Research output per year
Research output per year
Personal profile
Research Interests
- Fault diagnosis and condition monitoring
- Cost-effective wireless condition monitoring system
- Data compression and signal processing
- Machine learning
- Energy harvesting
Biography
Xiaoli Tang is currently a Machine Learning and Data Scientist - KTP Associate in College of Engineering & Physical Sciences. She was a research fellow of the School of Engineering and Technology at Aston University who worked in Optimising Wheel Alignment to Reduce Vehicle Particulate Emissions project funded by Innovate UK from April 2020 to July 2021. She has a strong background in the research field of rotating machine condition monitoring. She has rich experience in developing data fusion and compression methods, effective and efficient fault diagnosis approaches, vibroacoustic instrumentation and testing, intelligent online wireless condition monitoring systems.
Education/Academic qualification
PhD, University of Huddersfield
11 Jan 2016 → 10 Jan 2020
Award Date: 16 Sep 2020
Fingerprint
Dive into the research topics where Xiaoli Tang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
A Mobile Robot Based Monitoring Platform for Pipeline Leakage Diagnosis Based on Cross-correlation Analysis
Tang, W., Zhang, G., Gu, F. & Tang, X., 16 May 2021, Proceedings of IncoME-V & CEPE Net-2020. IncoME-V 2020. Zhen, D., Wang, D., Wang, T., Wang, H., Huang, B., Sinha, J. K. & Ball, A. D. (eds.). Vol. 105. p. 477-489 13 p. (Mechanisms and Machine Science; vol. 105).Research output: Chapter in Book/Published conference output › Conference publication
-
An evaluating study of using thermal imaging and convolutional neural network for fault diagnosis of reciprocating compressors
Deng, R., Tang, X., Song, L., Abdulmumeer, A., Gu, F. & Ball, A. D., 17 Oct 2020, In: International Journal of COMADEM. 23, 4, p. 23-26 4 p.Research output: Contribution to journal › Article › peer-review
-
An Evaluating Study of Using Thermal Imaging and Convolutional Neural Network for Fault Diagnosis of Reciprocating Compressors
Deng, R., Tang, X., Song, L., Abdulmumeen, A., Gu, F. & Ball, A. D., 28 Aug 2020, Advances in Asset Management and Condition Monitoring, COMADEM 2019. Ball, A., Gelman, L. & Rao, B. K. N. (eds.). Springer, Vol. 166. p. 1495-1503 9 p. (Smart Innovation, Systems and Technologies; vol. 166).Research output: Chapter in Book/Published conference output › Conference publication
-
Condition Monitoring of Lubricant Shortage for Gearboxes Based on Compressed Thermal Images
Tang, X., Li, K., van Vuuren, P. A., Guo, J., Otuyemi, F., Gu, F. & Ball, A. D., 28 Aug 2020, Advances in Asset Management and Condition Monitoring, COMADEM 2019. Ball, A., Gelman, L. & Rao, B. K. N. (eds.). Springer, Vol. 166. p. 927-938 12 p. (Smart Innovation, Systems and Technologies; vol. 166).Research output: Chapter in Book/Published conference output › Conference publication
-
Modelling and Analysis of Slewing Bearings with Quenched Soft Zone
Gui, J., Wang, G., Tang, X., Zhou, Z. & Jiang, Y., 28 Aug 2020, Advances in Asset Management and Condition Monitoring, COMADEM 2019. Ball, A., Gelman, L. & Rao, B. K. N. (eds.). Springer, Vol. 166. p. 351-362 12 p. (Smart Innovation, Systems and Technologies; vol. 166).Research output: Chapter in Book/Published conference output › Conference publication