杜盼, 孙道宗, 李震, 等. 基于故障树分析法的柑橘病虫害诊断专家系统[J]. 华南农业大学学报, 2022, 43(4): 106-112. DOI: 10.7671/j.issn.1001-411X.202110037
    引用本文: 杜盼, 孙道宗, 李震, 等. 基于故障树分析法的柑橘病虫害诊断专家系统[J]. 华南农业大学学报, 2022, 43(4): 106-112. DOI: 10.7671/j.issn.1001-411X.202110037
    DU Pan, SUN Daozong, LI Zhen, et al. An expert system for diagnosing citrus diseases and pests based on fault tree analysis[J]. Journal of South China Agricultural University, 2022, 43(4): 106-112. DOI: 10.7671/j.issn.1001-411X.202110037
    Citation: DU Pan, SUN Daozong, LI Zhen, et al. An expert system for diagnosing citrus diseases and pests based on fault tree analysis[J]. Journal of South China Agricultural University, 2022, 43(4): 106-112. DOI: 10.7671/j.issn.1001-411X.202110037

    基于故障树分析法的柑橘病虫害诊断专家系统

    An expert system for diagnosing citrus diseases and pests based on fault tree analysis

    • 摘要:
      目的  为解决柑橘病虫害防治工作中植物保护主业知识普及不足、高效病虫害诊断手段缺乏的问题,研制一种基于故障树分析法的柑橘病虫害诊断专家系统。
      方法  首先,利用故障树分析法计算病虫害发生的概率、建立病虫害知识库;其次,根据知识库以及正向推理策略设计实现专家系统的推理机;最后,利用微信开发者工具在微信小程序内搭建故障树分析法的计算规则、专家系统的推理机,构建基于故障树分析法的专家系统。
      结果  建立了一种包含病虫害模块、最新资讯模块、知识库查询模块、病虫害诊断模块、用户中心模块5大功能模块的柑橘病虫害诊断专家系统。经测试,系统可以在不同型号的手机中平稳运行,占用内存的平均大小为175 MB,系统启动的平均耗时为1.0984 s,页面切换的平均耗时为0.0495 s;连续运行系统1 h,手机与服务器的连接均未出现异常。
      结论  本系统运行稳定可靠、页面样式显示正常。用户通过此系统能够诊断病虫害并获得具体的防治技术,同时也能够了解专业的植物保护知识。

       

      Abstract:
      Objective  An expert system for diagnosing citrus diseases and pests based on fault tree analysis was developed to solve the problems of insufficient popularization of professional plant protection knowledge and lack of efficient diagnosis methods in the prevention and control of citrus diseases and pests.
      Method  First, fault tree analysis method was used to calculate the occurrence probability of diseases and pests and establish a knowledge base of diseases and pests. Secondly, based on the knowledge base and forward reasoning strategy, the reasoning engine of the expert system was designed and implemented. Finally, Weixin DevTools were used to equip the calculation rules of fault tree analysis method and the inference engine of expert system in weixin mini program, and build the expert system based on fault tree analysis method.
      Result  We established an expert system for diagnosing citrus diseases and pests with five functional modules: Pest knowledge module, latest information module, knowledge base query module, diseases and pest diagnosis module as well as user center module. After testing, the system could run smoothly in different types of mobile phones. The average size of memory occupied was 175 megabytes, the average time for system startup was 1.0984 s and the average time for page switching was 0.0495 s. After running the system continuously for 1 h, the connection between the mobile phone and the server was normal.
      Conclusion  The system is stable and reliable, and the page style is displayed normally. Users can exploit the system to diagnose diseases and pests and obtain corresponding control methods. Meanwhile, users can also learn professional plant protection knowledge from the system.

       

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