Low back pain has been reported to have a high prevalence among occupational drivers. Whole‐body vibration during the driving environment has been found to be a possible factor leading to low back ...pain. Vibration loads might lead to degeneration and herniation of the intervertebral disc, which would increase incidence of low back problems among drivers. Some previous studies have reported the effects of whole‐body vibration on the human body, but studies on the internal dynamic responses of the lumbar spine under multi‐axis vibration are limited. In this study, the internal biomechanical response of the intervertebral disc was extracted to investigate the biomechanical behaviour of the lumbar spine under a multi‐axial vibration in a whole‐body environment. A whole‐body finite element model, including skin, soft tissues, the bone skeleton, internal organs and a detailed ligamentous lumbar spine, was used to provide a whole‐body condition for analyses. The results showed that both vibrations close to vertical and fore‐and‐aft resonance frequencies would increase the transmission of vibrations in the intervertebral disc, and vertical vibration might have a greater effect on the lumbar spine than fore‐and‐aft vibration. The larger deformation of the posterior region of the intervertebral disc in a multi‐axis vibration environment might contribute to the higher susceptibility of the posterior region of the intervertebral disc to injury. The findings of this study revealed the dynamic behaviours of the lumbar spine in multi‐axis vehicle vibration conditions, and suggested that both vertical and fore‐and‐aft vibration should be considered for protecting the lumbar health of occupational drivers.
Both vibrations close to vertical and fore‐and‐aft resonance frequencies would increase the transmission of vibrations in the intervertebral disc, and vertical vibration might have a greater effect on the lumbar spine than fore‐and‐aft vibration. The larger deformation of the posterior region of the intervertebral disc in a multi‐axis vibration environment might contribute to the higher susceptibility of the posterior region of the intervertebral disc to injury.
With the constant evolution of information technology, the paradigm of human-computer interaction has progressively transitioned from emphasizing command behavior to a novel approach that prioritizes ...natural language and emotional communication. In response to this trend, the development of an effective model for emotion recognition has become imperative. Consequently, this paper introduces a novel Multi-axis EEG Channel Attention Model (MECAM) designed for emotion recognition. To enhance the model's capabilities, we employ a Split Depth-Wise Convolution with a larger convolutional kernel, resulting in the creation of four parallel branches. This not only reduces the computational complexity but also expands the receptive field of the model. The incorporation of a multi-axis attention mechanism, capturing both global and local information from the output features of parallel branches, further elevates the network's receptive field through the MBConv Block. The primary objective of MECAM is to adeptly extract discriminative features from EEG data, thereby enhancing the performance of emotion recognition. The model underwent rigorous validation using multiple datasets, including DEAP, SEED, and SEED-IV. In subject-dependent experiments, the accuracy of binary and ternary emotion classification tasks exceeded 95%, while the accuracy of the quaternary classification task surpassed 93%. In subject-independent experiments, the accuracy of most emotion classification tasks also exceeded 90%, with the exception of quaternary classification on DEAP, achieving an accuracy of 86.64%. The experimental results unequivocally underscore the superior performance of MECAM in EEG-based emotion recognition tasks.
This paper investigates the effects caused by simultaneous multiple random excitations on the fatigue-life of the specimen under test. In multi-axis accelerated fatigue testing, the test ...specifications are usually provided in terms of PSDs only. However, different combinations of the test specifications can significantly affect the fatigue behaviour of the specimen, resulting in altered failure modes and test durations. In this context, the original contribution of this paper is to provide a novel method for combining the PSD test specifications, which is able to recreate in the laboratory the most severe and damaging vibration environment possible. The aim of the present methodology is to get out the extreme dynamic response of the specimen by fully exploiting the total energy offered by the test specifications. This method avoids the risk of underestimating the fatigue damage to undergo the specimen during laboratory testing. The paper offers the mathematical implementation of the method and its experimental validation achieved throughout an intense test campaign. Fatigue tests have been performed on specially designed specimens, by exploiting a three-axial electro-dynamic shaker.
Image smoothing provides a fundamental operation for image processing, with a broad spectrum of applications. It is a challenging task which requires global analysis on image patterns with scale ...awareness. Existing deep models for image smoothing are insufficiently efficient in global perception and multi-scale processing. This letter proposes a deep model with an efficient multi-scale fusion architecture and a series of global processing blocks. The architecture enhances multi-scale feature flow by incorporating features of different scales into both the encoder and decoder blocks of a U-shape network, with multi-scale feature fusion modules inserted between the encoder and the decoder. The global processing blocks leverage the multi-axis processing mechanism to achieve joint local and global perception. Benefiting from these two key designs, our proposed model enjoys superiority in both smoothing performance and computational complexity, as demonstrated in the experiments on two benchmark datasets.
•Proposed a method for multi-axis random vibration topology optimization.•Enhancing vibration resistance and extending life during the topology phase.•Prompting the structure to add load-bearing ...paths to resist random vibration loads.•Guiding the topology towards forming a vibration-resistant structure.•Expanding HCA into the field of random vibration performance topology optimization.
