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教育背景 2012.01~2015.07, 香港城市大学,系统工程与工程管理专业, 博士 2007.09~2010.06, 电子科技大学,机械电子工程专业, 硕士 2003.09~2007.07, 电子科技大,机械设计制造及其自动化专业, 学士 工作经历 2018.10~~~至今 上海交通大学,工业工程与管理系,长聘教轨副教授、博士研究生导师 出访及挂职经历 2020年1月4日,智能制造“智设计,造未来”论坛,上海 2019年12月23~24日, 机械系统与振动国家重点实验室年会, 广东东莞 2019年11月22~24日,全国质量可靠性与PHM高峰论坛,浙江温州 2019年11月18~23日,2019年中国先进技术转化应用大赛总决赛,江西南昌 2019年11月9~12日,第十三届全国振动理论及应用学术会议,陕西西安 2019年10月25~28日,2019 Prognostics and System Health Management Conference (PHM-2019 Chongqing), Qingdao, China 2019年10月20~24日,Workshop in Machine Condition Monitoring, School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, Australia 2019年10月9~12日,第18届国际制造会议(18th International Manufacturing Conference,IMCC 2019),沈阳。 2019年9月9日~11日,2019年中国先进技术转化应用大赛半决赛(智能制造领域),江西新余北 2019年9月8日~9日,变革性技术研讨会,大连理工大学 2019年8月12日~14日,2019中国工业互联网大会,杭州 2019年7月5日~6日,2019 第九届质量科学与可靠性技术国际研讨会 2019年7月4日~5日,2019可靠性应用技术国际论坛,中国汽车工程协会 2019年6月25日~28日,The Fifth International Conference on the Interface between Statistics and Engineering, Seoul, South Korea 2019年5月24日~26日,第一届机械工程赣江学术论坛会议 2019年5日22日~月23日,轨道交通控制与安全国家重点实验室联合研讨会,北京交通大学 2019年5月3日~5月4日,Keynote Seminar on the Efficiency and Performance Engineering (CEPE) 2019 and the Launch of CEPE-CHINA 2018年8月10日~8月12日,2018年全国设备监测诊断与维护会议 2018年7月19日~7月21日,轨道交通控制与安全国家重点实验室联合研讨会,北京交通大学 2018年5月16日,香港城市大学和马来西亚Universiti Tunku Abdul Rahman联合研讨会 2018年4月23日,上海交通大学机械与动力学院 2018年4月8日~10日,苏州大学轨道与交通学院 2018年3月20日至21日,Hong Kong International Convention and Exhibition Centre,2018 Asia Pacific Rail Conference 2018年3月18日至19日,四川大学,建筑与环境学院 2017年12月7日至12月9日, 北京交通大学轨道交通控制与安全国家重点实验室 2017年11月30日至12月1日,高丽大学工业工程系 2017年9月25日,澳门大学工程院电机系 2017年3月19日至20日,南方科技大学力学与航空系 2016年9月27日至28日,中国汽车工业协会第二届汽车可靠性技术研讨会 2016年3月18日至19日,南方科技大学机械与能源系 2015年12月9日至10日,Workshop in Risk, Reliability, and Data Science, Organized by City University of Hong Kong 科研项目 *上海交通大学海外一流大学学术交流基金(2019年上海交通大学-新南威尔士大学)(2020/1~2021/1),上交负责人 *航天智控有限公司委托项目 (2019/12-2020/011),负责人 *上海交通大学长聘教轨副教授科研启动经费 (2018/10~2021/10),负责人 *晟碟信息科技(上海)有限公司委托项目 (2019/01~至今),负责人 *国家自然科学基金面上项目:变工况下旋转机械装备故障特征统计量及健康指数理论基础研究 (2020/01~2023/12) ,负责人 *Theme-based Research Scheme, Hong Kong: Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems (2016/01~2020/12, 40,840,000 HKD, Kwok L. Tsui首席教授为项目第一主持人),学术骨干 *General Research Fund (GRF), Hong Kong: Reliability and Degradation Modeling for Rechargeable Battery (2018/01~2020/12),第二负责人 *CityU Strategic Research Grant: Remaining Useful Life Modeling and Prediction of Rechargeable Batteries (2016/09~2017/09),第二负责人 代表性论文专著 围绕产品和设备健康监测、故障诊断及寿命预测理论及应用基础研究,提出了系统健康监测与管理框架、广义谱峭度理论、广义稀疏测度数学框架、基于布朗运动的广义状态空间寿命预测理论、广义几何布朗运动寿命预测理论、动态贝叶斯小波变换数学框架等新理论和新方法,研究成果主要发表在Mechanical Systems and Signal Processing、IEEE Transactions、ASME Transactions等国际权威期刊上,论文被引2500多次,12篇论文入选ESI高被引,H-Index27。 