Search Results (18)

Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need for direct pressure or position sensors. A fuzzy logic-based proportional–derivative (PD) controller is developed to mitigate boom oscillations, particularly under high-inertia load conditions and variable operator inputs. The controller dynamically adjusts gains through fuzzy logic-based gain scheduling, enhancing adaptability across a wide range of operating conditions. The proposed method addresses the limitations of classical PID controllers, which struggle with the nonlinearities, parameter uncertainties, and instability introduced by counterbalance valves and pressure-compensated proportional valves. Experimental data is used to design fuzzy rules and membership functions, ensuring robust performance. Simulation and full-scale experimental validation demonstrate that the fuzzy PD controller significantly reduces pressure overshoot (by 23% during extension and 32% during retraction) and decreases settling time (by 31.23% and 28%, respectively) compared to conventional systems. Frequency-domain stability analysis confirms exponential stability and improved damping characteristics. The proposed control scheme enhances system reliability and safety, making it ideal for excavators operating in remote or rugged terrains where conventional sensor-based systems may fail. This approach is generalizable and does not require modifications to the existing hydraulic circuit, offering a practical and scalable solution for modern hydraulic machinery. Full article

The Gobi Wall is a 321 km-long structure made of earth, stone, and wood, located in the Gobi highland desert of Mongolia. It is the least understood section of the medieval wall system that extends from China into Mongolia. This study aims to determine its builders, purpose, and chronology. Additionally, we seek to better understand the ecological implications of constructing such an extensive system of walls, trenches, garrisons, and fortresses in the remote and harsh environment of the Gobi Desert. Our field expedition combined remote sensing, pedestrian surveys, and targeted excavations at key sites. The results indicate that the garrison walls and main long wall were primarily constructed using rammed earth, with wood and stone reinforcements. Excavations of garrisons uncovered evidence of long-term occupation, including artifacts spanning from 2nd c. BCE to 19th c. CE. According to our findings, the main construction and usage phase of the wall and its associated structures occurred throughout the Xi Xia dynasty (1038–1227 CE), a period characterized by advanced frontier defense systems and significant geopolitical shifts. This study challenges the perception of such structures as being purely defensive, revealing the Gobi Wall’s multifunctional role as an imperial tool for demarcating boundaries, managing populations and resources, and consolidating territorial control. Furthermore, our spatial and ecological analysis demonstrates that the distribution of local resources, such as water and wood, was critical in determining the route of the wall and the placement of associated garrisons and forts. Other geographic factors, including the location of mountain passes and the spread of sand dunes, were strategically utilized to enhance the effectiveness of the wall system. The results of this study reshape our understanding of medieval Inner Asian imperial infrastructure and its lasting impact on geopolitical landscapes. By integrating historical and archeological evidence with geographical analysis of the locations of garrisons and fortifications, we underscore the Xi Xia kingdom’s strategic emphasis on regulating trade, securing transportation routes, and monitoring frontier movement. Full article

The application of blasting in modern engineering construction is prized for its speed, efficiency, and cost-effectiveness. However, the resultant vibrations can have significant adverse effects on surrounding buildings and residents. The challenge of optimizing blasting procedures to satisfy excavation needs while minimizing vibration impacts is a critical concern in blasting excavation. This research addresses this challenge through the development of a 3D simulation and analysis model for an underground pumped storage power plant in East China, utilizing the LS-DYNA finite element analysis software. To explore the influence of charging structures on rock fragmentation and vibration propagation, three distinct blasting programs were formulated, each featuring varied configurations within the machinery room. The analysis revealed that the adoption of an optimized charging structure can significantly decrease damage to the protective layer by approximately 40%, while also reducing the impact on the upstream and downstream side walls by 27.25% and 12.03%, respectively, without compromising the efficacy of the main blast zone. Moreover, the vibration velocities at the remote measurement point were found to be reduced across multiple directions, indicating effective control of the vibration effects. The post-implementation of the optimized blasting strategy at the site, the assessment of the retained surrounding rock integrity, and the impact on protected structures demonstrated that the proposed solution met satisfactory outcomes. This study underscores the potential of simulation-based optimization in managing vibration risks during blasting operations, offering a valuable tool for engineers and practitioners in the field of underground construction. Full article

