To achieve coordinated control of multi-speed operation in the spiral concrete batching machine, this paper proposes a trajectory tracking-based coordinated control method. By analyzing the working process of the spiral concrete batching machine, the coordinated relationship between lateral movement and concrete conveying rate is investigated, and a two-degree-of-freedom kinematic model for the batching machine is established. The error model for the trajectory tracking system of the batching machine is developed and discretized to meet the requirements of computer numerical calculation and real-time control. Based on model predictive control theory, a prediction equation for the trajectory tracking system is established. The objective function for the batching machine trajectory tracking is formulated, and the optimal control strategy is derived. Simulation results demonstrate that the trajectory tracking-based control method effectively achieves coordinated control of multi-speed operation in the spiral concrete batching machine.

To thoroughly explore the extensive applications and prospects of knowledge graphs in the domain of intelligent manufacturing, aiming to support the sustained development of the manufacturing industry, the domain of intelligent manufacturing has been categorized into four dimensions: vertical industry applications, manufacturing process applications, domain graph construction technology, and intelligent services. Through this study, the significance of knowledge graphs in driving the evolution of intelligent manufacturing is reviewed. Furthermore, a framework for an intelligent manufacturing knowledge graph, rooted in manufacturing domain knowledge data, is proposed. This framework encompasses three key modules: manufacturing domain data, graph construction, and intelligent services, providing theoretical support for the continuous upgrading of intelligent manufacturing. Research findings emphasize the crucial role of knowledge graphs in advancing the intelligence of the manufacturing industry and the broad potential of knowledge graphs in the field of intelligent manufacturing. Additionally, an outlook on future research directions for knowledge graphs in the domain of intelligent manufacturing is suggested, with a focus on exploring the integration of domain graphs with next-generation artificial intelligence technologies to propel the continuous innovation and intelligent evolution of manufacturing.

During the operation of an air cushion belt conveyor, factors such as fan air volume, number of air holes, and film thickness have a significant impact on the flow field characteristics and bearing capacity of the air cushion. By establishing a simulation model for the air cushion flow field, analyze the changes in air cushion pressure under different working conditions. Based on experimental comparison and analysis, the variation law of air cushion pressure under different air volume and number of air holes, as well as the variation of air film thickness and air film pressure under different air volume were analyzed. The results show that as the air volume increases, the film pressure gradually increases, and the film thickness changes from 5% to 30%. As the number of pores increases, the pressure gradient of the air cushion changes faster and exhibits a parabolic distribution, and the degree of change in air film thickness decreases. The experimental and simulation results show that the changes in the air cushion flow field are consistent, and the fan air volume is 15-20 m³/m, the optimal value K₁ for the stability of the air cushion flow field is 1.31, and the optimal working condition is 5 exhaust holes, which meets the requirements of actual operating conditions.

In order to investigate the effect of tower slewing motion on tip displacement and to provide a basis for collecting tip displacement data to improve the accuracy of tower steel structure damage diagnosis, this paper adopts a tower physical structure experiment bench to select three different strokes of high, medium and low slewing speeds, and to collect tip displacement during slewing motion and static tip displacement. A characterization study of the tip displacement for slewing stroke and speed change was carried out; the structural response characteristics of the slewing motion were established and characterized by noise characterization coefficients. The experimental results show that the collected tip displacements are close to static displacements when the slewing stroke is larger, the slewing speed is slower, and the noise characterization coefficient is smaller than a set threshold. The purpose of this study is to avoid the influence of slewing motion on the real-time monitoring of structural damage, and to give a scientific basis for the setting of the data acquisition conditions for the required tower steel structure damage diagnosis.

A theoretical model of stress distribution and contact width is established by Hertz contact theory. The reaction of roller under specific load is analyzed. The results shows that linear profile have significant edge contact stress concentration, which increases with the increase of load. The roller with logarithmic profile can solve the stress concentration, but it can't completely eliminate it. Under the same load, with the increase of the bias factor, the maximum contact stress of the roller decreases sharply at first and then increases slowly. The position where the maximum contact stress occurs shifts from both ends of the roller to the middle of the roller. The profile design of roller with logarithmic type can take a value between 1.0 and 2.5 for the bias factor based on working conditions, roller size and load conditions. The value of bias factor is adaptive to tilt error and the impact of tilt error on contact stress can be reduced by setting a reasonable value.