十篇代表性论文如下 [J1]导读语:统计学的峭度(kurtosis)、热力学的熵(Entropy)、金融的基尼指数(Gini index)以及信号处理的平滑指数(Smoothness index)为世界知名的稀疏测度,它们作为目标函数被广泛地使用在多个研究领域中。但这些稀疏测度间的数学关系尚不清楚,也没有统一的数学框架。本文从信号分解的角度把上述稀疏测度分解为标准化平方包络权重和这一数学框架,从而为稀疏测度提供了广义的数学框架,只要能为数学框架设计一种新权重就可以得到世上独一无二的新统计量。本文同时也介绍了在状态监测中如何设计权重来量化非平稳循环脉冲信号的循环平稳性。内容详见:Dong Wang, Zhike Peng, Lifeng Xi, The Sum of Weighted Normalized Square Envelope: A Unified Framework for Kurtosis, Negative Entropy, Gini Index and Smoothness Index for Machine Health Monitoring, Mechanical Systems and Signal Processing, 140 (2020), 106725. [J2]导读语:谱峭度(Spectral Kurtosis)是量化非平稳循环脉冲信号脉冲性的经典理论,在旋转装备早期故障诊断方面起着重要的理论支撑作用。过去大部分研究停留在谱峭度的应用阶段,并没发现谱峭度的本质特征。本文从信号分解的角度阐述了谱峭度的本质为利用L2/L1范数比量化平方包络信号,进一步推导出了广义谱峭度的数学定义(Lp/Lq范数比),并且证明了麻省理工Iman Soltani Bozchalooi博士等人提出的平滑指数(Smoothness index)为谱Lp/Lq范数比当p=1,q=0时的特例,从而建立了谱峭度与平滑指数间的数学桥梁。此外,推导了当复高斯噪声作为广义谱峭度的输入时,对应的广义谱峭度解析表达式。内容详见:Dong Wang, Spectral L2/L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals, Mechanical Systems and Signal Processing, 104 (2018) 290-293. [J3]导读语:基于几何布朗运动的寿命预测模型为预测学的经典理论,过去研究通过贝叶斯原理得到了基于几何布朗运动的寿命预测模型后验参数更新解析解,可实现在线寿命预测。但是此方法假设贝叶斯推理中的似然函数相邻时间点的布朗运动漂移系数相等,忽略了相邻时间点漂移系数对于似然函数的影响。本文针对经典理论中存在的问题,提出了随机游走积分几何布朗运动寿命预测理论,推导出了寿命预测模型后验参数更新广义解析解。通过交叉验证选择合适的参数,可以得到更精确的寿命预测值。内容详见:Dong Wang, Kwok-Leung Tsui, Statistical modeling of bearing degradation signals, IEEE Transactions on Reliability, 66 (2017) 1331 - 1344.。 [J4]导读语:布朗运动漂移系数状态空间模型理论在装备寿命预测领域中对于布朗运动漂移系数实时动态贝叶斯更新起着重要的理论支撑作用,并被国际众多学者直接应用于多种国际权威期刊所刊研究成果中。本文发现漂移系数状态空间模型在漂移系数预测阶段的预测估计等于更新阶段的后验估计,使得漂移系数的后验估计为有偏估计,从而降低了剩余寿命预测的准确度。针对漂移系数状态空间模型理论中的有偏估计问题,提出了多状态布朗运动漂移系数状态空间模型理论,通过更新阶段漂移系数多状态预测使得寿命预测领域布朗运动漂移系数估计为无偏估计,从而可以高效、精准地实施寿命预测,内容详见:Dong Wang, Kwok-Leung Tsui, Brownian motion with adaptive drift for remaining useful life prediction: revisited, Mechanical Systems and Signal Processing, 99 (2018) 691-701. [J5]导读语:在状态监测和故障诊断领域,当旋转机械装备发生早期故障时会产生非平稳循环脉冲信号,此信号具有脉冲性和循环平稳性的两个特点。过去研究从实验验证的角度发现了稀疏测度对于脉冲性噪声的敏感性,但没从理论上解释稀疏测度对脉冲性噪声敏感的原因。本文通过对非平稳循环脉冲信号建模以及理论上研究了稀疏测度量化非平稳循环脉冲信号的过程,最终发现了稀疏测度对脉冲性噪声敏感的根本原因,并且还从理论上解释了稀疏测度随旋转机械转速变化的原因。内容详见:Dong Wang, Zhike Peng, Lifeng Xi, Theoretical and Experimental Investigations on Spectral Lp/Lq Norm Ratio and Spectral Gini Index for Rotating Machine Health Monitoring, IEEE Transactions on Automation Science and Engineering. [J6]导读语:由于小波变换可以表征信号的局部特性,因此被广泛使用在状态监测和故障诊断中来提取局部故障引起的重复瞬态信号。在小波变换的使用中,小波最优参数选择至关重要。本文引入了小波参数分布这一新想法,把动态贝叶斯推理引入到小波变换中来迭代优化小波参数分布,最终提出了动态贝叶斯小波变换这一框架。同时也介绍了如何利用各种快速滤波算法来初始化合适的小波参数分布,大大提升了迭代优化速率。内容详见:Dong Wang, Kwok-Leung Tsui, Dynamic Bayesian Wavelet Transform: New Methodology for Extraction of Repetitive Transients, Mechanical Systems and Signal Processing, 88 (2017) 137-144. [J7]导读语:设备典型的退化过程包括两个阶段。