Screw type multi-component material batching device and its controller

Abstract

The invention discloses a screw-type multi-component material batching device and a controller thereof. The batching device includes a frame, multiple sets of lower bins and screw conveyors, a weighing hopper, a weighing module, a blanking valve, a mixing hopper, a control There is an hourglass-shaped distributor on the upper part of the metering hopper, and a distance sensor and a vibrating rod are respectively installed on the side wall of the lower silo and the frame. The controller adjusts the speed of the feeding pump to control the material level of the feeding bin within a narrow range, adjusts the operating speed of the screw conveyor, and performs iterative predictive control of its closing time based on the current and accumulated feeding errors. The invention adopts the distance sensor, the vibrating rod and the distributor to reduce the change of the material distribution and the impact during the feeding process, accelerate the convergence speed of the iterative prediction, obtain a higher feeding speed while ensuring the accuracy, and is suitable for small Quick batching of batches.

Description

technical field [0001] The invention relates to the field of quantitative batching, in particular to a screw type multi-component material batching device and a controller thereof. Background technique [0002] In industrial and agricultural manufacturing and commodity packaging, there are a large number of powder materials, such as polypropylene, polystyrene, polyvinyl chloride, light methyl cellulose, polypropylene nitrile, epoxy resin powder coating and other chemical raw materials, quartz sand, Raw materials for building materials such as cement, household chemical products such as washing powder, agricultural products such as millet and soybeans, grains and legumes, or processed food in powder, slag, and granular form, agricultural production materials such as feed, chemical fertilizers, and pesticides, as well as powdered and granular health care products, Chinese and Western medicines , condiments, etc. all need automatic quantitative packaging or ingredient manufactu...

AI Technical Summary

Problems solved by technology

In order to improve the feeding accuracy, various adjustment methods have appeared, such as the Chinese patent application number 201320001933.3, which adopts frequency conversion speed regulation for the screw, and gradually slows down the feeding speed when it is close to the target value, reducing the drop in the air; the application number is 201310234280.8 Chinese patent, in the three-speed frequency conversion feeding process of soda ash packaging machine, large and small screws are used to feed in multiple stages; the Chinese patent with application number 200920248298.2 considers that it is difficult to control the quantitative during fast feeding, and it is reduced by the method of fast first and then slow The impact of feeding drop; the final value of the blanking of these non-weighing schemes can only be close to the expected value, and the accuracy is not high

[0005] Weighing type quantification is used for metering, filling or feeding according to the set amount of material at one time. It needs to be weighed continuously during the feeding process, and the feeding amount is controlled according to the feedback of the weighing result. Because the weighing is affected by the impact of the feeding and the lagging material in the air. Large, the feeding speed and precision are facing many difficulties

In order to compensate for the interference of airborne materials on the measurement accuracy, many schemes adopt the technology of closing the valve in advance. For example, the Chinese patent application number 201410230888.8 divides the ingredient weighing process into three stages, and uses iterative learning control method to calculate in the last stage Turn off the advance control amount, but this scheme can only improve the blanking accuracy after the learning is completed, and the cumulative blanking accuracy during the learning process cannot be guaranteed

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