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Motors will act as sensors to analyse themselves

29 March, 2016

German researchers are developing intelligent motor systems that can monitor their own operation without needing any extra sensors. By transforming the motor itself into a sensor, the research team at Saarland University, led by Professor Matthias Nienhaus, is creating smart motors that can tell whether they are running smoothly, can communicate and interact with other motors, and can be controlled efficiently.

The researchers are using data collected from the motor while it is running to calculate quantities that would normally need to be measured using additional sensors. And they are teaching the drive how to make use of this knowledge. The ultimate goal is to make manufacturing processes more cost-effective and flexible, and to enable machinery and equipment to be monitored continuously for faults or signs of wear.

“We’re developing an important new type of sensor: the motor itself,” says Nienhaus. The technique will 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,” he adds. “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.”

The work is being carried out as part of a collaborative project called MoSeS-Pro (Modular sensor systems for real-time process control and smart state monitoring) with partners including Bosch Rexroth, Festo, Sensitec, Pollmeier, Canway Technology and Lenord+Bauer. The project has received €3.1m of funding from the German Federal Ministry of Education and Research.

In addition to Saarland University’s Centre for Mechatronics and Automation Technology (known as ZeMA), the project’s research partners are the Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) and the Department of Integrated Sensor Systems at Kaiserslautern University of Technology.

Nienhaus’ specialist area of research is miniature electromagnetic drive systems with power ratings from a tenth of a watt to several hundred watts.

Just like a doctor uses blood test data to draw conclusions about the health of a patient, Nienhaus and his team are using 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,” Nienhaus explains.

The more data that the researchers can gather from the motor while it is operating normally, the more efficiently they can control it. They analyse large amounts of motor data in to identify patterns that can be used to deduce something about the current status of the motor or to flag up changes arising from a malfunction or from wear. The team is developing mathematical models that simulate the various motor states, fault levels and degrees of wear.

Professor Matthias Nienhaus from the University of Saarland is developing a new kind of self-monitoring motor that doesn’t need sensors.
Photo: Oliver Dietze / Saarland University

The results are fed into a microcontroller. If a particular signal changes, the controller can identify the underlying fault or error and respond accordingly. The “sentient” motors can be networked to form an integrated complex that could open up opportunities in terms of maintenance, quality assurance and production. It could also lead to systems where if one motor fails, another takes over automatically.

To gather data from a motor, Nienhaus and his team monitor the distribution of the magnetic field strength within the motor and how it changes as the rotor spins. They use this data can be used to compute the position of the rotor and to draw other inferences about the status of the motor, allowing it to be controlled efficiently and error states to be detected reliably.

Nienhaus is currently testing several different methodologies to determine those best suited to acquiring data from motors.

The aim is to develop a suite of hardware and software modules that will make it easier to monitor and control drives and positioning systems, paving the way to fast, precise manufacturing processes that can be monitored and adjusted in real time. The researchers hope to identify which motor speeds generate the best data and which type of motor is best suited for this type of application.

Results from the project will be on show on the Saarland Research and Innovation stand at the Hannover Fair in April.

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