Force–displacement transducers are key components in in situ nanoindentation systems. The current existing capacitance-type transducers adopted in state-of-the-art commercial in situ nanoindentation systems are restricted by limited maximum ranges, and strain gauge-type transducers in the current in situ nanoindentation systems have the limitation of low resolution and high values of mass. In the paper, we propose a mechanical design and improvement of a low-mass strain gauge-type force–displacement transducer capable of performing high resolution in situ nanoindentation measurements. The transducer mainly consisted of a parallelogram-shaped flexure hinge and two strain gauges. Air resolution, in situ resolution, and mass experiments reported an air force resolution of 5 μN, an in situ force resolution of 5 μN inside a scanning electron microscope (SEM), and a mass of 6.53 g of such a strain gauge-type load–displacement transducer. Then, the transducer was assembled into a newly developed in situ nanoindentation–atomic force microscope (AFM) hybrid system and a newly developed in situ nanoindentation system. The proposed design successfully performed nanoindentation measurements inside SEM. Based on the results, the proposed strain gauge-type transducer shows great advantages compared to the current state-of-the-art transducers.

In rotating machinery, aerodynamic forces and oil film forces often lead to cross-coupling stiffness. This paper is aimed at studying the stick-slip whirling vibrations induced by the piecewise smooth rotor/stator frictions in a modified flexible rotor subjected to cross-coupling stiffness. Governing equations determining the sliding region and boundaries of piecewise discontinuous friction are defined. This analytical study was conducted to discuss the complex vibrations and bifurcations. Various types of sliding motions (continuous pure rolling, continuous crossing, and grazing–sliding) were observed in this research. Further, as for discussing the impacts of the parameters on nonlinear sliding vibrations, a parametric study was conducted. The obtained results reveal that with an increase in the cross-coupling stiffness coefficient, continuous pure rolling occurs earlier, and the disk vibration time around the contact regime becomes shorter. For studying the self-excited backward whirling vibration of stick–slip nonlinear motions, analytical formulations are established. Detailed vibration amplitude and frequency studies of friction-induced backward whirling vibrations were carried out. Numerical simulations were performed to compare them with the analytical solutions and to validate the results as well. The proposed theory and results provide fresh perspectives for predicting friction-induced whirlings and creating proper designs for turbo machinery.

Bearing health is key for maintaining good performance and safety in rotating machinery. As the diagnosis of mechanical faults develops toward intelligence and automation, accurate and systematic fault diagnosis algorithms are imperative. Focusing on the diagnosis of rolling bearing failures, this study utilizes a sliding time window to extract essential data segments. A series of signal processing techniques, including filtering, amplitude–frequency analysis, Hilbert envelope analysis, and energy analysis, is applied to establish a comprehensive dataset. For extraction of the hidden properties of the data, the recurrence quantity spectrum is defined for the input of the neural network. The goal is to obtain a cleaner dataset with enhanced features. A convolution neural network is constructed. Different activation functions in the activation layer are compared for better fault diagnosis algorithms. The established feature matrices are specifically defined to accurately identify the subtlest defects of bearings, thereby facilitating early detection. The proposed procedure distinguishes various fault modes. As for the multidimensional complexities of fault signals, this study carries out a comprehensive comparison of energies, recurrence quantification, and amplitude–frequency characteristics of bearing fault detection to assess the accuracy, computational efficiency, and robustness of bearing fault diagnosis. The proposed method and bearing fault detection procedures have potential in practical applications.