基本信息

yl6809永利教授，硕/博士生导师，常年致力于机电设备状态监测与故障诊断、智能运维、机器人巡检等领域的研究工作，主持国家及省部级项目20余项，发表高水平论文100余篇，其中SCI 检索论文 80余篇，EI 检索论文 50 余篇，授权发明专利 5 项，常年担任国内外高水平学术期刊的审稿人，担任北京市精密测控技术与仪器工程技术研究中心副主任、中国振动工程学会动态信号分析专业委员会副主任委员、故障诊断专业委员会委员、动态测试专业委员会委员、中国机械工程学会智能运维分会委员等职务。获得北京市自然科学奖二等奖等科技奖励3项。

教育背景

1994.09-1998.07：西安交通大学机械工程公司工学学士

1998.09-2003.11：西安交通大学机械工程公司 工学博士

工作经历

2004.03-2006.06：天津大学机械工程公司 博士后

2006.06-2009.12：yl6809永利集团机械工程与应用电子技术公司 讲师

2009.12-2020.07：yl6809永利集团机械工程与应用电子技术公司 副教授

2020.07-至今： yl6809永利 教授

研究方向

机电设备智能运维、巡检机器人、现代信号处理、人工智能

科研情况

1、国家自然科学基金项目，主持，间歇性低速重载设备微弱特征提取与早期故障诊断研究，2008.01-2010.12

2、国家自然科学基金项目，主持，基于磁记忆的低速重载齿轮潜故障早期诊断方法研究，2011.01-2013.12

3、国家自然科学基金项目，主持，变载行星轮系耦合故障机理及早期故障诊断方法研究，2014.01-2017.12

4、国家自然科学基金项目，主持，奇异谱分解理论及其在机械故障诊断中的应用研究，2018.01-2021.12

5、北京市教委项目，主持，低速行星齿轮箱早期故障微弱特征检测方法研究

6、北京市委组织部，主持，低速重载齿轮箱早期故障多尺度非线性特征提取方法与应用研究

7、首钢集团，主持，炼钢转炉倾动机构在线监测与诊断系统

8、首钢集团，主持，高速线材精扎机在线监测与诊断系统

9、首钢集团，主持，高速线材生产流程综合诊断系统

10、中钢集团西安重机有限公司，主持，eMonitor 800T高炉炉顶设备在线状态监测系统

11、天津金岸重工有限公司，主持，门座式起重机旋转机构在线检测系统研发

12、天津港股份有限公司，主持，面向LCC的港口设备状态监控与数据挖掘理论及应用研究

13、北京天地龙跃科技有限公司，主持，基于多参数的机电系统综合故障诊断方法研究及模拟实验

14、华能集团清洁能源研究院，主持，风力发电机主轴承故障机理与特征提取

部分科研获奖

1.2023年度北京市科学技术奖-自然科学奖-二等奖，复杂工况下机械系统故障特征提取及预示理论与方法

2. 2025年度新疆维吾尔自治区机械电子工业科学技术奖-自然科学奖-一等奖，大型风电机组传动链同频干扰状态下复合故障诊断技术与应用示范

3. 2025年度山东省自动化学会科学技术奖-科技进步奖-二等奖，高性能激光雷达云边端融合智能载运群控协同关键技术及产业

部分科研论文

[1] Chaoyong Ma, Wenxu Zhang, Lili Meng, Miaorui Yang, Kun Zhang, Yonggang Xu. A dual-objective optimized reweighted overlapping group sparse framework integrating frequency slice function for robust bearing fault diagnosis. Mechanical Systems and Signal Processing, 2026, 242: 113678.

[2] Kun Zhang, Jiayi Fan, Miaorui Yang∗, Hong Jiang, Yonggang Xu, Harmonic Fourier decomposition and its application in fault identification of rotating machinery system, Reliability Engineering & System Safety, 2026, 266: 111657.

[3] Miaorui Yang, Kun Zhang*, Haihong Tang, Yonggang Xu, Wenyu Huo, An adaptive feature extraction technique via bispectrum-driving graph domain for bearing fault diagnosis, ISA Transactions, 2025, 167, Part B: 1828-1840.

[4] Yanlei Liu,Yonggang Xu,Miaorui Yang,Hong Jiang, Kun Zhang*, Frequency pattern graph spectrum model and its applications in rolling bearing fault diagnosis, Mechanical Systems and Signal Processing, 2025, 240: 113426.

[5] Miaorui Yang, Kun Zhang*, Yanping Zhu, Long Zhang, Yonggang Xu, A new difference feature extraction method of slewing bearings in wind turbines via optimization bispectrum domain model, Expert Systems with Applications, 2025, 278:127325.

