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Rotating machineries in power and process plants, like pumps, turbines, etc., are vital for unimpeded operation and production. Component faults, such as bearing and gearbox failures, electrical faults in drives, imbalance of rotating parts, misalignment or high vibration amplitudes due to resonances, influence the vibration behavior of rotating machines. If this remains undetected, costly machine damage and unplanned outages can lead to limited availability and profitability of the plant.

 

DIROM allows the operator to increase the availability, reliability and maintainability of rotating machinery by performing optimal monitoring, diagnostics and asset management. DIROM is designed with smart algorithms as well as modular, reliable and robust hardware consisting of different kinds of sensors. Including the monitoring of asset failure modes, one or several distributed data acquisition and monitoring units (AMU), analog and / or digital communication interfaces to transfer collected data and related features to third-party systems if demanded and one data server for centralized archiving of all important asset data.


The DIROM AMU continuously and synchronously acquires, processes, monitors and stores sensor data pre- and post-trigger after recognized events, periodically or on user request. After data is stored in the AMU, the DIROM data server collects the measurement files, automatically extracts and analyzes the user-defined diagnostic features from the raw signals to identify impending component faults and the related severity.


Through the DIROM database software condition-based maintenance and asset management are enhanced. The measurement data, diagnostic results and reports are archived together with the maintenance reports and the machine construction information. Therefore, a complete machine lifetime log is centralized and accessible at any time.


Your Benefits

  • Protects assets and revenue through real-time monitoring, early anomaly detection and severity prediction
  • Improves reliability of assets
  • Reduces operational and investment costs by optimizing maintenance intervals and duration, repairs, replacements and spare parts management
  • Improves situational awareness and supports decision making with the online view of asset data like health and performance indicators, event logs and notifications

 

References

More than 25 systems in 4 plants in operation (in Germany, France, Finland and China)

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Publication

Maintenance optimization – predictive vs. preventive maintenance