Journal of Engineering and Thermal Sciences
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Cross-domain manifold structure preservation for transferable and cross-machine fault diagnosis
Get PDFTo address the decline or failure in the autonomous learning capability of traditional transfer learning methods when training and test samples come from different machines, resulting in low cross-machine fault diagnosis rates, we propose a cross-domain manifold structure preservation (CDMSP) method for diagnosing rolling bearing faults across machines. The CDMSP method can induce the manifold space projection matrices of the source and target domains more effectively. This method maps high-dimensional features into a low-dimensional manifold, preserving non-linear relationships and aligning distribution differences while maintaining cross-domain manifold structure consistency. Additionally, highly confidently labeled target domain samples are selected from each mapping result and added to the training dataset to enhance subspace learning in subsequent iterations. The CDMSP method is both simple and effective at capturing the underlying structures and patterns in the data. The CWRU dataset and our self-built test platform dataset were used to validate this method. Experimental results show that CDMSP, as a non-deep domain adaptation method of transfer learning, outperforms similar methods in cross-machine fault identification, achieving a maximum fault identification accuracy of 100 % with excellent convergence performance. Furthermore, simulated diagnostic experiments under noise interference indicate that CDMSP maintains high fault identification accuracy, even in noisy environments. Overall, CDMSP is an efficient and reliable new method for diagnosing cross-machine bearing faults
A review on motion sickness of autonomous driving vehicles
Get PDFThe objective of this study is to investigate the symptoms, types, etiology, and assessment methods of motion sickness in autonomous vehicles in order to gain a comprehensive understanding of its occurrence mechanism and emphasize the significance of enhancing autonomous vehicle algorithms for improved ride comfort. Thus, this paper provides a synthesis and discussion of various theories while exploring strategies for mitigating motion sickness from three perspectives: passengers, vehicles, and external equipment. Firstly, it summarizes the clinical manifestations and classification of motion sickness while conducting an in-depth analysis of associated factors. Secondly, it evaluates different approaches for quantitatively measuring the severity and extent of motion sickness. Subsequently, it analyzes the reasons behind increased motion sickness caused by autonomous vehicles and emphasizes the importance of algorithmic improvements to enhance travel comfort. Finally, mitigation strategies are proposed considering passengers' needs as well as advancements in accurate motion prediction models and optimization techniques for autonomous planning and control algorithms that can effectively reduce the risk of motion sickness. As application scenarios for autonomous technology continue to expand, meeting user requirements while ensuring safety has become a benchmark for assessing technical proficiency. Therefore, promoting unmanned travel services necessitates a thorough analysis of existing issues related to autonomous technology along with prioritizing algorithm design enhancements through effective means to achieve an enhanced user experience
Study on the mechanical characteristics and impact resistance improvement of substation masonry wall under flood load
Get PDFThis study examines the stress characteristics and deformation modes of masonry walls under flood loads in a 500kV substation project in Xinyang City, Henan Province. A simplified finite element model of substation masonry walls is developed in ABAQUS, considering dynamic water loads, the stress characteristics and deformation modes of masonry walls under flood loads are studied. Flood depth, water velocity, and erosion depth are selected as variables to carry out the parametric analysis of masonry enclosure walls under flood load, to investigate the dynamic response of walls under various parameters, and to examine the damage mechanism of the wall. The research findings suggest that stress levels are elevated at critical locations, such as the bottom center of the wall, the junction between the inner wall and structural column, and the connection between the foundation and structural column during flood loading. The safety of a masonry wall is significantly compromised when flood depth exceeds 0.8 m, water velocity exceeds 2.3 m/s, or erosion depth reaches 0.4 m. A proposed measure aims to enhance the performance of masonry walls by improving stress distribution and reducing stress concentrations, thereby significantly augmenting their load-bearing capacity
A novel cross-domain identification method for bridge damage based on recurrence plot and convolutional neural networks
Get PDFThe development of a bridge damage detection method relies on comprehensive dynamic responses pertaining to damage. The numerical model of a bridge can conveniently considers various damage scenarios and acquire pertinent data, while the entity of a bridge or its physical model proves challenging. Traditional methods for identifying bridge damage often struggle to effectively utilize data acquired from diverse domains, presenting a significant hurdle in addressing cross-domain issues. This study proposes a novel cross-domain damage identification method for suspension bridges using recurrence plots and convolutional neural networks. By employing parameter identification-based modal modification of numerical model, the gap between numerical model and physical models eliminated. Un-threshold multivariate recurrence plots are used for accurately characterizing dynamic responses and extracting deeper damage features. Due to the scarcity of experimental data, which limits the training of robust neural networks, a transfer learning tailored for convolutional neural networks is implemented. This strategy not only addresses the issue of small sample sizes but also significantly enhances the network's ability to identify structural damage across diverse bridge domains. The proposed damage identification method is validated using a combination of numerical simulations and physical experiments on a specific single-span suspension bridge. Results demonstrate that un-threshold multivariate recurrence plots reveal detailed internal structure and damage information. Furthermore, the utilization of improved convolutional neural networks effectively facilitates cross-domain structural damage identification, marking a significant advancement in the field of structural health monitoring
