Ebook: Proceedings of the 1st International Conference on New Materials, Machinery and Vehicle Engineering
New materials are constantly being developed which may improve or transform many aspects of our lives, and nowhere is this more exciting than in the fields of vehicle and machinery technology.
This book presents the proceedings of the 2022 International Conference on New Materials, Machinery and Vehicle Engineering (NMMVE 2022), held as a virtual event due to the COVID-19 pandemic and travel restrictions, from 18 - 20 March 2022.
NMMVE 2022 provides an international forum for researchers and engineers to present and discuss recent advances, new techniques, and applications in the fields of new materials, machinery and vehicle engineering, and attracts academics, scientists, engineers, postgraduates, and other professionals from a wide range of universities and institutions. A total of 121 submissions were received, from which 48 were accepted for inclusion in the conference and proceeding after a rigorous, standard single-blind reviewing process. The papers are grouped into 3 sections: machinery (30 papers); new materials (11 papers); and vehicle engineering (7 papers).
Providing an overview of the latest developments in these fields, the book will be of interest to all those wishing to know more about new materials and machine and vehicle engineering.
The 2022 International Conference on New Materials, Machinery and Vehicle Engineering (NMMVE 2022) was held successfully on March 18, 2022. Because of the COVID-19 pandemic and the strict traveling restrictions, the event had to take place virtually eventually. However, this did not prevent our participants from enjoying great keynote speeches and presentations.
NMMVE 2022 has attracted a great number of academics, scientists, engineers, postgraduates, and other professionals from a large range of universities and institutions. We aim to provide a high-level international forum for researchers and engineers to present and discuss recent advances, new techniques, and applications in the field of New Materials, Machinery and Vehicle Engineering.
A total of 121 submissions were received, among which 48 have been accepted to be included in the conference proceedings. We followed the standard single-blind reviewing process to evaluate papers. Each paper was manually assigned to reviewers after an initial paper bidding process. We would like to express our sincere gratitude to all the experts for their professional and detailed review comments, which have contributed to the high standard of this collection. We also thank the 27 universities and research institutes who took part in our program and special thanks to Zhenzhou University of Light Industry and Shandong University for their sponsorship.
We would like to thank the Steering Committee for their advice and guidance. We would also like to thank all the authors for their contributions to making NMMVE an exciting conference and call for their contributions to the future events of NMMVE. We also owe thanks to the PC and external reviewers for their hard work in reviewing and shepherding. Finally, we would like to thank IOS Press for the support of their publication services.
We hope you all enjoy your experience at NMMVE 2022!
Prof. Jinyang Xu, Shanghai Jiao Tong University
Prof. Yukui Cai, Shandong University
Prof. Mohamed El Mansori, Arts et Métiers ParisTech
In view of the current narrow field of view and low resolution of infrared images, the SIFT and SUFT algorithms have a long time to stitch images, a real-time infrared large field of view stitching algorithm based on Oriented FAST and Rotated BRIEF (ORB) is proposed. The algorithm makes full use of the priori information of the positional relationship between images, and adopts a matching algorithm based on a two-way matching strategy that is universal for infrared images in a variety of application scenarios, and finally introduces an adaptive weighted fusion algorithm that fades in and out. On the basis of ensuring the quality of image stitching, improving the running speed of the algorithm can realize fast and accurate stitching of infrared images with a large field of view. The experimental results show that under the same level of matching rate, the algorithm in this article has obvious advantages in terms of speed.
