动设备智能状态监测在化工企业的应用  

Application of intelligent status monitoring of dynamic equipment in chemical enterprises

作　　者：郭磊[1] GUO Lei(Urumqi Petrochemical Company Electromechanical Instrument Operation and Maintenance Center,Urumqi 830019,China)

机构地区：[1]乌鲁木齐石化公司机电仪运维中心,新疆乌鲁木齐830019

出　　处：《聚酯工业》2025年第2期59-61,共3页Polyester Industry

摘　　要：在化工生产领域,其流程复杂且具有连续性、高危性等特点。动设备作为核心生产工具,涵盖泵、压缩机、离心机等关键设备,其稳定运行直接关乎化工生产的安全性、高效性与经济性。一旦动设备出现故障,不仅会导致生产中断,造成巨大的经济损失,还可能引发安全事故,威胁人员生命安全,对环境造成严重破坏。传统的设备监测方式,如人工巡检和简单的定期检测,存在明显的局限性。通过实时监测、数据分析和智能预警,企业能够实现预测性维护,显著提高设备可靠性和生产效率。本研究通过实际案例验证了智能状态监测系统的有效性,展示了其在降低维护成本、减少非计划停机方面的显著优势。In the field of chemical production,the process is complex and has characteristics such as continuity and high risk.As the core production tool,dynamic equipment covers key equipment such as pumps,compressors,centrifuges,etc.Its stable operation directly affects the safety,efficiency,and economy of chemical production.Once the moving equipment malfunctions,it not only causes production interruption and huge economic losses,but also may lead to safety accidents,threaten personnel's life safety,and cause serious damage to the environment.Traditional equipment monitoring methods,such as manual inspections and simple periodic checks,have significant limitations.Through real-time monitoring,data analysis,and intelligent warning,enterprises can achieve predictive maintenance,significantly improving equipment reliability and production efficiency.This study verified the effectiveness of the intelligent state monitoring system through practical cases,demonstrating its significant advantages in reducing maintenance costs and minimizing unplanned downtime.

关 键 词：智能状态监测 预测性维护 人工智能 数据收集 

分 类 号：TQ051.5[化学工程]