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彭业萍      助理教授

性别:

邮箱: yeping.peng@szu.edu.cn

办公室: 机电楼s627室

人才称号:

最终学位: 博士

办公电话: 0755-86950053

导师资格: 硕士生导师

研究领域:

机械与生物摩擦学系统磨损状态监测、磨粒三维重建与形态表征、图像处理与机器视觉检测技术

主讲本科课程:

控制系统仿真

主讲研究生课程:

计算机视觉、数字信号分析与处理

教育背景:

2014 – 2017,西安交通大学机械工程学院博士学位
2014 – 2015,澳大利亚新南威尔士大学机械与制造工程学院联合培养博士
2011 – 2014,西安交通大学机械工程学院硕士学位
2007 – 2011,哈尔滨工程大学机电工程学院学士学位

工作履历:

2017-至今,深圳大学机电与控制工程学院助理教授

主持项目:

一、省部级
[1] 广东省自然科学基金博士启动-纵向协同项目:融合多元磨粒特征信息的风电变速器磨损状态在线辨识方法(项目编号:2018A030310522),2018.01-2020.12,在研

二、市级
[1] 深圳市科技计划基础研究(自由探索)项目:面向航空发动机健康评估的轴承磨损状态演变规律研究(项目编号:JCYJ20170818100522101),2018.01-2020.03,在研

三、其他
[1] 深圳大学新引进教师科研启动项目:运动磨粒的三维图像重构及智能识别方法(项目编号:2017032),2017.06-2019.05,在研

代表期刊论文:

一、SCI期刊论文
[17] Yeping Peng, Songbo Ruan, Guangzhong Cao*, Sudan Huang, Ngaiming Kwok, Shengxi Zhou. Automated product boundary defect detection based on image moment feature anomaly[J]. IEEE Access, 2019, DOI: 10.1109/ACCESS.2019.2911358.
[16] Yeping Peng*, Haiyan Shi, Hongkun Wu, Ruowei Li, Ngaiming Kwok, San Chi Liu, Shilong Liu, Md Arifur Rahnam. An optimum shift-and-weighted brightness mapping for low-illumination image restoration[J]. Imaging Science Journal, 2019, DOI: 10.1080/13682 199.2019.1592891.
[15] Hongkun Wu*, Ruowei Li, Ngaiming Kwok, Yeping Peng, Tonghai Wu, Zhongxiao Peng. Restoration of low-informative image for robust debris shape measurement in on-line wear debris monitoring[J]. Mechanical Systems and Signal Processing, 2019, 114: 539-555.
[14] Sudan Huang, Guangzhong Cao*, Yeping Peng, Chao Wu, Deliang Liang, Jiangbiao He. Design and analysis of a long-stroke planar switched reluctance motor for positioning applications[J]. IEEE Access, 2019, 7: 22976-22987.
[13] Guangzhong Cao, Songbo Ruan, Yeping Peng*, Sudan Huang, Ngaiming Kwok. Large-complex-surface defect detection by hybrid gradient threshold segmentation and image registration[J]. IEEE Access, 2018, 6: 36235-36246.
[12] Haiyan Shi, Shilong Liu, Hongkun Wu, Ruowei Li, Sanchi Liu, Ngaiming Kwok, Yeping Peng*. Oscillatory particle swarm optimizer[J]. Applied Soft Computing, 2018, 73: 316-327.
[11] Yeping Peng, Tonghai Wu, Guangzhong Cao*, et al. A hybrid search-tree discriminant technique for multivariate wear debris classification[J]. Wear, 2017, 392-393: 152-158.
[10] Yeping Peng, Tonghai Wu*, Shuo Wang, et al. Wear state identification using dynamic features of wear debris for online purpose[J]. Wear, 2017, 376-377: 1885-1891.
[9] Yeping Peng, Tonghai Wu*, Shuo Wang, et al. A microfluidic device for three-dimensional wear debris imaging in on-line condition monitoring[J]. Proceedings of the Institution of Mechanical Engineers, Part J- Journal of Engineering Tribology, 2017, 231(8): 965-974.
[8] Tonghai Wu*, Yeping Peng, Shuo Wang, et al. Morphological feature extraction based on multi-view images for wear debris analysis in on-line fluid monitoring[J]. Tribology Transactions, 2017, 60(3): 408-418.
[7] Yeping Peng, Tonghai Wu*, Wang Shuo, et al. Oxidation wear monitoring based on the color extraction of on-line wear debris[J]. Wear, 2015, 332-333: 1151~1157.  
[6] Yeping Peng, Tonghai Wu*, Wang Shuo, et al. Motion-blurred particle image restoration for on-line wear monitoring[J]. Sensors, 2015, 15(4): 8173~8191.
[5] Tonghai Wu*, Yeping Peng, Hongkun Wu, et al. Full-life dynamic identification of wear state based on on-line wear debris image features[J]. Mechanical Systems and Signal Processing, 2014, 42(1-2): 404-414.
[4] Tonghai Wu*, Yeping Peng, Chenxing Sheng, et al. Intelligent identification of wear mechanism via on-line ferrograph Images[J]. Chinese Journal of Mechanical Engineering, 2014, 27(2): 411-417.
[3] Tonghai Wu*, Yeping Peng, Ying Du, et al. Dimensional description of on-line wear debris images for wear characterization[J]. Chinese Journal of Mechanical Engineering, 2014, 27(6): 1280-1286.
[2] Hongkun Wu, Tonghai Wu*, Yeping Peng, et al. Watershed-based morphological separation of wear debris chains for on-line ferrograph analysis[J]. Tribology Letters, 2013, 53(2).
[1] Tonghai Wu*, Junqun Wang, Yeping Peng, et al. Description of wear debris from on-line ferrograph images by their statistical color[J]. Tribology Transactions, 2012, 55(5): 606-14.

