Ebook: Mechatronics and Automation Technology

Mechatronics and automation technology has promoted the intersection and interpenetration of many different disciplines, such as machinery, electronics, control, and computers, and has triggered technological reform and innovation in all engineering fields. It plays an important role in improving production efficiency, reducing energy consumption and improving product quality and safety. In the future, with further developments in science and technology, mechatronics and automation technology is set to become the core technology to advance the technological and industrial revolutions and bring convenience and innovation to more fields.

This book presents the proceedings of the 2nd International Conference on Mechatronics and Automation Technology (ICMAT 2023), which was held virtually on 27 October 2023. The aim of the conference is to provide a platform for scientists, scholars, engineers and researchers from universities and scientific institutes around the world to share the latest research achievements in mechatronics and automation technology, explore key challenges and research directions, and promote the development and application of theory and technology in this field. The conference was divided into three sessions: keynote speeches, oral presentations, and an online Q&A discussion. A total of 121 submissions were received, of which 77 were ultimately accepted after a rigorous peer-review process. These papers cover a wide range of topics within the scope of mechatronics and automation technology, including smart manufacturing; digital manufacturing; additive manufacturing; robotics; sensors; control; electronic and electrical engineering; intelligent systems; automation technology; and other related fields.

Exploring core areas of mechatronics and automation technology, the book will be of interest to all those working in the field.

For achieving zero discharge of desulfurization wastewater, the 2×1,000MW Unit of a power plant in Hunan adopts the process of “low-temperature flue gas evaporation and concentration+high-temperature flue gas bypass drying and curing”. The heat source of the low-temperature concentration tower comes from the flue gas (97°C) after the induced draft fan, for direct heat exchange in the tower through counter-current spraying of desulfurization wastewater, with the concentration ratio of 4 or above. The high-temperature flue gas bypass drying tower extracts high-temperature flue gas in front of inlet of the air pre-heater, and process the concentrated solution in the rotary atomizing and drying tower for zero discharge. This paper focuses on studying the thermodynamic calculation regarding the low-temperature flue gas evaporation and concentration system and high-temperature flue gas drying and curing system, so as to establish a balance of quality and capability, and calculate the basic data for system design by the trial method. Meanwhile, it further studies the quantitative calculation of impact of the zero discharge system on thermal and economic indexes such as boiler efficiency and standard coal consumption. The maximum processing rate of each 1,000MW Unit can reach 13m3/h, requiring 13.61% of low-temperature flue gas. The high-temperature drying tower is designed to dry the concentrated solution at a rate of 6m3/h, requiring 1.73% of high-temperature flue gas. As a result, the temperature of flue gas at the outlet of the air pre-heater can be lowered by about 3°C, the air temperature at the primary and secondary outlets can be lowered by about 1°C, the boiler efficiency can be decreased by 0.066%, and standard coal consumption can be increased by about 0.183g/kWh.

In recent years, with the rapid development of Internet of Things technology and its advantages in data communication and information transmission, it has been widely used in the field of shipbuilding industry. In order to realize the real-time monitoring of power quality of electric propulsion ships, this paper proposes a comprehensive energy management strategy for ships based on the Internet of Things technology. Considering the relationship between the operation of the ship’s micro-network and the load demand, the Internet of Things technology is used to load a variety of sensor devices on the ship in an embedded way to complete the real-time collection and operation management of the ship’s information. For the load fluctuation during the switching of operating conditions, the rule-based energy management strategy is adopted. By comparing the simulation results of the built simulation model in different modes and different operating conditions, it is shown that when the load is in short-term fluctuation, the strategy can effectively reduce the power fluctuation and improve the power quality of the DC side bus voltage.