In order to explore the safety threat of slope deformation to transmission lines, taking the transmission tower-line system as the research object, the overall finite element model of the tower-line system considering soil-structure interaction (SSI) effect is established, and the rationality of the numerical analysis model is verified based on the field measured data. On this basis, considering the relationship between the slope deformation area and the spatial position of the tower and the influence of the slope deformation angle, the response law of the stress characteristics of the tower-line system to the slope deformation is explored. The results show that when the towers are located above, below and inside the slope deformation body respectively, the failure mode and deformation resistance of the upper tower line system are significantly different. And with the increase of slope deformation angle, compared with horizontal slope deformation, the anti-deformation ability of tower-line system will decrease by 25%-50%. When the tower is located outside the slope deformation body, the anti-deformation ability of tower-line system will decrease most seriously, with the decrease range of 33%-50%.

The study examines wires in high-vibration zones of aircraft, where artificial damage was introduced to accelerate wear. Step-up-stress vibration testing was conducted to simulate accelerated aging and measure wire wear over a fixed period. Three surrogate models were developed using the wire diameter after artificial damage as the input and the experimentally obtained wire wear as the output. This established a nonlinear relationship between the initial artificial damage and the wear rate. The finite difference method was applied for time superposition to approximate the entire life cycle. Results indicate that the surrogate model using a back propagation neural network (BPNN) achieved the highest accuracy. Predicting lifespan through wear rate across the product's lifecycle can significantly reduce experimental costs. These findings provide theoretical and experimental guidance for future research on anti-wear technology and health management of aircraft wiring harnesses.

This paper proposes a robotic grasping technique based on object recognition and fully convolutional grasp quality convolutional neural network (FC-GQCNN). To address the limitations of traditional GQCNN, such as low computational efficiency and redundant feature calculations, an improved FC-GQCNN is developed. By replacing the fully connected layers in GQCNN with 1×1 convolutional layers, the proposed network can handle input images of arbitrary sizes. Furthermore, the integration of FC-GQCNN with the YOLOv8 object detection algorithm forms a YOLOv8-FCGQCNN cascade structure, effectively solving the challenges of object recognition and localization in complex environments. Experimental results demonstrate that this method achieves an 86% grasp success rate across 10 different objects, with an average detection time of 0.09 s per frame, which is 22 times faster than traditional GQCNN, significantly improving system efficiency. This method can accurately detect the grasping position of the object of interest and has higher reliability than the baseline method.

In order to meet the operation requirements of the Tianjin trunk line water conveyance box culvert of the South to North Water Transfer Project, a special multifunctional operation vehicle is developed and its high precision control is realized. Firstly, the structure and working mechanism of the multifunctional operation vehicle are described, and its kinematics models are established respectively. Secondly, a cross coupling synchronization control strategy is proposed to solve the problem of vehicle body attitude deviation caused by speed non-synchronization in dual motor independent control. Finally, the system model of multifunctional vehicle is built and the simulation analysis of cross coupling synchronization control is completed. The results of software simulation and system engineering application show that the proposed cross coupling synchronous control strategy can effectively improve the non-synchronization errors of double motors and improve the attitude control accuracy of the multifunctional vehicle for box culverts, and has strong engineering practicability and application popularization.

By predicting the wear trend of aeroengine, the wear state of aeroengine can be monitored effectively. Among the effective observation data reflecting the engine wear state, the oil analysis data can indirectly reflect the overall wear trend of aeroengine. Therefore, by establishing a trend prediction model based on oil sample analysis data, so as to realize the wear trend prediction of engine. However, the current models used in aeroengine trend prediction are mainly single prediction models, and the combined prediction models are only general linear combinations, with poor prediction effect. Therefore, a nonlinear variable weight combination prediction model based on support vector machine is proposed, and realizes the parameter optimization through particle swarm optimization algorithm. The oil sample analysis data is obtained through the bearing fatigue test of the whole life oil system, and the oil samples are collected at fixed intervals for performance analysis. Through the combination prediction analysis of the spectral analysis data, by comparing the prediction results of the combination prediction and the prediction results of the single prediction model, the prediction accuracy exceeds the prediction accuracy of the single prediction model, which fully verifies the superiority and effectiveness of the combination prediction model proposed in this paper.

