How can my facility use acoustic analysis?

Acoustic analysis has generally fewer applications than predictive maintenance (PdM) tools like infrared and vibration analysis, but what it lacks in breadth of application it makes up for in effectiveness. This is because there are two different and equally-useful parts of acoustic analysis.

Lubrication analysis (sonic)

The first part of acoustic analysis, sonic analysis, uses microphones that listen to the human-audible range of sound. Sonic analysis has considerably fewer applications than its sister analysis (ultrasonic), but it’s still a particularly useful tool for lubrication analysis.

Listening to moving parts with sonic microphones can help identify areas of assets that aren’t properly lubricated, which can then be fixed using proper lubricants. Additionally, sonic analysis helps contribute to lubrication training because facilities can identify areas that are consistently under- or over-lubricated and train technicians accordingly.

Distinguishing between multiple sounds (ultrasonic)

If a facility has a large number of assets (or an asset made up of a huge amount of different moving parts), sonic analysis no longer becomes useful because of the sheer amount of noise. At this point, ultrasonic analysis becomes a useful way of testing stress and motor function in complicated assets because it listens to sounds in the non-audible spectrum.

Take, for instance, a hydropower power station, which has a large number of moving parts. Ultrasonic microphones can, through machine learning, be trained to look for a specific sound that indicates failure and automatically submit a work order when that sound is found.

Diagnosing hidden machine stress

Some motors or moving parts may make a very loud sound when they stop working. However, this is a reactive maintenance scenario, meaning that the motor had to completely break before the maintenance team knew it needed to be fixed.

Using ultrasonic analysis, a facility can actually diagnose the stress on a motor by listening to changes in its frequency and highlighting abnormal sound patterns that indicate the motor is wearing down. That way, maintenance can be planned in advance to minimize downtime.