个人简介

孔金震，女，讲师，硕士生导师，河北工业大学“元光学者”。2023年于上海交通大学获得博士学位，长期从事设备故障预测及健康管理、动力电池健康状态评估及寿命预测理论与方法、智能运维与大数据分析等研究，主持天津市科研项目1项，作为学术骨干参与包括国家自然科学基金创新群体项目、国家重点研发计划、国家自然科学基金等多项国家级课题。发表SCI论文10余篇，出版英文专著1章，获批国家发明专利2项。担任Mechanical Systems and SignalProcessing、IEEE Transactions on Transportation Electrification、IEEE Sensors Journal、IEEE Transactions on Instrumentation & Measurement等国际学术期刊审稿人。

教育背景

2019.09-2023.06，上海交通大学，机械工程(工业工程)，博士，导师：王冬

2023.01-2023.05，新南威尔士大学，机械与制造工程，访问学者，合作导师：Zhongxiao Peng

2021.08-2022.01，新加坡国立大学，工业系统工程与管理，访问学者，合作导师：Zhisheng Ye

2017.09-2019.06，上海交通大学，机械工程，硕士（硕博连读），导师：彭志科

2013.08-2017.06，哈尔滨工程大学，机械设计制造及其自动化，学士

工作经历

2023.07-至今， ，讲师/元光学者

研究方向

设备故障预测与健康管理(PHM)

动力电池数据驱动寿命预测理论与方法

智能运维与大数据分析

退化建模数学优化模型研究

科研项目

1．天津市教委科研计划项目，2023.12-2026.12，主持

2．国家重点研发计划，2022.08-至今，参与

3．核电运行研究(上海)有限公司ERDB5.0项目，2021.03-2022.03，参与

4．教育部-中国移动科研基金研发项目，2021.01-至今，参与

5．国家自然科学基金面上项目，2020.01-2023.12，参与

6．大型先进压水堆及高温气冷堆核电站重大专项，2018.01-2020.06，参与

主要学术成果

学术论文：

[1]Kong Jin-Zhen, Cui Di, Hou Bingchang et al., New Short-long-term Degradation Model for Precise Battery Health Prognostics,IEEE Transactions on Industrial Electronics, 2022, 70(9): 9527-9537. (SCI，Q1，中科院一区TOP)

[2] Kong Jin-Zhen, Yang Fangfang, Zhang Xi et al., Voltage-temperature Health Feature Extraction to Improve Prognostics and Health Management of Lithium-ion Batteries,Energy, 2021, 223: 120114. (SCI，Q1，中科院一区TOP)

[3]Kong Jin-Zhen, Wang Dong, Yan Tongtong et al., Accelerated Stress Factors Based Nonlinear Wiener Process Model for Lithium-ion Battery Prognostics,IEEE Transactions on Industrial Electronics, 2021, 69(11): 11665-11674. (SCI，Q1，中科院一区TOP)

[4]孔金震,钱亚鹏,彭志科等,大型液压阻尼器仿真建模及静动态性能试验研究,噪声与振动控制, 2021, 41(1): 82. (中文核心)

[5] Kong Jin-Zhen, Liu Jie, Chen Yikai et al., A Data-driven Approach for Capacity Estimation of Batteries Based on Voltage Dependent Health Indicators.Journal of Physics: Conference Series, 2021, 1983(1): 012115. (EI)

[6]Wang Dong, Kong Jin-Zhen, Yang Fangfang et al., Battery Prognostics at Different Operating Conditions,Measurement, 2020, 151: 107182. (SCI，Q2，中科院二区)

[7]Wang Dong, Kong Jin-Zhen, Zhao Yang et al., Piecewise Model Based Intelligent Prognostics for State of Health Prediction of Rechargeable Batteries with Capacity Regeneration Phenomena,Measurement, 2019, 147: 106836. (SCI，Q2，中科院二区)

[8]Hou Bingchang, Feng Xiao, Kong Jin-Zhen et al., Optimized weights spectrum autocorrelation: A new and promising method for fault characteristic frequency identification for rotating Machine fault diagnosis,Mechanical Systems and Signal Processing, 2023, 191: 110200. (SCI，Q1，中科院一区TOP)

[9] Hou Bingchang, Wang Dong, Kong Jin-Zhen et al., Understanding importance of positive and negative signs of optimized weights used in the sum of weighted normalized Fourier spectrum/envelope spectrum for machine condition monitoring,Mechanical Systems and Signal Processing, 2022, 174: 109094. (SCI，Q1，中科院一区TOP)

[10]Yan Tongtong, Wang Dong, Kong Jin-Zhen et al., Definition of Signal-to-Noise Ratio of Health Indicators and Its Analytic Optimization for Machine Performance Degradation Assessment,IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-16. (SCI，Q1，中科院二区)

英文专著：

[1] Kong Jin-Zhen, Wang Dong, Two Statistical Degradation Models of Batteries under Different OperatingConditions,Artificial Intelligence, Big Data and Data Science in Statistics: Challenges and Solutions in Environmetrics, the Natural Sciences and Technology. Cham: Springer International Publishing, 2022: 269-282.(专著章节)

国际会议：

[1] Kong Jin-Zhen, Wang Dong, Multi-Stage Modeling and Remaining Charge-Discharge Cycles Prediction of Rechargeable Batteries Considering Capacity Regeneration Phenomena,30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, 2020. (国际会议)

[2] Yan Tongtong, Kong Jin-Zhen, Wei Sha et al., Generic Framework for Integration of Spectral fusion with Optimization Modelling for Machine Performance Degradation Assessment,14th International Conference on Damage Assessment of Structures, 2021. (国际会议，获得Best Paper Award)

[3] Hou Bingchang, Kong Jin-Zhen, Chen Yikai et al., Machine Condition Monitoring by Online Updated Optimized Weights Spectrum: An Industrial Motor Case Study,2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), 2022. (国际会议，获得Best Paper Award)

发明专利：

[1]王冬,孔金震,侯炳昌,刘洁,朱景哲，基于温度加速因子的锂离子电池剩余寿命预测方法及系统，公开号：CN113761751A，公开日：2021.12.07.

[2]王冬,孔金震,彭志科，基于健康因子提取的电池健康状况预测方法、系统及介质，授权号：CN113030744B，授权日：2022.06.28.

[3]王冬,孔金震,王玉婷,刘洁,冯潇,陆明,张彬,一种光纤端口发光功率衰减趋势预测方法，公开号：CN115545318A，公开日：2022.12.30.

[4]王冬,侯炳昌,孔金震,彭志科，一种基于优化故障特征频谱的机械故障诊断与状态监测方法，授权号：CN113639985B，授权日：2022.04.12.

所获荣誉

获得上海市优秀毕业生、黑龙江省三好学生、第十六届“东风日产杯”全国工业工程应用案例大赛一等奖、第五届上海市工程管理创新大赛一等奖、首届全球应用算法实践典范大赛BPAA全场大奖、第十七届“华为杯”中国研究生数学建模竞赛二等奖等。

学术兼职

中国仪器仪表学会会员，担任Mechanical Systems and Signal Processing、IEEE Transactions on Transportation Electrification、IEEE Sensors Journal、IEEE Transactions on Instrumentation & Measurement等国际顶级学术期刊和行业主流期刊审稿人。

联系邮箱

jinzhenkong@hebut.edu.cn

招生信息

招收机械工程、仪器科学与技术硕士生。团队提供良好的学习软硬件条件、科研津贴/奖励等，欢迎有理想抱负和责任心、热爱科研、有奋斗精神的同学加入！