Using AI to control mechanical vibrations

resonant-motionI’ve written a number of times about the industrial Internet of Things.  The various attempts to predicatively maintain assets seem to revolve heavily around the vibrations made by healthy vs unhealthy equipment.

For instance, a study from earlier this year highlighted the effectiveness of this method in factory equipment, whilst a number of startups are deploying a similar approach to monitoring the rail network.

Of course, many machines rely on vibrations and oscillations to work, and resonant motion is a problem that plagues many such devices.  So a recent study that claims to help machines avoid this trap is particularly interesting.

Avoiding resonant motion

The researchers used a combination of experiments and computer simulations to increase and decrease the speed of the rotor, and therefore help it avoid resonant frequency.

“Our method is analogous to pushing a car back and forth in order to get it out of a ditch,” the authors say.

The method is especially useful when the machine is initially turned on and the rotor speeds up.  As the rotor accelerates, the risk of reaching a resonant frequency increases, and it then becomes trapped at this frequency, which damages the machine.

Engineers have found previously that boosting power to the rotor can help overcome this, but this approach obviously requires more energy and a larger motor.

The new approach utilizes an increase or decrease in the speed of the rotor by a small amount, which allows greater control of the frequency of the rotor.  The method was tested in a computer model, with positive results.

“This result allows us to be more optimistic in practical applications since it provides an algorithm for how to move from one position to another with little effort,” the researchers say.

They next hope to test out their approach to see whether systems can be controlled at higher frequencies and also to test the effect of different start conditions.

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