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The MetroPT dataset for predictive maintenance.


ABSTRACT: The paper describes the MetroPT data set, an outcome of a Predictive Maintenance project with an urban metro public transportation service in Porto, Portugal. The data was collected in 2022 to develop machine learning methods for online anomaly detection and failure prediction. Several analog sensor signals (pressure, temperature, current consumption), digital signals (control signals, discrete signals), and GPS information (latitude, longitude, and speed) provide a framework that can be easily used and help the development of new machine learning methods. This dataset contains some interesting characteristics and can be a good benchmark for predictive maintenance models.

SUBMITTER: Veloso B 

PROVIDER: S-EPMC9747912 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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The MetroPT dataset for predictive maintenance.

Veloso Bruno B   Ribeiro Rita P RP   Gama João J   Pereira Pedro Mota PM  

Scientific data 20221213 1


The paper describes the MetroPT data set, an outcome of a Predictive Maintenance project with an urban metro public transportation service in Porto, Portugal. The data was collected in 2022 to develop machine learning methods for online anomaly detection and failure prediction. Several analog sensor signals (pressure, temperature, current consumption), digital signals (control signals, discrete signals), and GPS information (latitude, longitude, and speed) provide a framework that can be easily  ...[more]

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