基于多传感器数据融合的纸浆浓度自适应调节方法  

Adaptive Regulation Method of Pulp Concentration Based on Multi-sensor Data Fusion

作　　者：陈运财[1] CHEN Yuncai(Guangdong Engineering Polytechnic,Guangzhou 510520,China)

机构地区：[1]广东工程职业技术学院,广东广州510520

出　　处：《造纸科学与技术》2022年第5期57-62,共6页Paper Science & Technology

摘　　要：纸浆浓度控制过程中,需要对即时温度、浆液状态、料口状态等数据进行实时综合分析,受到不同传感器模量之间的差量的影响,实际控制调节效果与预期调节指令之间误差较大。通过对问题的分析发现,减小误差的关键在于提升多传感器之间的适应度,因此基于多传感器数据融合算法与思路,通过对常规纸浆浓度控制参数优化、多传感器控制量的浓度指标深度优化、多传感器优化量自适应优化、数据融合输出,实现提升调节精度,改善多传感器数据融合适应度的效果。实验通过3种不同函数环境的测试,证明了提出方法能够应对不同函数变量,精度调节纸浆浓度,并且在多传感器数据融合过程中,实现函数级别的自适应阈值优化,保证实际应用过程中的效果稳定。In the process of pulp concentration control, it is necessary to carry out real-time comprehensive analysis of immediate temperature, slurry state, material state and other data. Affected by the difference between different sensor moduli, the error between the actual control adjustment effect and the expected adjustment instruction is large. Through the analysis of the problem found that the key to reduce the error is to improve the fitness between multiple sensors. Therefore, based on multiple sensor data fusion algorithm and ideas, through the conventional pulp concentration control parameter optimization, multiple sensor control concentration index of depth optimization, multiple sensor optimization adaptive optimization, data fusion output, improve adjustment accuracy, improve the effect of multiple sensor data fusion fitness. Through three different function environments, the experiment proved that the proposed method can deal with different function variables, adjust the pulp concentration accurately, and realize the adaptive threshold optimization at the function level in the process of multi-sensor data fusion, to ensure the stability of the effect in the practical application process.

关 键 词：多传感器 数据融合 纸浆浓度 自适应调节 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]