{"id":14956853,"url":"https://github.com/aurelienmorgan/abnormal_vibrations_watchdog","last_synced_at":"2025-10-24T10:31:14.246Z","repository":{"id":236245435,"uuid":"296547978","full_name":"aurelienmorgan/abnormal_vibrations_watchdog","owner":"aurelienmorgan","description":"Time Series Anomaly detection. The monitored signal is made-up of machinery vibration sensor measurements.","archived":false,"fork":false,"pushed_at":"2020-12-07T13:00:14.000Z","size":9130,"stargazers_count":16,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-29T10:21:13.140Z","etag":null,"topics":["anomaly-detection","autoencoder","bayesian-optimization","data-pipeline","etl","jupyter-notebook","keras","lstm","mongo-db","pyspark","python","rnn","tensorflow","time-series"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/aurelienmorgan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2020-09-18T07:33:42.000Z","updated_at":"2025-01-04T13:37:05.000Z","dependencies_parsed_at":"2024-04-26T09:37:40.595Z","dependency_job_id":null,"html_url":"https://github.com/aurelienmorgan/abnormal_vibrations_watchdog","commit_stats":null,"previous_names":["aurelienmorgan/abnormal_vibrations_watchdog"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aurelienmorgan%2Fabnormal_vibrations_watchdog","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aurelienmorgan%2Fabnormal_vibrations_watchdog/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aurelienmorgan%2Fabnormal_vibrations_watchdog/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aurelienmorgan%2Fabnormal_vibrations_watchdog/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aurelienmorgan","download_url":"https://codeload.github.com/aurelienmorgan/abnormal_vibrations_watchdog/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":237950886,"owners_count":19392667,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["anomaly-detection","autoencoder","bayesian-optimization","data-pipeline","etl","jupyter-notebook","keras","lstm","mongo-db","pyspark","python","rnn","tensorflow","time-series"],"created_at":"2024-09-24T13:13:38.046Z","updated_at":"2025-10-24T10:31:06.920Z","avatar_url":"https://github.com/aurelienmorgan.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Mechanical Failure Watchdog\n##### Bearings Vibration Anomaly Detection\n\n\u003chr /\u003e\n\u003cbr /\u003e\n\nWelcome to this Deep Learning project page\u0026nbsp;!\n\nHere, we develop an RNN model in order to detect early the forewarning signs\nof forthcoming machinery hard failure.\n\nThe model we train is ready for deployment. Taking vibration sensor signal as input, it is able\nto raise an alert, would the working conditions deteriorate to an extend that\nthe material is very likely to fail in a foreseeable future, thus indicating that\noperation shall be stopped and replacement of the faulty part operated before\nlarger damage could be incurred.\n\nThe below notebook contains an end-to-end ETL data pipeline plus a whole Bayesian Optimization cycle\nfor the LSTM Autoencoder implemented to fit the bill\u0026nbsp;:\n\n\u003cbr /\u003e\n\n\n\n\n\n\n\u003cdiv style=\"width: 100%;\"\u003e\n    \u003ccenter\u003e\n        \u003cdiv\u003e\n            \u003ca href=\"https://htmlpreview.github.io/?https://github.com/aurelienmorgan/abnormal_vibrations_watchdog/blob/master/main.html?uncache=65645\"\n                target=\"self\"\u003e\u003cimg align=\"center\" alt=\"Jupyter Notebook\" src=\"./images/jupyter_notebook.png?uncache=1234\" height=\"40px\" /\u003e\u003c/a\u003e\n        \u003c/div\u003e\n    \u003c/center\u003e\n\u003c/div\u003e\n\u003cbr /\u003e\n\u003cbr /\u003e\n\n\n\n\nKEYWORDS :\n\t```Time Series```, ```Anomaly Detection```,\n\t```Tensorflow```, ```Keras```,\n     ```RNN```, ```LSTM```, ```Autoencoder```,\n     ```Bayesian Optimization```,\n\t```MongoDB```, ```PySpark```, \n    ```ETL```, ```Data Pipeline```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faurelienmorgan%2Fabnormal_vibrations_watchdog","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faurelienmorgan%2Fabnormal_vibrations_watchdog","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faurelienmorgan%2Fabnormal_vibrations_watchdog/lists"}