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Showing posts with the label I-Powered Condition Monitoring Architecture

AI in Industrial Condition Monitoring

  1. Introduction Industrial condition monitoring is essential for ensuring the efficient and safe operation of machinery, equipment, and infrastructure. AI-powered solutions enhance real-time monitoring, predictive maintenance, and failure detection using data-driven insights. By leveraging IoT sensors, machine learning (ML), big data analytics, and cloud computing , AI can analyze real-time and historical data, detect anomalies, and trigger alarms to prevent failures before they occur. 2. Importance of AI in Industrial Condition Monitoring Traditional vs. AI-Based Condition Monitoring Method Description Limitations Manual Monitoring Engineers inspect machines periodically. Time-consuming, error-prone, expensive. Rule-Based Alarms Fixed thresholds trigger alarms. Cannot adapt to changing conditions or detect complex patterns. AI-Powered Condit...