在第一阶段,设备处于健康状况呈平稳趋势。在第二阶段,设备的健康状况呈指数退化趋势。为了对这一退化过程进行解析建模,提出了两种新的混合效应模型。两种混合效应模型都能同时模拟退化过程的第一阶段和第二阶段。两种混合效应模型的主要区别在于,两种混合效应模型分别考虑了乘法正态随机误差和乘法布朗运动误差。因此,在实时状态监测数据可用的情况下,利用贝叶斯定理可从两个混合效应模型中推导出贝叶斯参数的闭合形式。结果表明,在轴承剩余寿命预测中,带乘法布朗运动误差的混合效应模型比带乘法正态随机误差的混合效应模型具有更高的预测精度。内容详见:Dong Wang, Kwok-Leung Tsui, Two novel mixed effects models for prognostics of rolling element bearings, Mechanical Systems and Signal Processing, 99 (2018) 1-13. [J8]导读语:谱峭度(Spectral Kurtosis)的基本思想是利用峭度来量化由带通滤波和希尔伯特变换构造的复数。在我们之前的研究中(Mech. Syst. Signal Pr.,Vol. 104(2018)290–293),从数学上证明了谱峭度可以分解为平方包络和平方L2/L1范数比。在此基础上,定义了谱L2/L1范数比,并将谱L2/L1范数比推广到谱Lp/Lq范数比。此外,当p = 1和q = 0时,从数学上证明了谱L1/L0范数比是谱平滑指数的倒数。与峭度相似,平滑指数(J. Sound Vib.,Vol. 308(2007)246–267)也被认为是表征重复瞬变信号的另一个重要统计参数。从而建立了谱峭度与谱平滑指数间的数学关系。本文正式定义了谱Gini指数,并从数学上阐明了它与谱L2/L1范数比的关系。并且,还计算了复高斯噪声的谱基尼指数,以便对谱基尼指数进行标准化和重新定义。再次,揭示了谱峭度、谱L2/L1范数比、谱Lp/Lq范数比、谱平滑指数与谱基尼指数之间的关系。最后,从数学上证明了谱峭度、谱L2/L1范数比、谱平滑指数和谱基尼指数的倒数都是平方包络最大值的单调递增函数,这表明谱峭度、谱L2/L1范数比,谱平滑指数和谱基尼指数的倒数受异常值的影响。内容详见:Dong Wang, Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients, Mechanical Systems and Signal Processing, 108C (2018) pp. 360-368. [J9]导读语:轴承性能退化评估旨在通过轴承健康指标来评估轴承的当前健康状况。近年来,人们提出了许多基于信号处理和数据挖掘的方法来构建轴承健康指标。然而,这些轴承健康指标的上下限并没有从理论上计算出来,它们强烈依赖于包括正常和故障数据在内的历史轴承数据。此外,大多数健康指标都是有量纲的,这意味着这些健康指标容易受到各种运行条件的影响。本文基于平方包络分析原理,对可加性高斯噪声情况下轴承性能退化评估进行了理论研究,包括平方包络分布的建立、广义无量纲轴承健康指标的构造和数学计算广义无量纲轴承健康指标的上下界。结果表明,平方包络服从非中心卡方分布,广义无量纲健康指标的上下界可以用数学方法确定。此外,在轴承性能退化过程中,广义无量纲健康指标对轴承早期缺陷非常敏感。内容详见:Dong Wang, Kwok-Leung Tsui, Theoretical investigation of the upper and lower bounds of a generalized dimensionless bearing health indicator, Mechanical Systems and Signal Processing, 98C (2018) 890-901. [J10]导读语:可充电电池成为最广泛使用的储能设备之一。放电速率和温度是影响电池放电容量衰减的两个关键因素。不同工况下电池放电容量衰减建模仍然是一个热门研究方向。本文提出了两种新的电池放电容量衰减模型。在第一个模型中,提出了容量衰减与放电速率之间的关系。第二个模型提出了容量衰减与温度的关系。然后,分别设计了两种贝叶斯动态更新过程,将单个运行电池的在线数据合并到两个电池衰减模型中。结果表明,所提出的两种新模型能准确预测不同放电速率和不同温度下的电池健康状态。内容详见:Dong Wang, Jin-zhen Kong, Fangfang Yang, Yang Zhao, Kwok-Leung Tsui, Battery Prognostics at Different Operating Conditions, Measurement, 151 (2020) 107182. 教学工作 *本科生班主任 *上海交通大学本科生授课情况 2018-2019,第二学期《服务管理》。 *香港城市大学本科生和硕士生授课情况 2014, Semester B, JC4059, Advanced monitoring and inspection technology. 2014, Semester B, SEEM 6014, The use of advanced condition monitoring methods to determine bearing localized faults via the Smart Asset Maintenance System (SAMS), 2013, Semester A, SEEM 6102, Demonstration of Support Vector machines to artificial intelligence. 2013, Semester B, SEEM 504B-507B, Non-destructive methods for real products inspection. 2012, Semester B, MEEM 3044, Microprocessor Programming and Applications. 2012, Semester A, GE1319, PZT based ultrasonic sensor design. 