by Alessandro Capo | Mar 2, 2022 | AI, Algorithms, Artificial Intelligence, Big Data, Condition Monitoring, Data Analysis, Data Engineering, Deep Learning, digital, Enegy Transition, Energy, Energy Transition, Health Index, Power Transformers, Predictive Maintenance, Sustainability
An interesting post on Linkedin has caught my attention in recent weeks. It was a contribution from CESI’s Innovation Manager who expressed a concept of enormous impact from my point of view: “High voltage engineering and technology do not scale: you...
by Alessandro Capo | Feb 3, 2022 | AI, Algorithms, Article, Artificial Intelligence, Big Data, Condition Monitoring, Data Engineering, digital, Enegy Transition, Energy, Energy Transition, Health Index, Moisture Measurements, News, Power Transformers, Predictive Maintenance, Product upgrade, Test engineering, Transformers Oil
The transformer health index (HI) theory is one of the most debated approaches in the power industry. It is widely endorsed in CIGRE brochures with various methodologies, approaches, and recommendations. This article is not a technical discussion, instead an addressal...
by Alessandro Capo | Jan 10, 2022 | AI, Article, Artificial Intelligence, Condition Monitoring, digital, Enegy Transition, Health Index, Power Transformers, Predictive Maintenance
Every now and then I think it makes you stop and think without being overwhelmed by the prevailing trends… In early December of 2021, we had the great opportunity to be exhibitors in the Hub Initiate of the ENLIT international fair dedicated to innovative startups...
by Seetalabs | Dec 1, 2021 | AI, Article, Artificial Intelligence, Condition Monitoring, digital, Enegy Transition, Health Index, Power Transformers, Predictive Maintenance
Electricity is an integral part of our life and its sudden unavailability can be highly disryptive. Therefore, power and energy companies strives to maintain grid integrity and service continuity. An abrupt power outage leads to market backlash, harsh regulatory...
by Seetalabs | Nov 25, 2021 | AI, Artificial Intelligence, Condition Monitoring, Data Analysis, Data Engineering, Power Transformers, Predictive Maintenance
In April 2020, a utility registers ultimate failure of a 100 MVA, 100/110 kV generator step-up (GSU) transformer. Built in 1980, the transformer was prone to particularly high level of hydrogen, ethylene, and acetylene presence in oil. The utility recognizes it as a...
by Seetalabs | Mar 8, 2021 | AI, Algorithms, Article, Artificial Intelligence, Condition Monitoring, Data Analysis, Data Engineering, Deep Learning, Health Index, Machine Learning, News, Power Transformers, Predictive Maintenance, Transformers Oil
Seetalabs is very excited to launch two new add-ons for existing and new users of their Ronin dahsboard to track the behavior of transformer fleets. What is Ronin? We are reinventing artificial intelligence (AI) applications for reliability-centered actions in...