Abstract: The non-magnetic drill pipe (composed of male and female thread joints and rod bodies) is the key component of the directional drilling technology equipment for gas extraction in coal mine tunnels. The thread joint and the drill pipe body are connected by continuous drive friction welding. In the study, it was found that the banded structure appeared in the joint of continuous drive friction welding of non-magnetic steel, which reduced the strength of drill pipe. At the same time, it is found that the heat flow mode is one of the key factors affecting the banded structure, and the heat flow mode is based on the evolution of the interface plastic ring. In this paper, through the review of the research status of the interface evolution law of non-magnetic steel continuous drive friction welding, the experimental method for the study of the interface evolution law of non-magnetic steel continuous drive friction welding is found. Read More

Abstract: Genetic algorithm is an algorithm based on the coding strategy and propagation principle of biological evolution. It constructs a universal framework suitable for solving complex system optimization problems. The algorithm is unique in its independence for specific application areas and strong adaptability to different problem types, making it able to effectively deal with extremely challenging problems. Genetic algorithm is especially suitable for global optimization problems and has the ability to jump out of the local optimal solution and search for the global optimal solution. In addition, it supports the definition of complex fitness evaluation functions and can impose constraints on the search space of variables. Read More

Abstract: A new structure of U-shaped permanent magnet synchronous linear motor is proposed to address the issue of low thrust in U-shaped coreless permanent magnet synchronous linear motors. The motor increased the electromagnetic thrust by 74.36% and controlled the thrust fluctuation within a small range by adding magnetic blocks in the primary and changing the main magnetic circuit structure. In the article, the permanent magnetic field in the motor air gap is first solved using analytical methods, and the influence of harmonic components on the motor thrust and thrust fluctuation is discussed through harmonic analysis of the magnetic flux density in the air gap. Then, the influence of several parameters on motor performance was analyzed, and the Taguchi method was used to screen the optimization variables. A mathematical model reflecting the functional relationship between optimization objectives and parameters was obtained through the response surface method. Finally, the multi-objective optimization algorithm of egret swarm was used to optimize the design of the motor and obtain the Pareto frontier. The effectiveness of the theoretical analysis was verified through finite element simulation. Read More

Abstract: Aiming at the problem of low prediction accuracy for photovoltaic power generation due to the strong randomness and volatility, a prediction model based on Improved Complete Ensemble Empirical Mode Decomposition With Adaptive Noise (ICEEMDAN) and Beluga Whale Optimization Deep Hybrid Kernel Extreme Learning Machine (BWO-DHKELM) is proposed. Firstly, the historical data are analyzed by Pearson Correlation Coefficient, and the meteorological data with high correlation are obtained as the input features of the prediction model. Secondly, the PV power is decomposed by ICEEMDAN to reduce its volatility. Then, DHKELM is constructed for each subsequence and several parameters of the model are optimized by BWO. Finally, the predicted values of each subsequence are summed to obtain the final prediction results. The effectiveness and superiority of the proposed model are verified by using real data from a PV plant in Jiangsu, China as an example. Read More

Abstract: With the goal of enhancing the overall performance of the column, which is one of the key components of the machine tool, a biomimetic design approach was employed in this study. Drawing inspiration from the leaf arrangement structure found in nature, the internal supporting structure of the column was designed using principles and methods of structural biomimicry. Subsequently, finite element static analysis was conducted on the biomimetic column structure. Sensitivity analysis of the optimized pillar structure dimensions was performed, resulting in a comprehensive design solution with superior performance. Following optimization, the mass of the column was reduced by 55.39 kg, representing a decrease of 2.7%; maximum deformation decreased by 0.0738 mm, reducing by 35.18%; maximum equivalent stress decreased by 0.44 MPa, a reduction of 5.4%; and the first-order natural frequency increased by 12.43 Hz, rising by 22.91%. Through effective optimization, while ensuring rigidity, the static and anti-vibration performance of the beam were improved, facilitating lightweight design. Read More

Abstract: Axial piston pumps are commonly used as key equipment in the petroleum industry to transport crude oil and petroleum products. Outlet flow pulsation refers to the periodic change of pump outlet flow in a certain period of time, which will have a certain impact on the petroleum industry. The export flow pulsation will affect the transportation stability of petroleum products, and the export flow pulsation will also affect the quality of petroleum products. The transition zone of the high and low pressure conversion of the distribution disc throttle groove during the operation of the axial piston pump will affect the flow backflow at its outlet, which further affects the flow pulsation. Therefore, the key parameters of different distribution trays are studied. The influence of the key parameters of the V-groove and the U-groove on the flow pulsation of the distribution plate was studied, and the U-shaped groove was optimized, and a V-shaped opening was added at the end of the U-shaped groove to reduce the flow pulsation. Read More

