Customization(Multiple times)

       [28] Shuo Wang, Kezhang Hu, Linyu Xia, Tonghai Wu*, Ning Xu. Prior-shape-guided photometric stereo model for 3D damage measurement of worn surfaces[J]. Tribology International, 2025, 201: 110219.(中科院1区,top期刊)

       [27] Shuo Wang, Yishi Chang, Tonghai Wu*, Zhidong Han, Yaguo Lei. Attribute-driven fuzzy fault tree model for adaptive lubricant failure diagnosis [J]. Journal of Dynamics, Monitoring and Diagnostics, 2024, 3(3): 604.

       [26] Pan Dou, Peiping Yang, Peng Zheng, Yaping Jia, Tonghai Wu, Shuo Wang, Min Yu. Ultrasound enabled simultaneous measurement of coating wear depth and lubricant film thickness in a sliding bearing[J]. Measurement, 2025, 240: 115602.

       [25] Ying Du, Yue Zhang, Tao Shao, Yanchao Zhang, Yahui Cui, Shuo Wang. DSU-LSTM-Based trend prediction method for lubricating oil[J]. Lubricants, 2024, 12(8): 289.

       [24] Shuo Wang, Zhidong Han, Hui Wei, Tonghai Wu*,  Junli Zhou. An integrated knowledge and data model for adaptive diagnosis of lubricant conditions[J]. Tribology International, 2024, 199: 109914.(中科院1区,top期刊)

        [23] Yan Pan, Bin Liang, Houde Liu*,  Tonghai Wu, Shuo Wang. Spatial-temporal modeling of oil condition monitoring: A review[J]. Reliability Engineering and System Safety, 2024, 248: 110182.(中科院1区,top期刊)

        [22] Tao Shao, Luning Zhang, Shuo Wang*, Tonghai Wu*, Qinghua Wang, Changfu Han. Fully unsupervised wear anomaly assessment of aero-bearings enhanced by multi-representation learning of deep features[J]. Tribology International, 2024, 196: 109724. (中科院1区,top期刊)      
        [21] Tao Shao, Peiping Yang, Shuo Wang*,Miao Wan, Tonghai Wu*. Wear depth estimation from single 2-D image based on shape from Shading and convolutional neural network hybrid model for in-situ wear assessment [J]. Wear, 2024, 538-539: 205205.  (中科院1区,top期刊)

        [20]  Shuo Wang, Miao Wan, Tonghai Wu*, Zichen Bai, Kunpeng Wang. Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor[J]. Friction, 2024, 12(6): 1194–1213. 中科院1区,top期刊

        [19] Qinghua Wang, Shuo Wang*Tonghai Wu*, Tao Shao, Yue Shu, Thompson Sarkodie-Gyan. Lambertian reflection separation under high  reflectiveness for worn surface reconstruction with insufficient samples [J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 3520310. 中科院2区

       [18] Tao Shao, Shuo Wang, Qinghua Wang, Tonghai Wu*, Zhifu Huang. Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images[J]. Friction, 2024, 12: 1098–1118. 中科院1区,top期刊

       [17]  Shuo Wang, Tao Shao, Tonghai Wu*, Thompson Sarkodie-Gyan,Yaguo Lei. Knowledge-guided convolutional neural network model for similar three-dimensional wear debris identification with small number of samples[J]. Journal of Tribology - Transactions of the ASME, 2023, 145(9): 091105.  (ASME会刊)

       [16] Qinghua Wang, Shuo Wang, Bo Li, Ke Zhu, Tonghai Wu*. In-situ 3D reconstruction of worn surface topography via optimized

 photometric stereo[J]. Measurement, 2022, 190: 110679.(中科院2区
       [15] Shuo Wang, Tonghai Wu*, Kunpeng Wang. Automated 3D ferrograph image analysis for similar particle identification with the

 knowledge-embedded double-CNN model[J]. Wear, 2021, 476: 203696.(中科院1区,top期刊
       [14] Shuo Wang, Tonghai Wu*, Kunpeng Wang, Zhongxiao Peng, NgaimingKwok, Thompson Sarkodie-Gyan. 3-D particle surface

 reconstruction from multi-view 2-D images with structure from motion and shape from shading[J]. IEEE Transactions on Industrial

