Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters

Tommaso Barbariol; Davide Masiero; Enrico Feltresi; Gian Antonio Susto

Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters

Machine Learning 2023-01-03 v1 Artificial Intelligence

Authors: Tommaso Barbariol , Davide Masiero , Enrico Feltresi , Gian Antonio Susto

Abstract

An Anomaly Detection (AD) System for Self-diagnosis has been developed for Multiphase Flow Meter (MPFM). The system relies on machine learning algorithms for time series forecasting, historical data have been used to train a model and to predict the behavior of a sensor and, thus, to detect anomalies.

Keywords

anomaly detection time series forecasting multiphase flow meter machine learning self-diagnosis sensor

Cite

@article{arxiv.2301.00014,
  title  = {Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters},
  author = {Tommaso Barbariol and Davide Masiero and Enrico Feltresi and Gian Antonio Susto},
  journal= {arXiv preprint arXiv:2301.00014},
  year   = {2023}
}

Related papers

View all related →