The construction industry is actively developing remote-controlled excavators to address labor shortages and improve work safety. However, visually induced motion sickness (VIMS) remains a concern in the remote operation of construction machinery. To predict the occurrence and severity of VIMS, we developed a prototype system that acquires multiple physiological signals with different mechanisms under a low burden and detects VIMS from the collected data. Signals during VIMS were recorded from nine healthy adult males operating excavator simulators equipped with multiple displays and a head-mounted display. Light gradient-boosting machine-based VIMS detection binary classification models were constructed using approximately 30,000 s of time-series data, comprising 23 features derived from the physiological signals. These models were validated using leave-one-out cross-validation on seven participants who experienced severe VIMS and evaluated through area under the curve (AUC) scores. The mean receiver operating characteristic curve AUC score was 0.84, and the mean precision–recall curve AUC score was 0.71. All features were incorporated into the models, with saccade frequency and skin conductance response identified as particularly important. These trends aligned with subjective assessments of VIMS severity. This study contributes to advancing the use of remote-controlled machinery by addressing a critical challenge to operator performance and safety. Full article

Remote operations have been greatly enhanced by advancements in technology, enabling remote control of machinery in hazardous environments. However, it is still a challenge to design remote control interfaces and provide feedback in a way that would enhance situational awareness without negatively affecting cognitive load. This study investigates how different audio feedback designs can support remote boom operation and, additionally, explores the potential impact of gamification elements on operator performance and motivation. Due to COVID-19 restrictions, this study was conducted remotely with 16 participants using a simulated environment featuring a virtual excavator. Participants performed digging tasks using two audio feedback designs: frequency-modulated beeping and realistic spatialized steam sounds. The findings indicate that both audio designs are beneficial for remote boom operations: the beeping sound was perceived as more comfortable and efficient in determining the proximity of a hidden object and helped in avoiding collisions, whereas spatial sounds enhanced the sense of presence. Therefore, we suggest combining both audio designs for optimal performance and emphasize the importance of customizable feedback in remote operations. This study also revealed that gamification elements could both positively and negatively affect performance and motivation, highlighting the need for careful design tailored to specific task requirements. Full article

AI-driven mineral prospectivity mapping (MPM) is a valid and increasingly accepted tool for delineating the targets of mineral exploration, but it suffers from noisy and unrepresentative input features. In this study, a set of fractal and multifractal methods, including box-counting calculation, concentration–area fractal modeling, and multifractal analyses, were employed to excavate the underlying nonlinear mineralization-related information from geological features. Based on these methods, multiple feature selection criteria, namely prediction–area plot, K-means clustering, information gain, chi-square, and the Pearson correlation coefficient, were jointly applied to rank the relative importance of ore-related features and their fractal representations, so as to choose the optimal input feature dataset readily used for training predictive AI models. The results indicate that fault density, the multifractal spectrum width (∆α) of the Yanshanian intrusions, information dimension (D₁) of magnetic anomalies, correlation dimension (D₂) of iron-oxide alteration, and the D₂ of argillic alteration serve as the most effective predictor features representative of the corresponding ore-controlling elements. The comparative results of the model assessment suggest that all the AI models trained by the fractal datasets outperform their counterparts trained by raw datasets, demonstrating a significant improvement in the predictive capability of fractal-trained AI models in terms of both classification accuracy and predictive efficiency. A Shapley additive explanation was employed to trace the contributions of these features and to explain the modeling results, which imply that fractal representations provide more discriminative and definitive feature values that enhance the cognitive capability of AI models trained by these data, thereby improving their predictive performance, especially for those indirect predictor features that show subtle correlations with mineralization in the raw dataset. In addition, fractal-trained models can benefit practical mineral exploration by outputting low-risk exploration targets that achieve higher capturing efficiency and by providing new mineralization clues extracted from remote sensing data. This study demonstrates that the fractal representations of geological features filtered by multi-criteria feature selection can provide a feasible and promising means of improving the predictive capability of AI-driven MPM. Full article

