RT info:eu-repo/semantics/article
T1 A Fault Detection System for a Geothermal Heat Exchanger Sensor Based on Intelligent Techniques
A1 Alaiz Moretón, Héctor
A1 Castejón Limas, Manuel
A1 Casteleiro Roca, José Luis
A1 Jove, Esteban
A1 Fernández Robles, Laura
A1 Calvo Rolle, José Luis
A2 Ingenieria de Sistemas y Automatica
K1 Ingeniería de sistemas
K1 Fault detection
K1 Geothermal heat exchanger
K1 Random decision forests
K1 Gradient boostings
K1 Extremely randomized trees
K1 Adaptive boosting
K1 K-nearest neighbors
K1 Shallow neural networks
K1 3313 Tecnología E Ingeniería Mecánicas
AB [EN] This paper proposes a methodology for dealing with an issue of crucial practical importance in real engineering systems such as fault detection and recovery of a sensor. The main goal is to define a strategy to identify a malfunctioning sensor and to establish the correct measurement value in those cases. As study case, we use the data collected from a geothermal heat exchanger installed as part of the heat pump installation in a bioclimatic house. The sensor behaviour is modeled by using six different machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks. The achieved results suggest that this methodology is a very satisfactory solution for this kind of systems.
PB MDPI
LK https://hdl.handle.net/10612/21141
UL https://hdl.handle.net/10612/21141
NO Aláiz-Moretón, H., Castejón-Limas, M., Casteleiro-Roca, J.-L., Jove, E., Fernández Robles, L., & Calvo-Rolle, J. L. (2019). A fault detection system for a geothermal heat exchanger sensor based on intelligent techniques. Sensors (Switzerland), 19(12). https://doi.org/10.3390/S19122740
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 26-jun-2024