In order to improve the working efficiency of excitation device of jujube harvester, an excitation device was designed by using eccentric block excitation mechanism. Through the combination of theoretical analysis and virtual simulation, the mass of eccentric block m, the motor speed n, the spring preload f were determined as test factors, and the angular acceleration α and amplitude A were used as evaluation indexes to carry out the combined test of orthogonal rotating center with three factors and five levels. First, this paper shows the maximum instantaneous angular acceleration α and the maximum amplitude A in space of the marking point of shift lever through 3D high-speed camera technology. Then, the Design-Expert v22.214.171.124 software was used for analysis of variance of experimental results, established the mathematical regression model of evaluation index and various relevant factors, and analyzed the influence of significant factors on evaluation index and optimized the test parameters. Final, the optimal parameters were determined as follows: eccentric mass m = 233 g, motor speed n = 1080 r/min, spring preload f = 35 N. According to the combination of optimal parameters, the results shown that under the optimal combination of parameters, the average amplitude was A = 46.73 mm, the average angular acceleration was α = 11.72 rad/s2, and the minimum inertia force generated by shell vibration was F = 9.87 N. It could be seen that the excitation device satisfies the requirements for jujube harvesting. The study may provide theoretical basis and technical reference for the improvement of the excitation system of the jujube harvester.
For the needs of gripping and transferring and assembling thin-walled fragile parts in industrial production, an internally supported manipulator configuration with finger-palm synergy features for thin-walled brittle cylindrical inner workpieces is proposed. Due to the poor impact resistance and low tensile strength of brittle materials, they are easily broken during the manipulator operation. In order to find the internal brace gripper finger configuration and stiffness matching for the operation of thin-walled fragile parts, and to explore the contact-collision law of the gripping process, the finite element model of the mechanical finger end parts was established by the integrated modeling method of Hypermesh and other software, and the change of the internal force of the mechanical finger contact with the workpiece when the gripping impact speed changes was studied. The corresponding constraints, loads and contact types are applied to the finite element model by LS-prepost software, and post-processing is performed to calculate the stress and strain clouds during the contact collision of the fragile parts. The simulation results show that the stress on the fragile part increases linearly with the increase of the impact speed of the manipulator: Under the speed of 4 mm/ms, the stress increases linearly and slowly. When the speed goes from 0.5 mm/ms to 4 mm/ms, the stress increases about 8 times in X, XY direction and about 14 times in Maximum Principal, Y direction. Above the velocity of 4 mm/ms the stress increases sharply and the model is destroyed. The results of the study establish the basis for optimizing the manipulator’s operating process.
Facial dyskinesia has small movement range and short duration, thus the recognition effect is not ideal. To improve the recognition accuracy of facial movement disorders, a recognition method combining deep 3D Convolutional Networks (C3D) and Long Short-Term Memory (LSTM) is proposed. First, face detection and face alignment on original videos are performed, then the eye area based on facial landmarks is cropped. Second, C3D is used to extract spatio-temporal features of videos. Then LSTM further processes temporal features. Finally, softmax classifier is used to recognize and classify types of facial dyskinesia. According to experiment results, the approach we proposed can obtain a high accuracy rate.
The edge detection algorithm based on sub-pixel can effectively improve the positioning accuracy of contour edges, but the quantitative evaluation method of sub-pixel positioning accuracy needs to be further studied. In this paper, a subpixel edge detection methodology supported by Zernike moment is initial analyzed. A triangle-based simulation method and a calibration-plate–based experiment method are proposed to judge the accuracy of the subpixel algorithm. The findings indicate that the proposed simulation method can quickly and quantitatively evaluate the accuracy of the sub-pixel detection algorithm. The effectiveness of the sub-pixel detection algorithm in improving the accuracy of edge detection is also verified.
Aiming at the position analysis of Stephenson III spherical six bar mechanism, a simple method to solve its input-output equation is given. The Stephenson III spherical six bar mechanism is regarded as composed of basic spherical four-bar chain and spherical two-bar group. The basic coordinate system and branch coordinate system are established respectively. The coordinates of each hinge point are solved with the help of geometric principle and displacement rotation theory. Based on the motion constraints of the basic spherical four-bar chain and the coupling constraints with the spherical two-bar group, the constraint equations of the spherical six bar mechanism are established by using spherical trigonometry. The constraint equations are simplified and eliminated by Sylvester’s resultant elimination method and triangular transformation formula, and then the constraint equations of the mechanism are obtained.
