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关键词： Shield construction parameters   Multisource information   Intelligent prediction   Scenario optimization   SHAP   BO-CatBoost-NSGA-III   GROUND SURFACE SETTLEMENT   TBM   ENERGY   ROCK   PRESSURE   MODEL  

摘要： In this paper, a hybrid intelligent framework comprising Bayesian optimization (BO), gradient boosting with categorical features (CatBoost) and the nondominated sorting genetic algorithm-III (NSGA-III) was proposed to support multiobjective optimization of shield construction parameters without large sample datasets, improve the shield performance, and ensure reliable and interpretable results. First, with the use of the specific tunneling energy, advancing speed and cutter wear as objective functions, a BO-CatBoost prediction model for shield construction parameters and various objectives was constructed, and the key influencing factors were identified via the SHapley Additive exPlanations (SHAP) method. Then, a BO-CatBoost-NSGA-III model was developed to obtain Pareto solutions under different scenarios involving the adjustment of the key influencing factors. Finally, adopting the Wuhan Metro as the background, the accuracy, stability, and generalizability of the constructed algorithm were verified. The results indicated that (1) the developed BO-CatBoost algorithm is superior to 9 other algorithms. The R-2 values of the proposed approach were 0.976 and 0.901-0.976 on the test set. (2) The developed BO-CatBoost-NSGA-III algorithm could be used to obtain Pareto solutions under different scenarios via the adjustment of the key influencing factors with the SHAP method, and the optimal solutions could facilitate improvements in the advancing speed, specific tunneling energy and cutter wear of 3.45 %, 6.09 %, and 0.52 %, respectively, with an overall average reliability of 90.5 %. (3) By comparing various prediction algorithms, optimization schemes of different objectives and geological conditions, the accuracy, stability, and generalizability of the constructed algorithm were verified. The developed BO-CatBoost-NSGA-III framework could enable dynamic adjustment of shield construction parameters for decision-making purposes in the event of conflicting shield constructi

关键词： TBM main bearing   Dynamic modeling   Local fault   Vibration response   Uneven load   LOAD-CARRYING CAPACITY   ROLLING-ELEMENT BEARINGS   ROLLER SLEWING BEARINGS   COMPUTATIONAL MODEL  

摘要： As the key component of TBM main driving system, the main bearing plays an indispensable role both in its service life and the normal operation of the TBM. While prior investigations predominantly focused on static analyses of the main bearing, only a scant few delved into its dynamic characteristics and the vibration mechanism. In order to explore the dynamic characteristics of TBM main bearing, a comprehensive dynamics model of the TBM main bearing considering local defects is established, the vibration mechanism of the main bearing with local defects is revealed, and the influence of uneven load is investigated. Furthermore, the effects of roller wear and bearing clearance on the vibration response of the main bearing are analyzed, which systematically describes the real motion of the main bearing. Finally, a main bearing scaling test rig is constructed, and the proposed model is validated through experiments and simulations, demonstrating its good accuracy. In addition, the results show that the incremental imposition of uneven load correlated with a rising trend in the root mean square (RMS) value of vibration response. Moreover, maintaining an optimal axial clearance is pivotal in ensuring the reliable operation of the main bearing. The research work in this paper provides theoretical scaffolding for the defect diagnosis of TBM main bearing, whilst also serves as an analytical cornerstone for future explorations into the dynamics of various types of thrust bearings.

关键词： 电动拖拉机   底盘   轻量化   结构优化  

摘要： 探讨了电动拖拉机底盘轻量化设计的方法和技术,并基于底盘轻量化的重要性论述了底盘轻量化的具体方法,包括选材、结构优化、工艺改进等方面。针对电动拖拉机的工作特点,提出了适合其底盘轻量化的具体措施,包括采用高强度轻质材料、减少焊接点及优化桥座结构等。最后,通过数值模拟和试验验证了轻量化设计的效果,证明了方法的可行性和有效性。研究成果对于提高电动拖拉机的性能和节能减排具有重要意义。

关键词： Tunnel boring machine   Disc cutter   Vibration   Loading characteristic   Rock fragmentation   DYNAMIC CHARACTERISTICS   SYSTEM   SCALE   MODEL  

摘要： The intense vibration of the TBM (Tunnel Boring Machine) cutter is an important factor leading to the failure of parts. Understanding the mechanism of vibration of the cutter has been a research hotspot in the field of TBM equipment. Clarifying the characteristics and the interaction mechanism of vibration of the cutter under the combined effect of various factors is a key entry point to solving this problem. In this study, experiments on rock breaking were carried out in the laboratory, and the cutting forces and acceleration of vibration of the cutters under different working conditions were measured, practical factors such as the thrust and the rotational speed of the cutterhead, and the cross-section of the cutter were considered. The experimental data showed that both feed parameters and cutter profiles influence cutter vibration. For a certain cutter profile, the vibration is fundamentally dependent on the volume of rock broken per unit of time, and the more the rock is broken, the more intensely elastic strain energy is stored and released. The cutterhead thrust can affect the depth of the cutter penetration into the rock, thus affecting the rock breaking volume, while the rotational speed of the cutterhead independently affects the rock breaking volume by changing the distance advanced per unit time. The simulation data showed that the shape of the outer profile affects the contact area between the cutter and the rock. varying with different cutter profiles, and the vibration intensity of different cutter profiles varies under the same operating conditions due to the frictional contact between the cutter and the rock chips after the rock breaking, resulting in the dissipation of energy and the reduction of the vibration intensity of the cutter. The elucidation of this mechanism will help provide scientific guidance for rapid estimation of the severity of cutter vibration in engineering applications and to explore new methods of reducing cutter vibration.

