EVALUATION OF THE STATE OF DYNAMIC WEIGHING BY THE KALMAN FILTER METHOD

Abstract

Currently, due to widespread computerization, the development of automated control systems is relevant. Due to the development of small businesses, the purchase of commercially available systems is a very expensive solution. It is possible to create similar control systems based on inexpensive microprocessor kits (in this particular case, the K1816VE35 microprocessor kit is used). In the future, such a system will not be difficult to improve, and it is also easy to implementinterfacing with various electronic computers (control from a personal computer). A system for measuring and regulating bulk raw materials (an automated weighing system) is to be developed, which provides control of the pneumatic transport automation with a 2-speed rotary dispenser, through which bulk raw materials are fed to a weighing hopper suspended on a load-bearing device. Measuring the weight of the bulk mass in the hopper of the scales, followed by automatic control of unloading of bulk raw materials from the hopper. The profitability of any industrial operation involving the weighing of raw materials, work in progress and finished products directly depends on the accuracy of the weight data. However, even when using high-precision weighing equipment, the method of collecting, recording and processing weight data for the micro ingredients system may be subject to errors and inaccuracies. This can cause a potential revenue drain that is difficult to detect and verify. In many cases, it is assumed that the cause of the problem is related to the weighing equipment, whereas in fact it is related to the traditional data collection and management system. In many factories where bulk products are mixed in batches, dosing scales is a manual, time-consuming operation in which the ingredients are weighed separately before loading into a blender or other technological container. A significant number of such plants can benefit from the installation of an automated weighing and dosing system.

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Published:

2022-05-26

Issue:

Section:

SECTION III. INFORMATION PROCESSING ALGORITHMS

Keywords:

Kalman filter, weighing process, process modeling, weighing conveyor, mathematical model