In order to solve the problem that the trajectory is not straight when piecewise polynomial interpolation method is used to plan the trajectory of excavator's linear operation in joint space, which leads to the inaccurate trajectory, this paper proposes a quintic polynomial interpolation method based on multidimensional trajectory to realize the accurate trajectory of excavator's linear operation. While using Matlab to draw the relevant images in motion, ikunc function is used to optimize the inverse solution of each point in the motion process, and joint Angle trajectory smoothing algorithm and particle swarm optimization algorithm are used to verify the minimum change of joint Angle in the optimal inverse solution of ikunc function. It is verified that the ikunc function is correct to obtain the minimum and best inverse solution of the joint Angle change, which indirectly achieves the energy optimal effect.

In recent years, intelligent control technology has occupied an increasingly significant position in the field of modern engineering research. With the rise of artificial intelligence technology, it provides more possibilities for construction machinery to realize intelligent control. In the development process of intelligent technology, the control accuracy of construction machinery system is improved, industrial production is more reliable and safe, and the production efficiency of enterprises is improved. This paper starts from the content of intelligent control technology, introduces various intelligent control technology theories and methods, and discusses the application of intelligent control technology in various construction machinery according to intelligent technology methods. At the same time, the key problems and technical system of future construction machinery under intelligent control are analyzed and studied, which provides reference for the intelligent development of construction machinery control technology.

In order to deal with the problems of single evaluation criteria and too subjective weight allocation in the evaluation scheme of module division, the evaluation criteria and calculation methods of module degree, module replaceable and module structural integrity of the product module division scheme were proposed. On this basis, multiple secondary evaluation indicators of module division were proposed to determine the weight allocation among evaluation criteria. The optimal and worst many criterion decision model in the distributed multiplicative preference environment is applied to determine the weight distribution of the relevant parameters in the method, and the will of all decision makers is comprehensively considered to make the final module division scheme more objective. Finally, the module division of the excavator working arm is used to verify the feasibility of the method.

To achieve rapid prediction of aerodynamic noise in the rearview mirror area of vehicles, an stochastic noise generation and propagation (SNGR) method is adopted. Unlike general aerodynamic noise simulation methods, this method is based on the reynolds-averaged navier-stokes (RANS) equation to solve the steady flow field, reconstructing the sound source term through a velocity random model, and finally using the finite interpolation method to solve the acoustic analogy equation, greatly reducing the computational period of aerodynamic noise simulation. Based on actual vehicle data, a wind tunnel model is established, with a speed of 120 km/h as the simulation condition. Under the same conditions, the SNGR method and the general unsteady method using large eddy simulation as the flow field calculation model are respectively used for simulation. The results show that the calculation time of the SNGR method is greatly reduced, and the calculation results are consistent in the frequency range of 500-5 000 Hz, proving the efficiency of this method. On this basis, the flow field results in the rearview mirror area are analyzed, and the design of the car rearview mirror is optimized based on the principle of aerodynamic noise generation. Install the rearview mirrors before and after optimization on the entire vehicle for wind tunnel experiments, and verify the accuracy of the SNGR method calculation results by comparing the sound pressure level reduction before and after rearview mirror optimization. The simulation and experimental error of this method is between 4%-5%, proving that this method can be used in the optimization stage of aerodynamic noise performance of vehicle rearview mirrors.

Aiming at the problems of multi-dimensional small failure probability and implicit function in the reliability analysis for bridge crane structure, that is difficult to solve using traditional reliability analysis methods, the one based on dynamic Kriging surrogate model combined with important sampling method is proposed. Firstly, the dynamic Kriging surrogate model of the implicit function is constructed utilizing two learning functions, and then the most probable failure point (MPP) is obtained by using the improved first order second moment method combined with the Kriging surrogate model. Secondly, the importance sampling density function is constructed with the MPP as the central point. Finally, the reliability degree is calculated by the importance sampling method based on the established surrogate model. By introducing a new stop criterion combined with learning function, the number of finite element calls is reduced. Verified by an engineering case, the proposed method can well balance the model accuracy, result error and calculation cost.

