Search Results (34)

In the process of operating subsoiling implements on sloping red soil in Southwest China, the subsoiler tip faces significant challenges due to strong soil adhesion and severe compaction. By employing engineering bionics, integrating bionic geometric structures and surfaces, this study focuses on the subsoiler tip and designs four types of bionic geometric surface structures: bionic convex hull, bionic micro-spike convex hull, bionic scales, and bionic micro-spike scales. Finite element force analysis and discrete element simulation experiments reveal that bionic surfaces and geometric structures exhibit significant advantages in terms of total deformation, equivalent elastic strain, and stress. These structures are less prone to deformation and fracture under loads, demonstrating a stronger bearing capacity. A discrete element simulation analysis indicates interference phenomena among the subsoilers during multi-subsoiler operations. Based on bionic multi-subsoiler implements, optimized designs were developed through discrete element simulations and soil bin tests. The optimized bionic multi-subsoiler implement features a micro-spike convex hull surface, with micro-spike scale surfaces arranged equidistantly along the edge corners of the shovel face: six on each side wing and three in the middle. The optimal operating parameters were a subsoiling speed of 1.25 m/s, an entry angle of 23.917°, and an entry depth of 280.167 mm. The relative errors between the simulated and experimental values for the soil looseness and soil disturbance coefficients were 19.7% and 18.1%, respectively. The soil bin test results showed soil looseness and soil disturbance coefficients of 19.5% and 17.6%, respectively. At this point, the resistance reduction and wear resistance performance were optimal. This study proposes a bionic design approach for reducing resistance and enhancing wear resistance during the subsoiling process in the viscous red soil of Southwest China, providing a reference for the design and development of new equipment for working in this soil environment. This study is the first to implement a composite biomimetic surface—combining crayfish-like micro-spike convex hulls and sandfish-like micro-scale scales—on multi-shank subsoiler tips, and to validate it using FEA, DEM, and soil tank testing. Under an optimized configuration and operating conditions, the mean particle disturbance velocity increased from 1.52 m/s to 2.399 m/s (+57.8%), and the simulation/experiment relative errors for the soil loosening and disturbance coefficients were approximately 1.03% and 2.84%, respectively. These results demonstrate an engineering-acceptable trade-off between disturbance efficiency and wear resistance and indicate a clear potential for industrial application. Full article

In the V-cycle of distributed electric wheel loaders (DEWLs), transport accounts for about 70% of the cycle, making energy saving urgent, while shovel-stage slip limits traction stability. This paper proposes a two-module control framework: (i) a preferred-motor transport strategy that reduces parasitic losses and concentrates operation in high-efficiency regions; and (ii) a load-ratio-based front–rear torque distribution for shoveling that allocates tractive effort according to instantaneous axle vertical loads so that each axle’s torque respects its available adhesion. For observability, we deploy a pre-calibrated lookup-table (LUT) mapping from bucket cylinder pressure to the front-axle load ratio, derived offline from a back-propagation neural network (BP-NN) fit. Tests on a newly developed DEWL show that, compared with dual-motor fixed-ratio control, transport-stage mechanical and electrical power drop by 18–37%, and drive-system efficiency rises by 6–13%. During shoveling, the strategy reduces the peak inter-axle slip from 22–35% to 13–15% and lowers the mean slip to 2.6–5.9%, suppressing sawtooth-like wheel-speed oscillations without sacrificing peak capacity. The method reduces parasitic energy flow, improves traction utilization, and is readily deployable. Full article

During the working process of the wheel loader, the repeated cycle of the shoveling and unloading process will produce an impact, so the loader is under a cyclic load for a long time, which leads to the frequent failure of its main parts. In this study, a new way of compiling the load spectrum of the loader’s working device and its application in fatigue life prediction is proposed. Through experimental data collection and preprocessing, the force of the cylinder block and hinge contact is corrected by mapping and inertia, which accurately reflects the actual force of the loader. The whole life cycle load spectrum is compiled by using the rainflow counting method and the extrapolation coefficient, and the test efficiency is optimized with the low-amplitude load omission method. By combining finite element analysis with material S-N curves using nCode DesignLife (version 11.1) and ANSYS Workbench frameworks (version 2024 R2), this research accurately predicts the fatigue life of the loader’s working unit and identifies key failure areas. The prediction results are consistent with the actual feedback data, and the accuracy of the method is verified. Full article

