+254 721 331 808    training@upskilldevelopment.com

Electrical Asset Condition Monitoring Training Course

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Course Duration 5 Days

Online Training Registration

Training Mode Platform Fee Enroll
Online Training Zoom/ Google Meet 900USD Register

Classroom/On-site Training Schedule

Course Date Location Fee Enroll
14/09/2026 to 18/09/2026 Nairobi 1,500 USD Register
14/09/2026 to 18/09/2026 Mombasa 1,750 USD Register
14/09/2026 to 18/09/2026 Dubai 4,900 USD Register
12/10/2026 to 16/10/2026 Nairobi 1,500 USD Register
12/10/2026 to 16/10/2026 Kigali 2,500 USD Register
12/10/2026 to 16/10/2026 Mombasa 1,750 USD Register
09/11/2026 to 13/11/2026 Nairobi 1,500 USD Register
09/11/2026 to 13/11/2026 Mombasa 1,750 USD Register
09/11/2026 to 13/11/2026 Nairobi 2,500 USD Register
14/12/2026 to 18/12/2026 Nairobi 1,500 USD Register
14/12/2026 to 18/12/2026 Kigali 2,500 USD Register
14/12/2026 to 18/12/2026 Dubai 4,900 USD Register
14/12/2026 to 18/12/2026 Mombasa 1,750 USD Register
11/01/2027 to 15/01/2027 Nairobi 1,500 USD Register
08/02/2027 to 12/02/2027 Nairobi 1,500 USD Register

Course Introduction

Electrical asset condition monitoring is a vital engineering practice used to assess the health, performance, and reliability of electrical equipment throughout its operational lifecycle. By continuously evaluating equipment conditions and identifying early signs of deterioration, organizations can prevent unexpected failures, optimize maintenance activities, and improve system availability. This Electrical Asset Condition Monitoring Training Course provides participants with comprehensive knowledge of condition monitoring principles, diagnostic technologies, inspection techniques, data interpretation methods, and practical applications used for managing electrical assets effectively.

Participants will gain detailed knowledge of condition monitoring methods applied to electrical assets including transformers, motors, switchgear, circuit breakers, cables, generators, batteries, and distribution systems. The course covers thermal imaging, insulation testing, partial discharge analysis, oil diagnostics, power quality monitoring, online monitoring systems, sensor technologies, and equipment health assessment techniques. Emphasis is placed on practical engineering approaches that help professionals identify degradation patterns, evaluate asset conditions, and make informed maintenance decisions.

The training combines theoretical concepts with practical applications through equipment assessment exercises, diagnostic data analysis, inspection procedures, testing demonstrations, failure investigation activities, and real-world electrical asset case studies. Participants will learn how to establish condition monitoring programs, select suitable diagnostic techniques, interpret monitoring results, and develop maintenance recommendations based on actual equipment health conditions.

The advancement of smart grids, Industrial Internet of Things (IIoT), artificial intelligence, digital twins, advanced sensors, cloud-based analytics, and intelligent asset management platforms is transforming electrical condition monitoring practices. This course explores emerging topics including AI-based equipment diagnostics, automated health assessment, remote monitoring systems, digital substations, predictive analytics, smart sensors, and real-time asset performance management technologies.

Participants will also examine major condition monitoring challenges including data accuracy, sensor reliability, equipment accessibility, diagnostic interpretation, integration with maintenance systems, cybersecurity requirements, and investment planning. Through practical examples and engineering case studies, the course demonstrates how effective condition monitoring strategies improve equipment reliability, reduce unplanned outages, extend asset life, enhance safety, and optimize maintenance resources.

Upon successful completion of the Electrical Asset Condition Monitoring Training Course, participants will possess the technical knowledge and practical skills required to implement and manage electrical asset monitoring programs. They will be equipped to evaluate equipment health, apply diagnostic techniques, analyze condition data, and support reliability improvement initiatives for modern electrical infrastructure.

Duration

5 days

Who Should Attend

  • Electrical Engineers

  • Reliability Engineers

  • Asset Management Engineers

  • Maintenance Engineers

  • Condition Monitoring Specialists

  • Power System Engineers

  • Utility Engineers

  • Industrial Electrical Engineers

  • Substation Engineers

  • Testing and Commissioning Engineers

  • Electrical Technicians

  • Facility Engineers

  • Operations Engineers

  • Maintenance Supervisors

  • Transformer Specialists

  • Protection Engineers

  • Engineering Consultants

  • Asset Performance Professionals

  • Engineering Managers

  • Engineering Graduates

Course Objectives

  • Develop comprehensive knowledge of electrical asset condition monitoring principles and industrial applications.

