基于互联网下马铃薯组培苗接种机器人分布式管理信息系统设计
发布时间：2019-06-01 21:39
【摘要】：当今组培苗接种工作仍以人工操作为主,部分企业尝试研究接种机器人代替人工操作,但工作效率依然低下,原因是组培苗个体存在着巨大的差异性。在上述背景下,本课题开始设计分布式管理信息系统,旨在提高接种工作效率和提高农机与农艺的融合度。本课题通过分布式系统架构建立管理信息系统,实现系统的异地化管理,确保数据在系统与数据库之间正常传输。管理信息系统以多层前馈神经网络方法,即BP(back propagation)神经网络方法,初步建立组培苗机械作业适应性的评价体系。利用评价体系对组培苗进行评价,根据评价结果,得到机械作业适应性优秀的组培苗的培养条件,为建立组培苗成长数学模型提供理论依据。通过数学模型培育出,个体差异性小且机械作业适应性优秀的组培苗,提高农机与农艺的融合度,从而提高组培苗接种工作的效率。主要工作如下:1.搭建管理信息系统平台。分析马铃薯组培苗接种机器人工作情况,结合互联网(web:world wide web)技术,应用WAMP(Windows+Apache+My SQL+PHP)工具,以分布式系统架构搭建管理信息系统运行平台。2.管理信息系统的设计与实现。设计数据库,以便管理工作中产生的数据;将管理信息系统划分为16个模块,如组培苗入库、组培苗记录、组培苗出库等;可以实现系统与数据库之间数据传输。3.本文以马铃薯组培苗为试验对象,测量其相关参数(植株高度、茎秆直径、节间长度、满足节间长度要求的个数),结合实验室已完成的相关试验,建立组培苗机械作业适应性的评价准则。4.建立系统评价体系。对标准BP神经网络进行改进(限幅转移函数、累积误差法),以组培苗植株高度、组培苗茎秆直径、满足节间长度要求的个数为评价条件,适合机械作业程度为评价指标,训练BP神经网络得到评价体系。选取200株组培苗数据作为测试样本,对评价体系进行测试,将结果与建立的评价准则进行对比,检测评价体系的正确率,最后得到评价体系正确率为99%。将评价体系嵌入到系统中,完成管理信息系统建设。
[Abstract]:Nowadays, the work of tissue culture seedling vaccination is still dominated by manual operation. Some enterprises try to study the inoculating robot instead of artificial operation, but the work efficiency is still low, because there are great differences among tissue culture seedling individuals. Under the above background, this paper began to design a distributed management information system, in order to improve the efficiency of vaccination and improve the integration of agricultural machinery and agronomy. In this paper, the management information system is established through the distributed system architecture, which realizes the heterogeneous management of the system and ensures the normal transmission of data between the system and the database. In the management information system, the evaluation system of mechanical adaptability of tissue culture seedlings is established by using multi-layer feedforward neural network method, that is, BP (back propagation) neural network method. The evaluation system was used to evaluate the tissue culture plantlets. According to the evaluation results, the culture conditions of the tissue culture seedlings with excellent adaptability to mechanical operation were obtained, which provided a theoretical basis for the establishment of the mathematical model of the growth of tissue culture seedlings. Through the mathematical model, the tissue culture seedlings with small individual difference and excellent adaptability to mechanical operation were cultivated to improve the fusion degree of agricultural machinery and agronomy, so as to improve the efficiency of tissue culture seedling vaccination. The main work is as follows: 1. Build a management information system platform. The working situation of potato tissue culture seedling inoculating robot was analyzed. Combined with Internet (web:world wide web) technology, the running platform of management information system was built with distributed system architecture by using WAMP (Windows Apache My SQL PHP) tool. 2. Design and implementation of management information system. The database is designed to manage the data generated in the work; the management information system is divided into 16 modules, such as tissue culture seedling storage, tissue culture seedling record, tissue culture seedling out of the database and so on; the data transmission between the system and the database can be realized. In this paper, potato tissue culture seedlings were taken as the experimental object to measure the related parameters (plant height, stem diameter, Internode length, the number of Internode length to meet the requirements of Internode length), combined with the related experiments completed in the laboratory. The evaluation criteria of mechanical adaptability of tissue culture seedlings were established. 4. Establish a systematic evaluation system. The standard BP neural network was improved (limiting transfer function, cumulative error method). The plant height of tissue culture seedling, the diameter of stem of tissue culture seedling, the number of internode length satisfied were taken as the evaluation conditions, and the degree of mechanical operation was used as the evaluation index. The evaluation system is obtained by training BP neural network. The data of 200 tissue culture seedlings were selected as the test samples, and the evaluation system was tested. The results were compared with the established evaluation criteria, and the correct rate of the evaluation system was obtained. Finally, the correct rate of the evaluation system was 99%. The evaluation system is embedded into the system to complete the construction of management information system.
【学位授予单位】：东北农业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242;TP311.52
本文编号：2490603
[Abstract]:Nowadays, the work of tissue culture seedling vaccination is still dominated by manual operation. Some enterprises try to study the inoculating robot instead of artificial operation, but the work efficiency is still low, because there are great differences among tissue culture seedling individuals. Under the above background, this paper began to design a distributed management information system, in order to improve the efficiency of vaccination and improve the integration of agricultural machinery and agronomy. In this paper, the management information system is established through the distributed system architecture, which realizes the heterogeneous management of the system and ensures the normal transmission of data between the system and the database. In the management information system, the evaluation system of mechanical adaptability of tissue culture seedlings is established by using multi-layer feedforward neural network method, that is, BP (back propagation) neural network method. The evaluation system was used to evaluate the tissue culture plantlets. According to the evaluation results, the culture conditions of the tissue culture seedlings with excellent adaptability to mechanical operation were obtained, which provided a theoretical basis for the establishment of the mathematical model of the growth of tissue culture seedlings. Through the mathematical model, the tissue culture seedlings with small individual difference and excellent adaptability to mechanical operation were cultivated to improve the fusion degree of agricultural machinery and agronomy, so as to improve the efficiency of tissue culture seedling vaccination. The main work is as follows: 1. Build a management information system platform. The working situation of potato tissue culture seedling inoculating robot was analyzed. Combined with Internet (web:world wide web) technology, the running platform of management information system was built with distributed system architecture by using WAMP (Windows Apache My SQL PHP) tool. 2. Design and implementation of management information system. The database is designed to manage the data generated in the work; the management information system is divided into 16 modules, such as tissue culture seedling storage, tissue culture seedling record, tissue culture seedling out of the database and so on; the data transmission between the system and the database can be realized. In this paper, potato tissue culture seedlings were taken as the experimental object to measure the related parameters (plant height, stem diameter, Internode length, the number of Internode length to meet the requirements of Internode length), combined with the related experiments completed in the laboratory. The evaluation criteria of mechanical adaptability of tissue culture seedlings were established. 4. Establish a systematic evaluation system. The standard BP neural network was improved (limiting transfer function, cumulative error method). The plant height of tissue culture seedling, the diameter of stem of tissue culture seedling, the number of internode length satisfied were taken as the evaluation conditions, and the degree of mechanical operation was used as the evaluation index. The evaluation system is obtained by training BP neural network. The data of 200 tissue culture seedlings were selected as the test samples, and the evaluation system was tested. The results were compared with the established evaluation criteria, and the correct rate of the evaluation system was obtained. Finally, the correct rate of the evaluation system was 99%. The evaluation system is embedded into the system to complete the construction of management information system.
【学位授予单位】：东北农业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242;TP311.52
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