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.

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 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.

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 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.

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.

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.

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.

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 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.