A Zhu-Wang-Tang damage constitutive model for sintered NdFeB considering crack spacing
Get PDFCurrently, research on the dynamic damage characteristics of sintered NdFeB is still in its early stages. Previous dynamic mechanical experiments on sintered NdFeB have shown that it is a strain rate-sensitive material. So, it is necessary to establish an appropriate damage constitutive model to describe the dynamic mechanical behavior of sintered NdFeB, with the aim of expanding its practical application range. This paper first establishes a damage evolution model by combining the Weibull distribution with a wing crack propagation model that considers crack spacing. Then, the damage model is integrated with the Zhu-Wang-Tang (ZWT) constitutive model to create the ZWT damage constitutive model. The model is fitted against previous experimental data to determine the specific parameters. Finally, to verify the accuracy of the newly established damage constitutive model, it is compared with the damage constitutive model proposed by Li. The comparison results fully affirmed the accuracy of the newly established ZWT damage constitutive model
Feedback force and velocity control of an arm exoskeleton to assist user motion
Get PDFThe paper proposes a feedback force and velocity control of an arm exoskeleton to assist user motion. The original published control so-called feedback hybrid force and position control was based on the force and position control and was designed to assist user motion. This original control was successful at providing assist for the user’s arm. This article presents an improved control scheme called the feedback force and velocity control. The proposed control is designed to regulate the velocities of joints of the exoskeleton and the feedback forces on links to assist user motion. The design and optimization of the feedback force and velocity control are realized by the Balancing Composite Motion Optimization (BCMO). The numerical method is realized in the paper to show that the proposed control is better than the original control in terms of less oscillation and fast response
Editor’s Letter. Malocclusion treatment tools evolution – mechanical vibration synergism. What is the current status of knowledge? Part II
Get PDFUse of fibre optic systems for detection of small leaks on trunk pipelines
Get PDFThis paper is devoted to the issue of efficiency of application of fibre optic leak detection systems for identification of small leaks on trunk pipelines. The main methods of leak detection currently in use have been considered, and parametric and fibre optic LDS have been selected for comparative analysis. In the course of the research a model of product leakage from an underground oil pipeline equipped with a fibre-optic LDS was built in the COMSOL Multiphysics software package. The result of the simulation was the estimated time of leak identification by the fibre-optic system, which turned out to be much shorter than that of the parametric LDS. Compensable environmental damage for each type of system was then calculated, confirming the effectiveness of fibre optic LDS for detecting small leaks on trunk pipelines due to the significant reduction in compensable damage
Identification of modal parameters of soil specimen based on impact force
Get PDFThis study used vibration testing signals of soil samples under external loading to identify modal parameters (including natural frequencies and damping ratios) with different compaction degrees. Based on these parameters, a novel approach was proposed for reliable roadbed vibration compaction control and compaction process optimization. The experimental section utilized six soil samples with varying compaction degrees as experimental subjects, using the hammering method as the excitation mode. Subsequently, the frequency response function and modal parameters of the sample system were obtained through the acquisition, analysis, and parameter identification of samples’ acceleration signals. Firstly, samples with compaction degrees ranging from 88 % to 97 % primarily exhibited three modes, with the second modal frequency response displaying the weakest amplitude, and the fundamental mode being the dominant one. Additionally, parameter identification results revealed that the fundamental modal frequency exhibited a significant negative exponential growth with increasing compaction degree, while the second and third modal frequencies showed significant linear growth. Furthermore, the average damping ratio also demonstrated a tendency toward linear change with increasing compaction degree. Finally, the feasibility of modal parameters being actively used in practical engineering is discussed. Consequently, this study aimed to propose an indicator system for accurately assessing the bearing level of compacted soils from a modal dynamics perspective and to integrate modal dynamic indicators with density-class indicators into further optimization design work on road compaction processes
Analytical modeling of cylindrical eddy current brakes and multi-objective optimization based on game theory
Get PDFWith the research and development of eddy current brake (ECB), today ECBs have been applied in a variety of fields including vibration control and braking of strong impact loads.The application of a new cylindrical structure eddy current brake (ECB) for strong impact braking of large machinery has been discussed recently. Its high-speed and high-kinetic-energy braking conditions require different analytical and optimization design models and methods from what has been addressed in previous studies. For subsequent more engineering-oriented research and optimization, modeling methods are needed, as well as analysis and optimization studies for braking forces and critical speeds of interest. In this work, a magnetic equivalent circuit model is established, and the influence of eddy current induced during application is taken into account by considering it as a magnetomotive force in the model. The braking force is calculated with the MEC model and an approximate electric field cross-section method. A small prototype experiment is carried out and proves the correctness of the proposed model. Using the proposed and FEM model, parameters of the ECB are analyzed. Then, aiming at design objectives of the ECB that are somewhat competitive under this special braking condition, a multi-objective optimization model is established using the Stackelberg game strategy. An FEM model is built and assessed based on optimization results. The results indicate that the multi-objective optimization model based on the Stackelberg game is effective for the design of this ECB structure