Instituto Tecnológico de la Energía, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain.
Research Group ADIRE, Institute of Advanced Production Technologies (ITAP), University of Valladolid, 47011 Valladolid, Spain.
Sensors (Basel). 2021 Jul 25;21(15):5037. doi: 10.3390/s21155037.
Sensorless speed estimation has been extensively studied for its use in control schemes. Nevertheless, it is also a key step when applying Motor Current Signature Analysis to induction motor diagnosis: accurate speed estimation is vital to locate fault harmonics, and prevent false positives and false negatives, as shown at the beginning of the paper through a real industrial case. Unfortunately, existing sensorless speed estimation techniques either do not provide enough precision for this purpose or have limited applicability. Currently, this is preventing Industry 4.0 from having a precise and automatic system to monitor the motor condition. Despite its importance, there is no research published reviewing this topic. To fill this gap, this paper investigates, from both theoretical background and an industrial application perspective, the reasons behind these problems. Therefore, the families of sensorless speed estimation techniques, mainly conceived for sensorless control, are here reviewed and thoroughly analyzed from the perspective of their use for diagnosis. Moreover, the algorithms implemented in the two leading commercial diagnostic devices are analyzed using real examples from a database of industrial measurements belonging to 79 induction motors. The analysis and discussion through the paper are synthesized to summarize the lacks and weaknesses of the industry application of these methods, which helps to highlight the open problems, challenges and research prospects, showing the direction in which research efforts have to be made to solve this important problem.
无传感器速度估计在控制方案中得到了广泛的研究。然而，它也是应用电机电流特征分析进行感应电机诊断的关键步骤：准确的速度估计对于定位故障谐波至关重要，可以防止误报和漏报，正如本文开头通过一个真实的工业案例所示。不幸的是，现有的无传感器速度估计技术要么不能提供足够的精度，要么适用性有限。目前，这阻碍了工业 4.0 拥有一个精确和自动的系统来监测电机的状况。尽管其重要性，但是没有研究审查这个主题。为了填补这一空白，本文从理论背景和工业应用的角度，调查了这些问题背后的原因。因此，本文主要从诊断的角度，对主要为无传感器控制而设计的无传感器速度估计技术的家族进行了回顾和彻底分析。此外，还通过实际示例对两种领先的商业诊断设备中实现的算法进行了分析，这些示例来自一个属于 79 台感应电机的工业测量数据库。通过本文的分析和讨论，总结了这些方法在工业应用中的不足和弱点，有助于突出该领域的开放问题、挑战和研究前景，指明解决这一重要问题所需的研究方向。