The restaurant intelligent cleaning robot, belongs to the field of robot technology, including driving the base, control the body and vision system. Mechanical arms are installed on both sides of the top of the machine body. One of the bottom end of the robot arm is installed with clamping claws, and the other mechanical arm bottom is installed with Clean hands for desktop cleaning. Driving wheels are symmetrically arranged on both sides of the bottom surface of the base, the body internal top installed vacuuming assembly, vacuuming components of the vacuum port through the pipe to connect the vacuum cover. Combined with lidar and other sensors, it can achieve automatic identification, automatic cleaning, multi-use, flexible movement. It also can reduce the probability of collision tables and chairs, the use of higher reliability, more convenient.
In view of the local wave shape problem of the rolling of cold continuous rolling mill, uneven distribution of emulsion along the width of strip steel, or uneven heating of the roll caused by the blockage of nozzle, the influence mechanism of the horizontal distribution of emulsion on the temperature field and hot roll shape of the working roll is analyzed. The influence mechanism of emulsion transverse distribution on strip shape is also analyzed. The strip shape distribution before and after emulsion adjustment is simulated. On this basis, the automatic prediction model of emulsion point cooling is established to ensure that the strip shape rolled by tandem cold mill does not have obvious shape defects and that the emulsion cooling capacity of each nozzle is uniform. This work provides technical guidance for the control of local wave shape on site. The local wave shape of finished strip can be significantly reduced after applied to the site.
Magnesium alloys have been widely applied in the advanced fields of aerospace, medical implants, automobile, etc. However, the ignition risks of magnesium alloys, especially at high cutting temperatures, have to be considered in the machining process. This article conducts numerical investigations on the effects of cutting tools on the cutting behaviors, especially the cutting temperature of magnesium alloy AZ31B. The impacts of the rake angle, the tool edge radius, and the friction coefficient are studied by simulations based on the orthogonal cutting models using the DEFORM software. The simulation results are studied and compared to analyze the correlations between the cutting parameters and the cutting temperature, as well as the underlying mechanisms. The conclusions of this numerical analysis can provide specific guidance to the design of cutting tools for the magnesium alloys.
Aiming at the complexity of the dynamic model of the EMA pitching mechanism and the feasibility of simplification, this paper discusses the influence of rocker and pushrod on the dynamic characteristics of the EMA pitching mechanism and effectively simplifies the dynamic model on the basis of ensuring the accuracy. Firstly, a simplified dynamic model is established based on Lagrange dynamic equation, equivalent inertia, and equivalent force arm. Then, in the pitch range, the inertia and force arm of the rocker and pushrod are converted into the inertia and force arm of the load respectively, and the dynamic error compensation model is established. Finally, based on the position closed-loop control model after PID optimal parameter setting, the simplified characteristics of the EMA pitching mechanism in this prototype are clarified. In this paper, the simplified model error compensation value solution method improves the accuracy of the simplified model by 92%. The simplified feasibility judgment method can effectively judge the simplified feasibility of the EMA pitching mechanism.
Due to the limited ability of feature expression learned by one branch, designing a Multi-granularity network for feature extraction has become one of the important directions in the field of person re-identification. This paper designs a Multi-granularity feature fusion network (MFN) to enhance person feature extraction. The network is composed of global branches and local branches, and the former use the convolution pyramid to extract multiple scales features, through the channel attention module (Split Attention, SA) fusion of global branches and local branches, so that the global branch to obtain a strong ability to express persons features; the local branches is a feature map extracted from the backbone network based on the idea of Part-based convolutional baseline. Split the feature map horizontally into 4 branches, and the ID loss is calculated separately for each local branch. The classification loss in the total loss is consist of the ID loss of the 4 local branches. The two interact in parallel to improve the recognition ability. The experimental results on the Market1501 and DukeMTMC-ReID datasets, Rank-1/mAP reached 94.9%/86.4% and 87.5%/76.8% respectively.
