This research addresses a sensor fault detection and recovery methodology oriented to a real system as can be a geothermal heat exchanger installed as part of the heat pump installation at a bioclimatic house. The main aim is to stablish the procedure to detect the anomaly over a sensor and recover the value when it occurs. Therefore, some experiments applying a Multi-layer Perceptron (MLP) regressor, as modelling technique, have been made with satisfactory results in general terms. The correct election of the input variables is critical to get a robust model, specially, those features based on the sensor values on the previous state.
CITATION STYLE
Alaiz-Moretón, H., Casteleiro-Roca, J. L., Robles, L. F., Jove, E., Castejón-Limas, M., & Calvo-Rolle, J. L. (2018). Sensor fault detection and recovery methodology for a geothermal heat exchanger. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10870 LNAI, pp. 171–184). Springer Verlag. https://doi.org/10.1007/978-3-319-92639-1_15
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