- Project Supervisor: Mehdi Bagheri
- Ending date: May 2018
- Location: Nazarbayev University, Astana, Republic of Kazakhstan
Unexpected faults are always jeopardizing distribution and power transformers as valuable assets in power network. Hence, various diagnosis techniques are utilized in order to prevent or at least detect transformer integrity after fault occurrence. The majority of diagnosis techniques is performing off-line and requires that transformer is disconnected from the power line. This is certainly undesirable for utility management and operator. Therefore, performing on-line diagnosis techniques is more preferable and faster than off-line techniques. The aim of this study is to perform real-time online diagnosis technique based on the analysis of the vibrational spectrum. It is supposed that vibrational signature of transformer is evaluated and transferred to cloud environment using Internet of Thing (IoT) structure.
Project team consists of BSc capstone project students from Nazarbayev university.
Team Leader: Aidar Suleimen
To contact the project group use one the following contact links:
Phone: +7 (777) 504-94-83
Address: Kabanbay Batyr 53, Astana, Republic of Kazakhstan