1. 基于深度学习理论的复杂机电装备健康监测与智能感知;(面向航天、航空领域)
2. 大数据环境下的瞬态信号仿真、建模与自适应表达技术;(面向高铁、风电装备)
3. 工业机器人多传感信息融合、深度发掘与预测性维护; (面向集群级智能工厂)
1.国防装备预研项目,6142004005,基于多源内置伺服信息的航天关节传动系统健康感知技术,2019/01-2020/12,主持
2.国家自然科学基金面上项目,51875434,基于内置编码器信息的关节减速器多源扭振行为分析与智能健康监测,2019/01-2022/12,主持
3.国家自然科学基金青年项目,51405373,变转速下机械动态信息的自适应提取与状态评估方法研究,2014/01-2017/12,主持
4.机械制造系统国家重点实验室青年基金项目,1221209701,基于自适应时频表达的变工况机械装备健康监测技术研究,2017/01-2017/12,主持
5.陕西省重点实验室青年学术骨干培植基金,3121000007,复杂服役条件下齿轮箱设备的瞬态工况辨识与早期故障信息提取研究,2015/01-2017/12,主持
6.国防基础科研计划,JCKY2018601C013,基于多源伺服信息的制造过程智能感知与诊断,2019/01-2020/12,项目骨干
7.高档数控机床与基础制造装备重大专项,2014ZX04001051,国产高档数控机床、系统及其技术在航空领域的综合应用验证及工艺研究,2014/01-2016/12,项目骨干
8.高档数控机床与基础制造装备重大专项,2009ZX04014-015,精密、重型机床可靠性设计与性能试验技术,2009/03-2011/12,项目骨干
1.M. Zhao, J. Jiao, and J. Lin, A Data-Driven Monitoring Scheme for Rotating Machinery Via Self-Comparison Approach, IEEE Transactions on Industrial Informatics, 15(2019) 2435-2445.
2.M. Zhao, J. Lin, Health assessment of rotating machinery using a rotary encoder, IEEE Transactions on Industrial Electronics, 65(2018) 2548-2556.
3.M. Zhao, X. Jia, J. Lin, Y. Lei, J. Lee, Instantaneous speed jitter detection via encoder signal and its application for the diagnosis of planetary gearbox, Mech Syst Signal Process, 98 (2018) 16-31.
4.M. Zhao, X. Jia, A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery, Mech Syst Signal Process, 94 (2017) 129-147.
5.L. Jing, M. Zhao, P. Li, and X. Xu, A convolutional neural network based feature learning and fault diagnosis method for the condition monitoring of gearbox, Measurement, 111(2017) 1-10.
6.Y. Miao, M. Zhao, J. Lin, and Y. Lei, Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings, Mechanical Systems and Signal Processing, 92(2017)173-195.