- Entry date 16.03.2026 Condition Monitoring – Special Offer for Wind Turbines GfM’s Peakanalyzer condition monitoring system has proven itself over many years in the monitoring...
-
Entry date 10.12.2025
Monitoring service for third-party systems using continuous online spectral analysis
-
Entry date 24.07.2025
Condition monitoring at HUSUM WIND 2025
-
Entry date 16.07.2025
Condition monitoring saves system operators a lot of money
-
Entry date 27.01.2025
Drum coupling monitoring - Automatic condition monitoring on cranes
-
Hannover fair
20.04.2026 - 24.04.2026
-
Dresden Machine Elements Colloquium 2026
06.05.2026
-
WindEnergy Hamburg 2026
22.09.2026 - 25.09.2026
-
Maintenance München
08.10.2026
-
34th Wind Energy Days in Linstow
10.11.2026 - 12.11.2026
Converter Bearing
A converter is a heat-resistant container in which steel is produced at around 1,500 °C. Large converters hold over 300 tons of liquid material and are refilled approximately 50 times per day. The converter must be swiveled for loading and unloading. This is done via pins that are guided in rolling bearings. These converter bearings only occasionally perform rotational movements that are also smaller than a full revolution. At the same time, they have to absorb a large static load as well as dynamic loads caused by the production process. This can lead to damage processes that can be diagnosed with the help of a suitable condition monitoring system.
In fact, classic vibration diagnosis with acceleration sensors and subsequent generation of spectra and envelope spectra is rather unsuitable for this. On the one hand, sufficiently long oscillation time signals cannot be recorded. On the other hand, the low rotation speed is the reason why hardly any high-frequency vibrations are generated.
GfM has created a reliable diagnostic procedure for diagnosing converter bearings and has successfully used it several times. Only the angle of rotation and signals from displacement sensors are used for this. The sensors can be retrofitted to existing systems. The signals are analyzed and reliably interpreted in the online condition monitoring system Peakanalyzer.




