vibration-analysis

Bearing fault detection public datasets collection.

Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

MCP server for predictive maintenance and machinery fault diagnosis. Gives AI assistants evidence-based vibration analysis - FFT, envelope, bearing fault detection, ISO 20816-3 severity - with a measured, blind CWRU benchmark. Local-first: raw signals never leave your machine. Includes a Claude Code plugin.

Collection of finite element models

This is a project for mechanical fault detection. The reason why it is called cute little bird may be because the eyesight of birds is particularly good, and they can detect small bugs. Besides, they are cute too. In the current version, we have tested some planetary gearbox vibration data in the lab, and there are 8 error types in total. And us…

A Comprehensive Guide to Active Control Methodology for Smart Beams

Mechanical engineering calculation examples in Python -- projectile motion, stress analysis (Mohr's circle, von Mises, tensile test), beam SFD/BMD, thermodynamic cycles (Rankine, reheat, refrigeration), damped vibration, and numerical methods. Runs in Jupyter Notebook/JupyterLab.

减速器振动测试数据清洗、RMS 统计、敏感区识别、趋势分析与工程可视化。

Matlab algorithm to automatically identify key vehicle characteristics from vibrations data collected on a suspension bridge

Python package to simplify rotary machines vibration-based analysis

진동 데이터 기반 PHM 예지보전 분석 프로젝트

Climate × vibration fusion for railway track-bed maintenance - a live, multi-agent digital twin (FAR AWAY 2026, Railways).

Python library to download public bearing and rotating-machinery fault datasets (CWRU, Paderborn, XJTU-SY, FEMTO, IMS, …) from their original sources and convert them into one Parquet format, with the same columns and labels for every dataset.

Structural Health Monitoring system that unifies deep learning and Finite Element modeling for real-time fault detection and dynamic response prediction in smart structures.

Official code, datasets, result artifacts, and supplementary experiments for MHFL-MCA multimodal machinery fault diagnosis.

SHPB_Processing.py - An open-source Python algorithm for correcting stress wave dispersion in split-Hopkinson pressure bar experiments

This project discusses implementation of deep learning model deployment for vibration prediction of motor

Vibration sensing using LSM6DSO

Vibration-based structural health monitoring on real bridge data: four Mahalanobis-distance strategies compared for separating damage from environmental drift, built from first principles (mean/covariance estimation, chi-square control limits) with diagnosed failure modes for each method.

FE-based reduced order models for rotordynamic and aeroelastic analysis of aircraft engines (Master Thesis, UniPD)