AI noise recognition system

Many different sources of noise are often found outdoors and indoors. Resultant noise from multiple sources is often time-varying (both in terms of noise level and spectrum). An example of the noise level waveform is shown in Figure 1.

Figure 1.

In practice, it is very often necessary to identify the acoustic events that make up the total noise in a given area. The event identification consists in linking individual acoustic events (occurring in specific time periods) with the specified classes (Figure 2). Performing such a classification manually can be very time consuming and prone to human error.

Figure 2.

To improve the process of creating acoustic timing, KFB Acoustics is currently running a project called “Intelligent system for identifying vibroacoustic threats”.

Thanks to artificial intelligence algorithms, the developed system will automatically identify acoustic events in real time and inform on an ongoing basis about identified events. Additionally, the system will be able to indicate the approximate location of the events. This is a significant advantage compared to other solutions, such as microphone arrays and intensity probes, where it is possible to determine only the direction of the arrival of the acoustic wave. Moreover, the available alternatives do not offer automatic event identification and are therefore incomplete alternatives. The implementation of the system will be based on a network of intelligent sensors, able to communicate not only with the central unit, but also with each other.

Examples of application: environmental acoustics, noise in industrial plants, monitoring the operation of machines and devices