Noise elimination from measured frequency response functions

It is inevitable that measured signals are contaminated with 'noise' when a data acquisition system is used for an experimental measurement. It is also well known in modal testing that the quality of measured frequency response functions (FRFs) is adversely affected by noise originating from test environment as well as electronic devices. This situation often leads to serious difficulties in many applications as they require high-quality FRF data. This paper presents a method based on singular value decomposition (SVD) for the elimination of noise from measured FRFs so as to improve the quality of the measured data. It is believed that this method will enhance the accuracy as well as the success rate of various applications that rely on measured FRFs.