潮群

副教授

所在系所:机电控制与物流装备研究所

电子邮件:chaoqun@sjtu.edu.cn

通讯地址:bat365在线中国官网登录入口A楼825室

个人主页:/teacher_directory1/chaoqun.html

个人简介
教学工作
科研工作
荣誉奖励

教育背景

2013/09 – 2019/03,浙江大学,机械电子工程,工学博士

2009/08 – 2013/06,合肥工业大学,机械设计制造及其自动化,工学学士





工作经历

2022/07 – 至今,bat365在线中国官网登录入口,bat365在线中国官网登录入口,副教授/博士生导师

2019/04 – 2022/06,bat365在线中国官网登录入口,bat365在线中国官网登录入口,博士后


研究方向

1. 高性能液压元件设计与电液驱控技术

2. 重大机电液装备健康管理与智能运维

 

欢迎机械、液压、计算机、电气、控制、通信、材料等学科背景的优秀本科生、硕/博士生和博士后加入

招生名额:每年可招收1~2名博士研究生+2~3名硕士研究生,常年招聘博士后

学术兼职

中国机械工程学会流控分会智能流控专业委员

中国机械工程学会高级会员、中国人工智能学会青年工作委员会委员

制造业自动化国家工程研究中心技术专家

工程科学与技术、西南交通大学学报、International Journal of Hydromechatronics等期刊青年编委

IOP Trusted Reviewer

《工程学导论》

科研项目

2025/01 – 2028/12,国家自然科学基金面上项目:高压高速微型柱塞泵服役性能退化机理与健康评估预测方法,主持
2024/11 – 2026/10,全国重点实验室开放基金:轮式起重机开式阀控回转系统操控性匹配设计数字化平台,主持

2024/11 – 2025/06,企业合作项目:某型作动器仿真-试验数据融合驱动的参数识别技术开发,主持

2024/04 – 2025/05,企业合作项目:5000psi高压柱塞泵服役性能建模仿真与分析研究,主持

2024/02 – 2024/09,企业合作项目:调距桨数字孪生系统开发,参与

2022/11 – 2025/12,bat365在线中国官网登录入口长聘教轨副教授科研启动经费项目:智能液压元件,主持

2022/11 – 2026/10,国家重点研发计划青年科学家项目:农业专用智能芯片开发,主持

2021/01 – 2023/12,国家自然科学基金青年项目:EHA柱塞泵复杂极端充液环境下配流副失效机理及表面性能强化技术研究,主持

2021/11 – 2024/10,国家重点研发计划课题:集成一体化电液执行机构设计与制造,子课题主持

2019/09 – 2021/03,中国博士后科学基金面上项目(一等资助)EHA柱塞泵复杂充液环境下滑靴失效机理及其流场调控,主持

2021/09 – 2023/12,国家重点实验室开放基金:大型掘进装备柱塞泵状态监测与健康维护技术研究,主持

2021/12 – 2023/11,广东省电子信息产品可靠性技术重点实验室开放基金:隧道掘进机液压泵健康评估与故障诊断技术研究,主持

2019/11 – 2021/10,上海市超级博士后奖励计划项目:重型锻造装备液压泵失效机理与故障诊断研究,主持

2020/06 – 2022/05,全国博士后创新人才支持计划项目:极端充液环境下超高速 EHA 柱塞泵摩擦副失效机理与流场调控研究,主持

2020/01 – 2022/12,教育部-中国移动科研基金建设项目:智能制造关键技术,参与

2019/06 – 2023/05,国家重点研发计划项目:全断面隧道掘进装备运行服务平台及智能终端研制,参与

2021/01 – 2024/12,国家自然科学基金面上项目:类矩形盾构环臂式电液伺服管片拼装机振动机理及其预测控制方法,参与

2017/07 – 2021/06,国家重点研发计划课题:拖拉机作业信息采集故障预警及远程诊断技术研究,参与

2017/01 – 2019/12,国家自然科学基金青年项目:高功率密度液压集成块的金属增材制造关键技术研究,参与

2014/01 – 2018/08973 计划课题:高压高速液压泵复杂动力学行为与固液热多场耦合机制,参与

代表性论文专著

[1]      汪文涛, 潮群*, 林泽宇, 刘成良. 轴向柱塞泵流量脉动成因及成分数值仿真分析, 2024, 录用.

[2]      Shao Yuechen, Chao Qun*, Zhang Zhiqiang, Liu Chengliang. An adversarial-based domain generalization method for the health evaluation of axial piston pumps. Physica Scripta, 2024, 99(10): 106002.

[3]      Chao Qun, Lu Sijie, Liu Chengliang, Wang Yuanhang. Unsupervised learning to detect wear faults in axial piston pumps by the similarity of periodic discharge pressure ripples. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2024, 238(18): 9278–9292.

