Abstract <p>Traffic safety in railway transport requires regular inspection of the condition of rails to identify and timely eliminate defects. Eddy-current flaw detection is one of the popular methods of nondestructive rail testing. The data (defectograms) obtained from eddy-current flaw detectors during rail testing are typically high-volume and therefore require efficient automated analysis. In this context, analysis means the process of detecting the presence of defective areas on defectograms, as well as identifying the structural elements of the rail track, taking into account noise and various types of interference. The threshold noise level is found to isolate signals from defects and structural elements. Its value can be distorted by electromagnetic influences superimposed on the signals, which have pronounced low frequency and periodicity. This interference raises the threshold noise level, complicating the detection of useful signals. In relation to this, these types of effects need to be suppressed. In this paper spectral subtraction is used as a method for interference reduction in eddy-current defectograms. The interference function is defined as the sum of the low-frequency harmonics of the discrete Fourier transform of the original signals. Then the cleaned signal can be found by subtracting the low-frequency range. The upper boundary of this range is referred to as the threshold harmonic frequency. This frequency is determined by minimizing the distance of the signal’s autocorrelation function and expected autocorrelation. Two types of expected correlation are proposed: Gaussian noise autocorrelation and the reference autocorrelation. Both approaches allow us to determine the threshold harmonic frequency at which periodic interference is most effectively suppressed. The method based on Gaussian noise autocorrelation method is, to some extent, universal for eddy-current defectograms, while the reference autocorrelation is data- and recording equipment-specific. The most suitable threshold harmonic frequency is found for the eddy-current defectogram data under consideration. The described approaches to suppressing periodic low-frequency interference may also be successfully applied in other fields beyond eddy-current testing.</p>

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Suppression of Additive Periodic Low-Frequency Interference on Eddy-Current Defectograms

  • L. Y. Bystrov,
  • A. N. Gladkov,
  • E. V. Kuzmin

摘要

Abstract

Traffic safety in railway transport requires regular inspection of the condition of rails to identify and timely eliminate defects. Eddy-current flaw detection is one of the popular methods of nondestructive rail testing. The data (defectograms) obtained from eddy-current flaw detectors during rail testing are typically high-volume and therefore require efficient automated analysis. In this context, analysis means the process of detecting the presence of defective areas on defectograms, as well as identifying the structural elements of the rail track, taking into account noise and various types of interference. The threshold noise level is found to isolate signals from defects and structural elements. Its value can be distorted by electromagnetic influences superimposed on the signals, which have pronounced low frequency and periodicity. This interference raises the threshold noise level, complicating the detection of useful signals. In relation to this, these types of effects need to be suppressed. In this paper spectral subtraction is used as a method for interference reduction in eddy-current defectograms. The interference function is defined as the sum of the low-frequency harmonics of the discrete Fourier transform of the original signals. Then the cleaned signal can be found by subtracting the low-frequency range. The upper boundary of this range is referred to as the threshold harmonic frequency. This frequency is determined by minimizing the distance of the signal’s autocorrelation function and expected autocorrelation. Two types of expected correlation are proposed: Gaussian noise autocorrelation and the reference autocorrelation. Both approaches allow us to determine the threshold harmonic frequency at which periodic interference is most effectively suppressed. The method based on Gaussian noise autocorrelation method is, to some extent, universal for eddy-current defectograms, while the reference autocorrelation is data- and recording equipment-specific. The most suitable threshold harmonic frequency is found for the eddy-current defectogram data under consideration. The described approaches to suppressing periodic low-frequency interference may also be successfully applied in other fields beyond eddy-current testing.