科研成果

        [37]   Wei Han, Bin Yang, Yaguo Lei, Na Lu, Naipeng Li, Shuo Wang, Chi-Guhn Lee. Predictive maintenance decision-making framework under stochastic imperfect maintenance effects[J]. Mechanical Systems and Signal Processing, 2026, 257: 114567.(中科院1区，top期刊)

        [36]   Shuo Wang, Linyu Xia, Yaguo Lei, Yishi Chang, Tonghai Wu*, Tingting Li, Xudong Zhang, Ke Feng. Intelligent wear state diagnosis: Wear rate and mechanism integrated model based on multi-dimensional particle informatics[J]. Tribology International, 2026, 224: 112293.(中科院1区，top期刊)

        [35]   Xiaolong Yang, Jingxuan Han, Gang Wan, Fengdi Zhu, Chuangji Qin, Ning Xu, Shuo Wang*. Unsupervised segmentation of wear surface defects in hydroturbine bearing pads guided by local anomaly scores[J]. Lubricants, 2026, 14(5), 202.

       [34]   周仙丽，常亦是，王硕*.融合分水岭与超像素的磨粒链高精度分割方法[J]. 润滑与密封, 2026.

       [33]  王硕，夏林豫，韩志栋，敬运腾，武通海，曹军义. 云边协同的润滑油智能监测系统设计与应用[J]，数字化转型，2025，6(2)：29-41.

       [32]  Chan Xu, Qiuxia Fan, Qianqian Zhang, Yunqi Tong, Shuo Wang, Tonghai Wu. Vibration-Based Wear Evolution Characterisation of Lubricated Rolling-Sliding Contact[J]. Lubricants, 2025, 13(2): 78.

       [31] Qinghua Wang, Shuo Wang*, Luning Zhang, Yayu Li, Chenyang Jia,Tonghai Wu*. Mechanism-guided wear severity assessment of worn surfaces with multiple damages[J]. Wear, 2025, 571: 205875.(中科院1区，top期刊)
             [30] Tao Shao, Luning Zhang, Shuo Wang*,Qinghua Wang, Linyu Xia, Tonghai Wu*. Structural region-induced inpainting for highlight removal in microscopic damage measurement of metal pairs[J]. Optics and Lasers in Engineering, 2025, 186: 108831.(中科院2区)

       [29] Shuo Wang,Yishi Chang, Hui Wei, Miao Wan, Tonghai Wu*, Ying Du. An integrated mechanism and data model for adaptive wear state diagnosis via moving wear particles[J]. Wear, 2025, 564-565: 205722.(中科院1区，top期刊)

       [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汇刊)

       [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汇刊）

       [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- linepurpose[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 evaluationin 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 weardebris[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.  

         [12] 王硕. 高端装备磨损状态演变监测及数字孪生建模. 2025年中国机械工程学会工业大数据与智能系统分会学术年会暨第八届大数据驱动的智能制造学术会议, 宜昌, 中国, 2025. (分论坛报告)

         [11] 王硕. 机械装备磨损状态演变监测及数字孪生建模. 第六届中国振动工程学会故障诊断专业委员会青年论坛, 马鞍山, 中国, 2025. (大会主题报告)

         [10] 王硕. 机械装备磨损状态演变监测及数字孪生建模. 中国航空学会可靠性工程分会第十三届学术年会, 马鞍山, 中国, 2025. (特邀报告，召集“装备健康状态监测与智能运维分论坛”)

         [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)

         [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].

       [32] 王硕，韩京轩，雷亚国，张鹿宁，武通海．知识图谱与大模型联动的滑动轴承表面损伤程度评估方法．申请号：2026107623932. (申请日: 2026.05.29)

       [31] 王硕，雷亚国，翟宇旸，任芳，张锦霖，武通海．基于磨粒监测与物理约束的装备剩余寿命预测方法及系统．申请号：2026107473371. (申请日: 2026.05.28)

       [30] 王硕，夏林豫，王青华，雷亚国，武通海．知识图谱与大语言模型联合的轴承智能维护决策方法．申请号：2026103310252. (申请日: 2026.03.18)

       [29] 王硕，王海洋，武通海，贾晨阳，贾亚萍，杨培平．超声数模融合的可倾瓦块推力轴承状态监测方法及系统．申请号：2026101999294. (申请日: 2026.02.11)

       [28] 王硕，韩京轩，张鹿宁，武通海，雷亚国．一种推力轴承表面损伤大模型检测方法及系统．申请号：2026101453410. (申请日: 2026.02.02)

       [27] 王硕，王青华，杨享泰，雷亚国，武通海．联合磨粒和振动监测的表面磨损体积时空分布预测方法．申请号：2025110033692. (申请日: 2025.07.21)

       [26] 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．专利号：202411801882.1. (授权日: 2026.03.17)

       [25] 武通海，高心如，张鹿宁，王硕，窦潘．一种基于故障树的推力轴承失效模式风险评估方法及系统．专利号：202411941112.7. (授权日: 2026.03.17)

       [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．专利号：2023110429421.1. (授权日: 2025.09.05)

       [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. 专利号: 202310352849.4.(授权日：2025.08.12)

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

               ferrograph image. 专利号：US12406473B2. (授权日：2025.09.02，美国专利)

       [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. (授权日：2025.08.12)

       [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．专利号：202211020066.8. (授权日: 2025.07.22)
         [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）

        [4] 王硕，张锦霖，夏林豫，韩京轩，武通海，多模态大模型驱动的磨粒类型智能辨识软件．软件著作权，登记号：2026SR0455749. 开发完成日: 2026.03.18

         [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