In open-pit mines, substantial amounts of dust are generated at various stages. Due to the long duration, repeated mechanical disturbance, and large volume of material handled during the shoveling and loading of blasting piles, this stage is recognized as one of the primary contributors to overall dust emissions in open-pit mining operations. The objective of this study is to investigate the spatial dispersion characteristics of dust at blasting piles and evaluate the influence of wind direction on dust migration and escape behavior. This study uses a full-scale numerical model to analyze the airflow and dust migration characteristics at blasting piles under different wind directions. Simulation results show that dust particles of different sizes exhibit distinct dispersion patterns: large particles settle near the source, medium particles migrate a moderate distance, and fine particles (PM2.5 and PM10) travel further and are more likely to escape from the pit. The leeward slope and pit bottom are identified as critical zones of dust accumulation and escape. Under both dump-side and stope-side wind conditions, respirable dust (d < 5 μm) accounts for more than 50% of the escaped particles, posing potential health risks to workers. These findings establish a scientific basis for targeted dust suppression strategies, supporting safer and more sustainable mine site management. Full article

The digging mechanism is the component of garlic harvesters that consumes the most energy. Consequently, there are theoretical gaps in the design of resistance reduction. These gaps are due to the complexity of the interaction dynamics between the shovel and the soil, and the insufficient understanding of the evolution patterns of soil damage. To address these challenges, this study develops a finite element model of the shovel–soil system using damage mechanics to characterize nonlinear interaction mechanisms under operational loading conditions. The methodology integrates three critical phases: (1) soil damage evolution analysis was employed to identify key damage parameters for model calibration; (2) systematic finite element simulations were used to evaluate the effects of system variables—entry angle, shovel blade bevel angle, forward speed, and vibration frequency—on forward resistance; (3) orthogonal experimental optimization of these parameters was carried out. Key results include the following: (i) A nonlinear relationship was identified between variables (entry angle, forward speed, and vibration frequency) and resistance reduction. Furthermore, the threshold for optimal performance was determined. The optimal parameters were identified as an entry angle of 20°, a forward speed of 0.39 m/s, and a frequency of 2.6 Hz. (ii) Validation through soil bin experiments, demonstrating strong agreement between simulated and measured load–displacement responses, confirming the predictive accuracy of the model. The research presented in this paper may offer insights into the principles of low-resistance designs for underground fruit harvesting. Full article

During the mining process of open-pit mines, multiple operations are prone to generating dust, especially during the blasting, where a significant amount of dust is raised and subsequently deposited on the surface of the blast pile. The impact of the blasting force further saturates the interior of the pile with dust. Subject to the combined effects of natural wind and shoveling operations, this dust is re-suspended and disseminated throughout the mine pit, posing a significant threat to the safe operation of the mine and the health of workers. This study comprehensively utilizes field testing and numerical simulations to delve into the migration characteristics of blast pile dust under the combined influence of wind and shoveling operations. Attention is paid to the effects of different wind speeds, wind directions, and shoveling operations on the distribution and migration trajectory of blast pile dust. The research results indicate that the movement of dust is primarily controlled by wind flow, determining its ultimate migration path and diffusion range. This study not only provides a significant theoretical foundation for precise prevention and control of dust pollution in open-pit mines but also has vital practical significance for enhancing the safety of mine operating environments and safeguarding the physical and mental health of workers. Full article

Research on electric wheel loaders (EWLs) has predominantly focused on battery management, hybrid technologies, and energy recovery. However, the influence of motor types and drivetrains on the drive performance of EWLs has received little attention in previous studies. This case study addresses this gap by examining different EWL configurations and analyzing the drive theory and force requirements by integrating classic vehicle theory with EWL-specific characteristics. The study compares an original EWL, equipped with Permanent Magnet Synchronous Motors (PMSMs) on both the front and rear axles with identical transmission ratios of 22.85, to a modified EWL, which features a Switched Reluctance Motor (SRM) on the front axle and a transmission ratio of 44.05. Walking and shoveling tests were conducted to evaluate performance. The walking test results reveal that, at motor speeds of 200 rpm, 400 rpm, and 600 rpm, energy consumption in R-drive mode is 68.56%, 71.88%, and 74.87% of that in F-drive mode when two PMSMs are used. When an SRM is applied with a transmission ratio of 44.05, these values shift to 73.90%, 70.35%, and 67.72%, respectively. This demonstrates that using the rear motor alone for driving under walking conditions can yield greater energy savings. The shoveling test results indicate that distributing torque according to wheel load reduces rear wheel slippage, and the SRM with a transmission ratio of 44.05 delivers sufficient drive force while operating within a high-efficiency speed range for the EWL. Full article

