Applications of adaptive fuzzy lifting wavelet transform in MFL signal processing

The processing of magnetic flux leakage signals is a key element in the MFL inspection technique and guarantees for the implementation of quantitative testing of pipelines. A de-noising algorithm adaptive fuzzy lifting wavelet transform is presented to solve the problem of noise reduction in MFL signals. According to the theory and characteristics of the lifting wavelet transform, the improved algorithm is proposed by using an adaptive algorithm. The problem of nonlinearity caused by the adaptive algorithm is solved by using an update first lifting scheme. To verify the effectiveness of the improved lifting scheme, a fuzzy threshold filter algorithm is applied to the noise reduction of the MFL signals. The results show that the improved lifting scheme has achieved better noise reduction than that achieved by traditional wavelet transform. It is a feasible way to process MFL inspection signals.