Vortex flowmeters are easily affected by vibration interference of pipelines and various equipment when used in industrial field. Especially in the measurement of small flow, the noise signal will be superimposed on the output signal of the sensor, the vortex signal is easily submerged, and the measurement of small flow is limited. Aiming at the problem that the small flow vortex signal is very weak and difficult to detect under actual working conditions, an adaptive stochastic resonance (ASR) detection method based on ensemble empirical mode decomposition (EEMD) is proposed. Firstly, the vortex signal is denoised and preprocessed by EEMD, and the appropriate component is selected to reconstruct the signal by using the correlation coefficient as the screening criterion. Then, the system parameters are optimized in parallel by particle swarm optimization to achieve the best stochastic resonance result. The numerical simulation and experimental research results show that this method can improve the output power spectrum amplitude of the vortex signal with small flow, effectively obtain the vortex frequency, realize the measurement of small flow, and enhance the detection ability of weak signal.
In view of the problem that the optical lens is difficult to withstand the impact of high overload, on the basis of the optical imaging function, measures in many aspects such as selecting the appropriate lens material, designing the appropriate diameter-to-thickness ratio and designing the colloidal vibration damping structure are adopted to improve the optical lens anti-high overload capability. The ANSYS simulation analysis and hammering test verify that the optical lens designed by this method can withstand overloads above 20,000g, and the optical imaging ability does not change before and after the hammering.
The study aims to improve the vibration isolation effect of the semi-active seat suspension system using a reinforcement learning control scheme. Mechanical tests on the designed magnetorheological damper to establish the mechanical model of the damper. According to the parameters of the seat suspension, the modeling of the magnetorheological semi-active seat suspension system is derived, and a control scheme based on reinforcement learning is proposed. Finally, the performance of the proposed control strategy is compared with the passive system and the sky-hook control under random single. It is shown that the RMS value of acceleration of the seat suspension is reduced by 21.2% compared to the sky-hook control, and by 10.6% compared with the passive system.
Smart actuators can sense external stimuli and produce controllable mechanical responses, and convert these energies into mechanical energy. They have great applications in the aerospace, electronic circuits, medical and other fields. As a new manufacturing method, the combination of 3D printing and smart actuators had developed rapidly in recent years. In this paper, we summarize the research progress of 3D printing smart actuators and its materials. The smart driver includes water responsive driver, pH responsive driver, temperature responsive driver, light responsive driver and magnetic field responsive driver. The smart driver materials can be divided into shape memory materials, piezoelectric materials, responsive smart hydrogels and electroactive polymers. In addition, their stimulative effect and driving mechanism have been studied emphatically.
The combination of machine vision and open CNC system contributes to develop various functions of CNC system such as visual inspection, condition diagnosis and machining error compensation. Focusing on the two commonly used software development platforms (Visual Studio, Qt) and three machine vision libraries (OpenCV, Halcon and EmguCV), this paper studies the operating efficiency of software platform for development of open CNC system with machine vision function. The operating efficiency of various schemes is experimentally compared. Finally, the machine-vision-based error compensation efficiency is studied by taking the curve grinding CNC system as an example. The optimization scheme based on operating efficiency is presented, which provides a basis for the selection of software platform for machine vision oriented CNC software.
In the research and development of target tracking, vision-based target tracking technology still has the problems of low accuracy and high cost. This paper designs a tracking system that uses a four-wheel differential mobile chassis as a carrier and uses the 36H11 series tags in Apriltag as a moving target. STM32F103 single-chip microcomputer is used as the core of motion control, and the classic PID control algorithm is used to adjust the wheel speed to achieve target tracking. STM32F765 single-chip microcomputer is used as the image processor of the OV7725 camera to solve the label information. The experimental results show that the Apriltag tag target can be better tracked when the PID parameters are adjusted properly. It can achieve near real-time tracking effect when the tag moving speed is slow, and it can move to the specified position quickly when it is far away from the target.
