Networked self-analyzing electric motors offer continuous monitoring solution

March 25, 2016 // By PAUL BUCKLEY
Transforming the motor itself into a sensor, the team led by Professor Matthias Nienhaus are creating smart motor
Engineers from Saarland University are developing intelligent motor systems that do not need additional sensors. Data collected from the motor while it is operating enables parameters to be calculated that in other systems need to be measured by additional sensors.

By transforming the motor itself into a sensor, the team led by Professor Matthias Nienhaus are creating smart motors that can tell whether they are still running smoothly, can communicate and interact with other motors and can be efficiently controlled.

The engineers are teaching the drive how to make use of the data and are currently working with project partners to study and test a number of different procedural methods. The ultimate goal is to make manufacturing processes more cost-effective and flexible and to enable machinery and equipment to be continuously monitored for faults or signs of wear.

The drive systems specialist Professor Matthias Nienhaus from Saarland University is working on developing a new kind of self-monitoring motor – one that does not need sensors.

"We’re developing an important new type of sensor: the motor itself," said Professor Nienhaus. "The advantage of this new approach is that the engineers simply collect data that is available from the normal operation of the motor. That makes our approach very cost-effective as there’s no need to install any additional sensors. We’re looking at elegant ways of extracting data from the motor and of using this data for motor control and for monitoring and managing processes. We are also working with project partners on improving the design and construction of miniature motors so that they yield the greatest possible quantity of operational information."

Just like a doctor uses blood test data to draw conclusions about the health patient, Professor Nienhaus and his team use motor data to determine the health of a drive system. "We examine how our measured data correlates with specific motor states and how specific measured quantities change when the motor is not operating as it should," said Professor Nienhaus.

Gathering data from the motor while it is operating normally is valuable for the research team; the more motor data they have, the more efficiently they can control the motor. The