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This report discusses the integration of artificial intelligence in vibration-based condition monitoring for predictive maintenance of rotating machinery. It highlights the effectiveness of vibration analysis in detecting faults and outlines a methodology involving sensor selection, data acquisition, and AI model development. The results demonstrate good classification accuracy and the potential for improved maintenance planning through AI-driven monitoring.

Author
java script
Language
EN