Rolling bearings face different damaging effects: Besides mechanical effects, current-induced bearing damage occurs in electrical drive systems. Therefore, it is of increasing interest to understand the differences leading to known electrical damage patterns. It is of utmost importance not to consider the harmful current passage in the machine element as an isolated phenomenon but to take into account the whole drive system consisting of the machine elements, the electric motor and the connected power electronics. This publication works toward providing an overview of the state-of-the-art of research regarding electrical bearing currents.
In the course of the electrification of powertrains, rolling element bearings are increasingly subject to electrical damage. In contrast to mechanically generated pittings, voltage-induced surface damage is a continuous process. Though several approaches for the description of the damage state of a bearing are known, a generally accepted quantification for the bearing damage has not been established yet. This paper investigates surface properties, which can be used as a metric damage scale for the quantification of the electric bearing damage progression. For this purpose, the requirements for suitable surface properties are defined. Afterwards, thrust ball bearings are installed on a test rig, with constantly loaded mechanically and periodically damaged electrically in multiple phases. After each phase, the bearings are disassembled, the bearing surfaces are graded and measured for 45 different standardized surface properties. These properties are evaluated with the defined requirements. For the ones meeting the requirements, critical levels are presented, which allow for a quantified distinction between grey frosting and corrugation surfaces. These values are compared with measurements presented in the literature showing that the identified surface properties are suitable for the quantification of electrical bearing damages.
Condition monitoring of technical systems has increasing importance for the reduction of downtimes based on unplanned breakdowns. Rolling bearings are a central component of machines because they often support energy-transmitting elements like shafts and spur gears. Bearing damages lead to a high number of machine breakdowns; thus, observing these has the potential to reduce unplanned downtimes. The observation of bearings is challenging since their behavior in operation cannot be investigated directly. A common solution for this task is the measurement of vibration or component temperature, which is able to show an already occurred bearing damage. Measuring the electrical bearing impedance in situ has the ability to gather information about bearing revolution speed and bearing loads. Additionally, measuring the impedance allows for the detection and localization of damages in the bearing, as early research has shown. In this paper, the impedance signal of five fatigue tests is investigated using individual feature selection. Additionally, the feature behavior is analyzed and explained. It is shown that the three different bearing operational time phases can be distinguished via the analysis of impedance signal features. Furthermore, some of the features show a significant change in behavior prior to the occurrence of initial damages before the vibration signals of the test rig vary from a normal state.
This paper presents a novel condition monitoring method for rolling bearings, based on measuring the electric bearing impedance. The method can diagnose the presence of damage by frequency-domain analysis, and its extension along the raceway by time-domain analysis. The latter enables the assessment of the severity and the progression of bearing damage. A fatigue test shows that the occurrence of pittings in the bearing raceways causes characteristic peaks in the impedance signal, and that the duration of the peaks increases during damage progression. A second test series with artificial damage shows that the duration of the peaks depends on the bearing load and the length of the damage along the raceway and confirms the explanation hypothesis.
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