Application of LSTM Network with Multi-frequency Measurement Sequences in Electrical Tomography for Moisture Detection in Buildings
Fragment książki (Rozdział monografii pokonferencyjnej)
MNiSW
200
konferencja
| Status: | |
| Autorzy: | Kłosowski Grzegorz, Rymarczyk Tomasz, Kulisz Monika, Oleszek Michał, Niderla Konrad |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Wersja dokumentu: | Elektroniczna |
| Język: | angielski |
| Strony: | 658 - 659 |
| Web of Science® Times Cited: | 0 |
| Bazy: | Web of Science | Google Scholar | Crossref |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | 23rd ACM Conference on Embedded Networked Sensor Systems |
| Skrócona nazwa konferencji: | 23rd SenSys 2025 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 6 maja 2025 do 9 maja 2025 |
| Miasto konferencji: | Irvine |
| Państwo konferencji: | STANY ZJEDNOCZONE |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| Damp walls are a significant problem that affects not only historical buildings. The effects of moisture inside walls include premature degradation of the structure and paintwork as well as health hazards for people staying inside the rooms (fungi, microorganisms, allergens). To effectively remove moisture, it is necessary to identify the areas where it occurs. Tomography is the only nondestructive method that allows for imaging the interior of walls. It is not common due to the low image resolution [1]. The aim of the research presented is to present a new concept of impedance tomography, taking into account many measurement sequences at different frequencies of electric current. A neural network with LSTM (Long Short-Term Memory) layers was used to transform the measurements into images. A comparison of the results of the new approach proves the advantage of the multi-frequency method over the traditional method, which brings closer the breakthrough moment in the dissemination of tomography as the main method of imaging moisture in walls. |