To address the challenge of autonomous orbiting of space satellites under the increasing number of satellites in space,the Satellite Tool Kit (STK) is used to simulate and analyze the orbiting of medium-orbit satellites under Multi-Global Navigation Satellite System (Multi-GNSS) signals. The four global navigation systems and augmentation systems are modeled by STK. The satellite signals from the navigation systems are received by the middle earth orbit (MEO) satellite. The satellite signals from the navigation systems are received by the middle earth orbit (MEO) satellite receiver, and the number of visible stars, the Dilution of Precision (DOP) value, and the navigation and positioning accuracy are used as the evaluation indexes. The navigation systems are received by the middle earth orbit (MEO) satellite receiver, and the number of visible stars, the Dilution of Precision (DOP) value, and the navigation and positioning accuracy are used as the evaluation indexes to study the optimal positioning mode of the middle-orbit satellites in the case of multi-GNSS. concluded that under single-system positioning, the positioning accuracy of BEIDOU system is higher, up to 4 meters accuracy. Under dual-system positioning, the combined accuracy of BEIDOU system is higher, up to 4 meters accuracy. Under dual-system positioning, the combined accuracy of BEIDOU and the Global Positioning System (GPS) is higher, with an accuracy of about 3 meters.

The vibration of railway wagons bearing is an important comprehensive quality index, which directly affects the quality and service life of bearing products. In this paper, the model of double row tapered roller bearing is established based on the method of dynamics to low vibration. The structure of bearing is designed optimally and the original and optimal comparison experiments and vibration characteristics are developed and analyzed respectively, and the accuracy of theory and structural optimization is verified. It is concluded that the bearing dynamics model is verified. In addition, the bearing vibration is reduced through structural optimization.

Aiming at the problem of frequent aging faults of insulated gate bipolar transistor modules, this paper takes IGBT aging fault characteristic parameter data collected from the intelligent sensing layer of the Internet of Things terminal as samples. In the computing fusion cooperation layer, multi-terminal cooperation training and establishment of an optimized random forest model is applied to the IGBT aging fault diagnosis system to realize the condition monitoring of IGBT devices. Firstly, the characteristic parameters of aging fault are selected from the data samples and preprocessed to establish the aging fault diagnosis data set. Secondly, the traditional random forest model is built and optimized by parameter optimization of base evaluator, parameter optimization of model frame and bagging method. The optimization model training was completed on the basis of cross-validation. Finally, the prediction effect of the model in this paper and other models on IGBT aging fault diagnosis data set was evaluated by various evaluation indexes. Finally, the optimized model fit well, the error between the training set curve and the test set curve was 1.19%, and the prediction accuracy on the test set could reach 98.81%. The feasibility and accuracy of the optimized random forest model applied to IGBT condition monitoring system in the Internet of Things environment are verified.

To address a range of practical tasks, it is necessary to employ installations that implement complex rotational-oscillatory motion of working elements, such as the stator and rotor. These installations incorporate principles and effects of nonlinear wave mechanics in multiphase media. The internal resonance effects in the system are induced by the interaction between high-frequency vibrations generated by the high-speed rotor’s working elements and low-frequency torsional vibrations of the stator. The primary control task in designing such installations is associated with the selection of electromechanical motors capable of realizing complex rotational-oscillatory motion and constructing a control system for them. The research results presented herein demonstrate a specific solution to this problem in the design of an installation for the pulverization of lignocellulosic raw materials.

As multiple types of loads and distributed resources such as electric vehicles, energy storage, and new energy power generation are widely accessible in the park, the characteristics of “source-grid-load-storage” interaction and multi-energy complementary coupling are increasingly apparent, and the traditional scheduling cannot meet the needs of accurate scheduling and real-time analysis of operation situation. The digital twin technology will greatly improve the intelligent level of the park’s comprehensive energy system by carrying out data acquisition and transmission, data processing and feature mining, operation scheduling and high-level decision-making for the park’s energy and power, and realizing the holographic mapping of the park’s comprehensive energy in the virtual information world. This paper firstly analyzes the principle and process of “source-grid-load-storage” operation situation deduction and multi-level scheduling of the park’s integrated energy system based on the digital twin technology, and secondly systematically expounds the key technologies of “source-grid-load-storage” collaborative regulation in the park from the aspects of aggregation modelling, rolling prediction, situation deduction, and optimal scheduling. Also, it points out the direction for the practical application of digital twin technology of integrated energy systems in the park. Finally, based on a comprehensive smart energy project on a campus in Shanghai, this article conducts an energy management experiment on a certain day, which proved that the system can maximize the consumption of new energy, make the heating mode more energy-saving and environmentally friendly, and effectively achieve peak shaving, valley filling, energy conservation and emission reduction.

