Dynamic weighing method for checkweigher

Abstract

The main purpose of this study is to examine the checkweigher system. It is necessary to accurately estimate the weight of the product in motion with a checkweigher. This is an estimation process, as the measurement data obtained in motion will never be as clean as the static measurement data. The measurement error tolerance is limited by state regulations. Therefore, a dynamic weight measurement system should obey particular regulations in order to be used in industry. The automatic weight control system, checkweigher, which is used in many areas from production to shipment in the industry, consists of three conveyor belts, at least two photocells, load cell, processor, control screen for the user and rejector/router arms. In the system, the product carried by the in-feed conveyor belt is guided by the output conveyor belt after passing over the conveyor belt connected to the load cell. At this point, at the time of passing over the conveyor belt connected to the load cell, data is received by the load cell at a sampling frequency of 1600 Hz and sent to the processor for processing. The working principle of the load cell depends on the stretching and compression state of the resistors called strain gauges. When force is applied to a load cell, some resistors compress while others flex. When this change is converted to voltage, an inference can be made about the weight of the product. There are many noise factors that affect the measurement signal. The time-variant low-pass filter in the cascade form can effectively filter out the noise from the load cell signal, but quite a lot of filters are required to achieve high accuracy. In this study, a different approach was tried with a time-variant low-pass filter in order to accelerate measurements. The number of cascade form low-pass filter is optimized to shorten the response time while providing regulation-complaint measurement accuracy. By applying the filter, it is aimed to reach the mass of the product from the oscillations with minimum number of filters. The maximum speed obtained within the error limits was specified. As a result, by reducing the number of filters and increasing the damping, the weight data of product from the oscillations were reached faster within the error limits given in the regulation.