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Liu S, Peng G, Li Z, et al. Low-frequency vibration isolation via an elastic origami-inspired structure[J]. International Journal of Mechanical Sciences, 2023: 108622.【TOP】
Mengyu Ji, Gaoliang Peng, Sijue Li,Wentao Huang,Weihua Li and Zhixiong Li, Iterative-AMC: a novel model compression and structure optimization method in mechanical system safety monitoring. Structural Health Monitoring. [Accept]【TOP】
Liu S, Peng G, Li Z, et al. Nonlinear stiffness analysis and programming of a composite origami metamaterial with embedded joint-type metastructures[J]. Composite Structures, 2023: 116761.【TOP】
Liu S, Peng G, Li Z, et al. Design and experimental study of an origami-inspired constant-force mechanism[J]. Mechanism and Machine Theory, 2023, 179: 105117.【TOP】
Li S, Liu F, Peng G, et al. A Lightweight SHM Framework Based on Adaptive Multisensor Fusion Network and Multigeneration Knowledge Distillation[J]. IEEE Transactions on Instrumentation and Measurement.2022, 71, 1-19.
Jiang Y, Huang W, Wang W, Peng G. A complete dynamics model of defective bearings considering the three-dimensional defect area and the spherical cage pocket[J]. Mechanical Systems and Signal Processing, 2023, 185: 109743.【TOP】
Ji M, Peng G, Li S, et al. A neural network compression method based on knowledge-distillation and parameter quantization for the bearing fault diagnosis[J]. Applied Soft Computing, 2022: 109331.【TOP】
Liu S, Peng G, Li Z, et al. Analytical jump-avoidance criteria of Duffing-type vibration isolation systems under base and force excitations based on concave-convex property[J]. Journal of Vibration and Control, 2022: 10775463221110653.
Wang Z, Huang W, Yi C, et al. Multisource cross-domain fault diagnosis of rolling bearing based on subdomain adaptation network[J]. Measurement Science and Technology, 2022.
Zhang Z, Peng G, Wang W, et al. Prediction-Based Human-Robot Collaboration in Assembly Tasks Using a Learning from Demonstration Model[J]. Sensors, 2022, 22(11): 4279.
Cheng F, Liang Z, Peng G, et al. An Anti-UAV Long-Term Tracking Method with Hybrid Attention Mechanism and Hierarchical Discriminator[J]. Sensors, 2022, 22(10): 3701.
Y Sun, G Peng, K Jin, S Liu, P Gardoni, Z Li. Force/motion transmissibility analysis and parameters optimization of hybrid mechanisms with prescribed workspace. Engineering Analysis with Boundary Elements, 2022,139: 264-277
Liu S, Sun Y, Peng G, et al. Development of a novel 6-DOF hybrid serial-parallel mechanism for pose adjustment of large-volume components[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022, 236(5): 2099-2114.
Li S, Peng G, Ji M, et al. Impact identification of composite cylinder based on improved deep metric learning model and weighted fusion Tikhonov regularized total least squares[J]. Composite Structures, 2022, 283: 115144.【TOP】
Liu S, Peng G, Jin K. Towards accurate modeling of the Tachi-Miura origami in vibration isolation platform with geometric nonlinear stiffness and damping[J]. Applied Mathematical Modelling, 2022.【TOP】
Liu S, Peng G, Jin K. Design and characteristics of a novel QZS vibration isolation system with origami-inspired corrector[J]. Nonlinear Dynamics, 2021: 1-23.【TOP】
Li S, Peng G, Mao D, et al. Intelligent Fault Diagnosis Using Limited Data Under Different Working Conditions Based on SEflow Model and Data Augmentation[M]//Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer, Singapore, 2021: 475-484.
G Peng, M Ji, Y Xue, Y Sun. Development of a novel integrated automated assembly system for large volume components in outdoor environment[J]. Measurement 168, 108294
Z Zhu, L Wang, G Peng, S Li.WDA: An Improved Wasserstein Distance-Based Transfer Learning Fault Diagnosis Method[J].Sensors 21 (13), 4394
Ji M, Peng G, He J, et al. A Two-Stage, Intelligent Bearing-Fault-Diagnosis Method Using Order-Tracking and a One-Dimensional Convolutional Neural Network with Variable Speeds[J]. Sensors, 2021, 21(3): 675.