二、中文核心期刊论文
[3] 钱秋阳, 曹广忠, 彭业萍*, 钟祥永. EtherCAT无线网关设计与实现[J]. 自动化仪表, 2018, 39(12): 48-51+59.
[2] 李世雄, 曹广忠, 李庆, 彭业萍*, 吕洁印. 基于锚点的边缘检测优化算法研究[J]. 电子测量与仪器学报, 2018, 32(11): 9-16.
[1] 武通海, 彭业萍, 盛晨兴, 吴教义. 基于在线铁谱图像的磨损机理智能辨识[J]. 机械工程学报, 2014, (05): 212-212.

代表会议论文:

[2] Ngaiming Kwok, Haiyan Shi, Yeping Peng, Hongkun Wu, Ruowei Li, Shilong Liu, Md Arifur Rahman. Single-Scale Center-Surround Retinex Based Restoration of Low-illumination Images with Edge Enhancement[C]. 9th International Conference on Graphic and Image Processing (ICGIP), 2017, Qingdao, China. (SPIE)
[1] Songbo Ruan, Yeping Peng, Guangzhong Cao*, Sudan Huang, Xiangyong Zhong. Man-machine interaction for an unmanned tower crane using wireless multi-controller[C]. International Conference on Intelligent Robotics and Applications (ICIRA), 2017, Lecture Notes in Computer Science, 10462: 381-392. (Springer, Cham)

代表专利:

[9] 彭业萍, 蔡俊豪, 曹广忠, 曹树鹏. 润滑油磨粒在线监测方法、终端及存储介质[P]. 申请号: 201810771554.X.
[8] 武通海, 彭业萍, 吴虹堃, 程俊. 一种基于数字视频的快速铁谱分析方法[P]. 专利号: ZL201310343023.8.
[7] 武通海, 彭业萍, 吴虹堃, 谢友柏. 一种基于视频获取的润滑油磨粒在线监测与分析方法[P]. 专利号: ZL201310141313.4.
[6] 武通海, 彭业萍, 张小刚, 张乐. 基于数字图像处理的磨损原位测量装置及方法[P]. 专利号: ZL201210076357.9.
[5] 武通海, 吴虹堃, 彭业萍, 谢友柏. 一种基于视频获取的润滑油磨粒在线监测探头[P]. 专利号: ZL201310141314.9.
[4] 武通海, 吴虹堃, 彭业萍. 面向在线铁谱图像自动识别的磨粒链自适应分割方法[P]. 专利号: ZL201310675708.2.
[3] 武通海, 王龙鑫, 彭业萍, 王硕. 一种基于磨粒图像颜色提取的在线氧化磨损状态监测方法[P]. 申请号: 201610052551.1.
[2] 武通海, 张小刚, 张乐, 彭业萍, 张亚丽. 基于电导率测量的在线润滑油微量水分传感器[P]. 专利号: ZL201210084173.7.
[1] 武通海, 张小刚, 张乐, 彭业萍, 张亚丽. 基于电导率测量的直插式润滑油微量水分传感器[P]. 专利号: ZL201210085008.3.

获得荣誉:

1.武通海,陈渭,彭业萍,等. 重大机械设备磨损状态在线监测系统,第十七届中国国际工业博览会高校展区优秀展品一等奖,中国国际工业博览会高校展区组委会教育部科技发展中心, 2015.
2.彭业萍. 2015年全国青年摩擦学学术会议优秀论文奖,中国机械工程学会摩擦学分会,2015.