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Featured Application: This study represents a breakthrough in the engineering of turning processes for manufacturing. By examining dynamic properties and vibration response during turning, it provides key insights for real-time machining system monitoring. The findings can improve surface quality and stability, particularly for slender, flexible shafts. Industries such as automotive, aerospace, and heavy equipment manufacturing can leverage these insights to optimize machine performance, reduce downtime, and boost productivity. This marks a significant stride towards more efficient manufacturing. The chatter that occurs during the turning operation, especially when cutting a slender and flexible shaft, determines the surface quality of the workpiece and the stability of the machining system. However, when building a dynamic model of a slender workpiece with a chuck and tailstock, it is generally regarded as a cantilever or simply supported beam, without consideration of the axial force and supported stiffness effect. In this work, a dynamic model for thin and flexible workpieces with different clamping boundary conditions was first built. Then, a finite element analysis (FEA) was used to study the influence of the axial force and supporting stiffness on the mode frequencies of the workpiece. A further analysis found that the relationship between support stiffness, axial force, and the dynamic response of the workpiece is nonlinear and far more complex than that of the simply supported beam model. The clamping force directly influenced the magnitude of the vibration response with the decrease of shaft stiffness during the turning process. These results were verified experimentally by measuring the vibrational response of slender shafts with different clamping modes using an on-rotor sensing (ORS) system. It proved that the proposed model shows advantages for the identification of dynamic vibration and quality control when machining slender workpieces. [ABSTRACT FROM AUTHOR]

Wear is one of the most common failures of hydrodynamic bearings. The main purpose of the present work was to investigate the effects of wear on lubrication performance and acquire efficient vibration signatures for fault diagnosis. In this paper, a finite element model (FEM) for a two-disk rotor supported on worn hydrodynamic bearings is presented in which the oil film force is evaluated by linear and nonlinear models. Numerical and experimental results indicate that the static and dynamic characteristics of the bearing are significantly changed by wear, leading to a drop in system critical speeds due to the deterioration of the constraint status provided by the bearings to the rotor. As the wear depth increases, the onset speed of oil whirl increases, while that of oil whip becomes lower, and large amplitudes of resonance and oil whip are more likely to be excited. More notably, all of the above vibration signatures in the y-direction are more sensitive to wear compared to those in the x-direction, which means that wear faults can be diagnosed by differences in vibration characteristics between the x- and y-directions. This research can provide a theoretical foundation and engineering guidance for the hydrodynamic bearing wear fault diagnosis. [ABSTRACT FROM AUTHOR]

To ensure reliable and efficient operation of gas turbines, multiple model (MM) approaches have been extensively studied for online fault detection and isolation (FDI). However, current MM-FDI approaches are difficult to directly apply to gas path FDI, which is one of the common faults in gas turbines and is understood to mainly be due to the high complexity and computation in updating hypothetical gas path faults for online applications. In this paper, a fault contribution matrix (FCM) based MM-FDI approach is proposed to implement gas path FDI over a wide operating range. As the FCM is realized via an additive term of the healthy model set, the hypothetical models for various gas path faults can be easily established and updated online. In addition, a gap metric analysis method for operating points selection is also proposed, which yields the healthy model set from the equal intervals linearized models to approximate the nonlinearity of the gas turbine over a wide range of operating conditions with specified accuracy and computational efficiency. Simulation case studies conducted on a two-shaft marine gas turbine demonstrated the proposed approach is capable of adaptively updating hypothetical model sets to accurately differentiate both single and multiple faults of various gas path faults. [ABSTRACT FROM AUTHOR]