Condition Monitoring: Monitoring for systems goes online

Whenever interval-based checks on machines and systems are no longer sufficient, alternative monitoring concepts must be established. Condition monitoring allows remote diagnostics – online and in real time. An overview of the state of the art is available from 16 to 18 October at the Maintain maintenance fair in Munich.

Frequency analyzes determine the state of wear of blowers, compressors and Co.

Frequency analyzes determine the state of wear of blowers, compressors and Co.

Photo: Bosch Rexroth

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Whether lack of security, accessibility or economy: all three examples It is common that interval-based maintenance would not meet the requirements. Condition monitoring allows users to constantly monitor their machines and systems online – in real time and remotely.

Condition Monitoring: Online monitoring of machines and systems in real time and remotely

The principle: condition-based maintenance. If a critical value is reached, the system is shut down in good time to prevent more serious damage. From 16 to 18 October, suppliers will be showcasing their solutions at the Maintain industrial maintenance trade fair in Munich.

The Maintain exhibitor and specialist for air and gas extraction solutions Aerzener presents a corresponding concept with “Delta Real Time Monitoring “. The real-time monitoring of rotary lobes for vibrations, pressures and temperatures is already being used in steel mills in Austria, the Belgian food industry, the glass industry and power plants. The machine manufacturer wants to go from precautionary component replacement to condition-based maintenance.

A vibration sensor is attached to the machine on both the drive and wheel sides, allowing the state of a unit to be determined at any time. Rolling bearings are precisely monitored by continuously observing indicators of wear.

Frequency analyzes determine the state of wear and cause of damage for blowers, compressors, motors and gearboxes. The advantage: the early diagnosis of damage long before a total failure of the machine. Unplanned shutdowns are thus reduced.

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