基于故障树的智慧农业车故障诊断

Fault Diagnosis of Intelligent Agricultural Vehicles Based on Fault Trees

  • 摘要: 针对智慧农业车故障定位复杂、诊断困难的问题,基于故障树分析法对智慧农业车从结构、运行特点以及故障形式等方面进行故障分析,并针对性的提出解决方案。智慧农业车有监控、机械、除草、喷洒四大功能模块构成,针对农业生产中除草、施肥、病虫害防治等环节的效率和精准度问题,基于故障树分析法,进行了智慧农业车的故障分析。结果表明机械磨损、电气短路、传感器失灵及控制系统故障为主要故障模式,其根本故障原因有环境恶劣、操作失误及维护不足等。为后续对农业机器的研究提供可靠的依据,有助于推动农业机械化、智能化的发展。

     

    Abstract: Aiming at the problems of complex fault location and difficult diagnosis of intelligent agricultural vehicles, fault analysis is carried out on intelligent agricultural vehicles from aspects such as structure, operation characteristics and fault forms based on the fault tree analysis method, and targeted solutions are proposed.The intelligent agricultural vehicle consists of four major functional modules: monitoring, machinery, weeding, and spraying. Regarding the issues of efficiency and accuracy in the links such as weeding, fertilizing, and pest and disease control in agricultural production, fault analysis of the intelligent agricultural vehicle is conducted based on the fault tree analysis method.The results show that mechanical wear, electrical short circuits, sensor failures, and control system malfunctions are the main fault modes, and the root causes of these faults include harsh environments, operational errors, and insufficient maintenance.This provides a reliable basis for subsequent research on agricultural machinery and helps promote the development of agricultural mechanization and intelligence.

     

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