The application of digital processing methods improving the identification of useful signal in case of great noise is presented. When inspecting the surface of real objects, the output signal from the probe usually comprises a low frequency component - a trend, with the duration much longer than the width of the topography of magnetic field from a defect. Further analysis of the magnetic field from the defect with the trend can dramatically decrease the reliability of inspection. The quality of the trend rejection from the signal is determined by the ratio between the signal duration and the width of the magnetic field topography from defect. In general the trend from a signal measured is interpolated by a polynomial of K power (usually K≤2). To reject random noise from signal we use digital filtering methods that lead to high accuracy and noise immunity of equipment. The main aspect when using digital filtration is the choice of a window function which is employed for spectrum analysis of signals. Processing with windows is used for controlling effects caused by side lobes in spectrum. Designing of the optimal window function for different tasks instead of choosing one from available functions is highly advisable. The application of correlation processing where theoretical defect model is used as a reference signal allows to increase essentially the signal-noise ratio. The above digital processing methods have proved to be decisive and have successfully been applied in eddy-current flaw detectors VD-12NFP that are manufactured by JSC "RII-Spectrum". Introduction: Test of real objects by eddy-current technique is connected with the need to eliminate interfering parameters which are caused by the surface under test. In this case we have magnetic field distorted and this decreases dramatically the reliability of test. That is why we need special processing of signal to exclude random noise, constant components and restore initial signal.
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