Rolling bearing is an important part guaranteeing the normal operation of rotating machinery, which is also prone to various damages due to severe running conditions. However, it is usually difficult to extract the weak fault characteristic information from rolling bearing vibration signals and to realize a rolling bearing fault diagnosis. Hence, this paper offers a rolling bearing fault diagnosis method based on successive variational mode decomposition (SVMD) and the energy concentration and position accuracy (EP) index. Since SVMD decomposes a vibration signal of a rolling bearing into a number of modes, it is difficult to select the target mode with the ideal fault characteristic information. Comprehensively considering the energy concentration degree and frequency position accuracy of the fault characteristic component, the EP index is proposed to indicate the target mode. As the balancing parameter is crucial to the performance of SVMD and must be set properly, the line search method guided by the EP index is introduced to determine an optimal value for the balancing parameter of SVMD. The simulation and experiment results demonstrate that the proposed SVMD method is effective for rolling bearing fault diagnosis and superior to the variational mode decomposition (VMD) method.

The pressure drop increases along with the decrease in the flow maldistribution in the two-stage distributing inlet headers of a plate-fin heat exchanger. To solve this issue, we proposed a new inlet header configuration with splitter plates to decrease the flow maldistribution and pressure drop simultaneously. We used computational fluid dynamic technology to analyze the flow properties in the inlet header configuration and calculated the flow maldistribution degree of the outlet channels and the pressure drop in the inlet header. We performed a sensitivity analysis between the structural parameters, the flow maldistribution degree, and the pressure drop. We determined the optimum values of the structural parameters (the construction of transition duct, the number of splitter plates, the inclined angle of outermost plates, the height of splitter plates, the height of inlet header, etc.), and acquired the optimum configuration of the improved inlet header. Compared with the traditional inlet header, the flow maldistribution degree and pressure drop decreased by 91.5% and 40.9%, respectively, using the proposed improved inlet header with splitter plates, which performed better than the conventional two-stage distribution inlet header.

Temperature greatly influences the mechanical response of acrylonitrile butadiene styrene (ABS). The tensile behavior of ABS was explored in this study. The tensile experiments were conducted at a wide range of temperatures (from 40^°C to 130^°C). A model was established to reveal the quantitative relationship between temperature and tensile behavior of ABS. The results of tensile experiments showed that tensile behavior of ABS exhibited glassy state and high-elastics state. The model was also divided into two parts that rely on the boundary of glass transition temperature, in which the parameters of the model were calculated by the fitting method. The model predictions showed a good agreement with the results of the experimental tensile test. This study provides the quantitative relationship between temperature and tensile behavior of ABS, which saves time and experimental costs.

The available amount of input data for uncertain parameters of composite laminated plates can vary, and the uncertain parameters can be decomposed into strong statistical variables, sparse variables and interval variables. Therefore, a new reliability optimization design methodology for composite laminated plate considering these uncertainty types simultaneously is proposed. The uncertainty types of elastic material parameters are identified, and the corresponding distribution parameters are calculated based on the Akaike information criterion. The reliability indices considering three uncertainty types are calculated based on linear approximation models of first-ply failure functions. A two-level reliability optimization algorithm is proposed to calculate the optimum stacking sequence for composite laminated plate, which can satisfy the lightweight requirement and reliability constraints. Comparisons with the optimization results of the Monte Carlo simulation method in two examples of composite laminated plates demonstrate the effectiveness of the proposed algorithm in conditions with multiple uncertain parameters due to insufficient input data.

Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.