Software Sensor for Airflow Modulation and Noise Detection by Cyclostationary Tools - Mohamad Alkoussa Dit Albacha; Laurent Rambault; Anas Sakout; Kamel Abed Meraim; Erik Etien; Thierry Doget; Sebastien Cauet (Sensors, 2020)
The paper presents tools to model low speed airflow coming from a turbulent machine. This low speed flow have instabilities who generate noise disturbances in the environment. The aim of the study proposed in this paper, is the using of cyclostationary tools with audio signals to model this airflow and detect the noisy frequencies to eliminate this noise. This paper also deals with the extraction in real time of the frequency corresponding to the noise nuisance. This extraction makes it possible to build a software sensor. This software sensor can be used to estimate the air flow rate and also to control a future actuator which will reduce the intensity of the noise nuisance. This paper focuses on the characteristic of the sound signal (property of cyclostationarity) and on the development of a software sensor. The results are established using an experimental setup representative of the physical phenomenon to be characterised.