In the intersection scenario, the running state of social vehicles, the control state of traffic lights and the accurate identification of track components have become the technical bottlenecks restricting the promotion and application of track inspection robots. Aiming at the requirements of track health inspection, firstly, the vision inspection system of the track inspection robot and the technical scheme of the navigation system was presented based on “Beidou +5G”. Secondly, the vision detection system model was built based on YOLOv8 algorithm, and the web crawler technology was innovatively used to capture sample data about traffic lights and car taillights from open source video resources to train the vision detection model. Then, transfer learning method and early stop method were used to optimize the detection accuracy of the trained model. The research results show that after adopting YOLOv8 algorithm and optimizing the model with transfer learning method and early stop method, the inspection robot can effectively detect the track components, vehicles and traffic lights at the switch junction, and effectively improve the inspection efficiency and accuracy.

The complex nonlinear characteristics and dynamic friction properties of the integrated brake-by-wire system were recognized as challenges for precise hydraulic pressure control. To address these issues, a precise hydraulic force control strategy was proposed for the integrated brake-by-wire system. Firstly, the structure and control framework of the integrated brake-by-wire system were analyzed, and equivalent simplified models were established for each component to facilitate controller design. Secondly, a three-layer cascade pressure control method was introduced for active braking in the integrated brake-by-wire system. Specifically, the pressure control layer was designed based on the active disturbance rejection control method, which mitigates the effects of hysteresis nonlinearity in the hydraulic system. The position control layer employs a robust sliding mode variable structure control method and addresses the dynamic and static friction issues in the transmission mechanism. The current control layer was designed using the linear matrix inequality method to enhance the braking motor's dynamic following performance. Joint simulation tests using AMESim-Simulink demonstrate that the integrated brake-by-wire system achieves good pressure control performance across various operating conditions, maintaining the steady-state pressure tracking error within 0.1 MPa, compared to the traditional proportion-integration(PI) control method, the mean transient pressure tracking error is reduced by 0.14 MPa using the proposed method, the mean steady-state pressure tracking error decreases by 0.8 MPa, and the response lag time is lowered by 0.04 s, which verifies the effectiveness of the control strategy proposed.

Buried pipeline is an important part of oil and gas transportation. The subsidence of gob area will cause the corresponding subsidence of the pipeline passing through the gob area, resulting in pipeline deformation, fracture and other accidents. Taking Puxian-Hejin pipeline crossing coal mining subsidence area as the research background, 3D printing technology was used to make up for the mismatch in mechanical similarity between pipeline simulation materials and geotechnical simulation materials, and the coupling simulation experiment between pipeline and rock and soil was constructed. The mining response of buried pipeline caused by coal mining was analyzed, and the correlation between pipeline movement deformation and stratum movement deformation was established. The research shows that the buried pipeline and the underlying rock strata do not synchronously settlement, resulting in delamination between the overlying rock strata and the underlying rock strata. The pipeline bends and deforms under the overlying rock load and its own weight. When the delamination span is large enough, the bending tensile stress on the bottom of the pipeline exceeds the allowable stress, resulting in tensile failure. The subsidence value of the buried pipeline is about 1.21 times of the formation subsidence value, and only 18% of the horizontal deformation of the formation is transmitted to the pipeline. The research results have guiding significance for the safe laying and daily maintenance of pipelines in subsidence area.

To address the current situation of low flatness, poor cutting quality and cane bud damage at the cane cutter due to insufficient optimization of the structure and motion parameters and installation coordination of the cutting tool of the cane seed cutter. Finite element cutting simulation tests were conducted using single-factor tests on the distance between the cutting edge and the pivot point of the transport roller, tool drop speed, tool installation offset angle, tool front angle and tool back angle of the cane seed cutter to determine the evaluation indexes affecting the cane seed cutting quality and the trend of the influence of each factor on this index. The significant interaction effect of each factor on the evaluation index was analyzed based on the rotating orthogonal test, and the quadratic polynomial regression model of the orthogonal test results was obtained. Combining the agronomic requirements with the cutting characteristics of the tool, the optimal evaluation index was established, the optimized optimal combination of parameters was obtained, and the cutting section simulation test and bench validation test were conducted. The final selection results are as follows: the distance between the incision and the fulcrum is 177.944 mm, the tool landing speed is 1.569 m/s, the tool installation offset angle is 5.923°, the tool front angle is 10.899°, and the tool back angle is 8.637°. The equivalent stress at the incision site and the sugarcane shoot site are 5.053 mm and 1.592 MPa, respectively. The comprehensive analysis error rate is 4.97%. This study can provide a research basis for the optimization of the structure parameters and installation parameters of sugarcane seed cutting knife and its motion parameters, so as to improve the seed cutting quality of cane.