Abstract: A modified Q-learning algorithm is proposed for the permutation flow shop scheduling problem. This algorithm initializes the environment with the job sequence and considers each processable job as an executable action. A reward function is defined as the reciprocal of the completion time. Moreover, the completion time is calculated using the principle of diagonalization of a two-dimensional matrix, significantly enhancing computational efficiency. The Boltzmann action exploration strategy is designed, where the probability of selecting an action decreases as the temperature coefficient T decreases, and the probability of randomly selecting an action decreases, favoring the selection of actions corresponding to larger Q values. Finally, the performance of the proposed algorithm is validated using instances of permutation flow shop scheduling problems of different scales. By comparing the results with standard instances and other algorithms, the accuracy of the algorithm is demonstrated. Read More

Abstract: Through a systematic review of relevant literature, this paper comprehensively elucidates the evolution of camera calibration techniques and analyzes key milestones in its development. It introduces traditional camera calibration, self-calibration, and neural network-based camera calibration methods along with their research status, summarizing the characteristics and applicable scenarios of each method in practical applications. Based on the latest research progress, it delineates the latest technologies and methods in the field of camera calibration, highlighting their respective advantages and limitations. Prospects for the future development of camera calibration techniques are provided, exploring potential breakthroughs in high-precision, high-robustness mapping models, and automatic, accurate marking of image feature points, thereby offering valuable insights for addressing complex scenarios in 3D measurement applications. Read More

Abstract: In this paper, an innovative method for energy recovery and management of the electronically controlled suspension system is proposed and simulated using MATLAB/Simulink, with the aim of enhancing energy efficiency and environmental sustainability. This method employs an integrated control approach based on force-position for tillage depth control. When the tractor suspension is positioned above the soil surface and descending, the PMSM switches to generator mode and uses the PMSM for energy recovery. The simulation results demonstrate the viability of energy recovery in heavy agricultural machinery, offering novel ideas and techniques for effective energy management in such equipment. Read More

Abstract: As the material living standards of residents rapidly improve, the demand for fruits and vegetables continues to rise. Agricultural greenhouses, as a critical means of increasing fruit and vegetable yields, require effective control of temperature, humidity, and light intensity to ensure rapid crop growth. Traditional manual monitoring and control methods are inefficient and labor-intensive. Against the backdrop of rapid developments in electronic technology, this paper innovatively designs a greenhouse IoT intelligent control system based on a microcontroller, achieving real-time monitoring and automated control of greenhouse environment parameters. The innovations of this system are evident in several aspects: Firstly, it employs an STM32 microcontroller as the main control chip, integrating YL-69 soil moisture sensors, GL5506 photodiodes, and DS18B20 temperature sensors to achieve high-precision detection of soil moisture, light intensity, and temperature. Secondly, an LCD1602 display is used to timely showcase real-time environmental parameters, and alarm thresholds can be set via buttons. If these thresholds are exceeded, a buzzer sounds an alarm. Concurrently, the system utilizes water pumps and supplementary LED lights to intelligently adjust humidity and light intensity within the greenhouse. Most importantly, by incorporating the ESP8266 module, the system achieves remote data transmission, allowing users to view real-time environmental parameters via a mobile app and set thresholds and control operations. This greenhouse IoT intelligent control system not only features alarm functions for exceeded environmental parameters but also enables automatic adjustment through intelligent devices and supports remote control, greatly enhancing operational convenience and system practicality. Overall, this system innovatively integrates various sensing technologies and IoT communication, providing an efficient and intelligent solution for the modern management of … Read More

Abstract: Aiming at the problem that the traditional model current predictive control of open-winding permanent magnet synchronous motor with common bus is easy to change its motor parameters, the current predictive control and model-free control are combined. On this basis, a linear state observer is added to estimate the system disturbance and solve the time-consuming and complicated problem of model-free control disturbance. The improved model-free current predictive control selects the best basic voltage vector and action time through the value function and voltage vector sector. The zero-sequence voltage to be compensated is obtained by the difference between the zero-sequence voltage generated by non-zero vector and the reference zero-sequence voltage, and the mixed zero vector injected and the action time are selected and calculated, so that the system can achieve optimal compensation. Finally, Matlab/Simulink is used for simulation, which verifies the effectiveness and feasibility of the experiment. Read More

Abstract: For the cordless hoisting system, a six-phase U-shaped permanent magnet linear vernier motor (SU-PMLVM) is proposed. The primary of the motor adopts a U-shaped segmented permanent magnet array, which is characterized by a high magnetization effect and a low magnetic leakage. In order to enhance the comprehensive performance of SU-PMLVM, the average thrust, thrust fluctuation, and no-load counter potential harmonic distortion rate are selected as optimization objectives. Taguchi's method is employed to expeditiously optimize SU-PMLVM in a multi-objective manner. Firstly, the optimization variables with the greatest influence on the objectives and the values of their factor levels are selected. Then, the designed orthogonal experiments are solved by using the finite element method, and the performance data of each optimization objective under different combinations of factor levels are obtained. Finally, the influence weights of the optimization variables in each optimization objective are clarified through the analysis of variance, and the optimal level combinations of the optimization variables are thus obtained. A comparison of the performance of the objectives before and after optimization indicates that the average thrust of the proposed motor has increased by 1.77%, the thrust fluctuation has been reduced by 40.06%, and the no-load reverse potential harmonic distortion rate has been reduced by 15.23%. Read More