EVALUATION CHARACTERISTICS OF THE BAGASSE DRYING PROCESS
Keywords:Pulp drying, processing of temperature data, mathematical expectation, standard deviation, histogram of distribution frequency
In the process of sugar production, much attention is paid to production automation, which controls the relevant technological parameters. Drying of pulp is an expensive and energy-intensive process. The use of only drying laboratory cabinets to control the moisture content of dry pulp is time consuming and can lead to deviations in the moisture content of the product. Installing humidity sensors as elements of the automation system at facilities with different temperature regimes at the inlet and outlet of the dryer is a simple and reliable way to save money, as it allows you to measure the humidity of dry pulp in the online stream, drying temperature and gas consumption. You can adjust the temperature, drying time, speed of movement of the product through the dryer and guarantee the required level of humidity of the product for granulation and storage. The case of dependence of pulp production on gas supply is considered. The input data is the gas flow rate over a fixed time t during which the specified output is produced. Build a graph of the frequency of distribution of each random variable, grouped into intervals. There are point estimates of this sample: mathematical expectation, standard deviation of each random variable to determine the optimal use of resources. To study the dependence of random variables, the parameters of the normal distribution law for these values are determined. To effectively use the pulp drying process, the dependence on the amount of gas supply to the number of products is considered. According to the given normal law of distribution of technological parameters of drying and production of pulp at the corresponding given expenses of gas it is possible to put forward a hypothesis about an interval estimation of distribution between production and consumption of gas. With a stable gas supply of 0.108, the production of pulp will be optimal. The directions of further research of the sugar production process in order to develop current mathematical models and systems for its automation are determined.
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