Your browser does not support JavaScript!

Data fusion algorithm for pulsed eddy current detection

Data fusion algorithm for pulsed eddy current detection

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Science, Measurement & Technology — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A weighted data fusion algorithm based on matching pursuit (MP)-wavelet packet (WP) atomic decomposition and its applications in pulsed eddy current (PEC) non-destructive testing systems for estimation of feature parameters is presented. MP-WP atomic decomposition is used to estimate each noise-free pulse response from its noisy observation of a single-sensor PEC probe and obtain the peak value parameter from each estimated response. A weighted data fusion algorithm, on the basis of minimum mean square error (MMSE), is applied to fuse each obtained peak value together to get final optimum parameter estimation. Based on the difference of each noisy pulse response and its estimation, the variance of noise in each pulse response can be computed, respectively. Accordingly, the weight of each pulse response for data fusion is calculated by the variance of its noise. Finally, the peak value parameter is estimated by the utilised data fusion algorithm. In terms of MMSE, this weighted fusion presents an optimum estimation of the feature parameter of multi-pulse responses of PEC sensor, compared with normal averaging process.


    1. 1)
      • L.J. Xu , X.M. Li , F. Dong , Y. Yang , L.A. Xu . Optimum estimation of the mean flow velocity for the multi-electrode inductance flowmeter. Meas. Sci. Technol , 1139 - 1146
    2. 2)
      • G.Y. Tian , A. Sophian , D. Taylor , J. Rudlin . Multiple sensors on pulsed eddy-current detection for 3-D subsurface crack assessment. IEEE Sens. J. , 90 - 96
    3. 3)
      • A.M. Rao , D.L. Jones . A denoising approach to multisensor signal estimation. IEEE Trans. Signal Process. , 1225 - 1234
    4. 4)
      • G.Y. Tian . Design and implementation of distributed measurement systems by fieldbus-based intelligent sensors. IEEE Trans. Instrum. Meas. , 1197 - 1202
    5. 5)
      • Y.L. Zhai , Y.S. Dai . Study of adaptive weighted fusion estimated algorithm of multisensor data. Acta Metrologica Sin. , 69 - 75
    6. 6)
      • Li, Y., Tian, G.Y., Theodoulidis, T.: `Fast analytical method for pulsed eddy current evaluation', Proc. 45th Annual British Conf. on NDT, 2006, p. 1–12.
    7. 7)
      • G.Y. Tian , A. Sophian . Defect classification using a new feature for pulsed eddy current sensors. NDT&E Int. , 77 - 82
    8. 8)
      • S. Mallat , Z. Zhang . Matching pursuit with time-frequency dictionaries. IEEE Trans. Signal Process. , 3397 - 3415
    9. 9)
      • H. Yashida . Matching pursuit with optimally weighted wavelet packets for extraction of microcalcifications in mammograms. Appl. Signal Process. , 127 - 141
    10. 10)
      • H.Y. Yang , J. Mathew , L. Ma . Fault diagnosis of rolling element bearings using basis pursuit. Mech. Syst. Signal Process. , 341 - 356
    11. 11)
      • G.Y. Tian , A. Sophian , D. Taylor , J. Rudlin . Wavelet-based PCA defect classification and quantification for pulsed eddy current NDT. IEE Proc., Sci. Meas. Technol. , 141 - 148
    12. 12)
      • G. Kerschen , P. De Boe , J.C. Golinval , K. Worden . Sensor validation using principal component analysis. Smart Mater. Struct. , 36 - 42
    13. 13)
      • L.J. Xu , J.Q. Zhang , Y. Yang . A wavelet-based multisensor data fusion algorithm. IEEE Trans. Instrum. Meas. , 1539 - 1545
    14. 14)
      • X.D. Zhang . (1995) Modern signal processing techniques.
    15. 15)
      • A. Sophian , G.Y. Tian , D. Taylor , J. Rudlin . A feature extraction technique based on principal component analysis. NDT&E Int. , 37 - 41

Related content

This is a required field
Please enter a valid email address