Emulating bearing faults : a novel approach

The relation between evolving mechanical faults in rotating electrical machines and their reflection in the machines’ electrical parameters still requires a lot of research. This implies serious obstructions in the evolution of e.g. Motor Current Signature Analysis as a complete and reliable condition monitoring technology. This paper presents the translation of common bearing faults into specific rotor-stator movements using finite element modeling. Subsequently, a novel method to elucidate the complex relation between rotor movements and the electrical parameters of an induction machine using an experimental test setup is described, dimensioned and simulated. Replacing one of the induction machine’s bearings with an Active Magnetic Bearing will give the opportunity to create specific rotor movements and consequently evaluate different programmable mechanical faults and their reflection in the stator current and/or voltage with high relevance and reproducibility

Emulating bearing faults — A novel approach

The relation between evolving mechanical faults in rotating electrical machines and their reflection in the machines’ electrical parameters still requires a lot of research. This implies serious obstructions in the evolution of e.g. Motor Current Signature Analysis as a complete and reliable condition monitoring technology. This paper presents the translation of common bearing faults into specific rotor-stator movements using finite element modeling. Subsequently, a novel method to elucidate the complex relation between rotor movements and the electrical parameters of an induction machine using an experimental test setup is described, dimensioned and simulated. Replacing one of the induction machine’s bearings with an Active Magnetic Bearing will give the opportunity to create specific rotor movements and consequently evaluate different programmable mechanical faults and their reflection in the stator current and/or voltage with high relevance and reproducibility

The reflection of evolving bearing faults in the stator current’s extended park vector approach for induction machines

Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology

Comparing MCSA with vibration analysis in order to detect bearing faults: a case study

Condition Monitoring on rotating electrical machines has proven to be economically beneficial in the last decades, especially for industrial production processes. Vibration analysis has already become a reliable and commercial tool to perform condition monitoring or predictive maintenance. Stator current analysis, a newer technology that is still being developed can possibly open new perspectives and opportunities in the world of predictive maintenance. This technology is also known as Motor Current Signature Analysis or MCSA. In this paper the advantages and disadvantages of both technologies are listed and compared from a practical point of view, supplemented with a case study. The case study contains a bearing fault detection in an induction machine driven by a frequency converter. The machine drives a fan with varying torque and speed conditions

Stator current measurements as a condition monitoring technology — The-state-of-the-art

Condition monitoring of electrical machines has proven to be economically beneficial within industrial production sites. This paper illustrates the technical implications of implementing Motor Current Signature Analysis (MCSA) as a tool for condition monitoring. The majority of machine failures are illustrated and are related to the state-of-the-art of MCSA. Because MCSA has become a valuable tool within the broader scope of condition monitoring during the last decade, a vast amount of new research opportunities can be presented. One of these opportunities is to determine Frequency Response Functions (FRFs) between the rotor vibrations and the stator current as a function of the operating point of the machine. This allows to estimate the mechanical machine fault vibrations out of the stator current frequency components, independently of its speed and load. This paper ends by presenting a research strategy to obtain this goal