Journal of Terramechanics最新文献_第2页

The benefit of using access materials for soil stress reduction depends on the material’s properties and vehicle mean ground pressure 使用通道材料减少土壤应力的好处取决于材料的性质和车辆的平均地面压力

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-10-10 DOI: 10.1016/j.jterra.2025.101097

Loraine ten Damme , Matthias Stettler , Renato P. de Lima , Thomas Keller

Construction activities can induce soil compaction due the use of heavy vehicles and repeated vehicle passes. Driving on access material reduces the risk of compaction, but data on soil stress reduction are lacking. This study investigated the effect of three access materials (0.5 m thick sand track, 0.3 m thick timber mattresses, and 0.1 m thick composite mats) on soil stress, relative to driving on unprotected soil. Mean normal stress was measured at 0.2 and 0.4 m soil depths for tracked and tyred construction vehicles (bulldozer, excavator, dump truck, and tractor-trailer). We used finite element modelling to investigate the effect of material’s thickness and stiffness on soil stress reduction. Measurements revealed that driving on access material reduced soil stress by 21–77 % and 0–60 % at 0.2 and 0.4 m depths, respectively. Stress reduction increased with increasing mean ground pressure and was larger for tyred than for tracked vehicles. The tested access materials reached a comparable effect, but simulations indicated that additional stress reduction could be achieved by increasing the stiffness or thickness of the material. Thus, more rigid or thicker material achieve greater soil stress reductions. These characteristics should be balanced against costs, transport, and ease of handling of the material.

由于重型车辆的使用和车辆的反复通行，施工活动会引起土壤压实。在通道材料上行驶减少了压实的风险，但是缺乏关于土壤应力减少的数据。研究了三种通道材料（0.5 m厚沙道、0.3 m厚木垫和0.1 m厚复合垫）对无防护土壤行驶时土壤应力的影响。测量履带式和轮式施工车辆（推土机、挖掘机、自卸车和牵引车-拖车）在0.2 m和0.4 m土壤深度的平均正常应力。采用有限元模型研究了材料厚度和刚度对土体应力减小的影响。测量结果显示，在0.2 m和0.4 m深度，对通道材料的驱动分别降低了21 - 77%和0 - 60%的土壤应力。应力减小量随着平均地压力的增加而增加，轮胎车辆的应力减小量大于履带车辆。测试的接触材料达到了类似的效果，但模拟表明，可以通过增加材料的刚度或厚度来实现额外的应力降低。因此，更硬或更厚的材料实现更大的土壤应力降低。这些特性应与成本、运输和材料处理的便利性相平衡。

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引用次数: 0

Real-time terrain classification for all-wheel drive robotic electric tractors using multi-sensor fusion and machine learning 基于多传感器融合和机器学习的全轮驱动机器人电动拖拉机实时地形分类

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-10-10 DOI: 10.1016/j.jterra.2025.101098

Tamiru Tesfaye Gemechu , Jun Zhou , Guoliang Lai , Ibrar Ahmad , Luke Toroitch Rottok , Yade Li , Tabinda Naz Syed , Muhammad Aurangzaib

Accurate terrain classification is essential for the effective and efficient operation of autonomous robots and off-road vehicles. This study proposes a novel multi-sensor fusion technique for off-road terrain classification using a robotic platform that matches the practical features of an electric tractor. The method employs proprioceptive signals from the vehicle body and all four wheels, including wheel torque, wheel speed, wheel slippage, and vibration. A high-speed counter was programmed using the STEP 7 Microwin environment and uploaded onto an S7-200 PLC to measure wheel torque and speed. An inertial measurement unit and a three-axis digital accelerometer were used to record vibrations from the vehicle body and wheel bracket, respectively. MATLAB Simulink was employed to synchronise sensors data. Signal pre-processing, segmentation, Savitzky-Golay filtering, feature-level fusion, and the Random Forest algorithm were incorporated into the developed terrain classification model. The proposed Random Forest-based model, validated using K-fold cross-validation, achieved up to 90% test accuracy. Performance on unseen labelled data demonstrated consistent classification accuracy between 80% and 90%, indicating strong generalisation across terrain types. Real-time testing with unseen and unlabelled data demonstrated the model’s robustness and stability, enabling reliable terrain prediction with minimal latency, suitable for real-world off-road autonomous vehicle applications.