The terrain in western Sichuan is complex and varied, and the geological structure is active, which makes the construction and maintenance of the traffic trunk line face the challenge of frequent geological disasters. Ensemble learning algorithm can optimize the shortcomings of the algorithm in geological hazard susceptibility assessment and improve the accuracy of the model, which has significant advantages in geological hazard susceptibility assessment. Taking the riverside high-speed as an example, 12 feature variables such as slope and relief were selected to construct the geological hazard susceptibility evaluation system. The forecasting performance of the modeling of the integrated algorithm and a single algorithm was compared and analyzed. The main control factors of the geological disasters along the riverside high-speed were discussed and the practicability of the model was verified. The results show that the proportion of high and extremely high geological hazard prone areas along the Yangtze River high speed is 18.21% and 9.85%, respectively, which are concentrated in the Leibo section and Jinyang section. The area under curve (AUC) of the receiver operating characteristics (ROC) curve and the precision-recall (P-R) curve in the integrated model. The AUC of ROC curve (0.84~0.86), the AUC of P-R curve (0.81~0.85) and the F₁ score (0.78~0.79) of the three single machine learning models are significantly higher, and the prediction performance is better than that of a single machine learning algorithm. The development of high-speed geological hazards along the Yangtze River is controlled by topographic and geomorphic factors. The new damage points are located in the highly prone areas of the model, which verifies the accuracy and reliability of the Stacking model.

In order to address the supply-demand imbalance in the increasingly complex and changing market environment, improving the accuracy of air cargo volume forecasting is of great significance for route planning and supply chain optimization. Firstly, based on monthly air cargo data from January 2000 to December 2022 as the training set, seasonal fluctuations and long-term trends were captured using seasonal and trend decomposition using loess (STL). Secondly, a deep learning time series prediction model (LSTM-SVR) was used to fit the nonlinear changes in cargo volume due to emergencies. Finally, the prediction model was tested based on monthly data for the entire year of 2023. The results indicate that the seasonal and combination prediction model (STL-SVR-LSTM) is more accurate in predicting air cargo volume during emergencies compared to traditional methods such as ARIMA, SVR, or LSTM. The data validation in 2023 shows that the root mean square error and average absolute percentage error of the seasonal and combination prediction models are 3.53 and 3.53%, respectively, with a goodness of fit score of 0.79. The LSTM model has the second best prediction results, with root mean square error and average absolute percentage error of 5.66 and 7.73%, respectively, and a goodness of fit score of 0.58, significantly better than the other two traditional models. It can be seen that this prediction model can adapt to the prediction of air cargo volume in complex environments, which is helpful in providing reference suggestions for enterprise operation and enhancing supply chain stability in case of emergencies.

In order to investigate the vortex characteristics and wave propulsion generated by the undulating pectoral fins of the flatworm, a simplified model of the flatworm's pectoral fin was re-established using the linear interpolation method in MATLAB. The relationship between thrust and kinetic energy, during the flatworm's swimming was derived, and the undulating posture of the flatworm was simulated using Fluent software. The results show that compared to similar MPF propulsion fish species such as rays and cownose rays, the flatworm, due to its narrow and elongated body structure, exhibits better stability, adaptability, and flexibility in water. When the Reynolds number is set to 1.05×10⁵, the pectoral fins of the flatworm demonstrates more stable thrust, effectively reducing flow separation and turbulence effects. At a frequency of 0.6 Hz and a wavelength of 2.5 m, the pectoral fins displays optimal undulating parameters, enhancing fluid mixing and energy transfer efficiency, thereby improving the flatworm's propulsion performance. It is concluded that, during the mid-phase of an undulation cycle, the pressure distribution on the pectoral fins changes significantly, with the lift efficiency being highest at the peak of the undulation.

