摘要
本文深入探讨了工程机械状态监测与故障诊断技术的最新发展。针对工程机械在运行过程中可能遇到的各种故障,提出一种基于数据驱动和机器学习的先进监测系统。该系统通过实时采集并分析工程机械传感器数据,利用深度学习模型进行故障诊断,提前发现并预防潜在故障。本文介绍了该系统的设计框架和关键技术,包括数据预处理、特征提取以及故障诊断模型的建立。
This article delves into the latest developments in state monitoring and fault diagnosis technology for construction machinery.A data-driven and machine learning based advanced monitoring system is proposed to address various faults that construction machinery may encounter during operation.The system collects and analyzes sensor data of construction machinery in real-time,uses deep learning models for fault diagnosis,and detects and prevents potential faults in advance.This article introduces the design framework and key technologies of the system,including data preprocessing,feature extraction,and the establishment of a fault diagnosis model.
作者
蒋秀英
Jiang Xiu-ying(Sichuan Chuanjiao Road and Bridge Co.,Ltd.,Sichuan Deyang 618300)
出处
《内燃机与配件》
2024年第15期76-78,共3页
Internal Combustion Engine & Parts
关键词
工程机械
状态监测
故障诊断
数据驱动
机器学习
深度学习
Construction machinery
Status monitoring
Fault diagnosis
Data driven
Machine learning
Deep learning