Peng G, Ji M, Xue Y, Sun Y, Development of a novel integrated automated assembly system for large volume components in outdoor environment, Measurement,2020,108294, https://doi.org/10.1016/j.measurement.2020.108294.
Chen Y, Peng G, Zhu Z, et al. A novel deep learning method based on attention mechanism for bearing remaining useful life prediction[J]. Applied Soft Computing, 2020, 86: 105919. 【ESI高被引论文】
Fengyu Xu, Fanchang Meng, Quansheng Jiang, Gaoliang Peng,Grappling claws for a robot to climb rough wall surfaces: Mechanical design, grasping algorithm, and experiments,Robotics and Autonomous Systems, 2020, 128:103501.
He J, Peng G L, Yu L T, et al. Establishment and application of heat flow coupling model[J]. Thermal Science, 2019, 23(1): 207-218.
Zhang Z, Wang W, Chen Y, et al. Prediction of Human Actions in Assembly Process by a Spatial-Temporal End-to-End Learning Model[R]. SAE Technical Paper, 2019.
Zhang L, Shan X, Liu Y, et al. Reducing the drag of underwater vehicle in the shape of a small boat by using piezoelectric transducers[C]//IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2019, 531(1): 012090.
Zhang C, Shan X, Peng G, et al. Modeling and simulation of the structural and electrical characteristics for a polarized piezoelectric sensor actuator[C]//IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2019, 531(1): 012053.
Wen S, Qi H, Niu Z, et al. Online estimation of boundary heat flux of participating media by an extented Kalman filtering technique[C]//Proceedings of the 9th International Symposium on Radiative Transfer, RAD-19. Begel House Inc., 2019.
Liu S, Peng G, Gao H. Dynamic modeling and terminal sliding mode control of a 3-DOF redundantly actuated parallel platform[J]. Mechatronics, 2019, 60: 26-33.
Zhu Z, Peng G, Chen Y, et al. A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosis[J]. Neurocomputing, 2019, 323: 62-75. 【ESI高被引论文】
Peng G, Sun Y, Xu S. Development of an Integrated Laser Sensors Based Measurement System for Large-Scale Components Automated Assembly Application[J]. IEEE Access, 2018, 6: 45646-45654.
Zhang W, Li C, Peng G, et al. A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load[J]. Mechanical Systems and Signal Processing, 2018, 100: 439-453.【ESI热点论文】
Chen Y, Peng G, Xie C, et al. ACDIN: Bridging the gap between artificial and real bearing damages for bearing fault diagnosis[J]. Neurocomputing, 2018, 294: 61-71.
Zhang W, Peng G, Li C, et al. A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals[J]. Sensors, 2017, 17(2): 425. 【ESI高被引论文】
Li C, Zhang W, Peng G, et al. Bearing Fault Diagnosis Using Fully-Connected Winner-Take-All Autoencoder[J]. IEEE Access, 2017.[SCI]
Zhang W, Peng G, Li C. Bearings fault diagnosis based on convolutional neural networks with 2-D representation of vibration signals as input[C]//MATEC Web of Conferences. EDP Sciences, 2017, 95: 13001.
Zhang W, Peng G, Li C. Rolling element bearings fault intelligent diagnosis based on convolutional neural networks using raw sensing signal[M]//Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer, Cham, 2017: 77-84.
Gaoliang Peng, Yu Sun, Rui Han, Chuanhao Li, Shaohui Liu. A measuring method for large antenna assembly using laser and vision guiding technology. Measurement, Volume 92, October 2016, pp. 400-412
Gaoliang Peng, Zhujun Zhang, Weiquan Li. Computer vision algorithm for measurement and inspection of O-rings. Measurement, Volume 94, December 2016,pp. 828-836
Gaoliang Peng Yu Sun Rui Han Chuanhao Li, (2016),"An automated assembly technology for large mobile radar antenna", Assembly Automation, Vol.36 Iss 4 pp. 429-438
Peng Gaoliang, Wang Gongdong, Liu Wenjian, Yu Haiquan. A desktop virtual reality-based interactive modular fixture configuration design system. Computer-Aided Design. 2010, 42(5): 432-444.
