Acceleration Datasets: Difference between revisions
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== Resources == | == Resources == | ||
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<li>Datasets | <li>Datasets available in [https://github.com/AI-REDGIO-5-0/E2Mech_DataSet GitHub]</li> | ||
<li>Provided by [https://dei.unibo.it/en/research/research-groups/actema ACTEMA]</li> | <li>Provided by [https://dei.unibo.it/en/research/research-groups/actema ACTEMA]</li> | ||
</ul> | </ul> | ||
Revision as of 11:18, 31 October 2025
Acceleration datasets for anomaly detection and predictive diagnosis in industrial automation.
Asset Description
The asset consists of datasets containing accelerations (along three axes) measured by means of a sensor board while the AI-REDGIO 5.0 E2mech experiment was running.
Asset Details
Dataset Information
Each dataset is represented in a csv file, where each column contains the acceleration measured for a time horizon equal to 4 times the mechanism's rotating period. Also, this data corresponds to a given angular speed and a healthy or faulty condition. The healthy and faulty information is included (in two separate datasets). This corresponds to different control algorithms adopted to steer the experiment mechanism. Conditions corresponding to the mechanism running at different angular speeds are provided (each with its own healthy and faulty scenario). All the information concerning the axis along which the measurement has been taken, the system’s angular speed, and the healthy or faulty situation is provided in the file name.
Usage
We provide a set of files concerning a pretty specific system’s condition (in terms of speed, measurements, healthiness), so that the interested user can either perform analysis, grouping them as needed (e.g., by selecting only a given acceleration axis or a system’s speed) and without the need of downloading a huge file (e.g. in json format) to be then parsed and split according to the desired work of analysis. In this respect, given the description of the data above, it should be pretty straightforward to import the files in one’s preferred data analytics tool (python, Matlab, R, etc…) and test condition monitoring and anomaly detection algorithms.
Maturity
The complete datasets concerning the 2nd iteration of the E2Mech experiment in the AI-REDGIO 5.0 project has been completed in September.
Licence
Open source
Resources
Acknowledgement
This work was funded by AI REDGIO 5.0 (101092069). The dataset has been created in the context of the AI REDGIO 5.0 E2Mech Experiment.