  • Understand condition monitoring techniques used for transformers, motors, switchgear, cables, and generators.

  • Apply diagnostic methods to identify early signs of electrical equipment degradation and failure.

  • Learn thermal imaging techniques for detecting abnormal electrical conditions and equipment defects.

  • Understand insulation testing, partial discharge analysis, and electrical diagnostic procedures.

  • Analyze equipment condition data to support maintenance planning and reliability improvement decisions.

  • Develop skills for establishing effective condition monitoring programs based on asset criticality.

  • Evaluate online monitoring technologies and sensor-based solutions for electrical asset management.

  • Explore emerging technologies including AI diagnostics, IoT monitoring, and digital asset platforms.

  • Strengthen practical condition monitoring skills through assessments, case studies, and diagnostic exercises.

Course Outline

Module 1: Fundamentals of Electrical Asset Condition Monitoring

  • Introduction to electrical asset condition monitoring principles and applications

  • Importance of condition assessment in reliability-centered maintenance

  • Relationship between asset health, performance, and maintenance strategies

  • Overview of electrical equipment monitoring technologies

Module 2: Electrical Asset Health Assessment

  • Principles of electrical equipment condition evaluation methods

  • Asset health indicators and performance assessment techniques

  • Equipment degradation mechanisms and aging characteristics

  • Developing asset condition assessment frameworks

Module 3: Transformer Condition Monitoring

  • Transformer health assessment and diagnostic techniques

  • Dissolved gas analysis and transformer oil monitoring methods

  • Transformer insulation condition evaluation practices

  • Transformer failure prediction and maintenance strategies

Module 4: Motor Condition Monitoring

  • Electrical motor health assessment techniques

  • Motor current signature analysis and diagnostic applications

  • Insulation, bearing, and winding condition monitoring

  • Predictive maintenance approaches for rotating equipment

Module 5: Switchgear and Circuit Breaker Monitoring

  • Condition assessment methods for switchgear equipment

  • Circuit breaker performance monitoring techniques

  • Contact wear, insulation, and mechanical condition evaluation

  • Diagnostic testing for medium and high voltage equipment

Module 6: Cable and Distribution System Monitoring

  • Underground and industrial cable condition assessment

  • Insulation testing and cable diagnostic methods

  • Distribution network monitoring techniques

  • Identifying cable degradation and failure risks

Module 7: Advanced Diagnostic Technologies

  • Thermal imaging applications for electrical inspections

  • Partial discharge monitoring and analysis techniques

  • Online condition monitoring systems and sensors

  • Power quality monitoring for asset health evaluation

Module 8: Digital Condition Monitoring Solutions

  • Internet of Things applications in asset monitoring

  • Artificial intelligence-based condition assessment methods

  • Digital twins and intelligent asset management platforms

  • Remote monitoring and cloud-based diagnostic systems

Module 9: Condition Monitoring Data Analysis

  • Collecting and managing equipment condition data

  • Interpreting diagnostic reports and measurement results

  • Developing maintenance recommendations from monitoring information

  • Integrating condition monitoring with maintenance systems

Module 10: Practical Applications and Industry Case Studies

  • Industrial electrical asset monitoring examples

  • Utility and power system condition assessment applications

  • Analysis of equipment failures and monitoring solutions

  • Development of a complete condition monitoring strategy

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.

Course Duration 5 Days

Online Training Registration

Training Mode Platform Fee Enroll
Online Training Zoom/ Google Meet 900USD Register

Classroom/On-site Training Schedule

Course Date Location Fee Enroll
14/09/2026 to 18/09/2026 Nairobi 1,500 USD Register
14/09/2026 to 18/09/2026 Mombasa 1,750 USD Register
14/09/2026 to 18/09/2026 Dubai 4,900 USD Register
12/10/2026 to 16/10/2026 Nairobi 1,500 USD Register
12/10/2026 to 16/10/2026 Kigali 2,500 USD Register
12/10/2026 to 16/10/2026 Mombasa 1,750 USD Register
09/11/2026 to 13/11/2026 Nairobi 1,500 USD Register
09/11/2026 to 13/11/2026 Mombasa 1,750 USD Register
09/11/2026 to 13/11/2026 Nairobi 2,500 USD Register
14/12/2026 to 18/12/2026 Nairobi 1,500 USD Register
14/12/2026 to 18/12/2026 Kigali 2,500 USD Register
14/12/2026 to 18/12/2026 Dubai 4,900 USD Register
14/12/2026 to 18/12/2026 Mombasa 1,750 USD Register
11/01/2027 to 15/01/2027 Nairobi 1,500 USD Register
08/02/2027 to 12/02/2027 Nairobi 1,500 USD Register

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