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.
Keywords: adaptive; fuzzy threshold; lifting wavelet transform; magnetic flux leakage signals; preprocessing
Document Type: Research Article
Affiliations: 1 Department of Electrical Engineering, Mechanical Engineering College, Shijiazhuang Vocational Technology Institute, Hebei Shijiazhuang 050005, People's Republic of China.
Publication date: 01 January 2010
- Official Journal of The British Institute of Non-Destructive Testing - includes original research and development papers, technical and scientific reviews and case studies in the fields of NDT and CM.
- Information for Authors
- Submit a Paper
- Subscribe to this Title
- Information for Advertisers
- Terms & Conditions
- Ingenta Connect is not responsible for the content or availability of external websites
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content