Simulation of a Vibroacoustic Sensor with the Application of a Kalman Filter

Recently the Kalman filter is one of the most efficient filtering algorithms used in many fields of science and technology. Due to its simplicity, it can be found in GPS receivers, in systems for processing sensor readings, in the implementation of control systems, etc. When designing control systems, one of the important tasks is the availability of a highly efficient and reliable system of sensors for the state of the control object. In addition to its reliability, the control process is also affected by sensor characteristics such as accuracy and speed. In order to ensure the stable operation of the control system, in addition to the above characteristics, it is necessary to eliminate external and internal interference, namely, the measurement and high-quality noise processing. The paper considers the problem of filtering vibroacoustic signals using an adaptive Kalman filter in order to further use the filtered array to solve the problem of vibroacoustic diagnostics. Currently, the objects of vibroacoustic diagnostics are internal combustion engines in which the components move relative to each other and, as a result, acoustic waves arise. These waves can be registered on the external parts of the machine, and the analysis of these waves makes it possible to judge the technological state of the machine. The results of modeling an adaptive filter in the Matlab/Simulink software environment of a real vibroacoustic signal are also presented. A device based on the Arduino Mega microcontroller was implemented, which was used to process field observations of the object of study.