State Monitoring and Fault Diagnosis Technology of Construction Machinery
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 ana-lyzes sensor data of construction machinery in real-time,uses deep learning models for fault diagnosis,and de-tects 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.
Construction machineryStatus monitoringFault diagnosisData drivenMachine learningDeep learning
NETL
NSTL
万方数据
