Shock and Vibration
 Journal metrics
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Acceptance rate25%
Submission to final decision95 days
Acceptance to publication17 days
CiteScore2.800
Journal Citation Indicator0.400
Impact Factor1.6

Accuracy-Improved Fault Diagnosis Method for Rolling Bearing Based on Enhanced ESGMD-CC and BA-ELM Model

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 Journal profile

Shock and Vibration publishes papers on all aspects of shock and vibration, especially in relation to civil, mechanical and aerospace engineering applications, as well as transport, materials and geoscience. 

 Editor spotlight

Chief Editor Dr Tai Thai is based at the University of Melbourne and his current research focuses on high strength materials for sustainable construction of buildings, bridges and other infrastructure.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

Burst Failure Characteristics and Energy Evolution Law of Coal with Prefabricated Cracks at Different Angles

In order to study the influence of fissures on the burst tendency of coal, the test and numerical simulation of the burst tendency of coal with different burst angles were carried out. The evolution law of the burst tendency index of coal under the influence of burst angle was analyzed, and the mechanism of energy storage and release of coal under the influence of fissure angle was revealed. The results show that compared with the specimens without prefabricated cracks, the uniaxial compressive strength of the specimens with 0° cracks is reduced by 48.4%, the dynamic failure time is increased by 279.4%, the burst energy index is reduced by 54%, and the burst energy velocity index is reduced by 87.9%. After that, with the increase of prefabricated crack angle, the uniaxial compressive strength of coal increases gradually, the dynamic failure time decreases gradually, the burst energy index increases gradually, and the burst energy velocity index increases gradually. That is to say, the larger the crack angle contained in the coal body, the stronger the burst tendency of the coal body, but it is still lower than that of the complete coal body. With the increase of prefabricated crack angle, the proportion of prepeak elastic energy of coal body increases, the less energy dissipation in the whole loading process of coal body, and the faster energy release rate during failure. The research results can provide some theoretical support for the prevention and control of rock burst disaster.

Research Article

Dynamic Performance Analysis of Semiactive Vehicle ISD Suspension Based on the Power-Driven-Damper Strategy

In this paper, the vehicle ISD (inerter-spring-damper) suspension and power-driven-damper control strategy are combined to the suspension design, and the power-driven-damper semiactive ISD suspension is proposed. The dynamic models of the passive suspension S1 and two semiactive ISD suspensions S2 and S3 are established. Based on the port-controlled Hamiltonian theory, the power-driven-damper semiactive control strategy is designed by analyzing the power transfer of suspension S3. Then, the parameters of the two models are optimized by the particle swarm optimization algorithm, and the optimization results show that the suspension S3 has better performance. The influence of the semiactive damping coefficient, the spring stiffness, and the inertance on the vibration suppression performance is investigated based on the suspension S3. The effect of parameter perturbation on power-driven-damper semiactive vehicle ISD suspension illustrates that the designed semiactive vehicle ISD suspension has better ride comfort in a wider range frequency and good robust performance.

Research Article

Research on the Load Bearing and Impact Resistance of a Novel Structure Exhibiting Both Positive and Negative Poisson’s Ratios

A ship equipment pedestal is a structure that connects power equipment to a hull. It must have a high load-bearing capacity and the ability to withstand large impact loads. In this paper, a novel structure with a positive-negative Poisson’s ratio is proposed. The deformation mechanism and mode of this structure under quasistatic compression loading are analysed via numerical simulation. Based on this new structure, a multicellular pedestal is designed, and its bearing capacity and impact resistance are analysed. The structural parameters of the pedestal are optimized. An experiment is conducted to evaluate the impact resistance of the pedestal model, which confirms that the proposed multicellular pedestal exhibits excellent impact resistance.

Research Article

In-Plane Dynamic Cushioning Performance of Concave Hexagonal Honeycomb Cores

In order to further study the cushioning performance of concave hexagonal cores (CHCs) and expand their application range, the in-plane finite element model of CHCs is established in this paper. A dynamic cushioning coefficient method was proposed to characterize the cushioning performance of CHCs. The dynamic cushioning coefficient curve and minimum dynamic cushioning coefficient (MDCC) of CHCs with different impact velocities and structural parameters are obtained. The influence rules of structural parameters and impact velocities on the MDCC are analyzed; the deformation mode and transformation empirical formula are also obtained. The results show that when other parameters are constant, the MDCC of CHCs decreases with the increase of impact velocity, increases with the increase of wall thickness and side length ratio, and decreases with the increase of expansion angle. The theoretical analysis is consistent with the finite element results, which further verifies the reliability of the model. This paper provides a solid theoretical basis for the industrial application of the cushioning performance of CHCs and forms a key technical support.

Research Article

A Multifactor Combination Optimization Design Based on Orthogonality for a Two-Degree-of-Freedom Floating Machine Gun Vibration System

This paper introduces a novel type of floating machine gun that can be simplified as a self-balancing two-degree-of-freedom mechanical system with distinct vibration characteristics. The model accounts for intricate motion patterns and encompasses numerous potential influencing factors. Multifactor combination optimization of the system represents a pressing engineering challenge. After establishing a simulation model for the machine gun and validating it experimentally, seven factors were chosen as optimization variables. The maximum recoil displacement of the inner receiver (MRD) and the firing rate were chosen to be indicators. Orthogonal combinations and variance analyses were used, and the effects of multiple factors were analyzed using SPSS software; these processes led to a determination of the optimal combination. The results indicated that the piston cylinder pressure, the bi-directional buffer spring energy storage, and the inner receiver mass significantly affected the MRD. Furthermore, the automaton mass and the reset spring energy storage were found to substantially affect the firing rate. Careful analysis of the variance results facilitated the determination of the optimal combination of parameter values. Remarkably, the optimal combination chosen resulted in an MRD reduction of approximately 20.2% and a firing rate increase of approximately 26.6%.

Research Article

Graph Feature Fusion-Driven Fault Diagnosis of Complex Process Industrial System Based on Multivariate Heterogeneous Data

The stable operation of the process industrial system, which is integrated with various complex equipment, is the premise of production, which requires the condition monitoring and diagnosis of the system. Recently, the continuous development of deep learning (DL) has promoted the research of intelligent diagnosis in process industry systems, and the sensor system layout has provided sufficient data foundation for this task. However, these DL-driven approaches have had some shortcomings: (1) the output signals of heterogeneous sensing systems existing in process industry systems are often high-dimensional coupled and (2) the fault diagnosis model built from pure data lacks systematic process knowledge, resulting in inaccurate fitting. To solve these problems, a graph feature fusion-driven fault diagnosis of complex process industry systems is proposed in this paper. First, according to the system’s prior knowledge and data characteristics, the original multisource heterogeneous data are divided into two categories. On this basis, the two kinds of data are converted to physical space graphs (PSG) and process knowledge graphs (PKG), respectively, according to the physical space layout and reaction mechanism of the system. Second, the node features and system spatial features of the subgraphs are extracted by the graph convolutional neural network at the same time, and the fault representation information of the subgraph is mined. Finally, the attention mechanism is used to fuse the learned subgraph features getting the global-graph representation for fault diagnosis. Two publicly available process chemistry datasets validate the effectiveness of the proposed method.

Shock and Vibration
 Journal metrics
See full report
Acceptance rate25%
Submission to final decision95 days
Acceptance to publication17 days
CiteScore2.800
Journal Citation Indicator0.400
Impact Factor1.6
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