种猪生产性能测定系统开发与性能测试

发布时间：2018-09-19 15:57

【摘要】：为开展种猪生产性能的智能化、自动化测定及开展种猪采食行为学研究,该研究设计了一种集自动识别、体质量感知、采食行为数据自动采集、数据分析与处理于一体的种猪生产性能智能测定系统。该系统主要由猪只耳标识别模块、精准下料控制模块、料槽及猪只个体称质量模块、现场数据通讯模块及远程中央控制模块组成。系统机械部分主要包括饲喂站的竖直侧墙、称质量平台、活动挡板、下料机构、料仓、控制盒、出料口开关及耳标识读器等组成。电路控制系统包括微处理器(LPC1766,内核为ARM Cortex-M3内核的微控制器)、RS232读卡器接口、数据存储芯片(预设存储256 KB数据)、看门狗电路、称质量电路、外围驱动电路、JTAG接口电路及稳压电源电路。系统性能测试结果表明:1)测量精度如下:饲喂下料没有范围限制,取决于喂料仓的储料状态,单次下料量及动态误差为93±2g;猪只体质量秤量程为0~200 kg,计量精度为10 g,称量动态误差占猪只体质量的0.5%以下,符合测定需求;2)对40头种公猪后裔的生长肥育猪饲喂测试结果表明,在25~60 kg体质量范围内,自由采食日均次数10~12次,日均采食时间78min,测试期间料肉比(FCR)为2.33:1,且生长规律符合Gompertz曲线,通过该模型预测的日增质量下降的拐点发生111~117d之间,对应的拐点体质量在63~64 kg范围内。上述实际观察及预测结果较好地反映了测定对象的生产性能,开发的软件及硬件系统达到了种猪生产性能测定的要求;3)系统下料控制部分,首次采用雨刷电机取代早期采用的步进电机,不仅成本下降,尤其结合圆柱式刮板下料机构,降低了单次下料量,改善了下料的精度;4)系统核心芯片采用进口器件,电路设计采用多重冗余和保护电路,软件的编写采用了多重功能验证,并通过长期可靠性测试;软件和硬件的冗余设计,提高了控制系统的可靠性,消除来自电源、电机、电磁波干扰,该测定系统具有极高的可靠性;测定的数据通过计算机系统可长期保存或升迁,便于数据量的积累和开展种猪选育的大数据挖掘分析。
[Abstract]:In order to carry out intelligent, automatic measurement of production performance of breeding pigs and research on feeding behavior of breeding pigs, a kind of automatic data collection for body mass perception, body mass perception and feeding behavior was designed. Data analysis and processing in one of the production performance of pig intelligent measurement system. The system is mainly composed of pig ear mark identification module, precision feeding control module, feed tank and pig individual weight module, field data communication module and remote central control module. The mechanical part of the system mainly includes the vertical side wall of feeding station, the mass platform, the movable baffle, the feeding mechanism, the silo, the control box, the outlet switch and the earmark reader. The circuit control system includes microprocessor (LPC1766, core is the microcontroller with ARM Cortex-M3 kernel) and RS232 card reader interface, data storage chip (preset storage 256KB data), watchdog circuit, quality circuit, etc. The peripheral drive circuit includes JTAG interface circuit and power supply circuit. The system performance test results show that the accuracy of the measurement is as follows: there is no limit to the range of the feedstock, which depends on the state of the feeding bin. The single feed quantity and dynamic error were 93 卤2g, the measuring precision was 10 g and the weighing dynamic error was less than 0.5% of the body weight of the pig. In the range of 25 ~ 60 kg body mass, the average daily intake was 10 ~ 12 times and the average daily intake time was 78 minutes. During the test period, the ratio of feed to meat was 2.33: 1, and the growth law was in accordance with the Gompertz curve. The inflection point of daily mass decline predicted by this model occurred between 111 and 117 days. The body mass of the corresponding inflection point is in the range of 63 ~ 64 kg. The above actual observation and prediction results well reflect the production performance of the tested objects, and the software and hardware system developed has met the requirement of testing the production performance of breeding pigs, and the discharge control part of the system has been developed. It is the first time that the wiper motor is used to replace the early step motor. Not only the cost is reduced, but also the input device is used in the core chip of the system, especially in combination with the cylindrical scraper cutting mechanism, which reduces the amount of single load and improves the precision of blanking. The circuit is designed with multiple redundancy and protection circuits, the software is verified by multiple functions, and the long term reliability is tested. The redundancy design of software and hardware improves the reliability of the control system and eliminates the power supply and motor. Because of electromagnetic wave interference, the system has high reliability, and the measured data can be saved or upgraded for a long time by computer system, which is convenient for the accumulation of data and the mining and analysis of big data breeding.
【作者单位】：中国农业科学院北京畜牧兽医研究所动物营养学国家重点实验室;北京农学院奶牛营养学北京市重点实验室;
【基金】：国家“十三五”重点研发课题(2016YFD0700205,2016YFD0700201) 北京市重大计划项目所属课题(D171100000417002)
【分类号】：S828

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