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农业机械故障智能检测与诊断技术应用OA

Research on iIntelligent detection and diagnosis technology of agricultural machinery failure

中文摘要英文摘要

农业机械由于长期在复杂、多变的田间环境中作业,极易发生磨损、腐蚀、传动失效、传感器异常等多种故障.本文综述当前农业机械设备常见故障类型与成因,分析基于振动信号、声音信号、热成像、电流波形等多种信息源的故障检测方法,并探讨专家系统、模糊逻辑、人工神经网络、支持向量机(SVM)等智能诊断技术在农业装备中的应用进展.通过构建多源信息融合与实时监测系统,对农业机械设备的运行状态可以实现早期预警与故障精准定位.旨在为农业机械故障检测技术的优化与农业智能装备的研制提供理论支持与技术参考.

Agricultural machinery is very prone to wear and tear,corrosion,transmission failure,sensor abnormalities and other faults due to long-term operation in complex and changing field environments.This paper reviews the current common failure types and causes of agricultural machinery and equipment,analyzes the failure detection methods based on vibration signals,sound signals,thermal imaging,current waveforms and other information sources,and discusses the progress of the application of intelligent diagnostic technologies such as expert systems,fuzzy logic,artificial neural networks,and support vector machines(SVM)in agricultural equipment.By building a multi-source information fu-sion and real-time monitoring system,the health status of agricultural machinery and equipment can realize early warn-ing and accurate positioning.The purpose of this paper is to provide theoretical support and technical reference for the optimization of agricultural machinery fault detection technology and the development of agricultural intelligent equip-ment.

孙佳伟

朝阳县农业综合行政执法队,辽宁 朝阳 122629

农业科技

农业机械故障检测智能诊断传感技术人工智能

agricultural machineryfault detectionintelligent diagnosissensing technologyartificial intelligence

《农机使用与维修》 2026 (6)

100-103,4

10.14031/j.cnki.njwx.2026.06.023

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