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.

Vibration and shock control systems are of vital importance to modern vehicles when incorporating crashworthiness goals and enhancing occupant safety to protect avionics or electronics during survivable crash events. The study proposes a method denoted as the optimal generalized Bingham number (GBN) control to improve the soft-landing control accuracy of a drop-induced shock mitigation system employing a magnetorheological shock absorber (MREA). Based on the theoretical and experimental analysis of the damping force characteristics of the MREA, the dynamics of a single-degree-of-freedom shock mitigation system are established, and the GBN is defined with consideration of quadratic damping. The optimal GBN control strategy for a magnetorheological shock mitigation system is proposed to achieve a soft landing. The deceleration, velocity, and displacement formulas of the payload are derived, and the dynamic response of the magnetorheological shock mitigation system, under different GBNs, is analyzed. In terms of soft-landing control accuracy, it is shown that the optimal GBN control strategy performs better for a linear stroke MREA when the control algorithm is based on quadratic damping rather than linear damping.

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.

In the paper, nonlinear vibration characteristics of a rotor system are investigated. Such a nonlinear rotor system is subjected to brush seal forces, which are obtained by integrating the bristle force along the entire ring. The nonlinear brush seal rotor system is constructed by merging a flexible rotor with nonlinear seal forces. The research is aimed at studying the nonlinear vibration characteristics and bifurcations of the motions under a variety of eccentricity circumstances. Different kinds of bifurcations are successfully obtained by mathematical discretization and mapping manipulation. Such a discrete mapping method successfully predicts the stable and unstable motions accurately. The period-doubling bifurcations and saddle node bifurcations of the rotor system are obtained. The sole unstable solutions are obtained, which are special, and a normal numerical integration method cannot solve this problem, which provides advantages in rotor design and motion control. According to the results, nonlinear resonances are found between the stable and unstable motions. The greater the eccentricity of the rotor, the greater the number of bifurcation points that occur during the rotor’s nonlinear motions, as well as the larger the ranges of speeds where the motions are unstable. Saddle node bifurcations generate unstable nonlinear motions and non-smooth motions, which may bring damage to the mechanical rotors. The period-doubling bifurcations produce the route from period-1 to period-2 motions in the nonlinear rotor system. The research provides a new perspective to study the bifurcations and stability of the nonlinear rotor systems.

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.

Traditional machine defect identification methods have problems such as poor adaptability and low accuracy. As for solving the problems, a large number of improved machine defect identification techniques based on artificial intelligence have been developed; however, all of these methods focus on the neural networks and ignore the connections and influences of the data nodes. This paper proposes a feature-enhanced method based on a data dynamic network for bearing defect identifications. The research preprocesses the data by means of optimization algorithms and defines nodes and edges of data for the construction of a data dynamic network. In order to further improve the accuracy of the machine bearing defect identification, the data are also washed for the energy analysis to be coupled with the data dynamic network for feature enhancement. The training sets and test sets are defined with different data coupling techniques. A performance evaluation of the proposed method is carried out by means of the evaluation function for more effective detection of bearing defects.