In tandem with the advancement of urban intelligent technology, the construction of remote monitoring platforms and databases for non-road mobile machinery is gradually improving in various provinces and cities. Employing the remote monitoring platform for non-road mobile machinery enables a detailed big data analysis of the actual operational state of the machinery. This method yields precise data on the activity levels of various machinery types. Importantly, it addresses the issue of reduced accuracy in emission inventories, which often arises from the conventional practice of using standard recommended values from the Guide to determine machinery activity levels during the compilation of non-road mobile machinery emission inventories. Based on the remote monitoring and management system of non-road mobile machinery, the actual value of the activity level of non-road mobile machinery was obtained, and the emission inventory of non-road mobile machinery in Shandong Province was established. The emission levels of PM, HC, NOx, and CO from main non-road mobile machinery, including forklifts, excavators, loaders, off-road trucks, and road rollers, were measured. The findings indicate that the operational activity levels of non-road mobile machinery in Shandong Province typically exceeded the guideline’s recommended values. Among them, the annual use time of port terminal ground handling equipment was the longest, with an average annual working time of 4321.5 h per equipment, more than six times the recommended value. Among all types of non-road mobile machinery, loader emissions accounted for the highest proportion, reaching 43.13% of the total emissions of various pollutants. With the tightening of the national standard for non-road mobile machinery from Stage II to Stage III, a significant reduction in actual mechanical emissions was observed, primarily manifested as a 91% decrease in NOx emissions. Based on the data from the remote monitoring platform, a new method for compiling the emission inventory of non-road mobile machinery is proposed in this paper. The calculated emission inventory can reflect more real emission situations and provide a reference and basis for emission control and sustainable emission reduction policy measures for non-road mobile machinery. Full article

To calculate, analyze, and predict the rotation angle during the deceleration and braking process of large remote-controlled excavators, this article established a spatial coordinate system based on a simplified model of a hydraulic excavator’s upper structure. Using the D-H parameter method, a mathematical model of the working device’s center of gravity and its rotational inertia was established. Based on the characteristics of the excavator’s hydraulic system and the relationship between brake torque variations, a prediction model was developed to forecast the stopping position (brake rotary angle) of the excavator’s bucket after braking. Subsequently, the predicted results were validated using simulation and compared with existing experimental data to assess the accuracy of the model. The findings demonstrate that the predictive model exhibited high precision with minimal error. The utilization of this model enabled effective forecasting of the excavator’s braking position changes, providing a theoretical foundation for the intelligent remote control of excavators. Full article

The 3D point clouds obtained from the low-cost, remote, and precise SfM (Structure from Motion) technique allow the extraction and acquisition of discontinuities and their characteristics both manually, with the compass and virtual ruler of the Cloud Compare software, and automatically with the DSE (Discontinuity Set Extractor) program, which is faster, more accurate, and safe. Some control plans have been used, which basically consist of identifying one or several fractures and taking measurements on them manually and remotely. The difference between both types of measurements is around 5°, which we believe is reasonable since it is within the precision and repeatability of measurements with a geologist’s compass. This work analyzes the stability of six slopes (five excavated and one natural) by applying five different analysis methodologies based on the rock mass classification system (SMR, RHRSmod, and Qslope), kinematic analysis, and analytical analysis (limit equilibrium). Their results were compared with what was observed in the field to identify the most appropriate analysis methodologies adjusted to reality. The necessary parameters for analyzing each of the slopes, such as orientation, quantity, spacing, and persistence of the discontinuities, were obtained from the automatic analysis. This type of analysis eliminates the subjectivity of the authors, although the findings are related and resemble those obtained manually. The main contribution of the article consists of the application of fast and low-cost techniques to the evaluation of slopes. It is a type of analysis that is in high demand today in many Andean countries, and this work aims to provide an answer. These methodologies suggested by scientific articles such as this one will later be integrated into some procedures and will be taken into account by technical reports. The results show that with the available information and by applying low-cost techniques, the SMR system is the methodology that presents the best results and adjusts better to the reality of the study area. Therefore, SMR is a necessary parameter to determine rockfall hazards through modified RHRS. Full article

Stumps left behind after the felling of trees represent an important source of renewable energy that could be used for fuel mixtures as a sustainable solution. The subject of this research was to determine the influence of tree species, stump diameter size, and subsoil on the time required for stump processing. Evaluated parameters included the mean time for one stump’s processing; the stump processing time based on the stump diameter; different soil types and tree species; and the tree species type (coniferous, broadleaved). The research was conducted in the territory of the Czech Republic in 2020/2021. There were 287 stumps and 6 tree species in total. The stumps were uprooted using a new prototype of grubbing head, developed at Mendel University in Brno, attached as an adapter on the boom of a JCB JS 220 LC excavator with a tracked undercarriage and was controlled remotely from an excavator cab. Research results confirmed that the processing time of one stump depends on the stump diameter (GLM), and the time needed for the processing of one stump increased with an increase in stump diameter in all experimental sites. An equation was suggested to predict the time needed to work on one stump. Full article