Fruit and vegetable picking is an important link in China’s agricultural production. The existing manual picking method has high labor intensity and low efficiency. The application of picking robots can greatly improve the efficiency of picking operations and reduce the dependence on manpower. Its research has great practical value. The machine vision system of the picking robot is currently a hot and key research area in this field. This article analyzes the key issues faced by the machine vision system research in terms of precise identification of picking objects, spatial positioning, and path planning in complex environments, and classifies and summarizes the latest research results of machine vision at home and abroad.

Sound field analysis of oil well string is very important for the detection of oil well dynamic liquid level. Acoustic wave state is a key parameter, which indicates the relationship between oil well string and oil level. Because the echo resonance signal of acoustic wave contains the relevant parameters of oil level reflection, it needs to be processed. In this paper, the combination of principal component analysis (PCA) and Kalman filter algorithm is proposed to process the oil well echo resonance signal. Experimental results show that this method can significantly improve the noise filtering of the signal, and then improve the state estimation of the system more efficiently.

Dynamic modeling and cushioning performance analysis are the basis for damper design. The present aims to provide a dynamic model and optimization method for viscoelastic damper. For this purpose, a new double-rod viscoelastic damper for high-speed impact is taken as an example to demonstrate the design process. Firstly, the structure of double-rod viscoelastic damper is described to reveal its working principle. According to the properties of mastic material, a Kelvin model with variable stiffness is established by Simulink. Secondly, the influence of key component parameters on cushioning performance was analyzed for further optimization. Thirdly, based on Simulated Annealing algorithm, the viscoelastic damper system’s left piston rod diameter, piston thickness and inner cylinder diameter are chosen as the optimization variables. The optimized viscoelastic damper’s peak cushioning force is 31% lower and its cushioning effectiveness is 28% higher. The numerical results provide theoretical recommendations for the double-rod viscoelastic damper design.

Deep hole machining accounts for a large proportion in machining. Due to the special depth of the hole being processed, the conventional deep hole drilling fixed cycle can lead to overheating of the tool after several times of drilling. Using the macro functions of the FANUC system, a new G code is developed to gradually reduce the depth of the drilling hole when processing deep holes. After being verified by the GLU28x40 CNC, the newly defined G code is input and programmed according to the prescribed syntax, Equivalent to a fixed loop implanted in the control system. When machining deep holes, it can effectively alleviate the problem of excessive tool temperature during the pecking drilling process and improve processing accuracy.

The mathematical model of servo control system is established, and the physical meaning of feedforward control is analyzed. Based on the servo three-loop control structure, a feedforward compensation mathematical model is constructed to reduce the tracking error of each axis of the CNC system. The application in FANUC CNC system shows that the large tool path tracking error of the servo system due to the phase lag and amplitude attenuation of the drive signal can be reduced by setting the appropriate feedforward coefficient during high-speed and high-precision machining.

In this paper, a novel half-bridge integrated zero-voltage full-bridge soft-switching DC-DC converter based on the secondary auxiliary resonant loop is proposed for medium to high power applications with medium and high voltage output. Compared with the other converters, this converter can eliminate circulation losses and reduce the reverse recovery losses of the rectifier diodes, improving the efficiency of the converter. The overall volume of the converter is reduced and the power density is increased. The principles, circuit characteristics and soft switching conditions of the converter are analyzed in detail. The performance and effectiveness of the circuit are verified by experiments based on a 1.2 kW–50 kHz circuit.

