Name
Abstract | ||
|---|---|---|
Thin-film sensors surfaces are becoming popular to collect data in several specific and complex processes, namely plastic injection or metal stamping, allowing the digitization of such processes through the use of Internet of Things technologies. A particular challenge in such thin-film sensors surfaces is the data acquisition and signal conditioning system, which implementation is complex due to the characteristics of these sensors (e.g., low amplitude and noisy signals), but even more complex when implemented in real industrial processes, which are subject to harsh conditions, namely noise, dirt and aggressive elements. This work describes a modular data acquisition and signals conditioning system for thin-film sensors surfaces, meeting the requirements of scalability, robustness and low-cost, meaning that it can be easily expanded according to the number of sensors required for the application scenario. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ISIE45063.2020.9152518 | 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) |
Keywords | DocType | ISSN |
Data Acquisition and Signal Conditioning,Thin-film Sensors Surfaces,Industry 4.0 | Conference | 2163-5137 |
ISBN | Citations | PageRank |
978-1-7281-5636-1 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nelson Rodrigues | 1 | 25 | 4.13 |
| José Lima | 2 | 0 | 0.34 |
| Pedro João Rodrigues | 3 | 0 | 0.34 |
| José Augusto Carvalho | 4 | 0 | 0.34 |
| Jorge Laranjeira | 5 | 0 | 0.34 |
| Wellington Maidana | 6 | 0 | 0.34 |
| Paulo Leitao | 7 | 102 | 16.48 |