关键词： 拖拉机   悬挂系统   动力学分析   模型验证  

摘要： 拖拉机作为一种重要的农业运输工具,可在田间与不同农业机械配合完成相关农艺操作过程。目前,农机具主要以悬挂的形式与拖拉机连接,但在进行田间试验中会发生底盘倾覆问题,故改善拖拉机底盘的动态性能对于提高拖拉机稳定性具有重要意义。针对以上问题,提出了一种拖拉机底盘前悬机架模型用于设计拖拉机底盘防倾覆悬架,并建立了拖拉机液压前悬架平面内动力学的验证模型,对拖拉机底盘倾覆进行分析。通过数值模拟与田间试验相结合的方法进行模型验证与分析,结果表明:构建的拖拉机底盘前悬架模型能够准确地模拟高、中负荷配置下的拖拉机真实模拟系统行为。研究结果可为拖拉机底盘的优化设计提供参数借鉴与理论依据。

关键词： 拖拉机   发动机故障诊断   数据挖掘技术   机器学习   特征选择  

摘要： 拖拉机是农业生产的重要工具,发动机是其核心部件,如发动机出现故障,将会直接影响农业生产效率和产量。为此,提出了一种使用数据挖掘技术进行拖拉机发动机故障诊断的方法。利用了机器学习技术和统计学,首先针对拖拉机田间运行信号噪音较大的问题,引入小波阈值去噪的方法;其次,基于卷积神经网络模型,引入一种注意力机制,提高故障诊断准确率,并通过对拖拉机传感器数据进行分析,可以帮助诊断和预测发动机故障;最后,通过实验结果验证了算法的有效性。研究结果不仅可以提高故障的准确性和效率,还能够节约维修成本和提高机器的利用率,具有较高的应用价值。

关键词： 拖拉机   电气故障诊断   LabVIEW   数据采集   模块化设计  

摘要： 设计了一种基于LabVIEW的拖拉机电气故障诊断系统,其采用模块化设计,可以自动检测和诊断拖拉机的电气故障,并提供可视化的诊断结果。系统由数据采集模块、信号处理模块、故障诊断模块和用户界面模块组成。数据采集模块负责采集拖拉机各个部件的电气参数数据,信号处理模块对采集到的数据进行处理和分析,故障诊断模块通过分析处理后的数据来判断拖拉机是否存在故障,并给出相应的诊断结果,用户界面模块提供友好的交互界面。试验结果表明:系统可以准确地诊断拖拉机的电气故障,具有良好的应用前景和推广价值。

关键词： 电动拖拉机   驱动电机系统   故障诊断   准确率   PSO-BP优化算法  

摘要： 驱动电机系统的故障可能导致电动拖拉机失控或发生意外情况,从而危及驾驶员和周围环境的安全,准确诊断故障可以帮助驾驶员及时采取措施,避免潜在的危险。为了进一步提高电动拖拉机驱动电机系统的故障诊断准确率,基于驱动电机系统的数据特征及故障类型,以BP人工神经网络模型为基础,通过PSO-BP优化后的人工神经网络模型构建电动拖拉机电机驱动电机系统故障诊断模型,并对传统BP神经网络模型的阈值和权重进行优化,以更快地收敛到全局最优解。通过采集驱动电机系统的数据,对基于PSO-BP故障诊断模型进行试验验证,结果表明:模型对5种故障状态诊断准确率较高,特别是退磁故障和IGBT故障这两种复杂的故障类型。研究内容能够为电动拖拉机驱动电机系统的故障诊断提供一种有效的方法和技术支持,可提高诊断准确率、保障驾驶员和周围环境的安全,提高了工作效率,降低了维修成本。

关键词： Tunnel boring machine   Rock cutting force   Disc cutter   Synergistic effect   Discrete element method  

摘要： The prediction of rock cutting force is critical for tunnel boring machine performance and cutterhead design. This paper presents a novel model for rock cutting force prediction based on the Colorado School of Mines (CSM) model, which incorporates the installation position of disc cutters by introducing installation radius and synergistic effect factors. Linear cutting tests in the laboratory and large-scale rotary cutting simulations in MatDEM software were conducted to examine the impact of these factors. Results indicate that the normal and rolling forces increase and stabilize as the installation radius increases. The synergistic effect produces three force modes in a cutting circle, with mode α having the largest cutting force, mode β having a smaller force, and mode γ having the smallest force. The impact of installation radius and synergistic effect varies with rock-cutter parameters. Multiple regression analysis was used to determine the introduced factors. The proposed model was validated with rock strength and operation data from the Irtysh River conveyance project. The results demonstrate that the proposed model outperforms the CSM model in predicting cutting force in field conditions.

关键词： 水力测功器   轴承故障诊断   转速跟踪   卷积神经网络(CNN)  

摘要： 高速、重载的复杂环境中,易导致水力测功器轴承故障多发,为准确诊断其轴承故障状态的问题,提出了一种基于转速跟踪处理和卷积神经网络(CNN)的水力测功器轴承故障诊断方法。首先,对振动数据进行转速跟踪预处理,以解决变转速情况下的特征提取问题;然后,对预处理后的信号进行快速傅里叶变化提取故障频谱特征,以频域信号生成汉克矩阵,并将其作为模型的原始特征输入训练卷积神经网络故障诊断模型;最后,采用训练好的轴承故障诊断模型实现水力测功器轴承故障在线诊断。仿真结果表明,所提出的基于转速跟踪处理和卷积神经网络的水力测功器模型是可行和有效的,并具有较好的泛化能力,能够准确、有效地诊断轴承的故障状态。