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基于无规则模糊逻辑算法的通信设备振动控制研究 被引量:1

Vibration Control of Communication Equipment Based on Irregular Fuzzy Logic Algorithm
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摘要 通信设备振动具有无规则性和逻辑模糊性特征,因此设计基于无规则模糊逻辑算法的通信设备振动控制方法。利用无规则模糊逻辑算法建立通信设备振动无规则模糊逻辑控制器,将振动信号和振动因素作为控制器输入,对振动信号和振动因素实施模糊化处理后,使用模糊推理方式得到振动信号综合模糊感觉强度,解析模糊感觉强度后获取通信设备振动模糊强度控制量。将模糊强度控制量输入到径向基(RBF)神经网络中,经过迭代输出反馈补偿误差,利用该误差校正模糊强度控制量后实现振动控制。实验结果表明,该方法推理的通信设备振动模糊感觉强度置信度最大为1.0,具备较强的模糊推理能力。该方法可有效控制通信交换机振动情况,控制成功率高,时间复杂度低,应用效果好。 The vibration of communication equipment has the characteristics of irregularity and logic fuzziness,so the vibration control method of communication equipment based on irregular fuzzy logic algorithm is designed.First,the irregular fuzzy logic controller of communication equipment vibra-tion is established by using the irregular fuzzy logic algorithm.Second,the vibration signal and vi-bration factor are taken as the controller input.After the fuzzy processing,the comprehensive fuzzy sense intensity of the vibration signal is obtained by using the fuzzy reasoning method,and the fuzzy sense intensity of the communication equipment vibration is obtained by analyzing the fuzzy sense in-tensity.Last,the fuzzy intensity control quantity is input into radial basis function(RBF)neural network,and the error is compensated by iterative output feedback.Consequently,the vibration control is realized after the fuzzy intensity control quantity is corrected by the error.The experimen-tal results show that the confidence degree of the fuzzy sense intensity of the vibration of the commu-nication equipment inferred by this method is 1.O,which has a strong fuzzy reasoning ability.This method can effectively control the vibration of the communication switch with high success rate,low time complexity and good application effect.
作者 郭贤斌 陈章斌 GUO Xianbin;CHEN Zhangbin(Fuzhou University of International Studies and Trade,Fuzhou 350202,China)
出处 《信息工程大学学报》 2023年第3期287-292,共6页 Journal of Information Engineering University
基金 福建省中青年教师教育科研资助项目(科技类)(JAT210524)。
关键词 无规则模糊逻辑 通信设备 振动控制 RBF神经网络 振动模糊强度 irregular fuzzy logic communication equipment vibration control RBF neural net-work vibration fuzzy intensity
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