BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Helsinki BEGIN:DAYLIGHT DTSTART:20240331T040000 TZOFFSETFROM:+0200 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20241027T030000 TZOFFSETFROM:+0300 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250405T095749Z UID:7923D2F5-6D4D-40CC-8142-163D65AC9E5A DTSTART;TZID=Europe/Helsinki:20240819T090000 DTEND;TZID=Europe/Helsinki:20240823T170000 DESCRIPTION:The IEEE Finland Section and IEEE Finland joint chapter IE13/PE 31/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 Ex pert at Power Systems. The assessment of the course will be based on atten dance\, active participation in the discussions\, and performance in Group Work and homework activities. It is worth mentioning that the course is f ree for our IEEE Members. Please note that this is an in-person course\, a nd we only have a few places available. Participants are responsible for o rganizing and paying their own travel costs\, accommodation\, and food.\n\ nPlease find the additional information as follows.\n\nCourse General Info rmation:\n\nThis 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 Discha rge (PD)\, its types and characteristic\, detection principles and methods \, analysis criteria and standards\, PD signals propagation and attenuatio n\, and calibration technique. The advanced condition monitoring and diagn ostics techniques will be described for transformers\, switchgears\, power cables\, and other electrical equipment installed in the substation inclu ding the details of pilot projects\, case studies and real-time measuremen ts. An overview of smart sensing infrastructure\, its application for digi tal transformation\, and digital substations will be carried out which bui ld the basis of Industry 4.0 for advanced condition monitoring\, diagnosti cs\, and predictive maintenance applications in power systems.\n\nLearning Outcomes:\n\nUpon successful completion of this course\, students will be able to:\n\n- Explain the meaning of condition monitoring & diagnostics a nd its applications\n- Explain PD monitoring techniques and standards\, li mits and advantages and disadvantages of online and offline PD monitoring\ , associated sensors\, PD data analysis and interpretation for the conditi on assessment of electrical equipment.\n- Explain different advanced condi tion monitoring & diagnostics systems for transformers\, switchgears\, pow er cables\, and other electrical equipment installed in the substation.\n- Develop condition monitoring plan to install advanced systems for the dia gnostics and predictive maintenance of electrical power assets\n- Explain elements of smart sensing infrastructure and develop strategy to implement it in power systems under Industry 4.0 initiative\n\nLearning Resources:\ n\nA set of course presentation slides\, and supporting materials based on publications\, white papers\, case studies\, and technology brochures wil l be available.\n\nLearning and Teaching Activities:\n\nThis 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 reinfo rce the theoretical concepts encountered in lectures and deliver brief pre sentation 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 adva nced condition monitoring systems for power assets to gauge their progress and understanding.\n\nAssessment:\n\nThe assessment of the course will be based on attendance\, active participation in the discussions\, and perfo rmance in Group Work and homework activities.\n\nLanguage:\n\nThe working language of the course is English.\n\nCo-sponsored by: Aalto University\n\ nSpeaker(s): Murtaza Hashmi \n\nAgenda: \nCourse Agenda (19 – 23rd Augus t 2024):\n\nDay 1\, August 19 (12:00 – 17:00)\n\nPD Monitoring & Diagnos tics in Electrical Equipment\n\n- Understanding condition monitoring & dia gnostics\, its significance\, associated parameters\, and advanced tools f or analysis.\n- Partial Discharge (PD)\, its types & characteristic\, dete ction principles & methods\, analysis criteria and standards.\n- PD signal s propagation and attenuation\, different types of noises or interferences and their elimination.