tilstandsovervåkningssystemer

Tilstandsovervåking, or condition monitoring, is a systematic process of monitoring the health of equipment by measuring physical parameters to detect anomalies and predict failures before they occur. It aims to reduce unplanned downtime, extend asset life, and enable maintenance that is based on actual condition rather than on fixed schedules.

Common methods rely on sensor data such as vibration, temperature, oil analysis, electrical signatures, and infrared thermography. Data can be gathered from IoT sensors, SCADA systems, PLCs, or handheld devices and analyzed using statistical methods, signal processing, machine learning, and diagnostic models to identify faults and estimate remaining useful life.

The typical workflow includes data acquisition, preprocessing, feature extraction, health assessment, prognosis, and maintenance decision-making. This supports maintenance strategies like condition-based maintenance and predictive maintenance, often guided by international standards such as ISO 13374 and ISO 18436. These standards help structure data interchange, diagnostics, and competency requirements in the field.

Applications span manufacturing, energy, transportation, and process industries, including motors, bearings, gears, pumps, transformers, wind turbines, and railway systems. Benefits include reduced downtime, lower maintenance costs, improved safety, and longer asset life. Challenges involve ensuring data quality and sensor placement, integrating with existing control systems, cybersecurity considerations, and maintaining skilled personnel to develop and interpret the analyses.

The concept emerged from reliability engineering and has evolved with advances in digital sensors, cloud analytics, and artificial intelligence to enable proactive maintenance decision making.