Characterization & Anomaly Detection in Radio Sensors: Algorithms for real-time fault detection and classification
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Engineering mathematics and computational science (MPENM), MSc
Publicerad
2024
Författare
Liljenzin, Oscar
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
In the ever-evolving field of radio technology, accurate sensor readings are a necessity.
Faults in sensors can be a costly endeavour. Thus, it is interesting to explore the
possibility of automatic fault detection using sensor readings. First different types
of faults that occur in radion sensors are modeled. Then different algorithms for
fault detection were implemented and evaluated. From this evaluation, it was found
that algorithms based on simple heuristics and statistics can in most cases, perform
similarly or even better than more advanced machine learning methods.