Abstract The resistance strain load cell has heavy creep error, which will lead to the low accuracy of weighing results. To reducing this error, a model compensation on the load cell’s creep error based on neural networks(NNs) is proposed, and the training algorithms of the model is given. The experimental results of the load cell which capacity is 50 kg and its accuracy class is C3 show that the creep errors of the load cell with this proposed model are less than those without compensation, and the maximal change of its creep errors is 0.0108 kg, it is less than that of the maximal permissible error defined by Chinese National Standard, GB/T 7551—2008 “Load cell”.
WANG You-gui,WU Shuang-shuang,CHEN Hong-jiang. Compensation Method for Creep Error of Load Cell Based on Neural Networks[J]. Acta Metrologica Sinica, 2018, 39(4): 510-514.
2018, Vol. 39 
