Search Results (4)

In China, there are around 36.7 million hectares of saline–alkali lands that hold utilization potential. Precision fertilization stands as a vital measure for enhancing the quality of saline–alkali soil and promoting a significant increase in crop yields. The performance of the fertilization device is a decisive factor in determining the effectiveness of fertilization. To optimize the fertilizer utilization rate in coastal saline–alkali soils and substantially reduce fertilizer waste, it is imperative to transport fertilizers to the deep soil layers and execute layered variable-rate fertilization. In light of this, a chisel-type variable-rate layered electronically controlled deep-fertilization device specifically designed for saline–alkali soils has been developed. Extensive experimental research on its fertilization performance has also been carried out. Drawing on the principles of soil dynamics, this paper meticulously investigates the structures of key components and the operating parameters of the fertilization device. Key parameters such as the penetration angle of the fertilizer shovel, the penetration clearance angle, the curvature of the shovel handle, the angle between the fertilizer baffle and the fertilizer pipe wall, the angle between the fertilizer pipe and the horizontal plane, and the forward speed are precisely determined. Moreover, this study explores the quantitative relationship between the fertilizer discharge amount of the fertilizer applicator and the effective working width. Simultaneously, this research mainly focuses on analyzing the impact of the forward speed on the operational effect of layered and variable-rate fertilization. Through a series of field experiments, it was conclusively determined that the optimal fertilization effect was attained when the forward speed was set at 6 km/h. Under this condition, the average deviation in the fertilization amount was merely 2.76%, and the average coefficients of variation in the fertilizer amount uniformity in each soil layer were 7.62, 6.32, 6.06, and 5.65%, respectively. Evidently, the experimental results not only successfully met the pre-set objectives, but also fully satisfied the design requirements. Undoubtedly, this article can offer valuable methodological references for the research and development of fertilization devices tailored for diverse crops cultivated on saline–alkali lands. Full article

Backgrounds: The transportation system within any mining project, which is responsible for delivering extracted ore to the crushing units or wastes to the wasting dumps as the destinations, poses a significant challenge in mining processes. On one hand, there are various transportation systems, notably the Truck–Shovel, the traditional method, and relatively newer and less common In-Pit Crushing and Conveying (IPCC) systems. On the other hand, choosing the most suitable system for a specific mining project depends on various factors, with technical aspects being one of the most critical. While there is extensive research on the Truck–Shovel system from a technical perspective, there is relatively limited research on IPCC systems. Methods: This research aims to carry out a comparative analysis of different transportation systems, encompassing Truck–Shovel, Fixed In-Pit Crushing and Conveying (FIPCC), Semi-Fixed In-Pit Crushing and Conveying (SFIPCC), Semi-Mobile In-Pit Crushing and Conveying (SMIPCC), and Fully Mobile In-Pit Crushing and Conveying (FMIPCC) systems. To achieve this goal, a technical index is introduced, which is based on three elements: the availability and the utilization of the system, as well as the consumption of power. This index will be developed as a system dynamics model, enabling the observation of each system’s performance throughout the operational lifespan of the mine. Results: Ultimately, based on the proposed method, the most effective transportation system based on the defined technical index can be identified at any time of the project. In this research, the Truck–Shovel system generally selected as the most preferred transportation system, except for two different periods. Conclusions: This study could successfully perform the selection among different transportation systems. Nevertheless, it was modeled and performed in a deterministic environment, but still the stochastic nature of the processes can be another topic of research. Full article

To address the issue of current garbage cleanup vessels being limited to performing garbage cleaning operations in the ocean, without the capability of transferring the garbage from the ocean to the land, this paper presents a spiral-propulsion amphibious intelligent robot for land garbage cleaning and sea garbage cleaning. The design solution is as follows. A mechanical structure based on a spiral drum is proposed. The interior of the spiral drum is hollow, providing buoyancy, allowing the robot to travel both on marshy, tidal flats and on the water surface, in conjunction with underwater thrusters. Additionally, a mechanical-arm shovel is designed, which achieves two-degrees-of-freedom movement through a spiral spline guide and servo, facilitating garbage collection. Our experimental results demonstrated that the robot exhibits excellent maneuverability in marine environments and on beach, marsh, and tidal flat areas, and that it collects garbage effectively. Full article

Fluctuating commodity prices have repeatedly put the mining industry under pressure to increase productiveness and efficiency of their operations. Current procedures often rely heavily on manual analysis and interpretation although new technologies and analytical procedures are available to automate workflows. Grade control is one such issue where the laboratory assay turn-around times cannot beat the shovel. We propose that for iron ore deposits in the Pilbara geophysical downhole logging may provide the necessary and sufficient information about rock formation properties, circumventing any need for real-time elemental analysis entirely. This study provides an example where petrophysical downhole data is automatically classified using a neuro-adaptive learning algorithm to differentiate between different rock types of iron ore deposits and for grade estimation. We exploit a rarely used ability in a spectral gamma-gamma density tool to gather both density and iron content with a single geophysical measurement. This inaccurate data is then put into a neural fuzzy inference system to classify the rock into different grades and waste lithologies, with success rates nearly equal to those from laboratory geochemistry. The steps outlined in this study may be used to produce a workflow for current logging tools and future logging-while-drilling technologies for real-time iron ore grade estimation and lithological classification. Full article