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塑料称重配料的神经元迭代AI算法

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本文针对动态的塑料称重配料系统,使用贝加莱X20系列CPU为控制硬件,在分析目前流行的多种AI算法基础上,运用若干种AI算法解决塑料称重配料系统中非线性、强干扰、不稳定滞后、随机性等问题,并且区别于专家系统,将算法应用到塑料称重配料设备的批量生产巾.实践证明,这套自适应AI算法可以基本满足塑料称重配料设备的高精度、高响应、易操作的客户需求,可为塑料称重行业提供一定的借鉴.
Neuron iterative AI algorithm for plastic weighing and batching
This article focuses on the dynamic plastic weighing and batching system,using the Baikalei X20 series CPU as the control hardware.Based on the analysis of various popular AI algorithms,several Al algorithms are used to solve problems such as nonlinearity,strong interference,unstable lag,and randomness in the plastic weig-hing and batching system.Different from expert systems,the algorithm is applied to the batch production of plastic weighing and batching equipment.It has been proven that this adaptive AI algorithm can basically meet the custom-er needs of high-precision,high response,and easy operation of plastic weighing and batching equipment,and can provide certain reference for the plastic weighing industry.

Plastic weighing ingredientsAI algorithmAdaptiveNeural networkIterative control

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佛山市必创自动化设备有限公司,广东佛山 528000

塑料称重配料 AI算法 自适应 神经元网络 迭代控制

2024

聚酯工业
全国聚酯生产技术协作组 大连合成纤维研究设计院股份有限公司

聚酯工业

影响因子:0.2
ISSN:1008-8261
年,卷(期):2024.37(2)
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