The aim of the project is to develop methods for automated fault-detection of ventilation units’ heat recovery and filters and assessment the faults’ impact on energy cost and indoor climate. Machine learning algorithms with rule-based fault detection are tested and methods for practical implementations are investigated.
| Project code | LEP19101 |
| Start date | December 16, 2019 |
| End date | September 30, 2020 |
| Project category | Contract |
| Lead | Martin Thalfeldt |
| Personnel | Hossein Alimohammadi, Juri Belikov, Eduard Petlenkov, Kristina Vassiljeva, Kadri Umbleja, Aleksei Tepljakov, Jarek Kurnitski |
| Partners | Nearly Zero Energy Buildings Research Group, DCEA, TalTech |
| Funding | Ruut8 OÜ |
| Project link | https://www.etis.ee/Portal/projects/Display/24a57b6a-d63a-45c1-8754-7ce545e6678b?lang=ENG |