Middle outrigger is the main support leg of tunnel erecting machine, and hydraulic system plays an important role in the erection process of prefabricated utility tunnel sections. To solve the problems of slow action and low positioning accuracy of hydraulic cylinder of middle outrigger, the hydraulic system of tunnel erecting machine is optimized through on-site experiments and AMESim simulation analysis. According to the erection process and hydraulic system principle of tunnel erecting machine, a preliminary analysis and on-site measurements of original middle outrigger hydraulic system are conducted, and an optimized system scheme applying high-frequency response proportional valve and accumulator is proposed. Then, the reasonable accumulator working parameters of optimized hydraulic system are explored, and the high-frequency response proportional valve control strategy based on feedforward compensation is studied. Finally, the optimized hydraulic system is simulated and compared with measurement data. The results show that the combination of high-frequency response proportional valve and accumulator can significantly improve the response characteristics and position control accuracy of hydraulic system. The hydraulic cylinder displacement of optimized system is increased by 82.2% within 0.5 s of system startup, and the maximum hoisting positioning error is ±2.0 mm, which can meet the erection and installation requirements of utility tunnels.

For the nut connection problems of narrow and deep cavity, invisibility, no access to traditional operating tools of aero-engine rotor, a new automation assembly method is advocated based on the image recognition and laser assisted positioning technology. The automated blind assembly torque device is developed with the functions of automatic folding of wrench head, accurate positioning, rapid nut recognizing, and electric loading, which can enter the narrow and deep operation space that is invisible to naked eye, to solve the low-level errors caused by artificial missing and wrong nuts, avoiding collision and damage on the inner wall of the shaft cavity. The device can carry out the compound tightening strategy with torque and angle to achieve the accurate automatic connection of engine rotor nut all the time, and the %GageR&R and %P/T of system precision are %22.21, %3.78 respectively through the test of automatic blind nut assembly, which will increase the accuracy and consistency on the large degree, which will lay the important foundation of the working stability and reliability of aero-engine farther.

The paper introduces mechanical character of boom for luffing jib crane, structural form and construction type of the inverted-Y boom are explained. A conversion section is arranged in the middle of the boom, the hoisting or luffing wire rope enters the boom head after bypassing the conversion section, the load of the boom is reduced by the pull of the wire rope. The example of derrick crane with maximum rated lifting capacity of 500 t is given, calculation of the boom shaft pressure, boom dead weight bending moment, wire rope tension and other loads on the boom chord of the magnitude of the axial force exerted, and analyze its proportion. It shows that the effect of hoisting or luffing wire rope can effectively reduce the dead weight bending moment of the boom, and offset part of the boom chord and belly rod axial force, improve the overall stability and bearing capacity of the boom, thus the design of the boom is optimized.

In order to improve the operating efficiency of excavator hydraulic system, a pump-driven valve-controlled load sensing system was designed. Pressure sensors are installed at the inlet and outlet of the multi-way valve respectively to perform real-time pressure feedback instead of the pressure compensation valve of the load sensitive system to achieve pressure compensation, and dynamically adjust the position of the main valve core and the swash plate swing angle of the electro-hydraulic proportional pump to drive the action of the hydraulic cylinder. The valve-controlled cylinder system in the pump drive valve control system is analyzed theoretically and the mathematical model is established. The experimental platform is designed with proportional valve test bench, BODAS controller and other electronic control and acquisition components, and the principle test of pump drive valve control is carried out, which verifies the correctness of the simulation model and pump drive valve control principle. The results show that when the system is in the pump drive valve control program, the output flow rate changes abruptly with the load change of step rise under different pressure differences. With the continuous increase of load pressure, the flow mutation becomes larger and larger, and the error between the output flow and the set flow also increases.

In shield construction, the tunneling attitude of the shield tunnel is an important parameter affecting the quality of the tunneling, which directly affects the track and the quality of the tunnel. Taking an earth pressure balance tunnel boring machine (TBM) as an example, the relationship between the weight of the main machine and the earth pressure and the bearing capacity of the foundation is determined from the theoretical level at the design of the shield machine, which is based on the analysis of the floating and sinking. The influence of the uneven mass distribution on the center of gravity is further analyzed. Finally, through the comprehensive study of the relationship between the force of the host and the thrust of the cylinder under the soil pressure model, the necessary conditions for the control of the driving attitude of the shield machine are determined. The results of this paper have important practical siginificance for improving the design and manufacturing of the shield machine and the construction level of the shield method in China.