[4]      Shao Yuechen, Chao Qun*, Xia Pengcheng, Liu Chengliang. Fault severity recognition in axial piston pumps using attention-based adversarial discriminative domain adaptation neural network. Physica Scripta, 2024, 99(5): 056009.

[5]      Hu Yong, Chao Qun*, Xia Pengcheng, Liu Chengliang. Remaining useful life prediction using physics-informed neural network with self-attention mechanism and deep separable convolutional network. Journal of Advanced Manufacturing Science and Technology, 2024, 4(4): 2024016.

[6]      Dong Chang, Tao Jianfeng, Hao Sun, Chao Qun, Liu Chengliang. Inverse transient analysis based calibration of surrogate pipeline model for fault simulation of axial piston pumps. Mechanical Systems and Signal Processing, 2023, 205: 110829.

[7]      Chao Qun, Shao Yuechen, Liu Chengliang, Yang Xiaoxue. Health evaluation of axial piston pumps based on density weighted support vector data description. Reliability Engineering and System Safety, 2023, 237: 109354.

[8]      鲁思杰, 潮群*, 刘成良. 多通道振动信息融合的柱塞泵异常检测方法. 液压与气动, 2023, 47(7): 28–36.

[9]      Dong Chang, Tao Jianfeng*, Chao Qun*, Yu Honggan, Liu Chengliang. Subsequence Time Series clustering based unsupervised approach for anomaly detection of axial piston pumps. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 3512212.

[10]   Chao Qun, Xu Zi, Tao Jianfeng, Liu Chengliang. Capped piston: a promising design to reduce compressibility effects, pressure ripple and cavitation for high-speed and high-pressure axial piston pumps. Alexandria Engineering Journal, 2023, 62: 509–521.

[11]   Chao Qun, Shao Yuechen, Liu Chengliang, Zhao Jiangao. New analytical leakage models for tribological interfaces in axial piston pumps. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2023, 237(19): 4566–4577

[12]   Chao Qun, Xu Zi, Shao Yuechen, Tao Jianfeng, Liu Chengliang, Ding Shuo. Hybrid model-driven and data-driven approach for the health assessment of axial piston pumps. International Journal of Hydromechatronics, 2023, 6(1): 76–92.  

[13]   Chao Qun, Wei Xiaoliang, Tao Jianfeng, Liu Chengliang, Wang Yuanhang. Cavitation recognition of axial piston pumps in noisy environment based on Grad-CAM visualization technique. CAAI Transactions on Intelligence Technology, 2023, 8(1): 206–218.

[14]   高浩寒, 潮群, 徐孜, 陶建峰, 刘明阳, 刘成良. 小样本下基于孪生神经网络的柱塞泵故障诊断. 北京航空航天大学学报, 2023, 49(1): 155–164.

[15]   Chao Qun, Gao Haohan, Tao Jianfeng, Liu Chengliang, Wang Yuanhang, Zhou Jian. Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network, Frontiers of Mechanical Engineering, 2022, 17(3): 36.

[16]   Chao Qun, Gao Haohan, Tao Jianfeng, Wang Yuanhang, Zhou Jian, Liu Chengliang. Adaptive decision-level fusion strategy for the fault diagnosis of axial piston pumps using multiple channels of vibration signals. Science China Technological Sciences, 2022, 65(2): 470–480.

[17]   Chao Qun, Wei Xiaoliang, Lei Junbo, Tao Jianfeng, Liu Chengliang. Improving accuracy of cavitation severity recognition in axial piston pumps by denoising time-frequency images. Measurement Science and Technology, 2022, 33(5): 055116.

[18]   Chao Qun, Xu Zi, Tao Jianfeng, Liu Chengliang, Zhai Jiang. Cavitation in a high-speed aviation axial piston pump over a wide range of fluid temperatures. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2022, 236(4): 727–737.

[19]   Chao Qun, Zhang Junhui, Xu Bing, Wang Qiannan, Lyu Fei, Li Kun. Integrated slipper retainer mechanism to eliminate slipper wear in high-speed axial piston pumps. Frontiers of Mechanical Engineering, 2022, 17(1): 1.

[20]   Chao Qun, Tao Jianfeng, Liu Chengliang, Li Zhengliang. Development of an analytical model to estimate the churning losses in high-speed axial piston pumps. Frontiers of Mechanical Engineering, 2022, 17(2), 15.

[21]   Chao Qun, Tao Jianfeng, Lei Junbo, Wei Xiaoliang, Liu Chengliang, Wang Yuanhang, Meng Linghui. Fast scaling approach based on cavitation conditions to estimate the speed limitation for axial piston pump design. Frontiers of Mechanical Engineering, 2021, 16(1): 176–185

[22]   Chao Qun. Derivation of the Reynolds equation in cylindrical coordinates applicable to the slipper/swash plate interface in axial piston pumps. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 2021, 235(4): 798–807.

