摘要
电梯曳引机作为驱动系统的核心部件,运行状态直接影响整部电梯的安全性与可靠性。为了及时发现隐性故障,提出一套基于振动信号特征提取的电梯曳引机故障预警系统,通过振动信号高频采样、小波包分解特征提取、构建故障分类支持向量机(Support Vector Machine,SVM)模型、自适应动态阈值预警相结合的策略,实现准确识别与预警典型故障状态。实验验证表明,该系统在故障识别、响应与误报控制方面均具有良好性能,具备实际应用价值。
As the core component of the drive system,the operating status of the elevator traction machine directly affects the safety and reliability of the entire elevator.To promptly detect latent faults,this paper proposes a fault early warning system for elevator traction machines based on vibration signal feature extraction.By combining high-frequency sampling of vibration signals,wavelet packet decomposition feature extraction,construction of fault classification Support Vector Machine(SVM)models,and adaptive dynamic threshold early warning strategies,it accurately identifies and issues early warnings for typical fault states.Experimental verification shows that the system has good performance in fault recognition,response,and false alarm control,and has practical application value.
作者
余丞
YU Cheng(Xiamen Special Equipment Inspection and Testing Institute,Xiamen 361000)
出处
《现代制造技术与装备》
2025年第11期81-83,共3页
Modern Manufacturing Technology and Equipment
关键词
电梯曳引机
振动信号
故障预警
elevator traction machine
vibration signal
fault warning
