2025-01-232025-01-232024-09-282025-01-23Montes-Sánchez, J.M., Domínguez Morales, J.P.,...,Jiménez Fernández, Á.F. (2025). Neuromorphic Audio for Predictive Maintenance in Peristaltic Pumps [Dataset]. idUS (Depósito de Investigación de la Universidad de Sevilla).https://hdl.handle.net/11441/167278This 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.image/pngapplication/octet-streamengAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/NeuromorphicMicrophoneAudioPeristaltic PumpPredictive MaintenanceNeuromórficoMicrófonoBomba peristálticaMantenimiento predictivoinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/openAccess10.12795/11441/167278