多源信息融合方法的精密魚類喂養(yǎng)
發(fā)布時間：2018-10-16 12:51
【摘要】：水產(chǎn)養(yǎng)殖是提高魚類食物或者漁業(yè)資源的有效途徑。近些年,差不多50%的海鮮源自水產(chǎn)養(yǎng)殖,并以每年大約9%的增長率增長。然而在水產(chǎn)養(yǎng)殖過程中,由于技術(shù)和資源利用不當,造成差不多有60%的飼料被浪費。合適的水產(chǎn)養(yǎng)殖管理,例如:水質(zhì)管理、魚類喂食管理、魚病診斷管理和技術(shù)資源的有效利用等能有效解決以上問題。針對水產(chǎn)養(yǎng)殖中的魚類生長所采用的傳感技術(shù)、無線傳感網(wǎng)絡、監(jiān)控系統(tǒng)、機器視覺以及建模策略已不再新穎。大多數(shù)與建模相關(guān)的文章多與多因子缺省數(shù)學模型相關(guān),技術(shù)相關(guān)的文章缺少整合系統(tǒng)。因此,本文的目的是研究與討論影響采食量建模的因子,并以信息融合的方式整合在水產(chǎn)養(yǎng)殖中應用的技術(shù)。此外,基于對聲波壓力數(shù)據(jù)的時間序列分析,構(gòu)建依據(jù)魚類生物量探索水情變化的軟件系統(tǒng)。本文簡要地確定并描述了當前的采食量建模發(fā)展現(xiàn)狀,并概述傳感器技術(shù)、機器視覺技術(shù)在水產(chǎn)養(yǎng)殖方面的應用,例如水質(zhì)、魚類行為、魚病、廢棄物管理。作者提出環(huán)境因子、營養(yǎng)因素、飼養(yǎng)因素、生理學因素是影響采食量所需考慮的重要因素,并以此為依據(jù)對飼養(yǎng)策略進行建模,以更有助于魚類的生長。作者同時提出了基于傳感器與機器視覺,對多方面的水產(chǎn)養(yǎng)殖因素例如水質(zhì)、魚類投喂、魚類行為、魚病診斷與廢棄物管理的進行融合。此外,在實驗室環(huán)境下設計的監(jiān)控系統(tǒng)已被用于研究魚類生物量對聲波壓力頻率、振幅、周期的影響。我們采用聲波壓力傳感器、模擬接收器(示波器)與軟件程序flukview來檢測在水產(chǎn)養(yǎng)殖用箱體中的波動現(xiàn)象。另外,文章還對在有魚、無魚狀態(tài)下的時間函數(shù)的參數(shù)進行了對比與數(shù)理統(tǒng)計。同樣地,以統(tǒng)計學的方式解釋了基于不同音程的離差測量(MOD)以及中心趨勢測量(MCT)結(jié)果。本研究證明了聲頻測量是一種簡單而有效的集約化水產(chǎn)養(yǎng)殖環(huán)境分析工具。相對于在空氣中傳播,聲波信號在水中傳播迅速,因此可以通過聲波壓力頻率測量出來。本研究成果是對基于聲波壓力測量來控制飼養(yǎng)廢棄物、高效飼養(yǎng)來提高水產(chǎn)養(yǎng)殖魚類生長的創(chuàng)新。本研究在結(jié)論部分對使用聲波壓力測量的需求、以及集成聲波技術(shù)與機器視覺技術(shù)的混合系統(tǒng)進行了展望。
[Abstract]:Aquaculture is an effective way to improve fish food or fishery resources. In recent years, almost 50% of seafood has come from aquaculture, growing at an annual rate of about 9%. However, in aquaculture, almost 60% of feed is wasted due to improper use of technology and resources. Appropriate aquaculture management, such as water quality management, fish feeding management, fish disease diagnosis management and effective use of technical resources, can effectively solve the above problems. The sensing techniques, wireless sensor networks, monitoring systems, machine vision and modeling strategies for fish growth in aquaculture are no longer novel. Most of the articles related to modeling are related to the multi-factor default mathematical model, and the technical related articles lack of integrated system. Therefore, the purpose of this paper is to study and discuss the factors that affect the modeling of feed intake, and integrate the techniques used in aquaculture by information fusion. In addition, based on the time series analysis of acoustic pressure data, a software system is constructed to explore water regime changes based on fish biomass. This paper briefly defines and describes the current situation of food intake modeling, and summarizes the applications of sensor technology and machine vision technology in aquaculture, such as water quality, fish behavior, fish disease, waste management. The author puts forward that environmental factors, nutrition factors, feeding factors and physiological factors are the important factors that need to be considered to influence the feed intake, and based on these factors, the feeding strategy is modeled, so as to be more helpful to the growth of fish. At the same time, based on sensor and machine vision, the authors proposed the fusion of various aquaculture factors such as water quality, fish feeding, fish behavior, fish disease diagnosis and waste management. In addition, the monitoring system designed in laboratory environment has been used to study the effects of fish biomass on acoustic pressure frequency, amplitude and period. Acoustic pressure sensors, analog receivers (oscilloscopes) and software program flukview are used to detect fluctuations in aquiculture tanks. In addition, the parameters of time function under the condition of fish and fish are compared with mathematical statistics. Similarly, the results of deviation measurement (MOD) based on different intervals and central trend measurement (MCT) are statistically explained. This study proved that audio measurement is a simple and effective tool for intensive aquaculture environment analysis. Sound signals travel rapidly in water relative to air, and can therefore be measured by acoustic pressure frequencies. This research is based on acoustic pressure measurement to control the feeding waste, high-efficiency feeding to improve the growth of aquaculture fish innovation. In the conclusion of this study, the requirement of acoustic pressure measurement and the hybrid system of acoustic wave technology and machine vision technology are prospected.
