MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation 核心 · 已核验

atlas:mimii-sound-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]. This dataset is made available by Hitachi, Ltd. under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. A baseline sample code for anomaly detection is available on GitHub: https://github.com/MIMII-hitachi/mimii_baseline/ *1: This version "public 1.0" contains four models (model ID 00, 02, 04, and 06). The rest three models will be released in a future edition. [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.

落地页

https://zenodo.org/records/3384388

许可证

CC-BY-SA-4.0 (判读置信:verified_official)

国内可访问性

国内直连:直连超时(慢或不稳定,非封锁证据) (2026-07-11 检测) 代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

发布年份

2019

发布方

Zenodo

设备类型

pump other

PHM 任务

anomaly_detection

故障工况

传感器

运行工况