准确的地形分类对于自主机器人和越野车辆的有效运行至关重要。本研究提出了一种新的多传感器融合技术，用于越野地形分类，该技术使用的机器人平台与电动拖拉机的实际特征相匹配。该方法利用来自车身和所有四个车轮的本体感受信号，包括车轮扭矩、车轮速度、车轮滑移和振动。使用STEP 7 Microwin环境编写高速计数器，并将其上传到S7-200 PLC上，用于测量车轮扭矩和转速。使用惯性测量单元和三轴数字加速度计分别记录来自车身和车轮支架的振动。采用MATLAB Simulink对传感器数据进行同步。将信号预处理、分割、Savitzky-Golay滤波、特征级融合和随机森林算法纳入到所开发的地形分类模型中。本文提出的基于随机森林的模型，使用K-fold交叉验证进行验证，达到了高达90%的测试准确率。在未见标记数据上的表现表明，分类准确率在80%到90%之间，表明在地形类型上具有很强的泛化性。使用未见过的和未标记的数据进行的实时测试表明，该模型具有鲁棒性和稳定性，能够以最小的延迟进行可靠的地形预测，适用于现实世界的越野自动驾驶汽车应用。

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引用次数: 0

Log detection for autonomous forwarding using auto-annotated data from a real-time virtual environment 使用来自实时虚拟环境的自动注释数据进行自主转发的日志检测

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-09-20 DOI: 10.1016/j.jterra.2025.101096

Mattias Lehto, Håkan Lideskog, Magnus Karlberg

Object detectors for autonomous forestry operations have previously been developed mainly by training on physical manually annotated data, which is both time-consuming and costly. Since the ground truth in the virtual model is known, the training data can be auto-annotated, enabling the creation of larger training datasets, while also improving time and cost efficiency. In this work, a virtual environment in Unity is used in co-simulation with a real-time digital twin of a physical forestry vehicle, to generate realistic auto-annotated training data, as captured by an onboard stereo camera. First, it is shown that a log detector trained on physical data can detect logs in the virtual environment. Second, new detectors are trained, using different shares of virtual and physical data. It is shown that a detector trained using only virtual data, can learn to detect logs in the physical world. Moreover, virtual pre-training is shown to improve the performance of physically trained and tested detectors, both at low availability of physical training data, and in terms of domain generalization. A detailed detector performance analysis also highlights further potential and opportunities for future improvements. Furthermore, the real-time capable virtual models enable future machine learning tasks utilizing different levels of Hardware-in-the-Loop.

以前，用于自主林业作业的目标探测器主要是通过对物理手动注释数据进行训练来开发的，这既耗时又昂贵。由于虚拟模型中的真实情况是已知的，因此可以对训练数据进行自动注释，从而可以创建更大的训练数据集，同时还可以提高时间和成本效率。在这项工作中，Unity中的虚拟环境用于与物理林业车辆的实时数字双胞胎共同模拟，以生成逼真的自动注释训练数据，由车载立体摄像机捕获。首先，证明了在物理数据上训练的日志检测器可以检测虚拟环境中的日志。其次，使用虚拟和物理数据的不同份额来训练新的检测器。结果表明，仅使用虚拟数据训练的检测器可以学习检测物理世界中的日志。此外，虚拟预训练可以提高物理训练和测试检测器的性能，无论是在物理训练数据可用性较低的情况下，还是在领域泛化方面。详细的检测器性能分析还强调了未来改进的进一步潜力和机会。此外，具有实时功能的虚拟模型可以利用不同级别的硬件在环实现未来的机器学习任务。

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引用次数: 0

Study on the adhesion law of rubber-soil interface under the influence of multiple factors 多因素影响下橡胶-土界面黏附规律研究

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-09-06 DOI: 10.1016/j.jterra.2025.101095

Mingyang Yuan , Ze Zhang , Hang Li , Zhiyuan Wang , Xiangxi Meng

Soil adhesion is one of the basic physical properties of soil, which is manifested as the ability of soil to adhere to foreign objects. Soil adhesion can cause additional energy consumption in mechanical operations in agriculture, engineering, transportation and other fields, which is an important scientific problem to be studied and solved urgently. In this paper, three kinds of rubber tires with different surface roughness were used as test materials, and soil samples from six regions were selected as test soil samples. The adhesion force of rubber-soil interface under different normal loads was tested, and the variation law of soil peak adhesion force and the peak moisture content to reach peak adhesion force under the combined action of various influencing factors were analyzed and discussed. The mechanism of peak moisture content change under load was proposed. The test results show that the adhesion force of the rubber-soil interface increases with the increase of surface roughness, normal load and clay content. This experiment further promoted the study of soil adhesion and helped to solve the energy consumption problem caused by soil adhesion in the transportation field.