In order to solve the problem of void feature detection of 3D ground-penetrating radar data, the test of void detection in polystyrene cubic simulation road is carried out in this paper. The B-scanning image was processed by binarization, corrosion, expansion and thin length, and the suspected void region was obtained, According to the characteristics of multi-channel detection of 3D ground-penetrating radar, a method is proposed to divide the B-scanning image of suspected void into several clusters and calculate the convergence of each cluster to identify and determine the void signal. The detection method has been verified in the engineering, The results show that in the process of the field test and verification, the algorithm of 3D ground-penetrating radar data void characteristic detection accurately recognizes 4 sites with void potential. Also, the 3D matching test successfully eliminated 8 suspected void regions, indicating that the 3D ground-penetrating void feature detection algorithm has excellent robustness in the task of void segmentation of radar images. The technique can detect the voids inside city roads accurately and fast which have great significance in reducing casualties and property damage.

The smart phone assistance system for the elderly based on WeChat mini program mainly solves the problem that the elderly can not or can not skillfully use smart phones. The system is designed with the idea of microservice architecture, and coded with WeChat mini program, SpringBoot framework, intelligent remote control and intelligent voice interaction technologies. In addition, in terms of interface design, the aging design is also carried out for the elderly. The smart phone assistant system for the elderly based on WeChat mini program aims to help the elderly adapt to the rapidly changing technological society, bridge the “Digital Divide” and create a “Digital Huilao” environment.

Experiments of active vibration control for flexible truss are studied, with a Stewart platform manipulator (SPM) employed as an active device at the bottom of the truss. A back-propagation neural network is designed to identity the controlled object. And on the basis of the identification model, this work constructs a neural network adaptive inverse controller (NNAIC). Then based on the dSPACE real-time simulation system, the control test system for the truss is built, on which the neural network adaptive inverse control experiments are carried out. The vibration amplitude decreases more than 93.8% and 89.6% with the structure continuously being excited at the first-order and second-order resonant frequency respectively. The results indicate the effectiveness of the control conducted by using SPM, and NNAIC has a good performance.

The reconfigurable wheel-track locomotion system integrates wheels and tracks to improve the efficiency and maneuverability of the vehicle. It can dynamically switch between the two locomotion modes based on road conditions, greatly enhancing the vehicle’s adaptability to the environment. Therefore, it has become a hot topic in special ground mobile platforms. This paper first proposes a distributed driving mobile platform. Based on the equivalent reconfiguration principle, a reconfigurable wheel-tracked locomotion system is designed which can transit between wheel mode, half-tracked mode and full-tracked mode. Then the basic structure of its mechanism, reconfiguration principle, and a method for track design are discussed. To minimize the required force capability of the electric actuator of the deformation mechanism, an optimization model for the hinge joint location of the actuator is established considering structure constraints. A Nonlinear programming by quadratic Lagrangian (NLPQL) was adopted to solve the constrained optimization problem. A finite element method (FEM) model was then established to verify the accuracy of the theoretical model. The results indicate that the relative error of actuating force between the theoretical model and the simulation is 13.5%. The optimized actuation mechanism can fulfill the reconfiguration function of the mobile platform. Finally, the mobile robot was built according to the optimization results and an experiment was carried out to test the pivot turning and mode transition functions of the robot. The robot was able to transit between the three modes while it’s in motion, which reveals the feasibility of the reconfigurable system and verifies the optimization model.