[6] Xue Zou, Kun Zhang*, Tongtong Liu, Zuhua Jiang, Yonggang Xu, An overlapping group sparse variation method for enhancing time-frequency modulation bispectrum characteristics and its applications in bearing fault diagnosis, Measurement, 2025, 249:117066.

[7]Kun Zhang, Dongbing Su, Yifei Zhang, Di Jin and Yonggang Xu*, A weighted subspace local averaging method and its applications in gearbox fault diagnosis, IEEE Sensors Journal, 2025, 25(7):11405-11415.

[8] Chaoyong Ma, Wenxu Zhang, Mengdi Shi, Xue Zou, Yonggang Xu, Kun Zhang*, Feature identification based on cepstrum-assisted frequency slice function for bearing fault diagnosis, Measurement, 2025, 246:116753.

[9] Wenyu Huo, Kun Zhang*, Zuhua Jiang, Miaorui Yang, Yonggang Xu, A targeted feature mode extraction method with adaptive local feature enhancement in rolling bearing fault diagnosis, IEEE Sensors Journal, 2025, 25(17).

[11]Kun Zhang, Yanlei Liu, Long Zhang, Chaoyong Ma*, Yonggang Xu, Frequency slice graph spectrum model and its application in bearing fault feature extraction, Mechanical Systems and Signal Processing, 2025,226: 112383.

[12]Chaoyong Ma, Nan Si, Kun Zhang*, Xiangfeng Zhang, Jia Chen, Yonggang Xu, A novel cross domain diagnosis method based on physical feature weighting and deep residual shrinkage network, Measurement Science and Technology, 2025, 36(1): 0161b6.

[13] Wenyu Huo, Zuhua Jiang, Zhipeng Sheng, Kun Zhang, Yonggang Xu*, Cyclostationarity blind deconvolution via eigenvector screening and its applications to the condition monitoring of rotating machinery, Mechanical Systems and Signal Processing, 2025, 222: 111782.

[14] Zuhua Jiang,Kun Zhang*,Xiangfeng Zhang,Chaoyong Ma and Yonggang Xu.The SAMgram a novel local enhancement and targeted extraction strategy for weak bearing fault characteristics. Structural Health Monitoring,2025.

[15] Miaorui Yang, Kun Zhang, Yonggang Xu*, Aijun Hu, Fengshou Gu, The harmonic modulation bispectrum: a modulated vibration signal analysis method for compound fault diagnosis of gearboxes, Structural Health Monitoring, 2024, 0(0).

[16] Xi Qiao, Kun Zhang, Xiangfeng Zhang, Long Zhang, Yonggang Xu*, HTG transformation: an amplitude modulation method and its application in bearing fault diagnosis, Measurement Science and Technology, 2024, 35: 106135.

[17] Xue Zou, Huaming Zhang, Zuhua Jiang, Kun Zhang*, Yonggang Xu, Toward accurate extraction of bearing fault modulation characteristics with novel time–frequency modulation bispectrum and modulation Gini index analysis, Mechanical Systems and Signal Processing,2024, 219: 111629.

[18] Jifeng Sui, Chaoyong Ma, Zuhua Jiang, Kun Zhang, and Yonggang Xu*, The CTIgram: a novel optimal demodulation band selection method and its applications in condition monitoring of rotating machinery, IEEE Transactions on Instrumentation and Measurement, 2024, 73: 3529109.

[19] Zhu Yan, Jingpin Jiao, Yonggang Xu*, Adaptive linear chirplet synchroextracting transform for time-frequency feature extraction of non-stationary signals, Mechanical Systems and Signal Processing, 2024, 220: 111700.

[20] Miaorui Yang, Kun Zhang*, Zhipeng Sheng, Xiangfeng Zhang, Yonggang Xu. The amplitude modulation bispectrum: A weak modulation features extracting method for bearing fault diagnosis. Reliability Engineering & System Safety, 2024, 250:110241.

[21] Chaoyong Ma, Chen Liang, Zuhua Jiang, Kun Zhang*, Yonggang Xu, A novel time-frequency slice extraction method for target recognition and local enhancement of non-stationary signal features, ISA Transactions, 2024, 146:319-335.

[22] Huan Yang, Kun Zhang, Zuhua Jiang, Xiangfeng Zhang, Yonggang Xu, Fault features diagnosis method of rolling bearing via optimized S synchroextracting transform, IEEE Transactions on instrumentation and measurement, 2023, 72: 3518708.

