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Until now the estimation of rolling bearing life has been based on engineering models that consider an
equivalent stress, originated beneath the contact surface, that is applied to the stressed volume of the
rolling contact. Through the years, fatigue surface–originated failures, resulting from reduced lubrication or
contamination, have been incorporated into the estimation of the bearing life by applying a penalty to the
overall equivalent stress of the rolling contact. Due to this simplification, the accounting of some specific
failure modes originated directly at the surface of the rolling contact can be challenging. In the present
article, this issue is addressed by developing a general approach for rolling contact life in which the surfaceoriginated
damage is explicitly formulated into the basic fatigue equations of the rolling contact. This is
achieved by introducing a function to describe surface-originated failures and coupling it with the traditional,
subsurface-originated fatigue risk of the rolling contact. The article presents the fundamental theory of the
new model and its general behavior. The ability of the present general method to provide an account for
the surface–subsurface competing fatigue mechanisms taking place in rolling bearings is discussed with
reference to endurance testing data.
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.