To solve automated guided vehicle (AGV) dispatching problem in situations such as mutual interference between the operating equipment and transportation network complexity makes loading and unloading system more complicated. The changes of quay and yard crane operation sequence and operational efficiency, and the uncertainty of AGV operating time. Thus a shared online AGV dispatching strategy combining shared dispatching and online dispatching is introduced to solve AGV dispatching problem. A mathematical model is proposed to describe AGV dispatching problem. AGA is introduced to solve this problem. Experiment with different AGV amounts shows the validity of the proposed method. With a strong reference meaning to AGV dispatching decision making.

A monitoring system for transportation of material ropeway of transmission line is designed for the difficulty in fully understanding the construction process and component stress state of material ropeway of transmission line. Based on wireless ad hoc network technology, tension sensors, high-precision positioning modules, and ad hoc network devices are integrated to achieve real-time collection and transmission of monitoring data for material ropeway transportation, such as tension of carrying rope, load of steering pulley, load of running car, position of running car, speed of material transportation. By combining the refined calculation method of material ropeway, the tension of the working rope during the transportation process of the material ropeway is calculated, which is compared with the monitoring data, and the visual display of the monitoring data and image data of the material ropeway transportation is achieved to realize the real-time monitoring of the material ropeway transportation status during the construction process. Through verification tests in transmission line engineering, the effectiveness and accuracy of the monitoring system for transportation of material ropeway of transmission line have been verified, which provides technical support for the transportation safety during the construction of the material ropeway.

Aiming at the vibration response of vehicle-mounted precision equipment in a motorized environment, a new type of combined vibration isolator based on spring and rubber structure is proposed under the constraints of known equipment characteristics and vibration isolation performance requirements, and then a three-dimensional vibration isolation system of the vehicle-mounted precision equipment is designed by connecting the vibration isolators in parallel. In this paper, a three-dimensional model of the vibration isolation system is established, and the vibration isolation performance of the system in transverse, longitudinal and vertical directions is analyzed based on ABAQUS, and the three-direction rms acceleration attenuation rates are 0.82, 0.94, 0.93, respectively; meanwhile, the random vibration test results show that the three-direction rms acceleration attenuation rates are 0.88, 0.75, 0.87, respectively, which is within 10% of the simulation result, verifying that the three-direction rms acceleration attenuation rates are within 10% of the simulation results. are within 10%, which verifies the accuracy of the simulation results and meets the demand for vibration reduction of vehicle-mounted precision equipment.

In order to monitor the thermal expansion, dynamic effects and vibration of pipelines during thermal function tests in nuclear power plants, displacement sensors need to be installed on high-energy pipes and equipment. The sensor bracket is the most critical structure and bearing unit of the monitoring system, and the feasibility study has always been a hot issue. The temporary support designed and made of C-shaped steel (that is, the domestic alternative product of the famous American pipeline system support brand unistrut steel) is not only structurally firm, but also the support rooting method will not damage the infrastructure of the plant. The mechanical characteristics and functional principles of the temporary support are studied by theoretical analysis and numerical simulation, and the maximum deflection of the support rod under the tensile (compressive) working load and the failure conditions of the support are analyzed. The critical condition and the limit value of the bearing capacity of the temporary support reaching the steady state are obtained, and the above theory combined with numerical simulation is applied to engineering practice.

The fuel consumption meter measurement method and bench test are generally used to analyze the economy and power performance of vehicles, but the two measurement methods have high costs and complex structures. In response to this problem, back propagation (BP) neural network and regression model were selected to calculate and predict the economy and power performance of explosion-proof rubber tire vehicle diesel engines. Through comparison with experiments, the accuracy of BP neural network and regression model prediction was studied. The results show that the error between BP neural network and regression model is less than 5% when predicting fuel consumption rate and evaluating power performance, and both can be used to predict the economy and power performance of rubber tire vehicles.

Lightweight design is an effective way to improve the economic and environmental protection of static pile driver, as the key component of the static pile driver, the combined fixture is important for its lightweight design. To realize the combined fixture structure safety and lightweight design goal, a three-dimensional model is established by using solid works, and ANSYS Workbench is used to analyze and evaluate the equivalent stress of the whole structure and main components under the condition of pile pressing. Based on the results of analysis and evaluation, the topology optimization method of superposition replacement is adopted to carry out the structural optimization design, while meeting the needs of safety and engineering practice, its total quality is reduced by about 30%, and the economic and environmental benefits are obvious.

Aiming at the problem of motor failure caused by complex factors interacting and interfering during the operation of pure electric mining trucks, a method based on principal component analysis (PCA) and random forest (RF) is proposed for predictive diagnosis. A dataset is constructed based on the actual collected motor failures of electric mining trucks, and the eigenvalue extraction and dimensionality reduction of the failure data are carried out using principal component analysis to reduce the dimensional redundancy of the data; the random forest prediction model is used to train and test the dimensionality-reduced data, and to predict the motor failure categories. The results show that the accuracy of motor fault type diagnosis using PCA-RF method reaches more than 97%, which is significantly improved compared with the accuracy of the method without dimensionality reduction processing. The accuracy of the above method for motor fault diagnosis of electric mining trucks is confirmed.

In order to solve the problems of insufficient monitoring strength, poor interaction and low digitization degree during the operation of mobile crane, the construction method of digital twin system for real-time monitoring of crane operation status was proposed. A five-dimensional digital twin model is introduced to establish a digital twin framework for virtual and real control of cranes. Build a physical space from the service scene and physical entity; Establish virtual space from virtual model and visual scene and action control. Based on MySQL database, the twin database is constructed by using inherent, collected and virtual information. Virtual and real interaction, dynamic monitoring and visualization are realized in combination with communication protocols. Taking YDC20/30 light and small mobile crane as an example, the feasibility of this method is verified, and a new scheme is provided for comprehensively controlling the service process of the crane.

Based on the stress model of excavator working device, a pin dynamic load test method considering eccentric load and side load of excavator working device is proposed. According to the stress characteristics of the pin shaft at the articulated hole between the bucket and the stick, a pin shaft load test sensor is designed to measure the dynamic load in the horizontal, vertical and lateral directions at the articulated point, and measure the displacement of the three oil cylinders of the excavator at the same time. A dynamic test system for the pin load of the excavator working device was established. Taking the domestic 50 t excavator as the prototype and the stonework as the working material, the excavation simulation loading test was carried out. The results show that the proposed pin load test method can accurately obtain the three-dimensional dynamic load of the pin at the joint of the bucket and the bucket. The maximum load occurs in the excavation section. The lateral load is negligible compared with the normal load. The results of the study provide the basis for the structural load spectrum test and fatigue optimization design of excavator.

In order to explore the effects of maintenance difficulty degree of component on the maintenance cost and availability of the model. Taking a mechanical component of electric multiple unit (EMU) as the research object, and a component reliability threshold as the decision variable, the two-parameter Weibull distribution is adopted to describe the evolution law of component failure rate, combined with the existing fixed period multi-level imperfect maintenance rule of EMU in China, a preventive maintenance strategy for single component of EMU with bi-objective optimization is established. Bi-level imperfect maintenance is implemented in the maintenance mode and the concept of efficiency-cost ratio is introduced to discriminate the selection of each maintenance method of the component. Considering four factors, the difficulty of detecting parts, the location of parts, the difficulty of disassembling parts and the complexity of parts. Analytic hierarchy process (AHP) is adopted to quantify the maintenance difficulty degree and to study impact on the cost and availability of maintenance. The analysis shows that the maintenance model considering the maintenance difficulty can effectively reduce the maintenance cost and improve the availability, which provides a theoretical reference for the development of the maintenance strategy of EMU.

It is also necessary to consider the impact damage, the loosening of components and the vibration of the structure caused by the impact load factors in the study of the vibration state of the equipment. In this paper, an impact load identification algorithm based on half cosine function is designed. The proper interval is determined by genetic algorithm, and the dimensions of beams, thin plates and trusses are determined by data method. The numerical simulation results show that the error of SCFF fitting method is lower than that of Tikhonov and Chebyshev orthogonal polynomial fitting (COPF), and the SCFF recognition advantage is more obvious with the increase of noise. The peak error of less than 10% is obtained, and the minimum value is reached under the parameter optimization, which indicates that the parameter optimization has good applicability. The test results show that the low-frequency vibration state of the cantilever beam caused by the impact load is inferred by analyzing the spectrum data of the response signal, and the correction of the model by the first four modes meets the feasibility requirements. When the SCFF method is used for identification, it can form a good agreement with the actual load and obtain a smaller peak error.

In order to solve the problems of incomplete balance equation, inaccurate balance equation and large error of cam contour caused by the influence of piston deflection on cam dynamic moment in existing cam construction of pedal brake unit, the structure of pedal brake cam and output force stability were studied. Firstly, the concept of optimum compensation angle is introduced, and the rotating moment of the thrust caused by piston deflection in two directions to the cam articulation point is included in the new balance equation, which makes the balance equation more complete, accurate and has less error. Based on this, a new cam mechanism is designed and constructed. Then, on the pedal brake unit routine tester, a comparative experiment is carried out on the stability of output force value between the original cam mechanism and the newly constructed cam mechanism with optimized compensation angle. Finally, the above data and the curves of action travel and output force are comprehensively compared and analyzed. The results show that the output force value stability of cam with compensation angle is better than that of cam without compensation angle. In actual operating stroke, the maximum difference of output force between two times is (-0.8, +0.6) kN with compensation angle cam error, and (-1.2, +1.2) kN without compensation angle cam error. The error with compensation angle cam is also less than that without compensation angle cam error.

In the railway container yard, there are few mature intelligent anti-lifting solutions available for train flatbed loading and unloading operations due to the poor detection accuracy or speed of traditional detection methods. This paper proposes a fast anti-lifting detection method for trains based on an improved back propagation (BP) neural network. By acquiring weight data from the four locks of the hoist, a flatbed lifting detection model is established using a BP neural network. During weight adjustment, a momentum factor and an adaptive learning rate are incorporated to optimize the model's performance. Through practical tests, this method demonstrates that this model achieves a high detection rate and fast detection speed, making it suitable for providing intelligent safety protection for automated rail mounted gantry in the railway container yard.

With the wide application of target detection technology in unmanned construction and other scenarios, traditional target detection algorithms face challenges such as low recognition accuracy, large computational volume, and slow processing speed in complex engineering environments. Based on these challenges, this paper proposes a target detection method based on improved YOLOv8 for engineering scenes, which improves the C2f structure by introducing the star block in YOLOv8, significantly reducing the number of model parameters and computational volume while ensuring the detection accuracy. Based on this, this paper introduces a lightweight shared and detail-enhanced convolutional detection head, which further improves the detail-capturing ability of the detection head and significantly reduces the computational burden. The experimental results show that compared with YOLOv8n on Roboflow-based engineering scene dataset, the mAP@0.5 and mAP@0.5: 0.95 of the improved model improves by 0.3% and 2.0%, while the number of parameters and computational volume decreases by 36.7% and 34.6%, and improves the frames per second (FPS) by 23.3% accordingly, which verifies the superiority of the improved algorithm in terms of lightweight and detection accuracy.

In order to explore the factors influencing the slip rate between tracked combine harvester and paddy soil, a coupled simulation model of tracked combine harvester and paddy soil is established by the RecurDyn software. Selecting the mass, driving speed, steering angular speed of the tracked combine harvester and the moisture content, positive slope, and oblique slope of the paddy soil as test factors, simulations under different conditions are implemented. Through a six-factor two-level PB (Plackett-Burman) test was conducted to screen out the slip rate significant factors that is soil moisture content, positive slope, and steering angle velocity. Then, a three-factor three-level BB (Box-Behnken) test was conducted on the three selected factors. The results show that soil moisture content, positive slope, and steering angle velocity have a very significant impact on slip rate, and the order of significance is steering angle velocity>soil moisture content>positive slope. As the positive slope and steering angle velocity increase, the slip rate increases significantly, while as the soil moisture content increases, the slip rate slowly decreases. The soil moisture content has a certain interaction with the positive slope and steering angular velocity. However, there is basically no interaction between positive slope and steering angular velocity. This study has important reference value and scientific significance for improving the path tracking accuracy and stability of tracked combine harvester for autonomous harvesting operation in paddy soil.