Analysis of influencing factors that can cause errors in the application of modern methods of sliding bearing diagnostics in machine and electrical systems
Abstract
Introduction/purpose: The paper presents the application of modern methods in the diagnostics of sliding bearings and the analysis of influencing factors that can cause errors in such an application. Possibilities to determine with certainty when and where problems affect sliding bearings during system operation are presented. It is also shown how the system will continue to function over time. Causes of failures and the manner of their elimination are predicted, as well as the time for planned maintenance of technical systems.
Method: The new method solves the problem of sliding bearing diagnostics by measuring the dynamic trajectories of the sleeve in the sliding bearing and by measuring vibration parameters on the inner and outer surfaces of the technical system. The dynamic trajectories of the bearing sleeve are measured with non-contact probes; therefore, the centering of probes in relation to the geometric center of the bearing is very important. Vibration parameters, directly related to the clearance in the sliding bearing, are measured on the inner and outer surfaces of the system. The choice of vibration parameters and measuring points is very important. This method has a number of advantages over other diagnostic methods, as it is easy to access measuring points.
Results: By measuring the dynamic trajectory of the sleeves in the plain bearing and vibration parameters on the inner and outer surfaces, the bearing clearance quantities are determined, including: normal condition, initial clearance size, its further increase, bearing clearance sizes, and the moment when the condition parameters are close to the upper limit of the permissible bearing clearance.
Conclusion: New diagnostic methods and monitoring systems can be widely applied to: internal combustion engines, all piston machines, hydroelectric power plants, thermal power plants, processing plants, and many other systems.
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