 Electronics, 2021, 68(2): 1626-1635.中科院1区,top期刊
       [13] Shuo Wang, Tonghai Wu*, Peng Zheng, NgaimingKwok. Optimized CNN model for identifying similar 3D wear particles in few

 samples[J]. Wear, 2020, 460-461: 203477.中科院1区,top期刊
       [12] Shuo Wang, Tonghai Wu*, KunPeng Wang, Thompson Sarkodie-Gyan. Ferrograph Analysis With Improved Particle Segmentation

 and Classification Methods[J]. Journal of Computing and Information Science in Engineering, 2020, 20(2): 021001.(ASME会刊)
       [11] Shuo Wang, Tonghai Wu*, Tao Shao, Zhongxiao Peng. Integrated model of BP neural network and CNN algorithm for automatic wear

 debris classification[J]. Wear, 2019, 426-427: 1761-1770.中科院1区,top期刊
       [10] Shuo Wang, Tonghai Wu*, Lingfeng Yang, Ngaiming Kwok,Thompson Sarkodie-Gyan. Three-dimensional reconstruction of wear

 particle surface based on photometric stereo[J]. Measurement, 2019, 133: 350-360.中科院2区
         [9] Shuo Wang, Tonghai Wu*, Jun Chen, Yu Han, Ting Yao. The generation mechanism and morphological characterization of cutting

 debris based on the finite element method[J]. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering

 Tribology, 2019, 233(1): 205-213. 
         [8] Tonghai Wu*, Yeping Peng, Shuo Wang, Feng Chen, Ngaiming Kwok, Zhongxiao Peng. Morphological feature extraction based on

 multiview images for wear debris analysis in on-line fluid monitoring[J]. Tribology Transactions, 2017, 60(3) : 408-418. 
         [7] Yeping Peng, Tonghai Wu*, Shuo Wang, Ying Du, Ngaiming Kwok, Zhongxiao Peng. A microfluidic device for three-dimensional wear

 debris imaging in on-Line condition monitoring[J]. Proceedings of iMeche, Part J: Journal of Engineering Tribology, 2017, 231(8): 965-974. 
         [6] Yeping Peng, Tonghai Wu*, Shuo Wang, Zhongxiao Peng. Wear state identification using dynamic features of wear debris for on- line 
purpose[J]. Wear, 2017, 376: 1885-1891.中科院1区,top期刊
         [5] Shuo Wang, Tonghai Wu*, Hongkun Wu, Ngaiming Kwok. Modeling wear state evolution using real time wear debris features[J]. 
Tribology Transactions, 2017, 60(6): 1022-1032. 
         [4] 程俊, 王硕, 武通海*, 陈峰. 基于拓展有限元的齿轮点蚀磨粒形态学特征模拟[J]. 机械工程学报, 2016, 15(52): 99-105. 
         [3] Tonghai Wu*, Ying Du, Yang Li, Shuo Wang, Zhinan Zhang. Synthesized multi-station tribo-test system for bio-tribological evaluation 
in vitro[J]. Chinese Journal of Mechanical Engineering, 2016, 29(04): 853-861. 
         [2] Yeping Peng, Tonghai Wu*, Shuo Wang, Zhongxiao Peng. Oxidation wear monitoring based on the color extraction of on-line wear 
debris[J]. Wear, 2015, 332-333: 1151-1157.中科院1区,top期刊
         [1] Yeping Peng, Tonghai Wu*, Shuo Wang, Ngai-ming Kwok, Zhongxiao Peng. Motion-Blurred Particle Image Restoration for On-line
Wear Monitoring[J]. Sensors, 2015, 15(4): 8173-8191.  