Aiming at the problem that it is difficult to directly use external heat sink to dissipate heat for high-power electronic devices with short-time operation in external insulation condition, the phase-change material with low melting point and high volume enthalpy value was adopted to optimize the design of energy storage structure and realize temperature control for electronic devices. Firstly, based on the constraints of electronic device volume, weight, external environment, thermal power, working time, etc., combined with the thermal performance of phase change materials, an integrated design of heat dissipation structure was carried out. Secondly, according to the characteristics of phase change material(PCM), an equivalent specific heat capacity thermal analysis method based on temperature feedback was proposed. Finally, the thermal conductivity of three PCM including paraffin, carbon composite and liquid metal, was analyzed by numerical simulation, and the heat dissipation performance of the three PCM in specificenergy-storage structures was evaluated by using heat source temperature rise and temperature equalization as indicators, and an optimal phase-change energy-storage structure of the electronic devices was determined. The results show that the PCM can significantly control the temperature rise in a certain period of time, which meets the temperature control requirements of electronic devices in small volume and external adiabatic environment. The volume enthalpy of PCM represents the energy storage capacity per unit volume of PCM. The higher the volume enthalpy, the smaller the volume of PCM required. Liquid metal can obtain better thermal properties because of its large enthalpy and high thermal conductivity.

The non-lethal electric shock weapon is a research hotspot in the field of non-lethal weapons. In recent years, the research on wireless long-range electric shock bullets has become a key issue within this field. Therefore, aiming at the design of non-lethal long-range low-velocity electric shock bullet empennage, three airfoils of Clark Y, Eppler 387 and NACA-66 with good aerodynamic characteristics at low velocity were selected. The simulation results of NACA0012 airfoil at 30 m/s using CFD software were compared with the literature simulation results and wind tunnel test results to verify the algorithm's effectiveness. Subsequently, the aerodynamic characteristics of the three airfoils at low velocity were simulated, and the lift coefficient, drag coefficient and lift-drag ratio corresponding to different angles of attack at 30, 35 and 40 m/s were obtained respectively. The results show that at the same flight velocity, the lift coefficient and drag coefficient of the three airfoils gradually increase with the increase of the angle of attack, but the growth rate of the lift coefficient gradually decreases, and the growth rate of the drag coefficient gradually increases. The lift-to-drag ratio increases first and then decreases with the increase of the angle of attack. After comparison, it is found that the aerodynamic performance of the airfoil Eppler 387 is better than that of the other two airfoils. The velocity of 40 m/s and the angle of attack between 4° and 6° are the best working conditions, which can not only meet the structural design requirements of non-lethal long-range low-velocity electric shock bullets, but also produce less drag while providing as much rolling moment as possible.

When a large number of containers arrive at a node during coal intermodal transportation, it can lead to problems such as container congestion and transfer delays during the transshipment process. Based on this, the criteria importance through intercrieria correlation (CRITIC) objective weighting method was adopted to quantify the risk of transfer delay in coal rail-road intermodal transportation, and then the risk was incorporated into the path optimization factors. Meanwhile, the improved activity-share-intensity-factor (ASIF) equation was introduced to measure the carbon emissions of transportation and transshipment node exchange processes. A carbon emission and transfer delay risk model for the entire freight transportation time was established. Based on the above model, a coal rail-road intermodal transportation path optimization model was proposed, with the objectives of minimizing carbon emissions, transportation costs, transportation time, and transfer delay risk. Through a case study, MATLAB programming was introduced, and the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) algorithm was designed to solve the example. The optimization results under different transportation decision conditions were simulated, respectively. By comparing the single-objective optimization results of minimum carbon emissions, minimum transportation costs, shortest transportation time, and minimum transfer delay risk with the multi-objective optimization results that comprehensively consider the above objectives, the advantages of multi-objective optimization in handling low-carbon path optimization for coal rail-road intermodal transportation were explored. The research results show that compared with single-objective optimization, the multi-objective optimization scheme can effectively reduce transportation costs, shorten transportation time, reduce comprehensive energy consumption, and lower the risk of transfer delay, achieving a comprehensive optimal combination of economy and safety in coal rail-road intermodal transportation. At the same time, it also provides a certain reference for the path optimization of rail-road intermodal transportation under different transportation demands and scenarios.