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Danfoss - Inverter Drives / Controls

Sensors - Controls - Intelligent Drives - Automation Systems

Condition Monitoring with Intelligent Drives

The easiest and most intuitive maintenance technique based on data from the actual application. The data acquired is used to monitor the health of the equipment in service. For this purpose, key parameters are selected as indicators to identify developing faults.

The condition of a piece of equipment typically degrades overtime. This is illustrated by the P-f curve which shows a typical degradation pattern. Functional failure occurs when the equipment fails to perform the intended function. The idea of condition-based maintenance is to detect the potential failure before an actual failure occurs.

Planning maintenance actions provide many advantages such as downtime reduction, elimination of unexpected production stops, maintenance optimisation and reduction in spare part inventory.

  • Corrective maintenance
  • Preventive maintenance
  • Condition-based maintenance
  • Predictive maintenance

Corrective and preventive maintenance are fault (event) or time-based. Therefore, maintenance is performed in case of fault(s) (corrective) or after pre-established operation hours (preventive). These types of maintenance do not use any feedback from the actual application.

With the introduction of Industry 4.0 and the availability of sensor data, condition-based and predictive maintenance is now possible. Such maintenance strategies use actual sensor data to determine the condition of the equipment in service (condition-based maintenance) or to predict future failures (predictive maintenance).

In the Industry 4.0 network, the drive plays an important role and is characterised by some enabling features:

Wireless connectivity to smart devices (smartphones and tablets).

Secure connectivity: The drive can connect to other elements in the network; including BMSs, PLCs, controllers, valves and sensors. In some applications the drive can be used as the main controller.

The drive as a sensor: Using motor current, voltage, power, motor torque and speed analysis to sense the motor performance and as a sensor hub directly acquiring data from the process sensors; such as vibration, pressure and temperature. Processed data and analytics signals provide indication of the condition of the drive, motor and application; used to trigger maintenance or system design improvements.

Evolution of Industrial Automation Systems

We have witnessed a profound change in technology, leading to a new way of working in a digital world; the fourth industrial revolution.

The first industrial revolution, during the 18th and 19th century, was a mechanical revolution; triggered by the invention of the steam engine. By the end of the 19th and early 20th century; the second industrial revolution unfolded with the adoption of mass production, electrification and changes in communication (the Electrical Revolution).

Later in the 20th century, the third industrial revolution brought advances in semiconductors, computing, automation and the internet (the Digital Revolution).

A possible definition for the fourth industrial revolution, Industry 4.0, is the intelligent networking of people, devices, and systems by utilising all possibilities of digitalisation across the entire value chain.

Trends in Industry 4.0 Automation Systems

The impact of Industry 4.0 on motor systems is a migration from the “automation pyramid” to “networked systems”. This means that the various elements of the system; such as motors, drives, controls and sensors, are interconnected and possibly connected to a cloud – a data centre where data is stored, processed and analysed for fast and accurate decision making.

For further information, please refer to our page in the Technical Data section of the Notebook.

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