本文選題：奶牛 + 反芻監測　； 參考：《東北農業大學》2017年碩士論文

【摘要】：畜牧業的每一次飛躍,都伴隨著一場技術革新,快速發展的同時,也暴露出當前我國牧場養殖體系的缺口,雖然已經成為第三大奶業生產國家,但我國依舊存在牛源緊缺,牧場管理方式落后,奶制品供給量達不到標準等問題,并且我國目前多數大規模牧場引進國外先進設備對奶牛反芻行為進行實時監測,但其技術壟斷,研發成本高昂。為此,本文研究了奶牛個體反芻行為檢測設備,實現成本較低,可自動化檢測奶牛反芻行為,從而掌握奶牛個體發情及身體健康情況,減少牧場人力物力,提升牧場工作效率,增添牧場收益。首先,對奶牛個體反芻行為檢測設備進行總體方案設計。主要包括設計需求、功能分析、總體設計以及工作原理,同時,對設備的抗干擾性進行設計,并從技術可行性以及經濟可行性對設備進行可行性分析。隨后,對奶牛個體反芻行為檢測設備進行硬件系統的詳細設計。選用MSP430F149型號單片機作為該設備的主處理器,LM386聲音傳感器采集奶牛反芻及采食時的聲音信號,并為此設備設計信號調理模塊,采用場效應管高輸入阻抗差動放大器進行聲音信號的放大,選用二階帶通有源濾波器對聲音信號進行濾波,應用mocro SDHC UHS-l存儲卡對信息進行存儲。因為奶牛反芻多數發生在夜晚并且不宜受到外界的干擾,所以數據傳輸模塊選用基于Zig Bee的無線傳輸方式。采用RFID射頻技術對奶牛個體身份進行識別。本設備的設計以低功耗為原則,故又對設備的供電方式進行全面分析,最終選取鋰亞電池對設備進行供電。最后,對奶牛個體反芻聲音識別算法進行研究設計并移植到奶牛個體反芻行為檢測設備中進行模擬仿真實驗。應用Cool Edit Pro軟件對奶牛反芻及采食行為的聲音頻譜進行特征分析,應用預加重以及加漢明窗方式將聲音信號做預處理,并獲取聲音信號短時平均能量以及短時平均過零率,以此對奶牛反芻聲音信號進行時域分析。隨后應用LPCC倒譜系數對奶牛反芻聲音信號進行頻域特征提取,得出奶牛反芻聲音頻率大約在400Hz-1KHz左右。將此算法移植到奶牛個體反芻行為檢測設備中,通過對比發現該算法能夠較好的檢測奶牛的反芻行為,可靠性較高。應用錄音儀器在農場采集連續5天同一頭奶牛的反芻及采食的聲音,應用本設備對錄音儀器進行5輪每輪5天的奶牛反芻次數模擬檢測,實驗結果表明,該設備性能穩定,可靠性較高,精準度達90%,可以有效的對奶牛反芻行為進行檢測。綜上所述,本文研究的奶牛個體反芻行為檢測設備具備奶牛反芻行為的檢測、反芻次數的測量以及數據無線傳輸的功能。應用嵌入式、單片機、傳感器、無線傳輸等技術,實現了自動化、智能化、信息化的監測奶牛反芻行為,為我國畜牧業的長足發展提供了支持。該設備實現成本低、易操作、精度較高、穩定性較好,對奶牛個體的身體健康狀況以及發情情況具有良好的指導性作用。
[Abstract]:Each leap forward in animal husbandry has been accompanied by a technological innovation and rapid development, at the same time, it has also exposed the gap in the current pastureland farming system in China. Although it has become the third largest dairy production country, there is still a shortage of cattle resources in our country. The management of pasture is backward, the supply of dairy products is not up to the standard, and most of the large-scale pastures in our country introduce foreign advanced equipment to monitor the ruminant behavior in real time, but its technology monopoly and high cost of research and development. Therefore, this paper studies the equipment of individual ruminant behavior detection in dairy cattle, which can realize low cost and can automatically detect cow ruminant behavior, so as to master individual estrus and body health of dairy cow, reduce manpower and material resources of pasture, and improve the efficiency of pasture work. Increase pasture income. First of all, the overall scheme design of individual ruminant behavior testing equipment is carried out. It mainly includes design requirements, function analysis, general design and working principle. At the same time, the anti-interference ability of the equipment is designed, and the feasibility of the equipment is analyzed from the technical feasibility and economic feasibility. Then, the detailed design of the hardware system for individual ruminant behavior detection equipment of dairy cattle was carried out. The MSP430F149 singlechip was chosen as the main processor of the equipment, and the LM386 sound sensor was used to collect the sound signals of cow ruminating and feeding, and the signal conditioning module was designed for this equipment. The high input impedance differential amplifier of FET is used to amplify the sound signal, the second order band-pass active filter is used to filter the sound signal, and the mocro SDHC UHS-l memory card is used to store the information. Because most cows ruminant occurs at night and is unsuitable for outside interference, the wireless transmission mode based on Zig Bee is used in the data transmission module. RFID radio frequency technology was used to identify the individual identity of dairy cattle. The design of the equipment is based on the principle of low power consumption, so the power supply mode of the equipment is analyzed comprehensively, and the lithium subbattery is selected to supply the power to the equipment. Finally, the algorithm of individual ruminant recognition is studied and designed and transplanted to the individual ruminant behavior detection equipment to simulate the simulation experiment. The acoustic spectrum of ruminant and feeding behavior of dairy cattle was analyzed by Cool Edit Pro software. The sound signal was preprocessed by pre-weighting and Hanming window, and the short time average energy and zero crossing rate of sound signal were obtained. The time domain analysis of the ruminant sound signal was carried out. LPCC cepstrum coefficient was then used to extract the frequency feature of the ruminant sound signal, and the frequency of ruminant sound was about 400Hz-1KHz. The algorithm is transplanted into the equipment for individual ruminant behavior detection of dairy cows. It is found that the algorithm can detect the ruminant behavior of dairy cows better and has higher reliability. The sound of ruminating and feeding of the same cow was collected by recording instrument in farm for 5 consecutive days. The equipment was used to simulate the ruminant times of dairy cows for 5 rounds and 5 days per round. The experimental results showed that the equipment was stable in performance. The reliability is high and the precision is 90, which can effectively detect the ruminant behavior of dairy cows. To sum up, the equipment of individual ruminant behavior detection in this paper has the functions of testing cow ruminant behavior, measuring ruminant times and wireless data transmission. With the application of embedded technology, single chip computer, sensor and wireless transmission technology, automatic, intelligent and informational monitoring of cow ruminant behavior has been realized, which has provided support for the rapid development of animal husbandry in China. The equipment has the advantages of low cost, easy operation, high precision and good stability. It has a good instructive effect on the individual health and estrus of dairy cow.
【學位授予單位】：東北農業大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：S823;TP274

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本文編號：1975795