Customization(Multiple times)

         [9] 王硕,常亦是,张鹿宁,武通海. Mechanism-driven Model for Adaptive Wear State Diagnosis via Moving Particle Monitoring. 3rd World Congress on Condition Monitoring, 北京, 中国, 2024. (报告)

         [8] 王硕. 重大装备关键部件摩擦学状态监测技术及应用. 2024年全国油液监测技术会议, 武汉, 中国, 2024. (报告)

         [7] 王硕. 机械装备摩擦学状态监测与智能诊断系统. 创新港首届关键卡脖子技术转化研讨会, 西安, 中国, 2024. (报告)

         [6] 王硕. 机械装备摩擦学状态全寿命监测技术及应用. 2024年全国青年摩擦学学术会议, 青岛, 中国, 2024. (报告)

         [5] 王硕. 机械装备磨损状态智能感知技术. 2023中国工业设备智能运维大会, 石家庄, 中国, 2023. (报告)

         [4] 王硕, 武通海*, 陈康, 刘京. 面向谐波减速器的磨损状态演变监测方法研究[C]. 2022全国设备监测诊断与维护学术会议, 太原, 中国, 2022. (报告)

         [3] Shuo Wang, Tonghai Wu*, Kunpeng Wang. Automated 3D ferrograph image analysis for similar particle identification with the knowledge-embedded double-CNN model[C]. 23rd International Conference on Wear of Materials, Banff, Canada, 2021. (Poster)
         [2] Shuo Wang, Tonghai Wu*, Tao Shao, Zhongxiao Peng. Integrated model of BP neural network and CNN algorithm for automatic wear
debris classification[C]. 22nd International Conference on Wear of Materials, Miami, USA, 2019. (Oral)
         [1] Shuo Wang, Tonghai Wu*, Lingfeng Yang. Three-dimensional feature extraction of wear particle based on multi-objects tracking and 
recognition[C]. 6st World Tribology Congress, Beijing, China, 2017. (Oral)

Blank8

         [2] GB/T 42983.4-2023. 工业机器人 运行维护 第4部分: 预测性维护 [S].

         [1] GB/T 42983.1-2023. 工业机器人 运行维护 第1部分: 在线监测 [S].

Blank7

       共申请国家发明专利25项,已授权12项,完成科技成果转化4项(专利转化超100万元)。                

 

       [25] 王硕夏林豫,邵涛,武通海基于多模态大模型的小样本旋转设备损伤辨识方法及系统.申请号:2024118018821. (申请日: 2024.12.06)

       [24] 王硕张鹿宁,邵涛,窦潘,武通海,马婕妤一种磨损表面损伤区域高光修复方法及系统.申请号:202411250448.9. (申请日: 2024.09.06)

       [23] 王硕,常亦是,夏林豫,杨培平,武通海一种残缺磨粒类型迁移辨识方法及相关设备.申请号:202411045858.X. (申请日: 2024.07.31)

       [22] 武通海,高心如,夏永刚,窦潘,赵文卓,王硕气穴情况下滚子轴承油膜厚度超声测量补偿方法及其系统.申请号:202410849611.7. (申请日: 2024.06.27)

       [21] 武通海,李亚雨,窦潘,张渝敏,赵文卓,王硕一种圆柱滚子轴承接触区反射信号提取方法及系统.申请号:202410849622.5. (申请日: 2024.06.27)

       [20] 武通海,张鹿宁,王青华,王硕一种磨损表面严重度评估方法、系统、介质及设备.申请号:202410849606.6. (申请日: 2024.06.27)

       [19] 武通海,夏永刚,吴泉忠,窦潘,王硕一种超声测量中参考信号的在机标定方法及系统.申请号:202410849612.1. (申请日: 2024.06.27)

       [18] 武通海,万淼,王硕,窦潘,雷亚国.一种基于磨粒特征优选的磨损状态精准辨识方法.申请号:2023110429421. (申请日: 2023.08.17)

       [17] 武通海,胡珂章,王硕王青华,邵涛.  融合全光源图像的磨损表面形貌光度立体重建方法及系统. 申请号: 202310352849.4.(申请日:2023.04.04)

