Visible to the public Application of Tensor Decomposition Methods In Eddy Current Pulsed Thermography Sequences Processing

TitleApplication of Tensor Decomposition Methods In Eddy Current Pulsed Thermography Sequences Processing
Publication TypeConference Paper
Year of Publication2020
AuthorsLiang, Y., Bai, L., Shao, J., Cheng, Y.
Conference Name2020 International Conference on Sensing, Measurement Data Analytics in the era of Artificial Intelligence (ICSMD)
Date Publishedoct
Keywordsautomatic optical inspection, coil noise, compositionality, cyber physical systems, decomposition, defect part, ECPT image sequences, ECPT Sequence Processing, Eddy Current Pulsed Thermography, eddy current pulsed thermography sequences processing, eddy current testing, Eddy currents, edge noise, image segmentation, image sequences, materials science computing, Matrix decomposition, matrix decomposition theory, metal defects, Metrics, nondestructive testing, pubcrawl, Sparse matrices, Steel, surface cracks, tensor decomposition, tensors
AbstractEddy Current Pulsed Thermography (ECPT) is widely used in Nondestructive Testing (NDT) of metal defects where the defect information is sometimes affected by coil noise and edge noise, therefore, it is necessary to segment the ECPT image sequences to improve the detection effect, that is, segmenting the defect part from the background. At present, the methods widely used in ECPT are mostly based on matrix decomposition theory. In fact, tensor decomposition is a new hotspot in the field of image segmentation and has been widely used in many image segmentation scenes, but it is not a general method in ECPT. This paper analyzes the feasibility of the usage of tensor decomposition in ECPT and designs several experiments on different samples to verify the effects of two popular tensor decomposition algorithms in ECPT. This paper also compares the matrix decomposition methods and the tensor decomposition methods in terms of treatment effect, time cost, detection success rate, etc. Through the experimental results, this paper points out the advantages and disadvantages of tensor decomposition methods in ECPT and analyzes the suitable engineering application scenarios of tensor decomposition in ECPT.
Citation Keyliang_application_2020