{'fraction_non_alphanumeric': 0.018274111675126905, 'fraction_numerical': 0.0, 'mean_word_length': 4.766081871345029, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Novel Method for Modeling the Magnetizing Yoke

Abstract Magnetic flux leakage is the most widely used method for oil and gas pipeline non destructive testing. The saturation level of the sample under test has a significant effect on its efficiency; therefore, the magnetizing yoke requires an elaborate design. The finite element method is the conventional approach used for this purpose, but it is very time consuming. In this article, a neuro-fuzzy method is presented to model the behavior of the magnetizing yoke. Modeling a few different designs with the finite element method and using the results for training the neuro-fuzzy model eradicates the necessity of modeling a huge number of designs with the finite element method. The acquired sub-optimal neuro-fuzzy network can then be employed to find a good design for the yoke. In this way, the time required for design phase is reduced considerably. The structure of the model was verified using the cross-validation method.