土壤附着力是土壤的基本物理性质之一，表现为土壤对外来物的粘附能力。在农业、工程、交通等领域的机械作业中，土壤黏附会造成额外的能源消耗，是一个亟待研究和解决的重要科学问题。本文以3种不同表面粗糙度的橡胶轮胎作为试验材料，选取6个地区的土样作为试验土样。测试了橡胶-土界面在不同法向载荷作用下的附着力，分析探讨了各种影响因素共同作用下，土壤峰值附着力和达到峰值附着力的峰值含水率的变化规律。提出了荷载作用下峰值含水率变化的机理。试验结果表明：橡胶-土界面的附着力随表面粗糙度、法向载荷和粘粒含量的增加而增大；本实验进一步推动了土壤附着力的研究，有助于解决运输领域土壤附着力带来的能源消耗问题。

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引用次数: 0

The bevameter technique – Its developments and a proposed framework for its recommended practice 测径仪技术。其发展及其推荐实践的建议框架

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-09-02 DOI: 10.1016/j.jterra.2025.101086

J.Y. Wong

This paper provides a concise comparison of the features and applications between the cone penetrometer technique and the bevameter technique. The developments of the bevameter technique since its inception in the 1960s are reviewed. Its roles in characterizing terrain engineering properties for evaluating off-road vehicle mobility are highlighted. A framework for the recommended practice for the bevameter technique is proposed for the consideration of the professional community in the terramechanics field.

本文简要比较了圆锥贯深仪技术和波径仪技术的特点和应用。回顾了自20世纪60年代测井仪技术问世以来的发展。强调了其在表征地形工程特性和评价越野车辆机动性方面的作用。提出了一种建议实施的框架，以供地质力学领域的专业团体考虑。

引用次数: 0

A vehicle dynamics-oriented estimator for soft soil/tyre contact parameters from experimental testing 一种基于车辆动力学的软土/轮胎试验接触参数估计方法

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-09-02 DOI: 10.1016/j.jterra.2025.101087

Luca Zerbato , Angelo Domenico Vella , Enrico Galvagno , Alessandro Vigliani , Silvio Carlo Data , Matteo Eugenio Sacchi

Modelling the interaction between tyres and unconsolidated soft surfaces has assumed a crucial role in predicting off-road vehicle performance in different machine areas such as planetary exploration and agriculture. The direct measurement of the soft soil/tyre contact parameters is a challenging task, addressed by expensive experimental campaigns and specific tools such as sensor-equipped wheels. In this paper an alternative cost-effective approach is proposed to estimate the contact parameters for semi-empirical formulations. The method relies on the experimental measurement typically available on the CAN bus of passenger vehicles. Specifically, the algorithm is tested with data gathered during acceleration manoeuvres performed on two different soft surfaces, i.e., snow and sand. The experimental signals are used to feed a 5 Degree Of Freedom (DOF) virtual vehicle equipped with a custom semi-empirical soil contact model. An optimisation problem with the target of minimising the differences between experimental and numerical traction performance is designed for the estimation of the sinkage module, cohesion, friction angle, elastic recovery and the multi-pass factor. Finally, the estimated parameters are validated using different experimental signals and data from literature, demonstrating the robustness of the methodology.

轮胎与松散软表面之间相互作用的建模在预测不同机械领域（如行星探索和农业）的越野车辆性能方面起着至关重要的作用。软土/轮胎接触参数的直接测量是一项具有挑战性的任务，需要昂贵的实验活动和特定的工具，如配备传感器的车轮。本文提出了一种具有成本效益的替代方法来估计半经验公式的接触参数。该方法依赖于乘用车CAN总线上的典型实验测量。具体来说，该算法在两种不同的软表面（即雪和沙）上进行加速操作时收集的数据进行了测试。实验信号被用来馈送一个5自由度（DOF）的虚拟车辆，该虚拟车辆配备了定制的半经验土壤接触模型。设计了一个优化问题，以最小化实验和数值牵引性能之间的差异为目标，用于估计下沉模块，内聚，摩擦角，弹性恢复和多通道因子。最后，使用不同的实验信号和文献数据对估计参数进行验证，证明了方法的鲁棒性。

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引用次数: 0

Efficient flexible tire-terrain interaction modelling 高效灵活的轮胎-地形交互建模

IF 3.7 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-08-04 DOI: 10.1016/j.jterra.2025.101081

Mahdi Maleki , József Kövecses

The analysis of tire dynamics is essential in simulating vehicle behavior. The forces exerted on a tire depend on the interaction between the tire and the terrain at the contact patch, and the tire structure directly influences this interaction. Complex models, such as finite element or lumped-parameter models, are typically required to represent tire flexibility accurately. However, these models are computationally expensive, making them unsuitable for real-time simulation.

