{'fraction_non_alphanumeric': 0.01229895931882687, 'fraction_numerical': 0.0, 'mean_word_length': 5.260355029585799, '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}}
Automatic design of fuzzy MF using Genetic Algorithm for fault detection in structural elements

Damage in a structural element may occur due to normal operations, accidents, deterioration or severe natural events such as earthquakes or storms. The effects of common damage on a structure are changes in natural frequencies, mode shapes and structural damping. Most often the extent and location of damage may be determined through visual inspection. But this is a time consuming and erroneous method. Since the measurement of natural frequencies easier than that of changes in structural damping, damage can be detected from dynamic analysis using natural frequencies. In this paper a combination of fuzzy logic and Genetic Algorithm has been used to find out crack location. The first three natural frequencies of the cracked structural element are taken as the, three independent input variables. Here membership functions are optimized by using genetic algorithm or we can say membership functions are automatically generated by using genetic algorithm.