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在食品罐头测控现场的环境温度发生变化时,真空度输出值会随温度的变化而变化。使用电涡流传感器进行罐头的真空度测量,并采用RBF神经网络的进行温度补偿,可以明显提高测量精度。
When the ambient temperature of the food can measurement and control field changes, the output value of the vacuum will change with the temperature. Using eddy current sensor to measure the vacuum degree of canned food and using RBF neural network for temperature compensation can obviously improve the measurement accuracy.