[23]   Zhao Jiangao, Fu Yongling, Wang Mingkang, Fu Jian*, Chao Qun*, Wang Shaopeng, Deng Ming. Experimental research on tribological characteristics of TiAlN coated valve plate in electro-hydrostatic actuator pumps. Tribology International, 2021, 155: 106782.

[24]   Zhao Jiangao, Fu Yongling, Ma Jiming, Fu Jian, Chao Qun, Wang Yan. Review of cylinder block/valve plate interface in axial piston pumps: Theoretical models, experimental investigations, and optimal design. Chinese Journal of Aeronautics, 2021, 34(1): 111–134.

[25]   魏晓良, 潮群*, 陶建峰, 刘成良, 王立尧. 基于频谱分析和卷积神经网络的高速轴向柱塞泵空化故障诊断. 液压与气动, 2021, 45(7): 7–13.

[26]   王立尧, 王远航, 孟苓辉, 李小兵, 潮群*, 陶建峰, 刘成良. 变分模态分解与极限梯度提升树融合的高速轴向柱塞泵空化等级识别. 液压与气动, 2021, 45(5): 62–67.

[27]   魏晓良, 潮群, 陶建峰, 刘成良, 王立尧. 基于LSTMCNN的高速柱塞泵故障诊断. 航空学报,2021, 42(3): 435–445.

[28]   徐孜, 潮群, 高浩寒, 陶建峰, 刘成良, 孟成文. 采用参数化解调的变转速下柱塞泵故障诊断方法. 西安交通大学学报, 2021, 55(10): 19–29.

[29]   Chao Qun, Tao Jianfeng, Wei Xiaoliang, Wang Yuanhang, Meng Linghui, Liu Chengliang. Cavitation intensity recognition for high-speed axial piston pumps using 1-D convolutional neural networks with multi-channel inputs of vibration signals, Alexandria Engineering Journal, 2020, 59(6): 4463–4473.

[30]   Chao Qun, Wei Xiaoliang, Tao Jianfeng, Liu Chengliang. Identification of cavitation intensity for high-speed aviation hydraulic pumps using 2D convolutional neural networks with an input of RGB-based vibration data. Measurement Science and Technology, 2020, 31(10): 105102.

[31]   Chao Qun, Zhang Junhui, Xu Bing, Wang Qiannan, Huang Hsinpu. Test rigs and experimental studies of the slipper bearing in axial piston pumps: a review. Measurement, 2019, 132: 135–149.

[32]   Chao Qun, Zhang Junhui, Xu Bing, Huang Hsinpu, Zhai Jiang. Effects of inclined cylinder ports on gaseous cavitation of high-speed electro-hydrostatic actuator pumps: a numerical study. Engineering Applications of Computational Fluid Mechanics, 2019, 13(1): 245–253.

[33]   Chao Qun, Zhang Junhui, Xu Bing, Huang Hsinpu, Pan Min. A review of high-speed electro-hydrostatic actuator pumps in aerospace applications: challenges and solutions. Journal of Mechanical Design, 2019, 141(5): 050801.

[34]   Chao Qun, Zhang Junhui, Xu Bing, Huang Hsinpu, Zhai Jiang. Centrifugal effects on cavitation in the cylinder chambers for high-speed axial piston pumps. Meccanica, 2019, 54(6): 815–829.

[35]   Zhang Junhui, Chen Yuan, Xu Bing, Chao Qun, Liu Gan. Multi-objective optimization of micron-scale surface textures for the cylinder/valve plate interface in axial piston pumps. Tribology International, 2019, 138: 316–329.

[36]   Zhang Junhui, Chen Yuan, Xu Bing, Pan Min, Chao Qun. Effects of splined shaft bending rigidity on cylinder tilt behaviour for high-speed electro-hydrostatic actuator pumps. Chinese Journal of Aeronautics, 2019, 32(2): 499–512.

[37]   Zhang Junhui, Li Ying, Xu Bing, Pan Min, Chao Qun. Experimental study of an insert and its influence on churning losses in a high-speed electro-hydrostatic actuator pump of an aircraft. Chinese Journal of Aeronautics, 2019, 32(8): 2028–2036.

[38]   Chao Qun, Zhang Junhui, Xu Bing, Wang Qiannan. Discussion on the Reynolds equation for the slipper bearing modeling in axial piston pumps. Tribology International, 2018, 118: 140–147.

[39]   Chao Qun, Zhang Junhui, Xu Bing, Wang Qiannan. Multi-position measurement of oil film thickness within the slipper bearing in axial piston pumps. Measurement, 2018, 122: 66–72.

[40]   Chao Qun, Zhang Junhui, Xu Bing, Shang Yaoxing, Jiao Zongxia, Li Zhihui. Load-sensing pump design to reduce heat generation of electro-hydrostatic actuator systems. Energies, 2018, 11(9): 2266.