This paper aims to investigate the effects of soil penetration resistance, tillage depth, and operating speeds on the deformation and fatigue of the subsoiling shovel based on the real-time measurement of tractor-operating conditions data. Various types of sensors, such as force, displacement, and angle, were integrated. The software and hardware architectures of the monitoring system were designed to develop a field operation condition parameter monitoring system, which can measure the tractor’s traction force of the lower tie-bar, the real-time speed, the latitude and longitude, tillage depth, and the strain of the subsoiling shovel and other condition parameters in real-time. The time domain extrapolation method was used to process the measured data to obtain the load spectrum. The linear damage accumulation theory was used to calculate the load damage of the subsoiling shovel. The magnitude of the damage value was used to characterize the severity of the operation. The signal acquisition test and typical parameter test were conducted for the monitoring system, and the test results showed that the reliability and accuracy of the monitoring system met the requirements. The subsoiling operation test of the system was carried out, which mainly included two kinds of soil penetration resistances (1750 kPa and 2750 kPa), three kinds of tillage depth (250 mm, 300 mm, and 350 mm), and three kinds of operation speed (4 km/h low speed, 6 km/h medium speed, and 8 km/h high speed), totaling 18 kinds of test conditions. Eventually, the effects of changes in working condition parameters of the subsoiling operation on the overall damage of subsoiling shovels and the differences in damage occurring between the front and rear rows of subsoiling shovels under the same test conditions were analyzed. The test results show that under the same soil penetration resistance, the overall damage sustained by the subsoiling shovels increases regardless of the increase in the tillage depth or operating speed. In particular, the increase in the tillage depth increased the severity of subsoiling shovel damage by 19.73%, which was higher than the 17.48% increase due to soil penetration resistance and the 13.07% increase due to the operating speed. It should be noted that the front subsoiling shovels consistently sustained more damage than the rear, and the difference was able to reach 16.86%. This paper may provide useful information for subsoiling operations, i.e., the operational efficiency and the damage level of subsoiling shovels should be considered. Full article

To address the problem of incomplete perception of limited viewpoints of ore blocks in future remote and intelligent shoveling-dominated mining scenarios, a method of using new view generation technology to predict ore blocks with limited view based on a latent diffusion model is proposed. Initially, an ore block image-pose dataset is created. Then, based on prior knowledge, the latent diffusion model undergoes transfer learning to develop an intelligent ore block shape prediction model (IOBSPM) for rock blocks. During training, structural similarity loss is innovatively introduced to constrain the prediction results and solve the issue of discontinuity in generated images. Finally, neural surface reconstruction is performed using the generated multi-view images of rock blocks to obtain a 3D model. Experimental results show that the prediction model, trained on the rock block dataset, produces better morphological and detail generation compared to the original model, with single-view generation time within 5 s. The average PSNR, SSIM, and LPIPS values reach 23.02 dB, 0.754, and 0.268, respectively. The generated views also demonstrate good performance in 3D reconstruction, highlighting significant implications for future research on remote and autonomous shoveling. Full article

