Dataset
Peristaltic pump aging detection dataset
Alternative title | Dataset para detección de envejecimiento de bombas peristálticas |
Author/s | Montes-Sánchez, Juan Manuel
Uwate, Yoko Nishio, Yoshifumi Vicente Díaz, Saturnino Jiménez Fernández, Ángel Francisco |
Data curator | Montes-Sánchez, Juan Manuel |
Department | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Language (ISO) | English (eng) |
Diffusion date | 2024-09-25 |
Deposit Date | 2024-09-25 |
Creation date | 2023-06-28 |
Version | v. 1.0 |
Abstract | This dataset contains samples coming from a hydraulic block from a biomedical equipment. The block mounts 3 Thomas SR10/30 DC standard perisltaltic pumps, which were filled with distilled water. Only one pump was running ... This dataset contains samples coming from a hydraulic block from a biomedical equipment. The block mounts 3 Thomas SR10/30 DC standard perisltaltic pumps, which were filled with distilled water. Only one pump was running at the same time during these recordings, always at maximum constant speed. The cassettes of the pumps were changed before each recording. We used cassettes with 2 different levels of degradation: NEW (unused) and OLD (lifetime already expired). We defined 3 different classes: Class 1 is STOP (no pump running), class 2 is NEW (one pump running with a new cassette), and class 3 is OLD (one pump running with an old cassette). The classified samples were recorded using several sensors: 3 accelerometers, 1 gyroscope, 1 magnetometer and 1 microphone. All data were recorded at the same time at the maximum available frequency using the device "ST SensorTile.box". The raw data has already been processed into sepparate different .csv files (.wav files for audio) using python code. |
Content | Each sensor has its own folder. The sensor folder name starts with ACC for accelerometer data, GYRO for gyroscope data, MAG for magnetometer data or MIC for microphone data. After that, the name of the sensor. At the end, ... Each sensor has its own folder. The sensor folder name starts with ACC for accelerometer data, GYRO for gyroscope data, MAG for magnetometer data or MIC for microphone data. After that, the name of the sensor. At the end, sampling frequency in Hz. For example: ACC_LISDW12_1600Hz folder contains data for the accelerometer named LISDW12 at a sampling rate of 1600Hz. Each sensor folder contains 17 .csv files except for the microphone folder, which contains 17 .wav files. Each file is a unique sample tagged with one class (1, 2 or 3). At the end of each filename this class is also included. For example, 0008_03.csv is the sample number 8, which corresponds to class 3 tagged data. |
Funding agencies | Agencia Estatal de Investigación. España Ministerio de Ciencia, Innovación y Universidades (MICINN). España |
Project ID. | PID2023-149777OB-I00 |
Dataset type | Datos numéricos, Grabaciones sonoras |
Citation | Montes-Sánchez, J.M., Uwate, Y.,...,Jiménez Fernández, Á.F. (2024). Peristaltic pump aging detection dataset. idUS (Depósito de Investigación de la Universidad de Sevilla). https://doi.org/10.12795/11441/162880. |
Files | Size | Format | View | Description |
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Peristaltic pump aging detection ... | 186.0Mb | [application/zip] | This document is not available in full text until 2025-07-14 . For more information contact idus@us.es. | |
Readme_peristaltic.txt | 11.33Kb | [Text file] | This document is not available in full text until 2025-07-14 . For more information contact idus@us.es. | |