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基于随机配置网络的海水养殖氨氮浓度软测量模型
引用本文:王魏,郭戈.基于随机配置网络的海水养殖氨氮浓度软测量模型[J].农业机械学报,2020,51(1):214-220.
作者姓名:王魏  郭戈
作者单位:大连海事大学船舶电气工程学院,大连116026;大连海洋大学信息工程学院,大连116023;大连海事大学船舶电气工程学院,大连116026;东北大学秦皇岛分校控制工程学院,秦皇岛066004
基金项目:国家自然科学基金项目(61503054)、大连市科技之星项目(2017RQ143)和辽宁省教育厅青年科技人才“育苗”项目(QL201912)
摘    要:氨氮浓度是水产养殖过程的重要监控指标,水中氨氮浓度过高,会产生较强的神经毒素,导致水生物大面积死亡,因此,需实时准确监测水产养殖过程中水的氨氮浓度。然而,由于影响海水水质因素较多,各因素之间关系复杂、相互影响,目前未能实现海水氨氮浓度的实时监测。通过分析海水养殖水体中氨氮的生成和硝化过程,选取水体中与氨氮浓度相关且易测的水质参数(温度、电导率、p H值、溶解氧质量浓度)为辅助变量,采用收敛速度快且泛化能力较强的随机配置网络建立了氨氮浓度软测量模型。为验证方法的有效性,设计了实验室海水养殖循环水系统,通过试验系统的实测数据,将该方法与其他几种神经网络建模方法进行了比较。结果表明,氨氮浓度随机配置网络模型具有更高的精度和更快的运行速度。基于模型设计了水产养殖水质监控系统,并将此方法嵌入上位机Win CC软件,实现了氨氮浓度的在线监测。

关 键 词:海水养殖  氨氮浓度  软测量  随机配置网络
收稿时间:2019/5/16 0:00:00

Soft Measurement Model for Ammonia Nitrogen Concentration in Marine Aquaculture Based on Stochastic Configuration Networks
WANG Wei and GUO Ge.Soft Measurement Model for Ammonia Nitrogen Concentration in Marine Aquaculture Based on Stochastic Configuration Networks[J].Transactions of the Chinese Society of Agricultural Machinery,2020,51(1):214-220.
Authors:WANG Wei and GUO Ge
Institution:Dalian Maritime University;Dalian Ocean University and Dalian Maritime University;Northeastern University at Qinhuangdao
Abstract:The concentration of ammonia nitrogen is one of the key indexes in the process of marine aquaculture.Excessive levels of ammonia nitrogen in the water produce strong neurotoxins,leading to large-scale death of aquatic organisms.Therefore,it is very important to monitor the concentration of ammonia nitrogen in water in real time and accurately.Due to many factors affecting seawater quality,and the complex factors often affect each other,there is no instrument to realize the real-time detection of seawater ammonia nitrogen concentration at present.Firstly,the current research status of ammonia nitrogen monitoring in water of aquaculture was reviewed.Then,the formation and nitrification process of ammonia nitrogen in marine aquaculture water was analyzed,and the parameters(temperature,conductivity,pH value and dissolved oxygen concentration)related to ammonia nitrogen concentration were selected as auxiliary variables.A soft measurement model of ammonia nitrogen concentration was established by using a stochastic configuration networks with high convergence speed and strong generalization ability.In order to verify the effectiveness,the proposed method was compared with other neural network modeling methods by using the measured data of the turbot intensive marine aquaculture system independently established by the laboratory.The results showed that the proposed method had higher generalization ability,higher prediction accuracy and faster running speed.Finally,the aquaculture water quality monitoring system was developed,and this method was embedded in the upper computer WinCC software to realize online monitoring of ammonia nitrogen concentration.
Keywords:marine aquaculture  ammonia nitrogen concentration  soft measurement  stochastic configuration networks
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