荣誉奖励 *工业和信息化部、科技部组织的中国先进技术转化应用大赛中荣获优胜奖(排名第二) *上海交通大学2019年度教职工考核“优秀” *Elsevier、IEEE、IOP出版社多个期刊杰出审稿人奖 *Hong Kong PhD Fellowship scheme (2011年来自全球103个国家4024名申请人中授予167名,2011年香港城市大学仅4名,工学院仅2名) *Chow Yei Ching School of Graduate Studies Scholarship (for non-local students)(工学院当年仅两名获得此奖) *Chow Yei Ching School of Graduate Studies Entrance Scholarship *Outstanding Academic Award *Research Tuition Scholarship *四川省优秀毕业生 *研究生特等奖 *校优秀毕业生 *优秀硕士论文 *2015年至2017年香港CSSA六校篮球联赛三连冠 *国家二级运动员(100米和200米短跑) *成都市金牛区100米高中组冠军、200米高中组亚军

研究领域

*稀疏测度 *智能运维与大数据分析 *预测与健康管理 *统计学习、机器学习与数据挖掘 *状态监测与故障诊断 *深度学习 *无损检测

近期论文

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*Dong Wang, Qiang Miao, Qinghua Zhou, Guangwu Zhou, An intelligent prognostic system for gear performance degradation assessment and remaining useful life estimation, Journal of Vibration and Acoustics-Transactions of The ASME, 137 (2015) 021004. *Dong Wang, Xuejun Zhao, Lin-Lin Kou, Yong Qin, Yang Zhao, Kwok-Leung Tsui, A simple and fast guideline for generating squared envelope spectra from spectral coherence for bearing fault diagnosis, Mechanical Systems and Signal Processing, 122 (2019) 754-768. *Dong Wang, Fangfang Yang, Kwok-Leung Tsui, Qiang Zhou, Suk Joo Bae, Remaining useful life prediction of lithium-ion batteries based on spherical cubature particle filter, IEEE Transactions on Instrumentation and Measurement, 65 (2016) 1282-1291. *Dong Wang, Yang Zhao, Fangfang Yang, Kwok-Leung Tsui, Nonlinear-Drifted Brownian Motion with Multiple Hidden States and Its Application to Prognostics of Lithium-ion Batteries, Mechanical Systems and Signal Processing, 93 (2017) 531-544. *Dong Wang, Peter W. Tse, Prognostics of oil sand pumps based on a moving-average wear degradation index and a general sequential Monte Carlo method, Mechanical Systems and Signal Processing, 56-57 (2015) 213-229. *Dong Wang, Peter W. Tse, Kwok Leung Tsui, An enhanced Kurtogram method for fault diagnosis of rolling element bearings, Mechanical Systems and Signal Processing, 35 (2013) 176-199. *Dong Wang, Peter W. Tse, A general sequential Monte Carlo method based optimal wavelet filter: a Bayesian approach for extracting bearing fault features, Mechanical Systems and Signal Processing, 52-53, (2015) 293-308. *Dong Wang, Qiang Miao, Some Improvements on A General Particle Filter based Bayesian Approach for Extracting Bearing Fault Features, Journal of Vibration and Acoustics-Transactions of The ASME, 137 (4) 041016. *Dong Wang, Qiang Miao, Smoothness index-guided Bayesian inference for determining joint posterior probability distributions of anti-symmetric real Laplace wavelet parameters for identification of different bearing faults, Journal