基于大数据分析的机动设备早期故障智能诊断技术研究与应用

Research and Application of Intelligent Diagnosis Technology for Early Fault of Mobile Equipment Based on Big Data Analysis

目前国内很多工厂的机动设备智能化诊断技术工作还处于起步阶段,动设备机组监测技术应用范围不广,故障智能诊断技术水平不高,现有设备的状态监测技术还不能满足机动设备智能化诊断和管理的需求,多数故障诊断还依赖于专家经验进行分析判断,部分安装了在线状态监测系统的设备,其在线状态监测系统发挥的作用有限,未能结合大数据分析开展故障预测,将大数据分析与在线状态监测系统相结合,基于设备状态监测和预测的维修方式,开展机动设备的故障诊断技术研究与应用,旨在通过系统的分析和诊断技术,提前识别设备的潜在问题和故障风险,从而制定适当的预防措施和维修计划,以便在故障发生前采取行动,减少停机时间和维修成本,从而真正实现动设备的预知性维修。

At present,many factories in China are still in the early stages of intelligent diagnosis technology for mobile equipment.The application scope of monitoring technology for mobile equipment units is not wide,and the level of intelligent fault diagnosis technology is not high.The existing equipment status monitoring technology cannot meet the needs of intlligent diagnosis and management of mobile equipment.Most fault diagnosis still relies on expert experience for analysis and judgment,and some equipment installed with online status monitoring systems,The online status monitoring system has limited effectiveness and has not been able to combine big data analysis for fault prediction.It combines big data analysis with online status monitoring systems and conducts research and application of fault diagnosis technology for mobile equipment based on equipment status monitoring and prediction maintenance methods.The aim is to identify potential problems and fault risks of equipment in advance through system analysis and diagnostic technology,Thus,appropriate preventive measures and maintenance plans can be formulated to take action before faults occur,reduce downtime and maintenance costs,and truly achieve predictive maintenance of moving equipment.