Assessment of the Correlation between the Monitored Operating Parameters and Bearing Life in the Milling Head of a CNC Computer Numerical Control Machining Center

Abstract

The present paper describes a study conducted at the request of the operator of machining center equipment. The operator observed undesirable indicators in terms of increased backlash and vibration of the milling head and poor quality of the machined surfaces. Vibration measurements and vibrodiagnostics were carried out before disassembling the milling head in the idle state. The bearings, lubricant, and friction regime were analyzed in the next step. The vibrodiagnostic methods used included VEL, ACC, EN2, EN3, and EN4, with recommended limits conforming to STN ISO 10816-3. The vibration values obtained indicated a problem with the bearings, exceeding the limit values. After disassembly of the bearings, abrasive wear, corrosion, and improper lubricant conditions were detected. Lubricant analysis showed the presence of abrasive and corrosive particles, indicating an unsatisfactory friction regime. Determining the optimum lubricant temperature and the effect on friction torque constituted other aspects of the study. Inspection of the bearing microgeometry confirmed unsatisfactory roundness. Furthermore, the assembly of tapered roller bearings with axial preload was analyzed with a focus on bearing stiffness, accuracy, and life. The results showed that preload improves shaft guidance accuracy and load distribution, promoting reliable operation and extending bearing life.

An Intelligent Diagnostic Method for Wear Depth of Sliding Bearings Based on MGCNN

“…We recorded the actual MWD change curve for a wear test, as illustrated in Figure 19. Setting D threshold = 1000 µm, we use the diagnostic results at various depths and corresponding times to fit an exponential function [60], as shown in Equation (19). The time at which this fitted curve reaches the failure threshold is taken as the predicted failure time.…”

“…Alexander and Evgeny [18] studied the thermal analysis of bearing assemblies based on FEM and developed a methodological basis for implementing automatic diagnostics. Baron et al [19] conducted diagnosis and analysis for bearings from the CNC machining center based on various vibrodiagnostic methods. In summary, existing intelligent diagnostic methods extract features from monitoring data and input them into classifiers or regressors for fault diagnosis or useful life prediction.…”