ASTM C93900 Bronze Plain-Bearing Bushing Vibration Dataset for Condition Monitoring and Deep Learning Applications

This repository contains the experimental vibration dataset associated with the article entitled "Vibration-Based Condition Classification of ASTM C93900 Bronze Plain-Bearing Bushings Using Deep Learning", submitted to the IEEE Open Journal of Instrumentation and Measurement (OJIM). The dataset was generated using an experimental rotating machinery test bench specifically developed for tribological and vibration analysis of ASTM C93900 bronze plain-bearing bushings operating under different fault conditions. Three bushing conditions were investigated: normal condition, clearance condition, and eccentric condition. Vibration signals were acquired using an ADXL345 MEMS accelerometer integrated with an ESP32S3 embedded acquisition platform under controlled operating conditions. The dataset comprises raw vibration signals obtained from seven experimental configurations involving different combinations of fault types and bearing positions. This dataset is intended to support research in condition monitoring, predictive maintenance, tribology, vibration analysis, fault diagnosis, and artificial intelligence applications in industrial systems. The public availability of this dataset aims to promote reproducibility and provide a benchmark for future studies involving vibration-based monitoring of plain-bearing bushings operating under real fault conditions.