Decoupling the complicated vibrational—vibrational (V—V) coupling of a multimode vibrational relaxation remains a challenge for analyzing the sound relaxational absorption in multi-component gas mixtures. In our previous work [Acta Phys. Sin. 61 174301 (2012)], an analytical model to predict the sound absorption from vibrational relaxation in a gas medium is proposed. In this paper, we develop the model to decouple the V—V coupled energy to each vibrational—translational deexcitation path, and analyze how the multimode relaxations form the peaks of sound absorption spectra in gas mixtures. We prove that a multimode relaxation is the sum of its decoupled single-relaxation processes, and only the decoupled process with a significant isochoric-molar-heat can be observed as an absorption peak. The decoupling model clarifies the essential processes behind the peaks in spectra arising from the multimode relaxations in multi-component gas mixtures. The simulation validates the proposed decoupling model.

Deep-learning-based fault diagnosis models perform well when the training and test sets have the same label set. However, these models are invalid in practical applications because they misclassify any unknown faults into existing known classes. An effective diagnosis model for practical industrial applications requires the ability to detect unknown faults as well as maintain high classification accuracy on known faults. To address this challenge, this article proposes a generic open-set classification method for vibration signals. We propose a variational encoder-classifier structure to extract the robust latent features that have different specific distributions with respect to their classes. According to the distances between the latent feature distributions, the samples from unknown faults are rejected using extreme value theory (EVT) and empirical threshold. In addition, we devised an EVT-based instance-level regularization weight function to allow the model to enhance the regularization on the samples that around the known and unknown decision boundaries, which can reduce the risk of bias in the empirical threshold setting caused by the hard training samples. Experimental results on five public rotating machinery vibration datasets reveal that the proposed method achieves the best performance for each dataset. This demonstrates the effectiveness and superiority of the proposed method for practical application scenarios.

It is still a challenge to employ the acoustic method to investigate the molecular relaxation phenomena in excitable gases. Here we present an algorithm to capture the primary relaxation processes by only measuring the sound absorption and sound speed of two operating frequencies at a single pressure, without the necessity of detecting the gas density. This algorithm is developed from the fact that the frequency-dependent sound absorption curve due to a single-relaxation process can be reconstructed from the two values of the relaxation frequency and the maximum relaxational absorption, and they can be synthesized by the acoustic measurements at two frequencies. Moreover, by acquiring the high-frequency sound speed, those two synthesized values can be used to reconstruct the sound dispersion curve. The simulations demonstrate the validity of the proposed algorithm and its robustness against errors of acoustic measurements.

Transfemoral amputees need prosthetic devices after amputation surgery, and the interface pressure between the residual limb and prosthetic socket has a significant effect on an amputee's satisfaction and comfort. The purpose of this study was to build a nonlinear finite element model to investigate the interface pressure between the above-knee residual limb and its prosthetic socket. The model was three-dimensional (3D) with consideration of nonlinear boundary conditions. Contact analysis was used to simulate the friction conditions between skin and the socket. The normal stresses up to 80.57 kPa at the distal end of the soft tissue. The longitudinal and circumferential shear stress distributions at the limb-socket interface were also simulated. This study explores the influences of load transfer between trans-femoral residual limb and its prosthetic socket.

Measuring adiabatic sound speed is an effective method to characterize gases with different molecular weights because sound speed mainly depends on molecular weight at a given temperature. However, it is still a challenge to apply this method to different gas mixtures with similar or even the same sound speeds. Acoustic relaxation in gases may overcome this challenge because sound speed becomes dispersive due to frequency-dependent heat capacity. Based on our previous work on reconstructing acoustic velocity dispersion with a simple measurement method, in this paper, we propose capturing the inflection point of velocity dispersion to identify gas mixtures. Standard detection areas are constructed using the theoretical location of the inflection point scaled by the acoustic velocity and relaxation frequency with different temperatures for target gases. The captured inflection point is located in the detection areas to obtain gas compositions. Thus, gas mixtures with the same molecular weights, such as 86.9% CO₂–13.1% N₂, 95% CO₂–5% H₂ and 95% CO₂–5% pH₂, can be differentiated using our method from only their acoustic velocities. The results show that the maximum absolute error of the compositions for CO₂ can be effectively reduced from 3.8% to 0.2% by our temperature correction function. Therefore, the proposed method can identify gas mixtures qualitatively and quantitatively by only measuring acoustic velocity.