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100+ datasets found
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Cite
Cristian Axenie; Stefano Bortoli (2020). Predictive maintenance dataset. [Dataset]. http://doi.org/10.5281/zenodo.3653909

Predictive maintenance dataset.

3 scholarly articles cite this dataset (View in Google Scholar)
zipAvailable download formats
Dataset updated
Feb 7, 2020
Dataset provided by
Huawei Munich Research Center
Authors
Cristian Axenie; Stefano Bortoli
Description

Public (anonymized) predictive maintenance datasets from Huawei Munich Research Center.

Datasets from a variety of IoT sensors for predictive maintenance in elevator industry. The data is useful for predictive maintenance of elevators doors in order to reduce unplanned stops and maximizing equipment life cycle.

The dataset contains operation data, in the form of timeseries sampled at 4Hz in high-peak and evening elevator usage in a building (between 16:30 and 23:30). For an elevator car door the system we consider: Electromechanical sensors (Door Ball Bearing Sensor), Ambiance (Humidity) and Physics (Vibration).

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