚, 雷军波, 刘成良, 陶建峰, 覃程锦. 基于微波反射法的谷物含水率在线检测装置研制[J].农业工程学报,2019,35(23):21-28.
Before 2019
[10] Qin C., Tao J., Liu C., A predictor-corrector-based holistic-discretization method for accurate and efficient milling stability analysis. International Journal of Advanced Manufacturing Technology, 2018, 96(5–8):2043–2054. (SCI, IF:3.563)
[09] Qin C., Tao J., Liu C., Stability analysis for milling operations using an Adams-Simpson-based method. International Journal of Advanced Manufacturing Technology, 2017, 92 (1–4):969–979. (SCI, IF:3.563)
[08] Qin C., Tao J., Liu C., An Adams-Moulton-based method for stability prediction of milling processes. International Journal of Advanced Manufacturing Technology, 2017, 89 (9–12):3049–3058. (SCI, IF:3.563)
[07] Qin C.*, Tao J., Wang M., Liu C., A novel approach for the acquisition of vibration signals of the end effector in robotic drilling. 2016 IEEE/CSAA International Conference on Aircraft Utility Systems, 2016, 7748106:522–526.
[06] Tao J., Qin C., Liu C.. Milling Stability Prediction with Multiple Delays via the Extended Adams-Moulton-Based Method. Mathematical Problems in Engineering, 2017, 2017:7898369. (SCI)
[05] Li, Y., Chen, J., Qin C., Liu, C.,Design of Precise Detection System for Wheat Seeding Quantity Based on AD7746 Analog to Digital Conversion Chip. Proceedings of 2018 International Computers, Signals and Systems Conference, 2018, pp. 706–711, 8941861.
[04] 陈建国, 李彦明, 覃程锦, 刘成良. 小麦播种量电容法检测系统设计与试验[J].农业工程学报,2018,34(18):51-58.
[03] 陶建峰, 朱瑶宏, 覃程锦, 庄欠伟. 类矩形隧道单机械臂管片拼装机运动学逆解[J].上海交通大学学报,2016,50(09):1473-1479.
[02] 王明斗, 陶建峰, 覃程锦, 刘成良. 空间余量最优的拼装机轨迹规划[J].浙江大学学报(工学版),2017,51(03):453-460.
[01] 陶建峰, 覃程锦, 黄德中, 顾建江. 类矩形盾构单机械臂管片拼装机静态误差计算[J].现代隧道技术,2016,53(S1):60-68.