Automated analysis of rotating probe multi-frequency eddy current data from steam generator tubes

P. Xiang, S. Ramakrishnan, X. Cai, P. Ramuhalli, R. Polikar, S. S. Udpa, L. Udpa

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


An algorithm is presented for the automated analysis of rotating probe multifrequency eddy current data obtained from nuclear power plant steam generator tubes (SGT). The algorithm consists of four steps, namely, a preprocessing stage for conditioning the data, a decision tree based feature extraction stage for identifying relevant features for analysis, a neural network based classification stage for identifying signals from various defect types and benign structures, and finally a blind deconvolution based characterization stage for accurately estimating the size and orientation of the detected defects. This algorithm is optimized to maximize the probability of detection (POD), while keeping the number of false alarms (PFA) at a minimum. Initial results presented in this paper look very promising and demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish (US)
Pages (from-to)151-164
Number of pages14
JournalInternational Journal of Applied Electromagnetics and Mechanics
Issue number3-4
StatePublished - 2000
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Automated analysis of rotating probe multi-frequency eddy current data from steam generator tubes'. Together they form a unique fingerprint.

Cite this