The development of the open-pit mining industry has set higher performance standards for mining electric shovels. Addressing issues such as low efficiency, high energy consumption, and high failure rates in working mining electric shovel devices, this paper comprehensively considers bulk mechanics, structural mechanics, and dynamics to conduct a multidisciplinary, collaborative design optimization for electric shovels by introducing the BLISCO method, which is based on an approximated model, into the structural-optimization design process of working electric shovel devices, aiming to enhance the overall performance of electric shovels. Firstly, a dynamic model of an electric shovel is established to analyze the hoist force and crowd force during the excavation process, and an accurate load input for the dynamic analysis is provided through the bulk material mechanics model. Additionally, to ensure that the stiffness of the boom meets the requirements, the maximum stress at the most critical position of the optimized boom is considered. Subsequently, the design variables are screened through experimental design, and an approximate model is established. Focusing on the hoist force, crowd force, maximum stress at the critical position of the boom, and the angle between the dipper arm and the wire rope, a mathematical model is constructed and optimized using a two-level integrated system co-optimization framework based on an approximate model (BLISCO-AM), followed by a simulation. Finally, a test bench for the electric shovel working device is constructed to compare pre- and post-optimization performance. Experimental results show that through the optimized design, the hoist force and crowd force required in a single excavation process are reduced by 6% and 8.48%, respectively, and the maximum angle between the wire rope and the dipper arm is increased by 4%, significantly improving excavation efficiency while ensuring the safety and reliability of the equipment. Full article

The semantic segmentation of the 3D operating environment represents the key to intelligent mining shovels’ autonomous digging and loading operation. However, the complexity of the operating environment of intelligent mining shovels presents challenges, including the variety of scene targets and the uneven number of samples. This results in low accuracy of 3D semantic segmentation and reduces the autonomous operation accuracy of the intelligent mine shovels. To solve these issues, this paper proposes a 3D point cloud semantic segmentation network based on memory enhancement and lightweight attention mechanisms. This model addresses the challenges of an uneven number of sampled scene targets, insufficient extraction of key features to reduce the semantic segmentation accuracy, and an insufficient lightweight level of the model to reduce deployment capability. Firstly, we investigate the memory enhancement learning mechanism, establishing a memory module for key semantic features of the targets. Furthermore, we address the issue of forgetting non-dominant target point cloud features caused by the unbalanced number of samples and enhance the semantic segmentation accuracy. Subsequently, the channel attention mechanism is studied. An attention module based on the statistical characteristics of the channel is established. The adequacy of the expression of the key features is improved by adjusting the weights of the features. This is done in order to improve the accuracy of semantic segmentation further. Finally, the lightweight mechanism is studied by adopting the deep separable convolution instead of conventional convolution to reduce the number of model parameters. Experiments demonstrate that the proposed method can improve the accuracy of semantic segmentation in the 3D scene and reduce the model’s complexity. Semantic segmentation accuracy is improved by 7.15% on average compared with the experimental control methods, which contributes to the improvement of autonomous operation accuracy and safety of intelligent mining shovels. Full article

The loader is one of the most widely used pieces of engineering machinery in the world for soil transportation, loading and unloading materials, and low-intensity shovel digging operations in harsh and complex operating conditions; it requires very frequent shifting and has other challenging characteristics. In order to realize automatic frequent shifting, we need to better design the shifting rules in the shifting process, improve the shifting quality and working efficiency, and solve the key engineering problems of energy saving and high efficiency in the shifting process of loaders. In this paper, a 7-ton wheel loader is taken as the research object, the loader shoveling process of the four operating modes is analyzed, and a multi-mode variable parameter shift law is designed. Aiming at the complicated and nonlinear characteristics of the power transmission system of the loader, an intelligent shift control method based on an RBF neural network is proposed. Finally, the simulation test and the clutch shift oil pressure test are carried out. From the test results, the clutch test oil pressure curve obviously shows a four-stage upward trend during shifting, and the buffering effect is obvious. The designed multi-mode variable-parameter intelligent shift law of the loader is reasonable and feasible, and the shift recognition rate reaches 97.92%, which provides theoretical support for the realization of intelligent automatic speed change control of the loader, and it certainly has engineering value. Full article

