The interruption of a three-phase induction motor (TIM) on production lines represents a high financial and operational cost. However, these machines are often exposed to mechanical and electrical failures that can cause unexpected stoppages. Among these failures, the voltage unbalance (VU) is a supply fault that can lead to winding wear, torque losses, overheating, and other side effects. In this context, the acoustic emission (AE) analysis stands out as a promising nondestructive technique (NDT) in TIM monitoring. However, the AE method was not previously completely validated for VU diagnosis, and several research gaps need to be filled. Therefore, this work proposes a novel AE approach for detection, phase identification, and magnitude classification of VU. For this purpose, an electrical machine monitored by piezoelectric sensors was subjected to different levels of unbalanced voltages. The AE signals were processed using the novel zero-cross-weighted energy (ZE) index. This metric was based on the energy of the wavelet transform (WT) coefficients weighted by zero-crossing rate values. Experimental results revealed that the proposed index proved to be effective for detecting the VU occurrence. Besides, ZE-based data separation was proposed and achieved VU phase identification. Finally, the magnitude of the unbalanced voltages was classified by linear regression. The accuracy parameters for detection, phase identification, and magnitude classification stated the reliability of the new approach. Finally, the efforts of this work provide new functionalities to traditional AE systems.

中文翻译：

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一种新的基于声发射的三相感应电机供电干扰评估方法

生产线上的三相感应电机 (TIM) 中断意味着高昂的财务和运营成本。然而，这些机器经常面临机械和电气故障，可能导致意外停机。在这些故障中，电压不平衡 (VU) 是一种电源故障，可导致绕组磨损、扭矩损失、过热和其他副作用。在这种情况下，声发射 (AE) 分析是 TIM 监测中一种很有前途的无损技术 (NDT)。然而，AE 方法之前并未完全验证 VU 诊断，需要填补几个研究空白。因此，这项工作提出了一种新的 AE 方法，用于 VU 的检测、相位识别和幅度分类。以此目的，由压电传感器监控的电机受到不同水平的不平衡电压的影响。使用新的零交叉加权能量 (ZE) 指数处理 AE 信号。该度量基于由过零率值加权的小波变换 (WT) 系数的能量。实验结果表明，所提出的指标被证明可以有效地检测 VU 的发生。此外，提出了基于ZE的数据分离并实现了VU相位识别。最后，通过线性回归对不平衡电压的大小进行分类。检测、相位识别和幅度分类的精度参数表明了新方法的可靠性。最后，这项工作的努力为传统的 AE 系统提供了新的功能。