DataSet: This dataset is a sound dataset for malfunctioning industrial machine investigation and inspection (MIMII dataset). It contains the sounds generated from four types of industrial machines, i.e. valves, pumps, fans, and slide rails. Each type of machine includes seven individual product models*1, and the data for each model contains normal sounds (from 5000 seconds to 10000 seconds) and anomalous sounds (about 1000 seconds). To resemble a real-life scenario, various anomalous sounds were recorded (e.g., contamination, leakage, rotating unbalance, and rail damage). Also, the background noise recorded in multiple real factories was mixed with the machine sounds. The sounds were recorded by eight-channel microphone array with 16 kHz sampling rate and 16 bit per sample. The MIMII dataset assists benchmark for sound-based machine fault diagnosis. Users can test the performance for specific functions e.g., unsupervised anomaly detection, transfer learning, noise robustness, etc. The detail of the dataset is described in [1][2].

[1] Harsh Purohit, Ryo Tanabe, Kenji Ichige, Takashi Endo, Yuki Nikaido, Kaori Suefusa, and Yohei Kawaguchi, “MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection,” arXiv preprint arXiv:1909.09347, 2019.

[2] Harsh Purohit, Ryo Tanabe, Kenji Ichige, Takashi Endo, Yuki Nikaido, Kaori Suefusa, and Yohei Kawaguchi, “MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection,” in Proc. 4th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2019.

Citation : Purohit, Harsh, Tanabe, Ryo, Ichige, Kenji, Endo, Takashi, Nikaido, Yuki, Suefusa, Kaori, & Kawaguchi, Yohei. (2019). MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection (public 1.0) [Data set]. 4th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2019 Workshop), New York, USA. Zenodo. https://doi.org/10.5281/zenodo.3384388

Hackster Project : https://www.hackster.io/manivannan/industry-4-0-predictive-maintenance-3bb415

YouTube tutorial : https://www.youtube.com/watch?v=GKu3tVDuA70

Contact : manivannan0212@gmail.com