[23] Miaorui Yang, Yonggang Xu*, Kun Zhang, Xiangfeng Zhang, Singular component decomposition and its application in rolling bearing fault diagnosis, Measurement Science and Technology, 2024, 35: 015120.

[24] Huan Yang, Kun Zhang*, Zuhua Jiang, Xiangfeng Zhang, Yonggang Xu., An adaptive time–frequency demodulation method and its applications in rolling bearing fault diagnosis, Measurement science and technology, 2023, 34 (12): 126101.

[25] Zhu Yan, Yonggang Xu*, Kun Zhang, Aijun Hu, Gang Yu, Adaptive synchroextracting transform and its application in bearing fault diagnosis, ISA transactions, 2023, 137: 574-589.

[26] Zuhua Jiang, Kun Zhang, Xiangfeng Zhang, Yonggang Xu*, A tacholess order tracking method based on spectral amplitude modulation for variable speed bearing fault diagnosis, IEEE transactions on instrumentation and measurement, 2023, 72: 3518708.

[27] Chaoyong Ma, Zhiqiang Yang, Yonggang Xu*, Aijun Hu, Kun Zhang, Periodic detection mode decomposition and its application in bearing fault diagnosis, IEEE Sensors Journal, 2023, 23(11): 11806-11814.

[28] Zhu Yan, Yonggang Xu*, Liang Wang, Aijun Hu, Feature extraction by enhanced time–frequency analysis method based on Vold-Kalman filter, Measurement, 2023, 207: 122383.

[29] Chaoyong Ma, Zhiqiang Yang, Kun Zhang, Ling Xiang and Yonggang Xu*, Optimization of ramanujan subspace periodic and its application in identifying industrial bearing fault features, IEEE Transactions on Instrumentation and Measurement, 2023, 72：3504407.

[30] Zuhua Jiang, Kun Zhang, Ling Xiang, Gang Yu, Yonggang Xu*, A time-frequency spectral amplitude modulation method and its applications in rolling bearing fault diagnosis, Mechanical systems and signal processing, 2023, 185: 109832.

[31] Zuhua Jiang, Kun Zhang, Ling Xiang, Yonggang Xu*, Differential spectral amplitude modulation and its applications in rolling bearing fault diagnosis, Measurement, 2022，201 :111755.

[32] Chaoyong Ma, Xingjie Ma, Yonggang Xu*, Ling Xiang, Kun Zhang, Enhanced seeded region growing algorithm and its application in signal decomposition, Measurement Science and Technology, 2022, 33, 095111.

[33] Kun Zhang, Yunjie Deng, Peng Chen, Chaoyong Ma, Yonggang Xu*, Quaternion empirical wavelet transform and its applications in rolling bearing fault diagnosis, Measurement, 2022, 195: 111179.

[34] Yonggang Xu*, Liang Wang, Aijun Hu, Gang Yu, Time-extracting S-transform algorithm and its application in rolling bearing fault diagnosis. Sci China Tech Sci,2022, 65: 932–942.

[35] Kun Zhang, Haihong Tang, Peng Chen, Yonggang Xu*, Aijun Hu, A method for extracting fault features using variable multilevel spectral segmentation framework and harmonic correlation index, IEEE Transactions on instrumentation and measurement, 2021, 71, 3505109.

[36] Yonggang Xu*, Liang Wang, Gang Yu, Yanxue Wang, Generalized S-synchroextracting transform for fault diagnosis in rolling bearing, IEEE Transactions on instrumentation and measurement, 2022, 71, 350314.

[37] Kun Zhang, Peng Chen, Miaorui Yang, Liuyang Song, Yonggang Xu*, The Harmogram: A periodic impulses detection method and its application in bearing fault diagnosis, Mechanical Systems and Signal Processing, 2022, 165: 108374.

[38] Kun Zhang, Weikang Tian, Peng Chen, Chaoyong Ma, Yonggang Xu*, Sparsity-guided multi-scale empirical wavelet transform and its application in fault diagnosis of rolling bearings, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021,43: 398.

[39] Kun Zhang, Ling Shi, Yue Hu, Peng Chen, and Yonggang Xu*, Variable spectral segmentation empirical wavelet transform for noisy signal processing, Digital Signal Processing, 2021, 117: 103151.

[40] Yonggang Xu, Yunjie Deng, Chaoyong Ma, Kun Zhang*, The Enfigram: A robust method for extracting repetitive transients in rolling bearing fault diagnosis, Mechanical Systems and Signal Processing, 2021, 158: 107779.