In order to improve the safety, parking efficiency and smoothness of the parallel parking of driverless cars, for the parking process needs to meet the path curve curvature is small, parking distance is short, the lane occupation is less, through the analysis of the characteristics of the parallel parking working conditions, put forward a NSGA-II algorithm based on the parking starting point of multi-objective optimization method. Firstly, based on the analysis of vehicle kinematics model, the quintic polynomial curve is used to construct the parking path, and the analytical function between the parking start point and various indexes is established; then, the NSGA-II algorithm is used to optimize the constructed multi-objective model, so as to obtain the optimal optional set of the parking start point; finally, the results of the simulation experiments show that: in order to satisfy the various objectives of the synergistic optimization as well as constraints, the proposed method of the design of the parking start point can achieve the parking path curve of less curvature and shorter parking distance.

Laser weapons are sensitive to target and environment, of which tactical decision aids is complex and amount of calculation. The deep learning mechanism of weapon command, use and operation are established, which contribute to forming the intelligent assistant decision-making ability of laser weapon operational use. Both of them are the key to solve the problems about laser weapon of operation and use. They are also the means to promote the laser weapons of technicalization and real combat. The authors proposed preliminary conception of intelligent assist decision making based on multi-source data, case-based reasoning, nonlinear logic in the paper.

In the field of production processing and manufacturing, often meet the thin-walled parts, this thin-walledt parts after processing, need to meet the part size, form tolerance parallelism requirements, in order to meet the part size, form tolerance parallelism requirements, in the chuck jaws installed on the self-made tooling, with a percentage table to find a good self-made tooling end runout, with self-made tooling positioning parts, quickly complete the processing of parts to improve production efficiency.

In this paper, a simulation analysis is conducted for liquid-filled deep drawing process of battery shell used on electric vehicles. Firstly, the plate liquid-filled forming experiments are conducted on our own hydraulic forming experimental platform, secondly, the hydraulic simulations based on the nonlinear finite element software DYNAFORM are conducted to demonstrate correctness of the finite model and the simulation method, and finally, based on the correctness of the finite element simulation method, finite element modeling and simulation analysis for the battery shell of electric vehicles are conducted to discuss the impact of different presser ring edge pressures and hydraulic pressures on the wall thickness of the battery shell, providing a reference for the practical application of the liquid-filled deep drawing process of battery shell.

The flue gas purification technology in aluminum electrolysis employs baghouse dust collectors as the main equipment. The efficiency of ash removal significantly affects the dust removal performance. The pulse blowing ash cleaning technology imposes more demanding requirements. This paper experimentally validates the impact of pulse ash cleaning on performance by varying the spray blowing distance and filter bag length. Additionally, it provides insights from the perspective of engineering design and application in aluminum electrolysis.

Stereolithography (SLA) is a 3D printing technology commonly used in many fields. This advanced printing technology makes it possible to produce a wide range of products with smooth surfaces with high precision. Nowadays, 3D printing technology is the Top most effective with almost absolute accuracy. Support is still needed to print corner protrusions. Still, a more significant concern is to minimize the cross-sectional area at each print layer to avoid bias when removing a print layer from the silicone. Support structures in small columns or frame structures to keep the model in the correct position during printing are often created in preparation for stereolithography 3D printing. These structures are printed with the model and removed after printing. The support structure has an essential influence on the quality and accuracy of the 3D-printed product. In this study, the survey model is fabricated based on SLA 3D printing technology with different support structures, and the mechanical properties of acrylonitrile butadiene styrene like resin (ABS like resin) are tested. Check the parameters on the compression testing machine, and the results show that the two-headed support structure is optimal for the surveyed plastic materials.

To address the problem of the LEACH routing protocol’s inapplicability to large-scale networks due to its lack of consideration for dynamic changes in the network, a wireless sensor network energy-efficient routing protocol based on a tree-like link topology structure is proposed. This protocol seeks parent nodes based on the remaining storage energy of cluster heads, geographical location information, and the load level of neighboring cluster heads. Through multiple iterations, it establishes a tree-like link with the base station, enabling multi-hop routing transmission between cluster heads and the base station. Simulation and performance analysis demonstrate that compared to the LEACH protocol, the proposed protocol effectively balances network energy consumption and overall network lifespan.