Table of contents

This volume of Journal of Physics: Conference Series presents the proceedings of the 1^st International Conference on Mechanics, Electronics, Automation and Automatic Control (MEAAC2023). The conference was held in Wuhan, China during May 13-15, welcoming around 50 attendants physical and online from home and abroad.

MEAAC2023 organized discussions on hot topics including intelligent manufacturing, robot system control, and smart cities and focused on the challenges during research as well as application. The conference consisted of one physical conference in the morning and one virtual conference in the afternoon, showcasing various sessions such as keynote speeches, oral reports, poster presentations, Q&A, etc. We had the utmost pleasure of having with us experts and scholars from around the globe sharing their latest findings and insights.

The MEAAC conference is conceived in the belief of promoting academic exchange within and across disciplines, addressing theoretical and practical challenges and advancing current understanding and application, during the process of which amity is spread, connections established and future collaborations enabled.

The MEAAC organizing committee extend their sincerest gratitude to all who have supported the conference in their ways, to the authors who have chosen this platform to publish their works and communicate with peers, to the participants who took an interest and attended the conference in person and/or online, to the chairs and committee members who have been indispensable in lending their professional expertise and judgment, to the keynote speakers who generously shared their vision and passion, and to the reviewers who held up the faith of being a scholar and contributed their experience and honest opinions. It has been a pleasure and honor working alongside them, and we look forward to future cooperation with them at future MEAAC conferences to come.

List of Conference Chair, Conference Co-chair, TPC Chair, Technical Program Committee are available in this Pdf.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Double Anonymous

• Conference submission management system: Morressier

• Number of submissions received: 42

• Number of submissions sent for review: 33

• Number of submissions accepted: 13

• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 31.0

• Average number of reviews per paper: 5.3

• Total number of reviewers involved: 137

• Contact person for queries:

Name: Ms. Liya Zhang

Email: info@meaac.org

Affiliation: MEAAC organizing committee

The dry cutting test of austenitic stainless steel 06Cr19Ni10 workpiece material was carried out with YBG205 coated tool. By scanning electron scanning microscope (SEM) and energy dispersive spectrum (EDS), the wear morphology and wear mechanism of the tool were analysed. The results showed that when cutting the stainless steel 06Cr19Ni10 with YBG205 coated tool, the main wear morphologies of the tool were flank wear, boundary wear, and tip damage. The wear mechanism were mainly adhesive wear and diffusion wear.

In new energy vehicles, due to the loss of the traditional engine noise source coverage, the air conditioning blower has become the main source of noises. In this work, the simulation of the radius of volute tongue (R), the gap of the tongue(d), the blade outlet angle (β) and the volute profile(A) were conducted to obtain the influence degree of each parameter on the aerodynamic noise and the efficiency of the blower, the numerical methods of which were verified by the experimental test. A global sensitivity analysis (GSA) methodology was adopted to study the effect of structural parameters of the automotive air conditioning blower on the aerodynamic noise and the performance. The GSA results show that β has the greatest effect whose global sensitivity coefficient is 0.86 under the noise target. A has the maximum coefficient which is 0.82 under the efficiency targe. When taking the all higher-order effect into consideration, it is R and β that have the greatest influence on the aerodynamic noise and the efficiency. According to the result of the second-order sensitivity analysis, it is crucial for optimizing the blower to consider the fit of R and β. The GSA results in this study provides a certain reference for the design of noise reduction and efficiency improvement of blowers.

To address the issue of motion coordination in lower limb exoskeleton rehabilitation robots, and to meet the basic characteristics of ergonomics and human kinematics, a humanoid design was adopted to design a lower limb exoskeleton rehabilitation robot. The Denavit- Hartenberg (D-H) mathematical model of the lower limb exoskeleton rehabilitation robot was established, and the motion characteristics of each joint were analyzed to obtain the D-H parameters during the motion process. The motion characteristics were analyzed from the perspectives of forward kinematics and inverse kinematics. The variation law of motion parameters during the motion process was obtained, and simulation analysis of the motion characteristics was performed. The results show that the maximum center of mass velocity is 0.45 m/s, which is reached within 0.8 seconds. After that, the velocity decreases, with a range of approximately -0.2 m/s to 0.55 m/s. It can be seen that the displacement and velocity changes of the exoskeleton robot legs are relatively stable, which meets the design requirements.

The parameters identification of suspension components provides a foundation for health assessment of the high-speed train. Considering the time-varying nonlinearity of suspension parameters caused by changing temperature, this work identifies the time-varying nonlinear parameters based on the wavelet multiresolution analysis (WMA) combined with the proposed improved Akaike information criterion (AIC). Firstly, the parameters variation law against time-temperature are fitted based on test data and the vibration responses of a two-degree-of-freedom suspension model are obtained. Secondly, the time-varying nonlinear parameters are expanded into scale coefficients using WMA. Thus, the identification of time-varying nonlinear parameters is transformed into the identification of time-invariant wavelet scale coefficients. Then the improved AIC is utilized to select the optimal basis functions and decomposition scales in noisy environments. The identified parameters vectors are used by the improved AIC as evaluation index of identification model to reduce the effect of noise. Finally, the time-varying nonlinear parameters are reconstructed based on the optimal wavelet scale coefficients. The results show that the time-varying nonlinear stiffness and damping coefficients can be accurately identified based on the WMA combined with the proposed improved AIC.

