长期从事机械装备状态监测与故障诊断、机械加工过程运行状态智能监测、振动信号处理与分析等方面的研究工作，主持/参与了包括国家自然科学基金项目、陕西省重点研发计划项目在内的纵项、横向科研项目20余项。主要项目情况如下：

1.  国家自然科学基金面上项目：深孔钻削过程切削力无传感器估计与抑振调控策略，参与，在研，2026.01~2029.12。

2.  国家自然科学基金青年项目：核电管板深孔钻削刀具系统时变异常振动智能识别方法研究，主持，结题，2020.01~2022.12。

3. 陕西省重点研发计划一般项目：基于稀疏分解和深度学习的科氏流量计高精度计量关键技术研发，主持，结题，2023.01~2024.12。

4. 陕西省重点研发计划一般项目：考虑制造不确定性的高耗能装备能效计量系统关键技术研发，参与，结题，2022.01~2023.12。

5.陕西省自然科学基础研究计划：核电管板深孔加工质量深度迁移学习在线识别方法研究，主持，结题，2020.01~2021.12。

6.中国博士后科学基金，深孔钻削刀具系统振动状态检测关键技术研究，主持，结题，2015.05~2021.05。

7.陕西省重点研发计划一般项目：以振动传递分解路径贡献度为判据的机床振动抑制技术的研究，参与，结题，2023.01~2024.12。

8. 陕西诺贝特自动化科技股份有限公司委托项目：高性能蠕动进给磨削轨迹创成与参数优化控制方法，参与，结题，2023.06~2024.12。

9.西安东风机电股份有限公司委托项目：科氏流量计固有振动特征信号精确提取方法，主持，结题，2020.10~2022.12。

10.中核西北建设集团有限公司委托项目：桥梁支座橡胶夹层结构状态检测技术，主持，结题，2023.06~2023.12。

在Mechanical Systems and Signal Processing，International Journal of Machine Tools & Manufacture，Journal of Sound and Vibration， Structural Health Monitoring， Smart Material & Structure，仪器仪表学报等国内外著名学术刊物上发表研究论文20余篇，申请国家发明专利6项，获陕西高等学校科学技术研究成果一等奖1项。

其中部分代表性成果如下：

(1) Yue Si, Wang Xu, Zhenchao Yang, Yanghe Liu, Lingfei Kong, Yanfei Zhang.Intelligent surface roughness detection for deep-hole drilling based on pyramid adaptive transformer with MSST data fusion[J]. Measurement, 2025.

(2) Yue Si, Yanyi Zhang , Lingfei Kong, et al. The unbalance state detection of Coriolis flowmeter based on Laplace wavelet sparse representation and customized detection indicator[J]. IEEE Transactions on Instrumentation and Measurement, 2025.

(3) Wang Xu, Yue Si , An Lei, Lingfei Kong, and Weichao Guo. A multi-scale adaptive transformer with feature enhancement for fault diagnosis of rolling bearings under imbalanced small-sample and cross-condition scenarios[J]. Structural Health Monitoring, 2025: 14759217251371293

(4) Yue Si, Lingfei Kong, Jih-Hua Chin, et al. Whirling detection in deep hole drilling process based on multivariate synchrosqueezing transform of orthogonal dual-channel vibration signals. Mechanical Systems and Signal Processing,.2022, 167: 108621. 

(5) Yue Si, Zhousuo Zhang, Lingfei Kong &Jianming Zheng. Condition monitoring of deep-hole drilling process based on improved empirical wavelet de-noising and high multiple frequency components of rotation frequency. International Journal of Advanced Manufacturing Technology. 2021.07.

 (6) Yue Si, Zhousuo Zhang, Lingfei Kong, et al. Looseness condition feature extraction of viscoelastic sandwich structure using dual-tree complex wavelet packet based deep autoencoder networ. Structural Health Monitoring. 2020.05. 

 (7) Yue Si, Zhousuo Zhang, Lingfei Kong, et al. Aging condition identification of viscoelastic sandwich structure based on empirical wavelet transform and Hilbert envelope demodulation. Composite Structures, 2019.05. 

(8) Yue Si, Zhousuo Zhang, Bohan Zhao, et al. A novel method for bonding state detection of explosive clad structure based on the Hilbert envelop energy ratio of mono-model signals. Smart Materials and Structures, 2018, 27(11): 115006. 

(9) Yue Si, Zhousuo Zhang, Hongfang Wang, Feichen Yuan, Feasibility Study of Bonding State Detection of Explosive Composite Structure Based on Nonlinear Output Frequency Response Functions, Steel and Composite Structures, 2017, 24(4) :391-397. 

(10) Yue Si, Zhousuo Zhang, Hongfang Wang, Feichen Yuan, Mono-modal Feature Extraction for Bonding Quality Detection of Explosive Clad Structure with Optimized Dual-tree Complex Wavelet Transform, Journal of Sound and Vibration, 2017, 392: 346-366.

(11) Yue Si, Xuyang Lia, Lingfei Kong， et al. Improved empirical wavelet denoising algorithm with application to whirling detection in deep hole drilling process. 54th CIRP Conference on Manufacturing Systems.2021

(12) 思悦,张炎羿,王丽洁,等.基于组合带阻滤波器与样本熵的科氏流量计挂壁故障检测方法.仪器仪表学报,2025,46(02):132-140.

(13) 思悦，孔令飞，郑建明等. 基于振动信号的深孔钻削涡振在线检测方法研究. 仪器仪表学报2020.06.

(14) 思悦, 孔令飞,郑建明,李淑娟,杨癸庚,元振毅,李言.  一种深孔钻削中孔圆度误差实时监测方法， 2020100652759，发明专利，已授权。

(15) 思悦,李淑娟,孔令飞,杨癸庚,元振毅,汤奥斐,李言一种爆炸复合管结合状态的定量识别方法，2018105747226，发明专利，已授权。

(16) 思悦,张炎羿,孔令飞,李淑娟. 基于稳态响应的科式流量计挂壁故障检测方法,2024111125199,发明专利，已授权。

(17)思悦,许望,元振毅,张燕飞,杨癸庚. 结合自适应空间注意力和补丁特征加权的ViT跨域故障诊断方法,2025100481955,发明专利，已授权。