Abstract
Abshacf-Aiming at the pipeline safety evaluation, this paper describer a magnetic flux leakage(MFL) model of pipeline defects inspection, designs a MFL intelligent inspection pig to inspect different pipelines. The intelligent Pig includes driver mbof system contmUer, data pmcssor and etc. It can be used for multi-radius pipelines and various work conditions It has high sensitivity for adopting multi-sensor data fusion. The structure design of the intelligent pig and its signal processing are discussed. Dimerent representation to various scale spectrums of noise and MFL signal is utilized to get rid of the noise based on Wavelet transform. For the multiscale and multiresolution features of orthogonal wavelet, signals are decomposed to independent frequency strips, an algorithm to recognize defect parameters based on wavelet basis function WBF) neural network is given. Applying the theory to eliminate noise and predict defect pmfdes fmm experimental MFL signals are presented. Kepvoni-magnetic pia lea!mge(MFL), intelligent pig &xi- mbot,
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