conditionmonitoring

Condition monitoring is the systematic collection and analysis of data from equipment to determine its health, detect anomalies, and predict failures before they occur. By providing evidence of asset condition, it supports maintenance decision-making and enables condition-based or predictive maintenance strategies rather than reactive repairs.

Techniques and data sources include online and offline methods. Sensors monitor vibration, temperature, pressure, humidity, lubrication quality, electrical signals, and acoustic emissions. Common techniques are vibration analysis (time and spectral domain), infrared thermography, ultrasonic testing, oil analysis and wear debris analysis, electrical signature analysis such as motor current signature analysis, and acoustic emission.

Process and workflow involve data collection and processing, storage, and analysis using statistical methods, trending, spectral analysis, and machine learning to detect patterns and estimate remaining useful life. The resulting maintenance recommendation is typically categorized as continue operation, inspection, repair, or replacement.

Applications and benefits span manufacturing, energy, transportation, and process industries. Condition monitoring helps minimize unplanned downtime, extend asset life, improve safety, and optimize maintenance costs. It supports decisions about when to inspect, service, or replace components, thereby improving overall asset performance.

Challenges and standards include data quality, sensor placement, integration across systems, interpretation of results, false positives, and cybersecurity. Standards such as ISO 13374 provide an information model for condition monitoring data exchange and diagnostics to support interoperability.