of Sound and Vibration, 345 (2015) pp.250-266. *Dong Wang, Kwok-Leung Tsui, Qiang Zhou, Novel Gauss-Hermite integration based Bayesian inference on optimal wavelet parameters for bearing fault diagnosis, Mechanical Systems and Signal Processing, 72-73 (2016) 80-91. *Dong Wang, An extension of the Infograms to novel Bayesian inference for bearing fault feature extraction, Mechanical Systems and Signal Processing, 80 (2016) 19-30. *Dong Wang, Yang Zhao, Cai Yi, Kwok-Leung Tsui, Jianhui Lin, Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings, Mechanical Systems and Signal Processing, 101C (2018) pp. 292-308. *Dong Wang, Qiang Miao, Rui Kang, Robust health evaluation of gearbox subject to tooth failure with wavelet decomposition, Journal of Sound and Vibration, 324 (2009) 1141-1157. *Dong Wang, Peter W. Tse, Wei Guo, Qiang Miao, Support vector data description for fusion of multiple health indicators for enhancing gearbox fault diagnosis and prognosis, Measurement Science and Technology, 22 (2011) 025102. *Dong Wang, Peter W. Tse, Yiu L. Tse, A morphogram with the optimal selection of parameters used in morphological analysis for enhancing the ability in bearing fault diagnosis, Measurement Science and Technology, 23 (2012) 065001. *Dong Wang, Peter W. Tse, A new blind fault component separation algorithm for a single-channel mechanical signal mixture, Journal of Sound and Vibration, 331 (2012) 4956-4970. *Dong Wang, Qiang Miao, Michael Pecht, Prognostics of lithium-ion batteries based on relevance vectors and a conditional three-parameter capacity degradation model, Journal of Power Sources, 239 (2013) 253-264. *Dong Wang, Wei Guo, Xiaojuan Wang, A joint sparse wavelet coefficient extraction and adaptive noise reduction method in recovery of weak bearing fault features from a multi-component signal mixture, Applied Soft Computing, 13 (2013) 4097-4104. *Peter W. Tse, Dong Wang, The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2”, Mechanical Systems and Signal Processing, 40 (2013) 499-519. *Peter W. Tse, Dong Wang, The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection: Part 2 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2”, Mechanical Systems and Signal Processing, 40 (2013) 520-544. *Dong Wang, Changqing Shen, Peter W. Tse, A novel adaptive wavelet stripping algorithm for extracting the transients caused by bearing localized faults, Journal of Sound and Vibration, 332 (2013) 6871-6890. *Dong Wang, Wei Guo, Peter W. Tse, An enhanced empirical mode decomposition method for adaptive blind component separation of a single-channel vibration signal mixture, Journal of Vibration and Control, 22 (2016) 2603-2618. *Dong Wang, Changqing