Magnetic Flux Leakage Based Rail Surface Defect Assessment Method
Main Article Content
Abstract
Due to the rolling friction, it is easy to produce harmful scratches, cracks, blocks and damage on the rail surface. In order to detect and evaluate the damage accurately and efficiently, this paper proposed an evaluation method based on magnetic flux leakage (MFL) detection, where the defect threshold is calculated by using the adaptive threshold method and the impact of noise on the results reduced. With the study on the relationship between the depth, detection speed and signal peak-to-peak value of the manual sample, quantitative statistics is made on the depth of the defect. By calculating the average severity of the damage within a length of the rail, the condition of the section is assessed. During the study, the feasibility of the method is verified by finite element simulation analysis for the three-section damage of the main line of the high-speed railway. The test results show that the method can evaluate the rail surface damage quickly and effectively.
Article Details
Issue
Section
Articles
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms: a. Authors retain copyright and grant the journal right of first publication, with the work two years after publication simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).