【學位授予單位】：中國農(nóng)業(yè)大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：S951.2
本文編號：2274412
[Abstract]:Aquaculture is an effective way to improve fish food or fishery resources. In recent years, almost 50% of seafood has come from aquaculture, growing at an annual rate of about 9%. However, in aquaculture, almost 60% of feed is wasted due to improper use of technology and resources. Appropriate aquaculture management, such as water quality management, fish feeding management, fish disease diagnosis management and effective use of technical resources, can effectively solve the above problems. The sensing techniques, wireless sensor networks, monitoring systems, machine vision and modeling strategies for fish growth in aquaculture are no longer novel. Most of the articles related to modeling are related to the multi-factor default mathematical model, and the technical related articles lack of integrated system. Therefore, the purpose of this paper is to study and discuss the factors that affect the modeling of feed intake, and integrate the techniques used in aquaculture by information fusion. In addition, based on the time series analysis of acoustic pressure data, a software system is constructed to explore water regime changes based on fish biomass. This paper briefly defines and describes the current situation of food intake modeling, and summarizes the applications of sensor technology and machine vision technology in aquaculture, such as water quality, fish behavior, fish disease, waste management. The author puts forward that environmental factors, nutrition factors, feeding factors and physiological factors are the important factors that need to be considered to influence the feed intake, and based on these factors, the feeding strategy is modeled, so as to be more helpful to the growth of fish. At the same time, based on sensor and machine vision, the authors proposed the fusion of various aquaculture factors such as water quality, fish feeding, fish behavior, fish disease diagnosis and waste management. In addition, the monitoring system designed in laboratory environment has been used to study the effects of fish biomass on acoustic pressure frequency, amplitude and period. Acoustic pressure sensors, analog receivers (oscilloscopes) and software program flukview are used to detect fluctuations in aquiculture tanks. In addition, the parameters of time function under the condition of fish and fish are compared with mathematical statistics. Similarly, the results of deviation measurement (MOD) based on different intervals and central trend measurement (MCT) are statistically explained. This study proved that audio measurement is a simple and effective tool for intensive aquaculture environment analysis. Sound signals travel rapidly in water relative to air, and can therefore be measured by acoustic pressure frequencies. This research is based on acoustic pressure measurement to control the feeding waste, high-efficiency feeding to improve the growth of aquaculture fish innovation. In the conclusion of this study, the requirement of acoustic pressure measurement and the hybrid system of acoustic wave technology and machine vision technology are prospected.
【學位授予單位】：中國農(nóng)業(yè)大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：S951.2
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相關(guān)期刊論文 前5條
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