A 5-day 4-credit Summer Course at Aalto University on Condition Monitoring and Diagnostics of Power Assets by Dr. Murtaza Hashmi
The IEEE Finland Section and IEEE Finland joint chapter IE13/PE31/IA34/PEL35, together with Aalto University, is offering an intensive 5-day 4-credit course on the Condition Monitoring and Diagnostics of Power Assets taught by Dr Murtaza Hashmi, a recognized Condition Monitoring Expert at Power Systems. The assessment of the course will be based on attendance, active participation in the discussions, and performance in Group Work and homework activities. It is worth mentioning that the course is free for our IEEE Members. Please note that this is an in-person course, and we only have a few places available. Participants are responsible for organizing and paying their own travel costs, accommodation, and food.
Please find the additional information as follows.
Course General Information:
This course will address state-of-the-art condition monitoring techniques used for different assets in electrical power systems. A brief overview of condition monitoring and diagnostics, associated monitoring parameters, and tools for analysis will be discussed. Special focus will be given on understanding advanced diagnostics technique of Partial Discharge (PD), its types and characteristic, detection principles and methods, analysis criteria and standards, PD signals propagation and attenuation, and calibration technique. The advanced condition monitoring and diagnostics techniques will be described for transformers, switchgears, power cables, and other electrical equipment installed in the substation including the details of pilot projects, case studies and real-time measurements. An overview of smart sensing infrastructure, its application for digital transformation, and digital substations will be carried out which build the basis of Industry 4.0 for advanced condition monitoring, diagnostics, and predictive maintenance applications in power systems.
Learning Outcomes:
Upon successful completion of this course, students will be able to:
- Explain the meaning of condition monitoring & diagnostics and its applications
- Explain PD monitoring techniques and standards, limits and advantages and disadvantages of online and offline PD monitoring, associated sensors, PD data analysis and interpretation for the condition assessment of electrical equipment.
- Explain different advanced condition monitoring & diagnostics systems for transformers, switchgears, power cables, and other electrical equipment installed in the substation.
- Develop condition monitoring plan to install advanced systems for the diagnostics and predictive maintenance of electrical power assets
- Explain elements of smart sensing infrastructure and develop strategy to implement it in power systems under Industry 4.0 initiative
Learning Resources:
A set of course presentation slides, and supporting materials based on publications, white papers, case studies, and technology brochures will be available.
Learning and Teaching Activities:
This course relies on lectures and interactive discussions as the primary delivery mechanism. A Group Work will be assigned to the students in the classroom to reinforce the theoretical concepts encountered in lectures and deliver brief presentation by each Group. In addition, a Home Work will be assigned to the students in the form of writing an essay to summaries the details of advanced condition monitoring systems for power assets to gauge their progress and understanding.
Assessment:
The assessment of the course will be based on attendance, active participation in the discussions, and performance in Group Work and homework activities.
Language:
The working language of the course is English.
Date and Time
Location
Hosts
Registration
- Start time: 19 Aug 2024 09:00 AM
- End time: 23 Aug 2024 05:00 PM
- All times are (UTC+03:00) Helsinki
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- Aalto University
- Otaniemi
- Espoo, Sodra Finlands Lan
- Finland
- Building: Maarintie 8
- Room Number: 2103
- Click here for Map
- Contact Event Hosts
- Co-sponsored by Aalto University
- Starts 09 February 2024 09:00 AM
- Ends 01 August 2024 11:59 PM
- All times are (UTC+03:00) Helsinki
- 0 in-person spaces left!
- No Admission Charge
Speakers
Murtaza Hashmi
Condition Monitoring and Diagnostics of Power Assets
This course will address state-of-the-art condition monitoring techniques used for different assets in electrical power systems. A brief overview of condition monitoring and diagnostics, associated monitoring parameters, and tools for analysis will be discussed. Special focus will be given on understanding advanced diagnostics technique of Partial Discharge (PD), its types and characteristic, detection principles and methods, analysis criteria and standards, PD signals propagation and attenuation, and calibration technique. The advanced condition monitoring and diagnostics techniques will be described for transformers, switchgears, power cables, and other electrical equipment installed in the substation including the details of pilot projects, case studies and real-time measurements. An overview of smart sensing infrastructure, its application for digital transformation, and digital substations will be carried out which build the basis of Industry 4.0 for advanced condition monitoring, diagnostics, and predictive maintenance applications in power systems.
Biography:
Dr. Murtaza Hashmi received Master’s Degree in electric power engineering from the Royal Institute of Technology (KTH) Stockholm, Sweden in 2001, and D.Sc. (Tech.) in condition monitoring and asset management of power assets from Aalto University, Finland in 2008. He worked as Power Distribution Specialist at ABB Oy Finland for 2 years. From 2010-2013, he worked as Senior Scientist with Energy Systems Knowledge Centre at VTT Technical Research Centre of Finland. Currently, he is working as Condition Monitoring Specialist at Power Systems, Saudi Aramco. His major interests are: reviewing and evaluating new technologies and innovation ideas to enhance reliability and extend life-time of High Voltage (HV) equipment; developing roadmap, deploying and implementing advanced intelligent technologies for remote, online and continuous condition monitoring of substation equipment to drive digital transformation in the future smart grid environment; and conducting Partial Discharge (PD) measurements for insulation diagnostics and predictive maintenance of HV equipment. He has delivered several keynote speeches, tutorials, and workshops as Invited Speaker in different conferences and forums at international level related to smart sensing applications for condition monitoring, diagnostic, and predictive maintenance. He has published more than 50 research articles in reputed refereed international journals and conferences. He is an active member of IEEE and GCC CIGRE.
Agenda
Course Agenda (19 – 23rd August 2024):
Day 1, August 19 (12:00 – 17:00)
PD Monitoring & Diagnostics in Electrical Equipment
- Understanding condition monitoring & diagnostics, its significance, associated parameters, and advanced tools for analysis.
- Partial Discharge (PD), its types & characteristic, detection principles & methods, analysis criteria and standards.
- PD signals propagation and attenuation, different types of noises or interferences and their elimination.
- Calibration of online PD monitoring system
Day August 20 (09:00 – 17:00)
Condition Monitoring & Diagnostics of Transformers
- Online Dissolved Gas Analysis (DGA) monitoring system
- Online drying & dehydrating breather systems
- Bushing monitoring system for bushing and winding health condition assessment
- Other monitoring systems based on PD measurements using ultrasonic and high frequency sensors
Day 3, August 21 (09:00 – 17:00)
Condition Monitoring & Diagnostics of Switchgears and Power Cables
- Online PD monitoring system for Gas Insulated Substations (GIS)
- Online asset monitoring systems for Air Insulated Substations (AIS)
- Condition monitoring systems for power cables
- PD monitoring & diagnostics case studies
Day 4, August 22 (09:00 – 17:00)
Condition Monitoring of Other Electrical Equipment
- PD monitoring in rotating machines
- Room-Temperature Vulcanizing (RTV) silicon rubber coating assessment for insulators, bushings and surge arresters
- Fault detection & localization system for overhead distribution lines
- Condition monitoring and predictive maintenance using advanced UV, optical and infrared imaging techniques
Day 5, August 23 (09:00 – 17:00)
Smart Sensing Infrastructure and Smart Grids
- Components of Industry 4.0 and its application in digital transformation
- Smart sensing infrastructure for smart grids
- Digital substations with advanced sensing technologies
- Group Work: Important elements of CM system – Sensors, data communication, data analysis, decision-making
- Explanation of Homework: An essay on advanced condition monitoring systems for transformers, switchgears, and power cables – Technology, implications, and challenges for implementation!