Fault Diagnosis of Suspended Electromagnet Based on Current Change Rate Increment
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摘要:
为提高复杂工况下悬浮电磁铁线圈故障诊断的准确性，基于故障前、后电流特性变化，考虑温度、加减载、气隙扰动等因素的影响，提出一种基于周期内电流变化率增量的电磁铁线圈故障诊断方法. 通过建立两电平控制下电磁铁线圈输出电流变化率增量的数学模型，分析得到电流变化特性，明确电磁铁线圈匝间短路是电流变化率增量异常的本质因素，即可通过检测电流变化率增量变化来作为故障判断条件；针对间隙变化导致电流变化率增量改变触发误诊断的问题，采用最小二乘法求解实际间隙与正常状态下电量变化率增量的关系式，建立查找表，从而根据间隙变化来实时调整电流变化率增量阈值. 经过仿真和实验验证：该算法适用于磁浮列车的各种工况，鲁棒性强；在线圈短路比5%时，故障诊断准确率高达97%，灵敏度高；能够在一个基波周期内完成故障诊断，诊断速度快.
Abstract:To improve the accuracy of fault diagnosis for suspended electromagnet coils under complex operating conditions, a fault diagnosis method for electromagnet coils based on the increment of current change rate within a cycle was proposed based on the changes in current characteristics before and after the failure, taking into account the effects of temperature, load variation, and air gap disturbances. By establishing a mathematical model for the increment of the electromagnet coil’s output current change rate under two-level control, the current variation characteristics were analyzed. It was clarified that an interturn short circuit in the electromagnet coil was the fundamental cause of abnormal current change rate increment, making it feasible to use the variation in current change rate increment as a criterion for fault detection. Moreover, to address the issue of false diagnoses triggered by changes in the air gap that affected the current change rate increment, the least squares method was used to derive the relationship between the actual air gap and the current change rate increment under normal conditions. A lookup table was then established to dynamically adjust the threshold of the current change rate increment in real time based on air gap variations. Simulation and experimental results verify that the proposed algorithm is suitable for various operating conditions of maglev trains, demonstrating strong robustness. When the coil’s short circuit ratio is less than 5%, the fault diagnosis accuracy reaches as high as 97%, with high sensitivity. Moreover, the algorithm is capable of completing fault diagnosis within a single fundamental cycle, ensuring rapid detection.
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图 1 正常状态下不同开关状态的电路模态
Figure 1. Circuit modes of different switching states under normal condition
图 3 正常状态下电流变化率增量拟合曲线
Figure 3. Fitting curve of current change rate increment under normal condition
图 4 不同短路比下故障特征对比曲线
Figure 4. Fault characteristic comparison curves under different short circuit ratios
图 6 电磁铁匝间短路故障仿真结果
Figure 6. Simulation results of electromagnet’s interturn short circuit fault
图 7 电磁铁线圈匝间短路加载仿真
Figure 7. Simulation of electromagnet coil’s interturn short circuit loading
图 8 电磁铁线圈匝间短路温度变化仿真
Figure 8. Simulation of temperature change during electromagnet coil’s interturn short circuit
图 9 电磁铁线圈匝间短路间隙扰动仿真
Figure 9. Simulation of air gap disturbance during electromagnet coil’s interturn short circuit
图 10 基于Cspace悬浮控制单元故障诊断实验平台
Figure 10. Fault diagnosis experiment platform based on CSpace suspension control unit
图 12 电磁铁线圈匝间短路实验波形
Figure 12. Interturn short circuit test waveforms of electromagnet coil
表 1 诊断性能对比
Table 1. Comparison of diagnosis performance
% 诊断方法 准确诊断率 误报率 漏诊率 电流斜率 90 2 8 Δk 97 1 2 
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