Bram Corne

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.

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.

Single point outer race bearing fault severity estimation using stator current measurements

Although numerous valuable research has been conducted by many authors, the relation between evolving mechanical faults and their fault-indicating reflections in the electrical signals of rotating electric machinery still requires extensive attention. This lack of information implies serious obstructions in the evolution of applying motor current signature analysis as a complete and reliable condition monitoring technology. However, as previous research of the authors resulted in the construction of a unique test-bench where specific mechanical faults can be introduced into an 11kW induction machine with high reproducibility and accuracy, the relations between evolving mechanical faults and their reflections in the stator current can be investigated and quantified experimentally. Using this mechanical fault-emulator, experiments where conducted where the severity of a single point outer race bearing fault and its corresponding signature in the stator currents spectral fault-components are accurately analyzed. These evolving faulty components are trended and characterized, resulting in the desired quantification of the mechanical fault-severity. Based on these results, it is possible to inversely estimate the severity of single point outer race bearing problems by acquiring nothing more then the stator current time-functions.