The main defect of additive manufacturing technology based on laser melting is that large thermal deformation is easily generated inside the part during the forming process. The traditional method is to adjust the process parameters, stress relief annealing and other hardware methods. From the point of view of design, this paper proposed a method to reduce the deformation by changing the product structure and configuration without changing the process form and design goals. The layer-by-layer thermal process model is considered as a constraint in the SIMP topology method, and the MMA is applied as the optimization solver to take care of the multi-constraints topology optimization. Then, the Heaviside based morphological filter is applied to control the minimum length of the part in the optimization results. The validity of the proposed method is tested by the MBB beam and cantilever compliance minimization problems.

Silage equipment can crush crops into small materials, which can be used as feed for livestock farms to achieve efficient and reasonable utilization of resources. In this paper, based on the completion of the overall scheme design of a modular backpack silage equipment, the integration of crop crushing, bundling and coating is realized. At the same time, a control system suitable for the silage equipment based on programmable logic controller (PLC) and touch screen is developed to improve the working efficiency of the equipment. In the production experiment, the technical parameters of the prototype and the indicators of the product meet the design objectives.

In this paper, a distributed esophageal pressure measurement sensor is proposed. Optical frequency domain reflection (OFDR) technology is adopted to measure the axial strain change of the optical fiber. By designing a sensitizing structure, the sensing performance can be well improved. The analysis based on finite element simulation of the sensor is carried out and its feasibility is verified. Compared with the solid high-resolution esophageal manometry system widely used at this stage, the proposed sensor is low cost and simple in structure. The sensitivity of the sensor can reach 65.920μɛ/kPa.

Voltage type flux observer has attracted much attention because of its less mathematical calculations and ease of implementation. The only issue with the flux estimation approach is the integration mechanism; using a pure integrator may cause integrator saturation and a DC bias issue, whereas using the low pass filter (LPF) and a self-adaptive band-pass filter (SABPF) would result in magnitude and phase angle errors. This work offers an improved flux linkage estimation approach with a proportional integral (PI) DC offset compensator, resolving the DC drift issue associated with the observer's pure integrator. Compared to the standard voltage type flux observer, the DC offset is removed, the LPF and phase adjustment are eliminated, and low-speed armature position estimate accuracy is improved. The proposed method can reduce calculation. As a result, the control period is reduced. The Matlab Simulink framework findings are presented to validate the performance and effectiveness of the proposed strategy.

Sulfur hexafluoride (SF6) gas is a stable gas that is widely used in gas insulated lines (GILs) in power systems. However, in GIL, SF6 gas is in the environment of high temperature, high pressure and high voltage for a long time, SF6 gas will decompose into toxic gas, damage electrical equipment, and pose a huge threat to human body and ecological environment. In addition, SF6 gas is a greenhouse gas that is strictly forbidden to leak. Once leaked, it will cause great harm to the environment. Therefore, it is necessary to recover and purify the SF6 gas in the power system GIL. In this paper, a molecular model of carbon nanotubes is constructed, and the density functional theory is used to analyze the changes of charge distribution, density of states and molecular orbitals after adsorption of SF6 decomposition products by carbon nanotubes, and determine the gas-sensing response of carbon nanotubes to gas molecules characteristic.

Image is the main source of information acquisition and exchange. Image processing technology can realize man-machine dialogue, but it still faces many challenges, such as the lack of image edge information. In order to better realize the neural network image processing, this paper builds two kinds of neural network models based on memristor on the MATLAB platform. Then these two neural network models are used to enhance the image. The image is illustrated by the comparison of the histogram, the enhanced image and some objective criteria through the pulse coupled neural network and the improved neural network. The improved neural network is more efficient than the pulse coupled neural network in processing the edges and internal details of the image, highlighting the outline of the key part of the image, and effectively realizing the image enhancement. The advantages of the neural network with memristor in image processing are illustrated.

To accept and process the requests many IoT devices give, the server on the IoT platform must open many threads. Enhancing server speed while working with constrained processors, memory, and other resources is extremely difficult. In this paper, we propose a thread scheduling model that abstracts server resources, combines queues to handle resource contention, avoids the issue of frequent switching of the server's underlying processor context in traditional thread scheduling, and combines with a specific thread weighting mechanism to enable the server to handle more requests from IoT devices with the same overhead. Finally, we carry out tests to show that our model is valid.

It is still a great challenge to detect pedestrians in crowded scenes. Recent works mainly focus on enhancing the feature representation of the visible region. Although this strategy is effective, it fails to fully exploit the appearance information contained in the full-body region. To this end, we propose a Dual-Mimic learning model, which consists of the occluded to unoccluded (Occ-Unocc) and the full-body to visible (Full-Vis) mimic learning branches. Both branches can reduce the intra-class feature variances of pedestrians by different mimicking strategies. Besides, we define an occlusion attribute to describe the occlusion pattern of each detection. Based on the occlusion attribute, we propose the Occlusion-aware NMS (Occ-NMS), which can effectively remain the occluded instance with low confidence. We conduct extensive experiments on standard benchmarks of CityPersons and Caltech, and our method achieves a new state-of-the-art performance at 36.34% MR⁻² and 25.07% MR⁻² on heavy occlusion sets.

After the fault circuit breaker at the end of the long line of the large mode operation system fails, the composite voltage sensitivity of the 220 kV and above double bus connection failure protection is insufficient, and the line release complex voltage locking function needs to be switched on and off manually, which cannot be automatically adapted after the system mode changes. To solve this problem, the compound voltage locking logic is cancelled, and the zero negative sequence power direction discrimination is used to simplify the startup failure circuit, which improves the adaptability and reliability of line failure discrimination under various operating conditions.