\n- Calibration of online PD monitoring system\n\nD ay August 20 (09:00 – 17:00)\n\nCondition Monitoring & Diagnostics of Tr ansformers\n\n- Online Dissolved Gas Analysis (DGA) monitoring system\n- O nline drying & dehydrating breather systems\n- Bushing monitoring system f or bushing and winding health condition assessment\n- Other monitoring sys tems based on PD measurements using ultrasonic and high frequency sensors\ n\nDay 3\, August 21 (09:00 – 17:00)\n\nCondition Monitoring & Diagnosti cs of Switchgears and Power Cables\n\n- Online PD monitoring system for Ga s Insulated Substations (GIS)\n- Online asset monitoring systems for Air I nsulated Substations (AIS)\n- Condition monitoring systems for power cable s\n- PD monitoring & diagnostics case studies\n\nDay 4\, August 22 (09:00 – 17:00)\n\nCondition Monitoring of Other Electrical Equipment\n\n- PD m onitoring in rotating machines\n- Room-Temperature Vulcanizing (RTV) silic on rubber coating assessment for insulators\, bushings and surge arresters \n- Fault detection & localization system for overhead distribution lines\ n- Condition monitoring and predictive maintenance using advanced UV\, opt ical and infrared imaging techniques\n\nDay 5\, August 23 (09:00 – 17:00 )\n\nSmart Sensing Infrastructure and Smart Grids\n\n- Components of Indus try 4.0 and its application in digital transformation\n- Smart sensing inf rastructure for smart grids\n- Digital substations with advanced sensing t echnologies\n- Group Work: Important elements of CM system – Sensors\, d ata communication\, data analysis\, decision-making\n- Explanation of Home work: An essay on advanced condition monitoring systems for transformers\, switchgears\, and power cables – Technology\, implications\, and challe nges for implementation!\n\nRoom: 2103\, Bldg: Maarintie 8\, Aalto Univers ity\, Otaniemi\, Espoo\, Sodra Finlands Lan\, Finland LOCATION:Room: 2103\, Bldg: Maarintie 8\, Aalto University\, Otaniemi\, Esp oo\, Sodra Finlands Lan\, Finland ORGANIZER:Mahdi.Pourakbari@ieee.org SEQUENCE:31 SUMMARY:A 5-day 4-credit Summer Course at Aalto University on Condition Mon itoring and Diagnostics of Power Assets by Dr. Murtaza Hashmi URL;VALUE=URI:https://events.vtools.ieee.org/m/405191 X-ALT-DESC:Description: <br /><p>The IEEE Finland Section and IEEE Finland joint chapter IE13/PE31/IA34/PEL35\, together with Aalto University\, is o ffering an intensive 5-day 4-credit course on the Condition Monitoring and Diagnostics of Power Assets taught by Dr Murtaza Hashmi\, a recognized Co ndition Monitoring Expert at Power Systems. The assessment of the course w ill be based on attendance\, active participation in the discussions\, and performance in Group Work and homework activities. It is worth mentioning that the <span class="il">course is&nbsp\;<strong>free</strong></span><st rong>&nbsp\;</strong>for our<strong>&nbsp\;IEEE Members</strong>. Please<s trong>&nbsp\;note that</strong> this is an <strong><span style="color: #e6 7e23\;">in-person</span></strong> course\, and we only have <strong>a few places</strong> available. Participants <span style="color: #e67e23\;"><st rong>are responsible</strong></span>&nbsp\;for organizing and paying their own travel costs\, accommodation\, and food.&nbsp\;</p>\n<p>Please find t he additional information as follows.&nbsp\;&nbsp\;</p>\n<p><span style="t ext-decoration: underline\;"><strong>Course General Information:</strong>< /span></p>\n<p>This course will address state-of-the-art condition monitor ing techniques used for different assets in electrical power systems. A br ief overview of condition monitoring and diagnostics\, associated monitori ng parameters\, and tools for analysis will be discussed. Special focus wi ll be given on understanding advanced diagnostics technique of Partial Dis charge (PD)\, its types and characteristic\, detection principles and meth ods\, analysis criteria and standards\, PD signals propagation and attenua tion\, and calibration technique. The advanced condition monitoring and di agnostics techniques will be described for transformers\, switchgears\, po wer cables\, and other electrical equipment installed in the substation in cluding the details of pilot projects\, case studies and real-time measure ments. An overview of smart sensing infrastructure\, its application for d igital transformation\, and digital substations will be carried out which build the basis of Industry 4.0 for advanced condition monitoring\, diagno stics\, and predictive maintenance applications in power systems.</p>\n<p> <strong>Learning Outcomes:</strong></p>\n<p>Upon successful completion of this course\, students will be able to:</p>\n<ul>\n<li>Explain the meaning of condition monitoring &amp\; diagnostics and its applications</li>\n<li >Explain PD monitoring techniques and standards\, limits and advantages an d disadvantages of online and offline PD monitoring\, associated sensors\, PD data analysis and interpretation for the condition assessment of elect rical equipment.