In this work, we develop a reduced model for flexible tire-terrain interaction. A reduced model is a lower-fidelity representation that captures essential features of a complex system at a significantly lower computational cost. Our model efficiently represents the influence of tire flexibility on vehicle dynamics by computing the effective stiffness of the tire and combining it with a rigid body wheel model.

We observe that the contact patch size, which depends on tire deformation, directly affects traction forces. A larger contact patch enables the generation of greater frictional force before slipping. In the proposed model, effective stiffness is used to determine the contact patch size, which then scales the friction coefficient accordingly.

Simulation results demonstrate efficient real-time performance with high accuracy, making the model well-suited for diverse vehicle simulation applications.

轮胎动力学分析是模拟车辆性能的基础。施加在轮胎上的力取决于轮胎与接触处地形的相互作用，而轮胎的结构直接影响这种相互作用。通常需要复杂的模型，如有限元或集总参数模型来准确地表示轮胎的灵活性。然而，这些模型的计算成本很高，不适合实时仿真。在这项工作中，我们开发了一个柔性轮胎-地形相互作用的简化模型。简化模型是一种较低保真度的表示，它以较低的计算成本捕获复杂系统的基本特征。该模型通过计算轮胎的有效刚度，并将其与刚体车轮模型相结合，有效地反映了轮胎柔性对车辆动力学的影响。我们观察到，接触片的大小直接影响牵引力，这取决于轮胎的变形。更大的接触片可以在滑动前产生更大的摩擦力。在该模型中，使用有效刚度来确定接触片的大小，然后相应地缩放摩擦系数。仿真结果表明，该模型实时性好，精度高，适合多种车辆仿真应用。

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引用次数: 0

Physics informed Gaussian process models for real-time simulation of tire terrain interactions for off- road conditions 物理告知高斯过程模型的实时仿真轮胎地形相互作用的越野条件

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-07-28 DOI: 10.1016/j.jterra.2025.101077

Suhas A. Kowshik, Andrew Fisseler, Arun R. Srinivasa, J.N. Reddy

We propose a Gaussian process machine learning model (GPM) for real-time simulation of tire-terrain interactions, especially under off-road conditions. Compared to purely empirical models or classical Neural Networks, the GPM requires much less input data for training, has greater ability to explain, and is able to quantify uncertainty in predictions. The model can seamlessly incorporate any combination of physics-based numerical simulations, empirical or semi-empirical models, and experimental data and produce real-time predictions of the interaction parameters (such as normal and shear forces, tire sinkage, etc.) along with uncertainty estimates on its predictions. The key idea is to use empirical models such as the steady-state Becker-Wong model as the baseline and “learn” the difference due to the dynamic response of the tire from detailed physics-based models or experimental data or any combination. We show that the result is able to make highly accurate predictions of the tire response in real-time. Such simplified models can be useful for training autonomous off-road vehicles under various conditions. They are also useful for virtual testing of different vehicle designs on different terrain.

我们提出了一个高斯过程机器学习模型（GPM），用于实时模拟轮胎与地形的相互作用，特别是在越野条件下。与纯粹的经验模型或经典神经网络相比，GPM需要更少的训练输入数据，具有更强的解释能力，并且能够量化预测中的不确定性。该模型可以无缝地结合基于物理的数值模拟，经验或半经验模型以及实验数据的任何组合，并产生相互作用参数的实时预测（如法向和剪切力，轮胎下沉等）以及对其预测的不确定性估计。关键思想是使用经验模型，如稳态Becker-Wong模型作为基线，并从详细的基于物理的模型或实验数据或任何组合中“学习”轮胎动态响应的差异。我们表明，该结果能够对轮胎的实时响应做出高度准确的预测。这种简化的模型可以用于训练各种条件下的自动越野车辆。它们还可用于在不同地形上对不同车辆设计进行虚拟测试。

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引用次数: 0

Calibration and validation of a discrete element model for sand and fine grain soil for use in vehicle mobility applications 用于车辆移动应用的砂和细颗粒土壤的离散元素模型的校准和验证

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-07-26 DOI: 10.1016/j.jterra.2025.101082

