Degradation Assessment for Critical Assets in Power Generation

Degradation assessment for critical assets in power generation has great significance for power industry. Existing degradation assessment models failed either in combining the multimodal condition monitoring data or in removing time-varying working condition influences, resulting in inaccurate and/or unreliable degradation assessment results. In order to achieve robust and accurate degradation assessment for power generation critical assets, this project aims at developing new models based on both maintenance data and condition monitoring data from ENMAX. It is expected to obtain more accurate degradation assessment results over existing models. This study is critical for ENMAX to optimize their capital asset management decisions and maximize long-term profits whilst delivering high service levels to customers with acceptable and manageable risks. Furthermore, the interns will gain experience in addressing application-oriented research problems.

Faculty Supervisor:

Ming Zuo

Student:

Weixuan Tang

Partner:

ENMAX Energy Corporation

Discipline:

Engineering - mechanical

Sector:

Energy

University:

Program: