Créé le : 05/03/2019
Noise radiated by rotating and reciprocating machines is often a mixture of multiple complex sources, the successful reduction of which is a research field of intensive research. In this paper an advanced source separation approach is pre-sented, based on cyclic Wiener filtering, which takes into account the cyclosta-tionarity property of the signals. The aim of the Wiener filter is the separation of noisy measurements their contributions from the specific N sources and the remaining "noise". Traditionally this can be achieved by using reference signals which are strongly coherent with the sources of interest and uncorrelated with all the other interfering sources and the masking noise. The Wiener filter could be estimated using the raw signals (Graw) or only the random part of the signals (Gres). Moreover, the filters can be underestimated if the Signal-to-Noise Ratio (SNR) of the reference signals is low, thus leading to the paradox that the level of an extracted source contribution is higher than the en-semble of the sources. In order to increase its’ robustness, it is proposed to esti-mate the cyclic Wiener filters using an additional constraint which imposes that the sum of the estimations of the contributions of the periodic parts of each source equals to the periodic part of the total contribution of the sources as is calculated by the synchronous averaging procedure. This produces a new estimator of the Wiener filter, obtained from a constrained least square optimization. Furthermore, in this study a general strategy is proposed in order to select over which part of the signals (raw or residual) should the filters be estimated. This strategy is based on the number of the available references and the expected number of sources and the link with the multivariable statistical regression. The proposed method is applied on vibroacoustic signals captured at an in-dustrial test rig in order to quantify the contributions of "hydraulic noise" (origi-nating mainly by four hydraulic pumps) and "mechanical noise" (originating from the various rotating parts of the engine).