       [16] Shuo Wang, Jing Liu, Tonghai Wu, Miao Wan, Yaguo Lei, Junyi Cao. Method and system for enhancing online reflected light

               ferrograph image. US, 18154760. (申请日:2023.01.13)

       [15] 王硕, 王青华, 武通海, 邵涛. 一种联合低频形状和高频法向量形貌重建方法. 申请号: 202211654274.3. (申请日:2022.12.22)

       [14] 王硕,万淼,武通海,雷亚国,曹军义.一种基于改进Mask-RCNN网络的磨粒链分割方法及系统.申请号:202211020066.8. (申请日: 2022.08.24)
       [13] 王硕, 邵涛, 武通海, 王青华.  基于多注意力机制的磨损表面损伤深度估计方法及系统. 专利号:202210689847.X. (授权日: 2024.03.01)
       [12] 武通海, 刘京, 王硕, 万淼. 一种基于时空域联合信息的运动磨粒检测跟踪方法及系统. 专利号:202210662548.7. (授权日: 2024.02.23)
       [11] 王硕, 刘京, 武通海, 万淼, 雷亚国, 曹军义. 一种在线铁谱反射光图像增强方法及系统. 申请号: 202210550282.7. (授权日: 2024.06.28)
       [10] 武通海, 韩志栋, 潘燕, 敬运腾, 王硕, 雷亚国, 曹军义. 一种基于多指标监测的油液失效诊断溯源方法及系统. 申请号:202210662547.2. (申请日:
2022.06.13)
         [9] 武通海, 胡珂章, 王青华, 王硕. 一种融合先验引导和域适应的磨损表面朗伯反射分离方法. 专利号: 202111508929.1. (授权日: 2024.01.09)
         [8] 武通海, 王硕, 郑鹏, 王昆鹏, 曹军义, 雷亚国. 一种基于知识引导CNN的小样本相似磨粒辨识方法. 专利号: 202010584092.8.(授权日: 2022.10.28)
         [7] 武通海, 王昆鹏, 王硕, 杨羚烽. 一种基于条件生成对抗网络的磨粒形貌数据库创建方法.专利号: 201910489382.1. (授权日: 2021.4.27)
         [6] 武通海, 朱可, 王昆鹏, 王硕. 一种运动磨粒多表面三维形貌的获取方法.专利号: 201910185038.3. (授权日: 2021.5.4)
         [5] 武通海, 杨羚烽, 王硕. 面向在线铁谱图像磨粒识别的局部自适应阈值分割方法.专利号: 201810119775.9. (授权日: 2020.6.25)
         [4] 武通海, 邵涛, 王硕, 陈峰. 一种多纹理特征融合的磨粒类型自动识别方法. 专利号: 201810118514.5. (授权日: 2020.3.24)
         [3] 武通海, 邵涛, 王硕, 陈峰. 一种基于颜色主分量提取的磨粒材质自动识别方法. 专利号: 201810162476.3. (授权日: 2021.1.19)
         [2] 武通海, 王硕, 霍彦文, 杨羚烽. 一种基于光度立体视觉的多个磨粒三维形貌同步获取方法. 专利号: 201710794153.1. (授权日: 2019.9.4)
         [1] 武通海, 徐金平, 吴虹堃, 王硕, 李小芳 . 一种风电变速器的润滑油在线监测方法. 专利号: 201510141574.5. (授权日:2017.11.03)

Customization(Multiple times)

         [3] 王硕,张鹿宁,邵涛,武通海,窦潘,基于机器视觉的航发轴承故检评估与图谱辅助决策系统.软件著作权,登记号:2024SR1918398. 开发完成日: 2024.11.27

         [2] 王硕,万淼,窦潘,武通海,运动磨粒图像分析系统.软件著作权,登记号:2023SR1256441. 开发完成日: 2022.12.30

         [1] 武通海,万淼,王普健,王硕,润滑油磨粒图像监测系统.软件著作权,登记号:2022SR1377747. 开发完成日: 2022.03.15