Extending a Prognostic Bearing Test Simulator with Smart Data Acquisition and Monitoring Capabilities

Predictive maintenance is essential for modern industrial systems, enabling early fault detection and efficient asset management. This paper presents an enhanced prognostic bearing test simulator that upgrades a laboratory platform for controlled accelerated degradation experiments. The system integrates a LabJack T7 Pro data acquisition unit with a web-based application, enabling automated data logging, structured storage, and remote visualization. These features reduce manual effort, improve data consistency, and enhance usability for real-time monitoring and experiment control. The developed platform supports diverse operating conditions and generates high-quality datasets for testing predictive maintenance strategies. The paper outlines the system architecture, data framework, and experimental validation, demonstrating its relevance for advancing diagnostics in rotating machinery.