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Rolling-element bearings are high-precision components that need to be stored and handled carefully to perform as designed. Proper storage and
handling of a bearing before, during
and after installation is important because once debris enters a bearing, it
reduces the life.
Experienced operators can often
tell if a machine is not working
properly, on the basis that it does
not ‘sound right.’ The same principle can be applied — using modern electronics — to identify the exact cause of the problem.
Sensitive accelerometers can detect and analyze the vibrations from industrial equipment, highlighting problems such as misalignment
or bearing imbalance. The technique
is known as vibration analysis. It can
identify bearing failure in the very early stages, when there is a microscopic defect on the raceway, for example. The problem is that the
identifying signal is usually drowned out in all the other noise emanating from the machine.
For a 5-megawatt wind turbine prototype,
aerodyn employs the latest control and software technologies, including a comprehensive PC-based control solution and the new modular TwinCAT Wind Framework. The TwinCAT Wind Framework features the latest software engineering and Big Data applications to extend current Industry 4.0 concepts to the wind energy industry. The modular software supports, for example, the direct provision of sensor data to the operator’s database, and in general enables the easy adaption of the wind turbine operation management to future requirements.
This paper presents a method for the acoustic analysis of electric motors in noisy industrial environments. Acoustic
signals were measured via acoustic camera 48-microphone array, which has the capability to localize a sound
(or sounds) source and, in turn, separate those sounds from intrusive background noise. These acoustic analysis results are then compared with vibration measurements; vibration monitoring is a well-known and established technique used in condition monitoring, and in this work vibration measurements were used as a reference signal for assessment of the value of the acoustic measurements. Vibration signals were measured by piezoelectric accelerometers. Two induction motor cases were examined — a healthy motor case, and a combination of static eccentricity with soft foot case. As shown, acoustic analysis appears to be a valuable technique for condition
monitoring of electric motors — particularly in noisy industrial environments.