COURSE OVERVIEW:

Condition monitoring is the cornerstone of modern proactive asset management, transforming maintenance from a reactive task into a data-driven science. This course provides an advanced examination of the technologies and methodologies used to assess the real-time health of power system equipment, including transformers, switchgear, generators, and cables. Participants will explore the physics of equipment degradation—such as thermal aging, chemical decomposition, and partial discharge—learning how to capture and interpret the subtle signals that precede catastrophic failure.

The scope of this training addresses both online and offline monitoring techniques, emphasizing the integration of sensors and digital diagnostics into existing substation and plant infrastructures. It covers a diverse range of analytical tools, including infrared thermography, vibration analysis, and sophisticated chemical assessments like Dissolved Gas Analysis (DGA). The curriculum focuses on the development of a "Health Index" for critical assets, providing technical personnel with a framework for predicting the Remaining Useful Life (RUL) of equipment and optimizing maintenance intervals to maximize system availability.

Coverage includes the use of artificial intelligence and machine learning in the interpretation of complex diagnostic data, enabling the detection of patterns that are invisible to the naked eye. Attendees will learn to manage the challenges of data overload, focusing on how to filter and prioritize alerts from continuous monitoring systems. By bridging the gap between raw sensor data and actionable maintenance intelligence, the course equips professionals to lead their organizations toward a zero-failure philosophy that enhances safety and reduces the total cost of ownership for power system assets.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

• Design a comprehensive condition monitoring program for utility assets.
• Interpret multi-gas Dissolved Gas Analysis (DGA) for transformer health.
• Utilize infrared thermography to identify high-resistance electrical joints.
• Detect and locate partial discharge (PD) in high-voltage insulation systems.
• Analyze vibration signatures to identify mechanical faults in rotating machines.
• Implement online monitoring for bushings and surge arrestors.
• Evaluate the condition of circuit breaker contacts using dynamic resistance.
• Utilize acoustic and ultrasonic sensors for identifying internal arcing.
• Develop a "Health Indexing" model for transformers and switchgear.
• Integrate condition monitoring data into a central SCADA or CMMS.
• Interpret oil quality trends, including acidity, furan, and moisture.
• Apply predictive analytics to estimate the remaining useful life of assets.

TARGET AUDIENCE:

This course is intended for Asset Management Professionals, Maintenance Engineers, Reliability Specialists, and Senior Technicians responsible for the health and performance of power system infrastructure.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximize the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.