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.

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.

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.

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.

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.

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.

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.

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.

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 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.