三相感应电动机轴承故障检测的新方法

Respuestas Pub Date : 2020-09-01 DOI:10.22463/0122820X.2936
Carlos Cáceres-Amaya, J. Duarte-Forero, G. Valencia-Ochoa
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引用次数: 0

摘要

本研究展示了一种检测、分类和定位呈现球故障、保持架故障和外滚圈故障的轴承的方法。本研究采用三相感应电机,测量定子电流和电压信号。通过计算总谐波畸变并使用斯托克韦尔变换,得到了电信号的不同特征,从而可以确定轴承的故障条件、故障类型的分类以及故障轴承的位置(风扇侧或负载侧)。通过计算电流和电压信号的总谐波失真之间的差值,可以确定0.004的阈值,该阈值将健康状态和故障状态区分开来。联合使用斯托克韦尔变换和费舍尔评分算法使我们能够以92.5%的平均精度对故障条件进行分类。与位于风扇侧的轴承相比,在负载侧具有缺陷的轴承的位置在信号中产生更大的振幅。这种行为允许为球型错误建立1.6的阈值,为笼型错误和外圈错误建立0.001的阈值。由于所获得的结果,本文提出的算法被认为是一种具有高度可靠性的诊断异步电机轴承的工具。
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A new methodology for detection of bearings faults in three-phase induction motor
This study shows a methodology for the detection, classification, and location of bearings that presented ball faults, cage faults, and outer race faults. For this study, a three-phase induction motor was used, in which the stator current and voltage signals were measured. By calculating the total harmonic distortion and using the Stockwell Transform, different characteristics were obtained in the electrical signals that allowed defining fault conditions in the bearing, classification of the type of fault, and the location of the defective bearing (fan side or load side). By calculating the difference between the total harmonic distortion of the current and voltage signal, it is possible to identify a threshold value of 0.004 that separates a healthy condition and a fault condition. The joint use of the Stockwell Transform and the Fisher Scoring Algorithm allows us to classify the fault conditions with an average precision of 92.5%. The location of a bearing with defects on the load side generates a greater amplitude in the signal compared to those located on the fan side. This behavior allows establishing a threshold value of 1.6 for ball faults and 0.001 for cage faults and outer race. Due to the results obtained, the algorithm proposed in the study is considered to be a tool with a high degree of reliability for the diagnosis of bearings in induction motors.
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