{'fraction_non_alphanumeric': 0.010520163646990065, 'fraction_numerical': 0.0023378141437755697, 'mean_word_length': 5.61003861003861, '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}}
Investigation of Load Schedules of Electrical Machines of a Mining Enterprise Using Wavelet Analysis

Modern trends in the development of the energy sector determine the problems of modernizing the technical equipment park, applying modern methodologies and designs, and reorienting to resource-innovative development. The coal industry enterprises are one of the objects to which the development strategy of the integrated power grid of the Russian Federation until 2035 is aimed to solve the problem of rational use of fuel and energy resources, including implementation of automated systems for measurement and production process control. To conduct a reliable analysis, it is necessary to eliminate noise components and outliers that occur during the data transmission process and that are caused by individual features of the technological process of an enterprise. In this paper, a wavelet transform is used for solving this problem. It helps in identifying trends, analyzing individual features for further use in a predictive control system. Modernization of the long-outdated technical complex of enterprises in the fuel and energy sector, implementation and application of modern methods of controlling the production process will make it possible to rationally choose price categories, make a short-term forecast required for prompt decision making and properly control electricity consumption process of the enterprise. Wavelet analysis also allows controlling operation and electricity consumption schedule of each individual consumer of a coal industry enterprise that makes it possible to evaluate the periodicity of its operation in time and determine the uniformity of its loading and downtime.