Shen, An equivalent cyclic energy indicator for bearing performance degradation assessment, Journal of Vibration and Control, 22 (2016) 2380-2388. *Dong Wang, K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: revisited, Mechanical Systems and Signal Processing, 70-71 (2016) 201-208. *Dong Wang, Kwok-Leung Tsui, Yong Qin, Optimization of segmentation fragments in empirical wavelet transform and its applications to extracting industrial bearing fault features, Measurement, 133 (2019) 328-340. *Dong Wang, Jin-zhen Kong, Yang Zhao, Kwok-Leung Tsui, Piecewise Model Based Intelligent Prognostics for State of Health Prediction of Rechargeable Batteries with Capacity Regeneration Phenomena, Measurement, 147 (2019) 106836. *Dong Wang, Qiang Zhou, Kwok-Leung Tsui, On the distribution of the modulus of Gabor wavelet coefficients and the upper bound of the dimensionless smoothness index in the case of additive Gaussian noises: revisited, Journal of Sound and Vibration, 395 (2017) 393-400. *Dong Wang, Changqing Shen, An equivalent cyclic energy indicator for bearing performance degradation assessment, Journal of Vibration and Control, 22 (2016) 2380-2388. *Dong Wang, Wei Guo, Xiaojuan Wang, A joint sparse wavelet coefficient extraction and adaptive noise reduction method in recovery of weak bearing fault features from a multi-component signal mixture, Applied Soft Computing, 13 (2013) 4097-4104. *Dong Wang, Wei Guo, Extraction of sparse equalized signals in recovery of potential cyclic impulses from a multi-fault signal mixture, Journal of Vibration and Control, 20 (2014) 1735-1750. *Dong Wang, Fangfang Yang, Yang Zhao, Kwok-Leung Tsui, Remaining useful life prediction of lithium-ion batteries at different discharge current rates, Microelectronics Reliability, 78 (2017) 212-219. *Dong Wang, Fangfang Yang, Yang Zhao, Kwok-Leung Tsui, Prognostics of Lithium-ion Batteries Based on State Space Modeling with Heterogeneous Noise Variances, Microelectronics Reliability, 75 (2017) 1-8. *Dong Wang, Kwok-Leung Tsui, Qiang Miao, Prognostics and health management: a review of bearing and gear health indicators, IEEE Access, 6 (2018) 665-676. *Fangfang Yang, Dong Wang, Yinjiao Xing, Kwok-Leung Tsui, Prognostics of Li(NiMnCo)O2-based lithium-ion batteries using a novel battery degradation model, Microelectronics Reliability, 70 (2017) 70-78. *Qiang Miao, Dong Wang, and Hong-Zhong Huang, Identification of characteristic components in frequency domain from signal singularities, Review of Scientific Instruments, 81 (2010) 035113. *Fangfang Yang, Dong Wang, Yang Zhao, Kwok-Leung Tsui, Suk Joo Bae, A study of the relationship between coulombic efficiency and capacity degradation of