Peng Gaoliang Chen Guangfeng, Wu Chong, Xin Hou,Jiang Yang. Applying CBR and RBR to develop a VR based integrated system for machining fixture design, Expert Systems with Applications. 2011, 38 (1): 26-38.
Peng Gaoliang, Xin Hou, Chong Wu, et al. Fast collision detection approach to facilitate interactive modular fixture assembly design in a virtual environment. International Journal of Advanced Manufacturing Technology. 2010, 46:315-328.
Peng Gaoliang, Chen Guangfeng, Liu Xinhua. Using CBR to develop a VR based integrated system for machining fixture design, Assembly Automation. 2010 ,30 (3): 228-239
Peng Gaoliang, Yu Haiquan, Liu Xinhua. A desktop virtual reality-based integrated system for complex product maintainability design and verification, Assembly Automation. 2010, 30(4):333–344
Peng Gaoliang, Gao Jun, He Xu, Towards the development of a desktop virtual reality-based system for modular fixture configuration design, Assembly Automation. Vol.29, No.1, 2009:19–31.
Peng Gaoliang, He Xu, Yu Haiquan, Precise manipulation approach to facilitate interactive modular fixture assembly design in VE, Assembly Automation. Vol.28, No.3, 2008: 216-224
Gaoliang Peng, Xin Hou, Jun Gao and Debin Cheng, A visualization system for integrating maintainability design and evaluation at product design stage. International Journal of Advanced Manufacturing Technology, 2012, 61(1-4), pp 269-284
Gaoliang Peng, Yang Jiang, Jie Xu, Xin Li. A collaborative manufacturing execution platform for space product development enterprise. International Journal of Advanced Manufacturing Technology. 2012, 62(5-8): 443-455
Peng Gaoliang, He Jun, Yang Shaopeng, Application of the fiber-optic distributed temperature sensing for monitoring the liquid level of producing oil wells, Measurement, 2014,58:130-137
Li Xin, and Peng Gaoliang. Research on leakage prediction calculation method for static seal ring in underground equipments. Journal of Mechanical Science and Technology, 2016, 30 (6): 2635-2641
Li Xin, Peng Gaoliang, Li Zhe，Prediction of seal wear with thermal-structural coupled finite element method, Finite Elements in Analysis and Design, 2014,83: 10-21
Zhang Xutang, Peng Gaoliang, Zhuang Ting, Hou Xin, knowledge reuse-based computer-aided fixture design framework, Assembly Automation, 2014 34(2):169-181
Xinhua Liu, Gaoliang Peng, Xiumei Liu and Youfu Hou. Disassembly sequence planning approach for product virtual maintenance based on improved max–min ant system. International Journal of Advanced Manufacturing Technology, 59(5-8), pp 829-839, 2012
Xinhua Liu, Gaoliang Peng, Xiumei Liu. Development of a collaborative virtual maintenance environment with agent technology. Journal of Manufacturing Systems, 29(4), pp 173-181, 2010/10
Jiang Yang, Peng Gaoliang, Liu Wenjian. Research on ontology-based integration of product knowledge for collaborative manufacturing. International Journal of Advanced Manufacturing Technology. 2010, 49 (9-12): 1209-1221
Yu Haiquan, Peng Gaoliang, Liu Wenjian. A practical method for measuring product maintainability in a virtual environment. Assembly Automation, 31(1), pp 53-61, 2011
Xu He, Gao Xiaozhi, Peng Gaoliang. Optimization of Reconfigurable Mobile Robots Based on Modified Harmony Search Method. Bio-inspired Computing: Theory and Applications special issue for Transactions of the Institute of Measurement and Control.
Bi Feng-Yang, Jin Tian-Guo, Peng Gaoliang, Liu Wen-Jian. A rapid design and design knowledge management system for mould of autoclave forming resin matrix composite components. Polymers and Polymer Composites, 20(1-2), pp 183-190, 2012
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