</li>\n<li>Explain different advanced condition monitoring &amp\; diagnostics systems for transformers\, switchgears\, power cables\ , and other electrical equipment installed in the substation.</li>\n<li>De velop condition monitoring plan to install advanced systems for the diagno stics and predictive maintenance of electrical power assets</li>\n<li>Expl ain elements of smart sensing infrastructure and develop strategy to imple ment it in power systems under Industry 4.0 initiative</li>\n</ul>\n<p><st rong>Learning Resources:</strong></p>\n<p>A set of course presentation sli des\, and supporting materials based on publications\, white papers\, case studies\, and technology brochures will be available.</p>\n<p><strong>Lea rning and Teaching Activities:</strong></p>\n<p>This course relies on lect ures and interactive discussions as the primary delivery mechanism. A Grou p Work will be assigned to the students in the classroom to reinforce the theoretical concepts encountered in lectures and deliver brief presentatio n by each Group. In addition\, a Home Work will be assigned to the student s in the form of writing an essay to summaries the details of advanced con dition monitoring systems for power assets to gauge their progress and und erstanding.</p>\n<p><strong>Assessment:</strong></p>\n<p>The assessment of the course will be based on attendance\, active participation in the disc ussions\, and performance in Group Work and homework activities.</p>\n<p>< span style="text-decoration: underline\;"><strong>Language:</strong></span ></p>\n<p>The working language of the course is&nbsp\;<strong>English</str ong>.</p><br /><br />Agenda: <br /><p><strong>Course Agenda (19 &ndash\; 2 3<sup>rd</sup> August 2024):</strong></p>\n<p><strong>Day 1\, August 19 (1 2:00 &ndash\; 17:00)</strong></p>\n<p><strong><em>PD Monitoring &amp\; Dia gnostics in Electrical Equipment</em></strong></p>\n<ul>\n<li>Understandin g condition monitoring &amp\; diagnostics\, its significance\, associated parameters\, and advanced tools for analysis.</li>\n<li>Partial Discharge (PD)\, its types &amp\; characteristic\, detection principles &amp\; metho ds\, analysis criteria and standards.</li>\n<li>PD signals propagation and attenuation\, different types of noises or interferences and their elimin ation.</li>\n<li>Calibration of online PD monitoring system</li>\n</ul>\n< p><strong>Day August 20 (09:00 &ndash\; 17:00)</strong></p>\n<p><strong><e m>Condition Monitoring &amp\; Diagnostics of Transformers</em></strong></p >\n<ul>\n<li>Online Dissolved Gas Analysis (DGA) monitoring system</li>\n< li>Online drying &amp\; dehydrating breather systems</li>\n<li>Bushing mon itoring system for bushing and winding health condition assessment</li>\n< li>Other monitoring systems based on PD measurements using ultrasonic and high frequency sensors</li>\n</ul>\n<p><strong>Day 3\, August 21 (09:00 &n dash\; 17:00)</strong></p>\n<p><strong>&nbsp\;</strong><strong><em>Conditi on Monitoring &amp\; Diagnostics of Switchgears and Power Cables</em></str ong></p>\n<ul>\n<li>Online PD monitoring system for Gas Insulated Substati ons (GIS)</li>\n<li>Online asset monitoring systems for Air Insulated Subs tations (AIS)</li>\n<li>Condition monitoring systems for power cables</li> \n<li>PD monitoring &amp\; diagnostics case studies</li>\n</ul>\n<p><stron g>Day 4\, August 22 (09:00 &ndash\; 17:00)</strong></p>\n<p><strong>&nbsp\ ;</strong><strong><em>Condition Monitoring of Other Electrical Equipment</ em></strong></p>\n<ul>\n<li>PD monitoring in rotating machines</li>\n<li>R oom-Temperature Vulcanizing (RTV) silicon rubber coating assessment for in sulators\, bushings and surge arresters</li>\n<li>Fault detection &amp\; l ocalization system for overhead distribution lines</li>\n<li>Condition mon itoring and predictive maintenance using advanced UV\, optical and infrare d imaging techniques</li>\n</ul>\n<p><strong>Day 5\, August 23 (09:00 &nda sh\; 17:00)</strong></p>\n<p><strong><em>Smart Sensing Infrastructure and Smart Grids</em></strong></p>\n<ul>\n<li>Components of Industry 4.0 and it s application in digital transformation</li>\n<li>Smart sensing infrastruc ture for smart grids</li>\n<li>Digital substations with advanced sensing t echnologies</li>\n<li><u>Group Work: </u>Important elements of CM system & ndash\; Sensors\, data communication\, data analysis\, decision-making</li >\n<li><u>Explanation of Homework</u>: An essay on advanced condition moni toring systems for transformers\, switchgears\, and power cables &ndash\; Technology\, implications\, and challenges for implementation!</li>\n</ul> END:VEVENT END:VCALENDAR