Tamer Wasfy , Omar Elmaraghi , Omkar Ghike , Ashwin Gaonkar , Hazim El-Mounayri , Paramsothy Jayakumar , Srinivas Sanikommu

In this paper, a procedure for calibrating a discrete element (DE) computational soil model for use in prediction of ground vehicle mobility is presented. The procedure relies on using the results of two small-scale physical soil experiments: (1) confined uniaxial compression; and (2) unconfined shear strength under different levels of normal stress and normal prestress. The confined uniaxial compression is an approximate hydrostatic compression test that is used to calibrate the DE bulk density, plastic strain, and elastic strain as a function of hydrostatic stress. The unconfined shear strength test is used to calibrate the DE inter-particle friction coefficient and adhesion stress as a function of the soil plastic strain. The test devices and experimental test procedures are presented in the paper. The DE model calibration procedure is demonstrated in the paper using two types of soils: silt–clay and sand-silt. The model is then validated by comparing its results for those two types of soil to experiment results for the following 3 tests: (1) confined shear strength test; (2) full-scale tracked vehicle drawbar-pull test; and (3) single tire drawbar-pull test. Within the middle of the slip range, the simulation results agree within ± 10 % on average with the experimental results for validation tests (2) and (3).

本文提出了一种用于预测地面车辆移动的离散元（DE）计算土壤模型的标定方法。该程序依赖于使用两个小规模物理土壤试验的结果：(1)受限单轴压缩；(2)不同正应力和正预应力水平下的无侧限抗剪强度。承压单轴压缩是一种近似的静水压缩试验，用于校准DE体密度、塑性应变和弹性应变作为静水应力的函数。无侧限抗剪强度试验用于标定DE颗粒间摩擦系数和黏附应力随土体塑性应变的函数关系。本文介绍了试验装置和试验过程。本文以粉质粘土和砂质粉土两种土壤为例，演示了DE模型的标定过程。通过将两种土的模型结果与试验结果进行对比，验证了模型的有效性：(1)约束抗剪强度试验；(2)全尺寸履带车辆拉拔试验；(3)单胎拉拔试验。在中间滑移范围内，仿真结果与验证试验(2)和(3)的实验结果平均吻合在±10%以内。

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引用次数: 0

A novel soil stress estimation method of wheel-soil interaction using photoelasticity 基于光弹性的轮-土相互作用土应力估算新方法

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2025-07-17 DOI: 10.1016/j.jterra.2025.101076

Kenji Nagaoka, Yuto Yoshida

This paper proposes a new approach to understanding the wheel-soil interaction, which is an indirect estimation method of soil stress distributions beneath a traveling wheel soil using a photoelastic method. Thus far, several photoelastic methods have been discussed for the wheel-soil terramechanics, but it is difficult for the previous configuration to simulate the dynamic behaviors of natural soil, e.g., compaction, failure, or wheel ruts. Accordingly, achieving both the stress visualization and the dynamic behaviors of soil is a significant challenge to make the photoelastic method more practical. To cope with this challenging issue, we have developed a novel experimental setup consisting of a photoelastic wheel (top layer), soil (middle layer), and a photoelastic plate (bottom layer). By vertically sandwiching the soil between the photoelastic wheel and plate, the soil stresses can be indirectly estimated to satisfy the boundary stress conditions. To achieve this approach, we conducted calibration tests of the photoelastic wheel and plate, and then identified the force vector and contact patch corresponding to the visualized stresses. In this paper, we demonstrate that it is possible to indirectly estimate how the stress propagates and attenuates in the soil by the proposed method.

本文提出了一种新的认识轮土相互作用的方法，即利用光弹性法间接估计轮下土体的应力分布。到目前为止，已经讨论了几种光弹性方法用于车轮-土壤的地形力学，但是以前的配置很难模拟自然土壤的动态行为，例如压实，破坏或车轮车辙。因此，实现应力可视化和土的动力特性是使光弹性方法更加实用的重要挑战。为了应对这一具有挑战性的问题，我们开发了一种新的实验装置，由光弹性轮（顶层），土壤（中间层）和光弹性板（底层）组成。通过将土垂直夹在光弹性轮和板之间，可以间接估计出满足边界应力条件的土应力。为了实现这一方法，我们对光弹性轮和板进行了标定试验，然后识别出与可视化应力相对应的力矢量和接触贴片。在本文中，我们证明了通过提出的方法间接估计应力如何在土壤中传播和衰减是可能的。

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引用次数: 0