Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]

This dataset contains processed audio 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. There are two differe...

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Detalles Bibliográficos
Autores: Montes-Sánchez, Juan Manuel, Domínguez Morales, Juan Pedro, Vicente Díaz, Saturnino, Jiménez Fernández, Ángel Francisco
Tipo de recurso: conjunto de datos
Fecha de publicación:2025
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/167278
Acceso en línea:https://hdl.handle.net/11441/167278
https://doi.org/10.12795/11441/167278
Access Level:acceso abierto
Palabra clave:Neuromorphic
Microphone
Audio
Peristaltic Pump
Predictive Maintenance
Neuromórfico
Micrófono
Bomba peristáltica
Mantenimiento predictivo
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oai_identifier_str oai:idus.us.es:11441/167278
network_acronym_str ES
network_name_str España
repository_id_str
spelling Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]Audio neuromórfico para mantenimiento predictivo en bombas peristálticas [Dataset]Montes-Sánchez, Juan ManuelDomínguez Morales, Juan PedroVicente Díaz, SaturninoJiménez Fernández, Ángel FranciscoNeuromorphicMicrophoneAudioPeristaltic PumpPredictive MaintenanceNeuromórficoMicrófonoBomba peristálticaMantenimiento predictivoThis dataset contains processed audio 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. There are two different predictive maintenance scenarios. In the first one, 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). In the second scenario, air bubbles were introduced into the tube. This second scenario also has 3 classes: Class 1 is STOP (no pump running), class 2 is NORMAL (no air bubbles), and class 3 is BUBBLE (air bubbles present). A single microphone was used for all recordings. The .wav audio files were processed using a 64 channel Neuromorphic Auditory Sensor (NAS) into .aedat files, which are the present in this dataset. This neuromorphic audio data were also converted into cochleogram images using the software pyNAVIS, and they are also present in this format (.png files).There is one folder for each of the two scenarios (aging and bubble). Inside those folders there are 3 subfolders, one for each data type (AEDAT, PNG and WAV). For WAV and AEDAT, 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.wav is the sample number 8, which corresponds to class 3 tagged data. PNG cochleogram images represent 500ms audio time each and are named after their source AEDAT file followed by their starting time mark in microseconds.Arquitectura y Tecnología de ComputadoresTEP108: Robótica y Tecnología de computadoresAgencia Estatal de Investigación. EspañaMinisterio de Ciencia, Innovación y Universidades (MICINN). EspañaMontes-Sánchez, Juan Manuel2025info:eu-repo/semantics/datasetDatasetImageSoundimage/pngapplication/octet-streamapplication/ziptext/plainhttps://hdl.handle.net/11441/167278https://doi.org/10.12795/11441/167278reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésMontes-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/10.12795/11441/162880https://hdl.handle.net/11441/162880PID2023-149777OB-I00info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1672782026-06-17T12:51:07Z
dc.title.none.fl_str_mv Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
Audio neuromórfico para mantenimiento predictivo en bombas peristálticas [Dataset]
title Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
spellingShingle Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
Montes-Sánchez, Juan Manuel
Neuromorphic
Microphone
Audio
Peristaltic Pump
Predictive Maintenance
Neuromórfico
Micrófono
Bomba peristáltica
Mantenimiento predictivo
title_short Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
title_full Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
title_fullStr Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
title_full_unstemmed Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
title_sort Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]
dc.creator.none.fl_str_mv Montes-Sánchez, Juan Manuel
Domínguez Morales, Juan Pedro
Vicente Díaz, Saturnino
Jiménez Fernández, Ángel Francisco
author Montes-Sánchez, Juan Manuel
author_facet Montes-Sánchez, Juan Manuel
Domínguez Morales, Juan Pedro
Vicente Díaz, Saturnino
Jiménez Fernández, Ángel Francisco
author_role author
author2 Domínguez Morales, Juan Pedro
Vicente Díaz, Saturnino
Jiménez Fernández, Ángel Francisco
author2_role author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnología de Computadores
TEP108: Robótica y Tecnología de computadores
Agencia Estatal de Investigación. España
Ministerio de Ciencia, Innovación y Universidades (MICINN). España
Montes-Sánchez, Juan Manuel
dc.subject.none.fl_str_mv Neuromorphic
Microphone
Audio
Peristaltic Pump
Predictive Maintenance
Neuromórfico
Micrófono
Bomba peristáltica
Mantenimiento predictivo
topic Neuromorphic
Microphone
Audio
Peristaltic Pump
Predictive Maintenance
Neuromórfico
Micrófono
Bomba peristáltica
Mantenimiento predictivo
description This dataset contains processed audio 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. There are two different predictive maintenance scenarios. In the first one, 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). In the second scenario, air bubbles were introduced into the tube. This second scenario also has 3 classes: Class 1 is STOP (no pump running), class 2 is NORMAL (no air bubbles), and class 3 is BUBBLE (air bubbles present). A single microphone was used for all recordings. The .wav audio files were processed using a 64 channel Neuromorphic Auditory Sensor (NAS) into .aedat files, which are the present in this dataset. This neuromorphic audio data were also converted into cochleogram images using the software pyNAVIS, and they are also present in this format (.png files).
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
Dataset
Image
Sound
format dataset
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/167278
https://doi.org/10.12795/11441/167278
url https://hdl.handle.net/11441/167278
https://doi.org/10.12795/11441/167278
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv 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
https://hdl.handle.net/11441/162880
PID2023-149777OB-I00
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv image/png
application/octet-stream
application/zip
text/plain
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869411630670938112
score 15,811543

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