Computational Engineering Commons^™

Zechipc: Time Series Interpolation Method Based On Lebesgue Sampling, Luis Miralles-Pechuán, Muhammad Atif Qureshi, Matthieu Bellucci, Brian Mac Namee

Books/Book Chapters

In this paper, we present an interpolation method based on Lebesgue sampling that could help to develop systems based time series more efficiently. Our methods can transmit times series, frequently used in health monitoring, with the same level of accuracy but using much fewer data. Our method is based in Lebesgue sampling, which collects information depending on the values of the signal (e.g. the signal output is sampled when it crosses specific limits). Lebesgue sampling contains additional information about the shape of the signal in-between two sampled points. Using this information would allow generating an interpolated signal closer to the …

Valve Health Identification Using Sensors And Machine Learning Methods, Muhammad Atif Qureshi, Luis Miralles-Pechuán, Wood, Galway Technology Park, Parkmore, Galway, Ireland, Brian Mac Namee

Books/Book Chapters

Predictive maintenance models attempt to identify developing issues with industrial equipment before they become critical. In this paper, we describe both supervised and unsupervised approaches to predictive maintenance for subsea valves in the oil and gas industry. The supervised approach is appropriate for valves for which a long history of operation along with manual assessments of the state of the valves exists, while the unsupervised approach is suitable to address the cold start problem when new valves, for which we do not have an operational history, come online.

For the supervised prediction problem, we attempt to distinguish between healthy and …