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety. Full article

Newly collected morphobathymetric and seismic reflection data from the Valli di Comacchio coastal lagoons, south of the Po River delta (Northeast Italy), combined with historical, remote sensing, and geodetic data highlight a complex geological evolution during the Holocene, strongly affected by anthropic control. All data allowed us to define the present-day depositional environment of the lagoons and reconstruct their recent (late Pleistocene/Holocene) geo-history. We focused on the effects of the anthropic impacts in modifying the pristine environments created by the Holocene transgression along the Adriatic Sea coast, at the mouth of a major river. They include land reclamation works, artificial damming, channel excavations, fluvial diversions, and a recent (last decades) increase in subsidence rate due to gas and water withdrawals. Despite the development of economic activities, which promoted occupation and exploitation of this area in the last millennia, the post-Glacial evolution of the lagoons shows the important role of inherited morphological features, such as sand ridges and barriers. This complex and relatively well-documented evolution makes the Comacchio lagoons a unique example of deep connections between natural processes and long-term human controls, offering insights into the management policies of these important and delicate environments challenged by global changes. Full article

Empirical evidence shows that the expansion of impervious surface threatens soil organic carbon (SOC) sequestration in urbanized areas. However, the understanding of deep soil excavation due to the vertical expansion of impervious surface remains limited. According to the average soil excavation depth, we divided impervious surface into pavement (IS₂₀), low-rise building (IS₁₀₀) and high-rise building (IS₃₀₀). Based on remote-sensing images and published SOC density data, we estimated the SOC storage and its response to the impervious surface expansion in the 0–300 cm soil depth in Guangzhou city, China. The results showed that the total SOC storage of the study area was 8.31 Tg, of which the top 100 cm layer contributed 44%. The impervious surface expansion to date (539.87 km²) resulted in 4.16 Tg SOC loss, of which the IS₂₀, IS₁₀₀ and IS₃₀₀ contributed 26%, 58% and 16%, respectively. The excavation-induced SOC loss (kg/m²) of IS₃₀₀ was 1.8 times that of IS₁₀₀. However, at the residential scale, renovating an IS₁₀₀ plot into an IS₃₀₀ plot can substantially reduce SOC loss compared with farmland urbanization. The gains of organic carbon accumulation in more greenspace coverage may be offset by the loss in deep soil excavation for the construction of underground parking lots, suggesting a need to control the exploitation intensity of underground space and promote residential greening. Full article

On February 14th, 2018, in the North-Western sector of the Municipality of Rome (Central Italy), in the framework of an excavation for building construction, a portion of a piling wall piling wall collapsed in an already densely urbanized area. Soil behind the collapsed piling wall slipped inside the excavation site dragging seven cars parked on one side of the road running parallel to the piling wall and affecting some residential buildings located on the opposite side of the road. Fortunately, no injuries were counted but the 22 families living in the buildings next to the damaged wall were evacuated. Following the piling wall collapse, the Civil Protection of Rome, thanks to the technical support of the Research Centre on Geological Risks (CERI) of the Sapienza University of Rome, started a continuous monitoring of the affected area through remote sensing techniques. In the first hours following the collapse, a Terrestrial Synthetic Aperture Radar Interferometer (TInSAR) and a terrestrial laser scanner (TLS) were installed with the aim to control the evolution of the process, to support the local authority to manage the associated residual risk, and to ensure the safety of workers during emergency operations. In this paper we discuss some of the results obtained by the monitoring of the involved area. Thanks to the comparisons between different surveys and the reconstruction of the pre-event geometries, the total volume involved in the failure was estimated around 850 m³. In addition, through the analysis of data acquired by the 18 multi-temporal TLS scans and the three and a half months of continuous TInSAR monitoring, the movement involving a portion of the filling material used for stabilization works was observed and described. Such movement, reaching a total displacement of about 270–300 mm, was monitored and reported in real time. Full article

Many solutions about the teleoperation of unmanned robotic excavators have been studied continuously. However, if excavators that are remotely controlled were employed, the probability of an accident would be higher. For this reason, there have been many ways proposed to attempt to reduce accidents in these dangerous situations. In this paper, a novel methodology will be introduced with a focus on the multiple excavators themselves. The proposed method details how one excavator can be generated or expressed as an obstacle in the Configuration-Space (C-space) with respect to another excavator’s side for collision avoidance each other. This method is based on kinematics information which is measurable and given. Therefore, this method can be used or applied independently by using widely used pose sensors and wireless communication devices. The phase of mathematical derivation about obstacle sets is described in detail. The results are shown in accompanying figures and tables for demonstrating that the proposed method detected the proximity and found the collision-free zone accurately. The proposed system can be powerful when applied to a teleoperation system, where it would be particularly useful and helpful to the operator. Full article