A belt conveyor is an efficient continuous carriage machine which successively moves powder or particles such as mineral, coal, gravel, sand, fertilizer, grains as well as packaged products by using a belt. To accurately measure the total weight of bulk materials conveyed continuously or the weight of individual packaged products moving quickly on a belt conveyor is important for developing a belt checkweigher.
There have been many studies to improve weighing accuracy. Those studies are basically focused on two kinds of methods; one is model-based and the other is filter-based.
Most of those studies are focused on dynamic weighing of packaged products in fast motion on a belt conveyor. However, there has been little literature for improving weighing accuracy of the belt conveyor that successively conveys bulk materials unequally distributed on the belt.
Kim Mun Hyok, a section head at the Faculty of Automatics, proposed a new hybrid weighing scheme using the discrete wavelet transform (DWT) and adaptive noise cancellation (ANC) to more accurately weigh the successively conveyed bulk material unequally distributed on the belt.
The proposed scheme uses wavelet decomposition and reconstruction to remove noises of high frequency and uses an adaptive filter to suppress noises of low frequency.
The simulation and experimental results show that the proposed scheme optimally removes various types of noises from belt conveyors and measures the weight with accuracy degree of ±0.5%.
If further details are needed, please refer to his paper “A DWT and ANC-based continuous weighing scheme of bulk materials in belt conveyor” in “Journal of Instrumentation” (SCI).