铁道科学与工程学报2026，Vol.23Issue(8)：4066-4076,11.DOI:10.19713/j.cnki.43-1423/u.T20251663
基于黏着特性自适应识别的列车轮对空转故障检测
Adhesion characteristic adaptive identification-based slipping fault detection for train wheelset
摘要
Abstract
Long-term operation of trains accelerates the aging and wear of wheelsets,which may compromise operational stability and pose potential safety hazards.Accurate detection of the wheelset slipping faults is crucial for enhancing train operational safety and reducing maintenance costs.However,traditional detection methods struggle to adapt to complex and varying operating conditions,which often leads to false detections of wheelset slipping faults.To address this issue,this paper proposed a train wheelset slipping fault detection method based on adaptive identification of adhesion characteristics,aiming to improve the detection speed and reduce the false detection rate of the slipping fault.First,an adaptive sliding mode observer-based wheelset load torque estimation method was proposed.By integrating the dynamic variation characteristics of the sliding surface,the observation performance of the load torque was corrected.Then,considering the axle load distribution and adhesion coefficient variation under different line conditions,a moving average detection index was designed,and an adhesion characteristic adaptive identification-based wheelset slipping fault detection mechanism was established.Finally,the proposed method was experimentally validated on a hardware-in-the-loop simulation platform for train wheelset operation state monitoring.Experimental results demonstrate that the proposed detection method does not trigger the slipping fault detection threshold when the train transitions from the flat railway line to a ramp railway line.Meanwhile,it achieves millisecond-level slipping fault detection when the wheelset experiences slipping faults.Compared to the traditional method,the proposed method effectively reduces the false detection rate of the slipping fault.Specifically,it does not trigger the slipping fault detection signal when the train transitions from a flat railway line to a ramp railway line,improves detection speed performance by 50%under the wet railway conditions,and enhances detection speed performance by up to 80%under the icy and snowy rail conditions.The experimental performance metrics demonstrate that the proposed method is better suited to different operating conditions of the train,offering more accurate and faster detection performance.关键词
自适应识别/黏着特性/空转故障/检测/列车轮对Key words
adaptive identification/adhesion characteristic/slipping fault/detection/train wheelset分类
交通工程引用本文复制引用
王明强,殷士才,宋宗莹,徐琰淞,王兴中,彭涛..基于黏着特性自适应识别的列车轮对空转故障检测[J].铁道科学与工程学报,2026,23(8):4066-4076,11.基金项目
国家能源集团科技创新项目(GJNY-22-7) （GJNY-22-7）
中南大学轨道交通节能控制与安全监测湖南省重点实验室资助项目(2017TP1002) （2017TP1002）