Considering the lack of effective solutions for multi-axis random vibration topology optimization problems, and recognizing that multi-axis random vibration excitation is the most common loading conditions experienced by structures during their operational life, this paper proposes a multi-objective topology optimization method for multi-axis random vibration. By combining Hybrid Cellular Automata (HCA) and Analytic Hierarchy Process (AHP), this method aims to enhance the vibration resistance of structures and extend their fatigue life during the topology optimization phase. To validate the effectiveness and engineering practicality of this method, two engineering cases were designed: a cantilever beam case and an automotive steering knuckle case. Multi-objective topology optimization were conducted with objectives including mass, stiffness, and vibration intensity metric (root-mean-square stress). The two cases demonstrate that the control group's topology model exhibits weaker resistance to random vibrations and shorter fatigue life. In contrast, the validation group's topology model introduces an additional load path near the excitation point, effectively dissipating the impact of vibration excitation. This enhances the structure's vibration resistance and significantly extends its fatigue life.
This short communication article critically reviews the modern trends in advanced filament winding machinery and filament wound composite pressure vessels (CPVs) and their potential applications. ...Firstly, it explores the historical development and advancements in filament winding machinery, which is essential to understand and assess the future state-of-the-art filament winding technique. Secondly, the classification of CPVs is further elucidated concentrating on composition, operating pressure, liner material, and load-bearing capability. It is classified that Type I, II, III, IV, and V of CPVs have been introduced and developed from all-metal to all-composite construction, which significantly reduces the weight of 75% to all-metallic pressure vessels. Thirdly, commercial and potential applications of CPVs have been introduced. Finally, this article provides an outlook on opportunities and challenges of advanced filament winding machinery and CPVs, which gains new insights into integrated design, manufacturing, and performance evaluation on CPVs with artificial intelligence (AI), digitalization, and visualization techniques.
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•The state-of-the-art of filament winding machinery and composite pressure vessels (CPVs) are reviewed.•Advanced multi-axis filament winding machineries are compared.•Classification of CPVs with type I, II, III, IV and V is evaluated.•Opportunities and challenges of advanced filament winding machinery and CPVs are discussed.
Not only is it important to know how large the overall change in vibration should be for occupants to perceive an improvement in comfort, but also how large this change should be in specific ...frequency bands. Relative difference thresholds (RDT) of primary (0.5-4 Hz) and secondary (9-80 Hz) ride are estimated for 14 automotive engineers seated in a vehicle on a 4-poster test rig over two roads. Resulting stimuli differed in magnitude and spectral shape. The median RDTs estimated for primary and secondary ride were 16.68% and 13.82% on the smooth road, and 9.50% and 24.67% over the rough road. Statistically significant differences were found in the medians of the RDTs between (1) primary and secondary ride on the two roads and (2) the two roads for changes in the primary and secondary ride, suggesting that Weber's law does not hold.
•A singularized geometrical parameter model is constructed to avoid the problems of indefinite equation and posture non-solution.•The modeling error of the Jacobian model is considered and ...compensated for the obtained geometric parameter.•An error predictive evaluation method is given to achieve optimal error compensation.•The precise Jacobi correction method is appliable for a wide use in multi-axis mechanisms.
The Jacobian model is a prevalent tool for error compensation in multi-axis parallel mechanisms. However, discrepancies between the model's nominal and actual geometrical parameters, combined with equivalent replacements and high-order rounding in the modeling process, lead to equation solving challenges and modeling errors. These inaccuracies result in residual errors in the Jacobian model compensation. To address these problems, this paper proposes an optimal Jacobian correction approach. This is based on a geometrical parameter singularized Jacobian correction model, and a module for the evaluation of coupling errors for multi-axis parallel mechanisms was incorporated. Instead of relying on iterative processes, a singularized geometrical error solution method (SESM) was developed. Through this method, precise derivation of the Jacobian correction parameters is ensured, effectively addressing the indefinite equation challenge and partial posture non-solution problem. Moreover, modeling errors resulting from equivalent infinitesimal replacements and the overlooking of high-order minor values are compensated for by the SESM. It was observed that varying singularized geometrical parameters in the Jacobian model can produce different coupling effects and compensation outcomes. Therefore, a sensitivity-based error predictive evaluation method (EPEM) was introduced. By this method, the optimal correction parameter of the Jacobian model across the entire workspace is identified, ensuring precise pose error compensation. The proposed method was validated using a three-axis parallel mechanism. Through these tests, its superior efficacy was revealed. In comparison to the traditional uncorrected Jacobian compensation, reductions in position and orientation errors by 64.93% and 55.29%, respectively, were achieved. This method provides a new approach for error modeling, equation solving, and parameter correction for multi-axis mechanism error compensation and precision equipment development.
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