by Seetalabs | Nov 5, 2022 | AI, Data Engineering, Health Index, R&D
All data is biased. But not all bias comes from data alone. Join a new perspective of research Whenever we talk about data, we talk about bias that may come with data-driven decisions. As soon as artificial intelligence (AI) enters this mix, the implications could be...
by Alessandro Capo | Apr 27, 2022 | AI, Article, Artificial Intelligence, Condition Monitoring, Data Analysis, Data Engineering, Enegy Transition, Energy, Energy Transition, Health Index, Machine Learning, Power Transformers, Predictive Maintenance, Product upgrade, Transformers Oil
While Ronin continues to support important operators in the power and energy sector, we did learn some meaningful lessons about the global electrical transformers maintenance market. Four Main Trends in Transformers Maintenance Market Strategic investments in...
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 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... 