[41]   Chao Qun, Zhang Junhui, Xu Bing, Chen Yuan, Ge Yaozheng. Spline design for the cylinder block within a high-speed electro-hydrostatic actuator pump of aircraft. Meccanica, 2018, 53(1–2): 395–411.

[42]   Zhang Junhui, Chao Qun, Xu Bing. Analysis of the cylinder block tilting inertia moment and its effect on the performance of high-speed electro-hydrostatic actuator pumps of aircraft. Chinese Journal of Aeronautics, 2018, 31(1): 169–177.

[43]   Zhang Junhui, Chen Yuan, Xu Bing, Chao Qun, Zhu Yi, Huang Xiaochen. Effect of surface texture on wear reduction of the tilting cylinder and the valve plate for a high-speed electro-hydrostatic actuator pump. Wear, 2018, 414: 68–78.

[44]   Chao Qun, Zhang Junhui, Wang Qiannan, Xu Bing, Chen Yuan. Experimental verification of slipper spinning motion in axial piston pumps. ASME/BATH 2017 Symposium on Fluid Power and Motion Control, USA, 2017

[45]   Zhang Junhui, Chao Qun, Xu Bing, Pan Min, Wang Qiannan, Chen Yuan. Novel three-piston pump design for a slipper test rig. Applied Mathematical Modelling, 2017, 52: 65–81.

[46]   Zhang Junhui, Chao Qun, Wang Qiannan, Xu Bing, Chen Yuan, Li Ying. Experimental investigations of the slipper spin in an axial piston pump. Measurement, 2017, 102: 112–120.

[47]   Xu Bing, Chao Qun, Zhang Junhui, Chen Yuan. Effects of the dimensional and geometrical errors on the cylinder block tilt of a high-speed EHA pump. Meccanica, 2017, 52(10): 2449–2469.

[48]   Zhang Junhui, Chao Qun, Xu Bing, Pan Min, Chen Yuan, Wang Qiannan, Li Ying. Effect of piston-slipper assembly mass difference on the cylinder block tilt in a high-speed electro-hydrostatic actuator pump of aircraft. International Journal of Precision Engineering and Manufacturing, 2017, 18(7): 995–1003.

[49]   Zhang Junhui, Li Ying, Zhang Daqing, Xu Bing, Lv Fei, Chao Qun. A centrifugal force interaction analysis on the piston/cylinder interface leakage of bent-axis type piston pumps. IEEE International Conference on Aircraft Utility Systems, China, 2016.

[50]   Xu Bing, Li Ying, Zhang Junhui, Chao Qun. Modeling and analysis of the churning losses characteristics of swash plate axial piston pump. International Conference on Fluid Power and Mechatronics, China, 2015.

[51]   徐兵, 潮群, 张军辉, 李莹. 基于平衡系数的滑靴优化模型. 浙江大学学报(工学版), 2015, 6: 1009–1014.

 


软件版权登记及专利

发明专利
[1] 轴向柱塞泵健康状态评估预测方法及智能化终端, CN 2024102150416, 公开.
[2] 液压缸内泄漏检测方法及其在TBM撑靴液压缸中的应用, CN 202211716104.3, 公开.
[3] 柱塞泵异常检测方法、装置、电子设备及存储介质, CN 202211644391.1, 公开.
[4] 一种柱塞泵旋转组件绕流损失模拟测量方法,ZL 202110984812.4, 授权

[5] 一种柱塞泵空化程度检测方法、装置及终端, ZL 202010109714.1,授权

[6] 一种基于PICA-VMDHilbert边际谱的轴向柱塞泵空化等级识别方法,ZL 201911259308.7, 授权

[7] 一种高压高速轴向柱塞泵斜盘倾角和振动特性测量装置, CN 201810289213.9, 公开

[8] 补偿三柱塞孔缸体压紧力的静压支承结构, ZL 201611057325.9, 授权


软件版权登记
[1] 盾构装备健康监控与智能运维平台V1.0, 2021SR2088477
[2] 隧道掘进机(TBM)岩渣监测服务软件V1.0, 2023SR1485992

第十九“挑战杯”全国大学生课外学术科技作品竞赛2024年度“揭榜挂帅”专项赛特等奖 指导教师

bat365在线中国官网登录入口2024年度优秀导师奖

上银优秀机械博士论文奖(优秀奖)2021,中国机械工程学会

神农中华农业科技进步一等奖,2021,中国农学会

中国机械工业科学技术特等奖,2020,中国机械工业联合会

全国博士后创新人才支持计划,2020,人力资源和社会保障部

浙江省优秀博士学位论文,2020,浙江省研究生教育学会

上海市“超级博士后”激励计划,2019,上海人力资源和社会保障局