commercial lithium-ion batteries, Energy, 145 (2018) 486-495. *Changqing Shen, Dong Wang, Fanrang Kong, Peter W. Tse, Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier, Measurement, 46 (2013) 1551-1564. *Xiang Wan, Dong Wang, Peter W. Tse, Guanghua Xu, Qing Zhang, A critical study of dimensionality reduction methods for gear crack degradation assessment under different operating conditions, Measurement, 78 (2016) 138-150. *Jingjing Zhong, Peter W. Tse, Dong Wang, Novel Bayesian inference on optimal parameters of support vector machines and its application to industrial survey data classification, Neurocomputing, 211 (2016) 159-171.

学术兼职

*上海交大/航天智控智能运维工业互联网研究中心副主任 *中国振动工程学会副秘书长、工作委员会秘书长 *中国质量发展研究院成员 *机械系统与振动国家重点实验室固定成员 *IEEE Transactions on Instrumentation and Measurement副主编 *担任Elsevier、IEEE、Sage、Springer等出版社的多种SCI源刊同行评审专家 Mechanical Systems and Signal Processing Journal of Sound and Vibration Technometrics IIE Transactions IEEE Transactions on Signal Processing IEEE Signal Processing Letters IEEE Transactions on Reliability IEEE Transactions on Industrial Electronics IEEE Transactions on Industrial Informatics IEEE Transactions on Instrumentation and Measurement IEEE Transactions on Vehicular Technology IEEE Transactions on Automation Science and Engineering IEEE/ASME Transactions on Mechatronics Communications in Statistics – Theory and Methods Measurement Science and Technology Microelectronics Reliability Reliability Engineering and System Safety Measurement Signal Processing International Journal of Distributed Sensor Networks Journal of Vibration and Control Applied Mathematical Modelling Nonlinear Dynamics Computers & Industrial Engineering Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering Journal of Power Sources International Journal of Mechanical Sciences Journal of Intelligent Manufacturing Digital Signal Processing Knowledge-based systems Journal of Energy Storage International Journal of Production Research Neurocomputing Powder Technology Applied Energy Applied Soft Computing Neural Computing and Applications International Journal of Acoustics and Vibration Structural Health Monitoring-An International Journal International Journal of Electrical Power and Energy Systems Journal of Loss Prevention in the Process Industries Computer Methods and Programs in Biomedicine Sensors and Actuators A: Physical Journal of Low Frequency Noise Vibration and Active Control Journal of Zhejiang University-SCIENCE A Nondestructive Testing and Evaluation Annals of Nuclear Engineering Aerospace Science and Technology Chinese Journal of Aeronautics *担任领域内多个国际会议职务 *担任智利国家科技发展基金评审专家 *上海交通大学学位论文评议人

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