During the operation of a wheel loader, the external load acting on the bucket undergoes many changes, resulting in significant changes in the load ratio on the front and rear axles. For this reason, controlling a standard wheel loader is not trivial. In addition, in the case of a distributed electric wheel loader (DEWL), the operating control algorithm is often complex and is, therefore, the subject of optimization studies. This study compared the electric power consumption across different vertical loads, speeds, and travel directions for single-front, single-rear, and dual-motor configurations, both during transporting and pre-shoveling operations. The analysis led to the development of control rules based on energy-saving objectives. Under the shoveling condition, it was observed that vertical loads can lead to an insufficient driving force and skidding, necessitating the proposal of a new optimized control scheme. The results revealed that the optimal solution for transporting is the single-motor drive control scheme without a mechanical connection between the front and rear motor. With the single-motor control scheme, comparing the preferred controlled motor with the unselected motor under different loads, the average electrical power savings for forward, backward, and circling were at least 3.51%, 3.12%, and 0.34%, respectively. Under the pre-shoveling condition, the optimal control scheme was identified as the single rear motor control scheme, effectively reducing electrical power consumption. In response to the issues encountered during the shoveling condition, an economical solution involving the modification of the front axle transmission ratio has been proposed, along with an optimized control scheme based on vertical load variations. Full article

The electric wheel loader is a new prototype in powertrains and drivetrains that saves energy consumption and diminishes emissions as earthmoving machinery. Dual-motor drive in the front and rear axles of electric wheel loaders helps the distribution of drive torque. However, challenges arise during shoveling conditions, particularly when one motor generates torque exceeding the ground’s adhesion force, leading to tire slippage. This study thoroughly examines the mechanical structure of the working unit and elucidates the correlation between wheel load and hydraulic pressure in the base chamber of the tilt cylinder. This analysis is accomplished through a combination of theoretical derivations and experimental tests. The experiments involve a 5 ton rated load electric wheel loader tested across five running cases as well as weighing tests on a 15 ton rated load electric wheel loader. Based on the experiment discoveries, a dual-motor drive electric wheel loader is designed with specific transmission ratios for the front and rear drivetrains, and a torque distribution strategy is proposed based on wheel load during shoveling. Running condition tests demonstrate sufficient drive force for the new electric wheel loader, and shoveling tests reveal a significant reduction in tire slippage when employing the proposed torque distribution strategy compared to evenly distributed torque in the front and rear axles. Moreover, the driving force during the shoveling process remains undiminished. This indicates that the newly designed loader, in conjunction with the proposed strategy, exhibits excellent shoveling efficiency. Full article

The rational structural design of polycrystalline diamond compact (PDC) cutters effectively enhances the performance of drill bits in rock fragmentation and extends their service life. Inspired by bionics, a bionic PDC cutter was designed, taking the mole claw toe, shark tooth, and microscopic biomaterial structures as the bionic prototypes. To verify its rock-breaking effectiveness, the finite element method was employed to compare the rock-breaking processes of the bionic cutter, triangular prism cutter, and axe cutter. The study also investigated the influence of different back rake angles, cutting depths, arc radii, and hydrostatic pressures on rock breaking using the bionic cutter. Prior to this, the accuracy of the finite element model was validated through laboratory tests. Subsequently, a drill bit incorporating all three types of cutters was constructed, and simulations of rock breaking were conducted on a full-sized drill bit. The results demonstrate that the bionic cutter exhibits superior load concentration on the rock compared to the triangular prism cutter and the axe cutter. Additionally, its arc structure facilitates the “shoveling” of the rock, making it more susceptible to breakage under tensile stress. As a result, the efficiency of the bionic cutter surpasses that of the triangular prism and axe cutters. Similarly, it exhibits minimal fluctuations and values in cutting force. As the back rake angle and cutting depth increase, the MSE and cutting force of all three cutters also increase. However, the bionic cutter consistently maintains the lowest MSE and cutting force, confirming the superiority of its bionic structural design. The MSE and cutting force of the bionic cutter fluctuate with the increase of the arc radius, and the optimal arc radius falls within the simulation range, between 21 mm and 23 mm. Compared to the other two types of cutters, bionic cutters possess a unique structure that allows for better release of internal stress within the rock, thereby ensuring higher efficiency in rock-breaking, particularly in deep geological formations. The rock breaking simulation results of full-sized drill bits show that the use of a bionic cutter can improve the drill bit’s ability to penetrate the formation, reduce the possibility of drill bit bounce during the rock breaking process, prevent the occurrence of stick-slip, improve the drilling stability, effectively improve the efficiency and service life of the drill bit during the rock breaking process, and reduce the drilling cost. It is concluded that the research results of bionic PDC cutters are helpful to the development of high-performance drill bits and the reduction of drilling costs. Full article