{'fraction_non_alphanumeric': 0.009656652360515022, 'fraction_numerical': 0.0, 'mean_word_length': 5.43448275862069, '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 Fault Diagnosis and Comprehensive Evaluation Methods for the Electrical System

With the development of the technology, the electrical system products is becoming more and more complicated and more and more diversified. It is more and more important to use the intelligent method to conduct the fault diagnosis and comprehensive evaluation to ensure the efficiency of the electrical system. This paper puts forward a fault diagnosis and comprehensive evaluation methods for the electrical system. The deep learning algorithm is used in the single fault factor evaluation for improving the accuracy of the single fault factor evaluation. Then, with the evaluation results, a fuzzy comprehensive evaluation model is designed and to obtain the whole performance evaluation result of the electrical system. The results of experiments demonstrate that the proposed method has better properties in efficiency than the competing methods.