Object detection algorithms have been widely used in important fields such as national defense, military industry and transportation. However, due to the limitation of computing power and power consumption of hardware devices, most of the object detection models deployed in mobile devices are lightweight models, and their detection accuracy can not fully meet the needs of complicated scenes. This paper proposes a new model adding path aggregation and attention mechanism to nanodet, an anchor-free detection model, and improves the detection accuracy with litte cost. On our dataset, tested with RTX 3080TI the AP50 reaches 62.09% and only cost little additional inference time. It has a good reference value for the deployment of lightweight model in engineering practice.
Drill pipe angle is one of the key parameters for adjusting drilling technology, which needs real-time measurement. In this paper, an angle sensor based on triboelectric nanogenerator is proposed. The sensor can be set to different resolutions by designing different EVA sheets. Taking 12 EVA sensors as an example, the test results indicated the sensitivity is 0.08∘/V, the linearity is 5.2%, and the maximum relative error is 6%. In terms of self-supply capability, the self-supply sensor can output maximum voltage are 29 V, a maximum current are 50 nA, and a maximum load power are 110 nW. In the case of 50000 working cycles, its test performance has not significantly decreased, showing high stability.
Digital Twin (DT) is considered to be the general purpose technology of the 4th industrial revolution, and realizing its engineering application universality is the common endeavor objective of both universities and companies. Based on the theoretical framework and technical route of DT, this paper focuses on its application exploration for new energy ships. Via blending technologies of cloud computing, open source software, the marine control system and characteristics of new energy, authors carry out a feasibility analysis from the shipboard and cloud architecture and implementation plan respectively. A DT of propulsion system is developed, deployed and operated online on a new energy ship (NES). Meanwhile, the DT data is used to correct the calculation deviation of the battery State of Charge (SOC) by the ship’s physical system. The research in this paper will provide a decision-making platform for situations such as safe operation, fault diagnosis, and condition-based maintenance, and also provide an effective solution for future DT system design of new energy ships.
In order to determine the main parameters affecting the kinematic performance of the quadrupedal bionic horse robot, this paper investigates the sensitivity analysis of structural parameters on performance changes. Based on the introduction of the structure of the bionic horse robot used for equine-assisted therapy, the establishment of a kinematic model, and the kinematic analysis by the closed-loop vector method, the kinematic relationship between the trajectory of the foot end of the bionic horse and the structural parameters is calculated by full differential calculations, and the influence laws of the changes of the structural parameters on the change of the trajectory of the foot end of the bionic horse are analyzed, and the indexes for evaluating the sensitivity of the structural parameters are introduced, so that the key structural parameters with high sensitivity to the robot performance are obtained. The results are verified by simulation. This research lays the foundation for further optimization of the structural parameters of the robot.
The accurate registration of visible image and three-dimensional point cloud is the prerequisite of image fusion. How to improve the registration accuracy is the focus of current research. In this paper, a registration algorithm of visible image and three-dimensional point cloud based on point features is proposed. Firstly, the visible image is preprocessed to correct the distortion of the camera. Then, the appropriate self-build calibration field is set, and the homonymous feature points in visible image and point cloud are obtained by using the blob detection algorithm. Finally, the corresponding registration model parameters of visible image and point cloud are calculated based on multiple pairs of homonymous feature points. Experimental results show that this method can achieve centimeter level registration accuracy.
Cutting chatter has a tremendous impact on the machining steadiness of machine tools and seriously restricts the machining efficiency. In order to realize the on-line monitoring and especially forecasting of cutting chatter, a method for chatter feature extraction based on mean square frequency (MSF) is proposed. By analyzing the cutting force signal in frequency domain, the ratio of MSF is calculated as a feature based on chatter sensitive frequency band extracted by wavelet packet transform. The results display that the presented method is able to identify the cutting chatter in advance effectively and realize chatter early warning, which provides conditions for further chatter suppression.