Research on Energy Efficiency Characteristics of Mining Shovel Hoisting and Slewing System Driven by Hydraulic-Electric Hybrid System

Mining shovel is a crucial piece of equipment for high-efficiency production in open-pit mining and stands as one of the largest energy consumption sources in mining.However,substantial energy waste occurs during the descent of the hoisting system or the deceleration of the slewing platform.To reduce the energy loss,an innovative hydrau-lic-electric hybrid drive system is proposed,in which a hydraulic pump/motor connected with an accumulator is added to assist the electric motor to drive the hoisting system or slewing platform,recycling kinetic and potential energy.The utilization of the kinetic and potential energy reduces the energy loss and installed power of the min-ing shovel.Meanwhile,the reliability of the mining shovel pure electric drive system also can be increased.In this paper,the hydraulic-electric hybrid driving principle is introduced,a small-scale testbed is set up to verify the feasibil-ity of the system,and a co-simulation model of the proposed system is established to clarify the system operation and energy characteristics.The test and simulation results show that,by adopting the proposed system,compared with the traditional purely electric driving system,the peak power and energy consumption of the hoisting electric motor are reduced by 36.7%and 29.7%,respectively.Similarly,the slewing electric motor experiences a significant decrease in peak power by 86.9%and a reduction in energy consumption by 59.4%.The proposed system expands the application area of the hydraulic electric hybrid drive system and provides a reference for its application in over-sized and super heavy equipment.

Clinical Outcomes of Patients Who Perform High-Load Activities after Total Hip Arthroplasty in Snowy Agricultural Areas

Background: In snowy agricultural areas, weeding and snow shoveling are essential activities, and sports activities are common recreational activities. Clarifying the relationships between the degrees of these activities after total hip arthroplasty (THA) and the clinical outcomes may enable us to predict the results of THA for high-load activity patients. Methods: The subjects were 227 post-THA patients who were followed up between 2012 and 2014. Patient-reported outcomes were investigated by the Japanese Orthopaedic Association Hip Disease Evaluation Questionnaire (JHEQ) and a questionnaire on postoperative activity. In addition, the Japanese Orthopaedic Association Hip Score (JOA score) was used to quantify hip function. Results: Patients who resumed activities had significantly higher JOA and JHEQ scores than patients who had given up their activities. However, 25.8% of patients had not resumed weeding with a squatting posture. Furthermore, 20% had not resumed sports activities. The most common reason for giving up these activities was fear of implant failure. Conclusions: If the patients were informed that there is no problem restarting their activities after THA, the patients could resume activities and their clinical outcomes may be improved.

A comparison of strategic mine planning approaches for in-pit crushing and conveying, and truck/shovel systems

In a global environment where energy and labor are becoming increasingly expensive, continuous mining systems such as In-Pit Crushing and Conveying(IPCC) systems have been advanced as offering a real alternative to conventional truck haulage systems. The implementation of IPCC systems in hard rock operations in open pit mines however requires different and more comprehensive planning approaches in order to adequately reflect the practical aspects associated with these. This paper investigates the impact that these approaches may have on the implementation of IPCC systems on a basic metalliferous deposit amenable to open pit exploitation. A strategic life of mine plan to provide numerous economic indicators for each approach is analyzed and compared to traditional truck haulage systems. The mine planning and evaluation process highlights the increased overall resource recovery that may accompany the use of IPCC systems. This investigation also provides insights into the issues associated with IPCC and the scale and type of operation and orebody that is likely to provide a feasible alternative to truck haulage.

Impulse force reductions and their effects on WBV exposures in high impact shovel loading operations

When shovels load the dump trucks with over 100-ton passes under gravity dumping conditions, they will create a large impact force on the dump truck body which generates high frequency shock waves which expose the operators to whole body vibrations （WBV）. The main cause of such truck vibrations is the large impact force due to the gravity dumping of large tonnage passes. Therefore a rigorous mathematical model has been developed for the impact force containing all the necessary factors upon which it depends. Latter, a thorough analysis shows that percentage reduction of 7.19%, 9.40%, 13.27%, 14.8%, 17.30% and 18.13% can he achieved by reducing the dumping distance to 6.33 m, 6.0 m, 5.5 m, 5.33 m, 5.0 m and 4.9 m, respectively, as compared to when the dumping distance was 7.33 m. Even more reduction in the magnitude of impact force can he observed if the shovel pass gets divided into more than two sub-passes. Therefore, these models can he used to figure out the number of sub-passes into which a single ore pass can he divided and/or the extent to which the dumping distance can he reduced which would reduce the impact force significantly enough to obtain safer yet economic operations.

Novel Hybrid Physics‑Informed Deep Neural Network for Dynamic Load Prediction of Electric Cable Shovel

Electric cable shovel(ECS)is a complex production equipment,which is widely utilized in open-pit mines.Rational valuations of load is the foundation for the development of intelligent or unmanned ECS,since it directly influences the planning of digging trajectories and energy consumption.Load prediction of ECS mainly consists of two types of methods:physics-based modeling and data-driven methods.The former approach is based on known physical laws,usually,it is necessarily approximations of reality due to incomplete knowledge of certain processes,which introduces bias.The latter captures features/patterns from data in an end-to-end manner without dwelling on domain expertise but requires a large amount of accurately labeled data to achieve generalization,which introduces variance.In addition,some parts of load are non-observable and latent,which cannot be measured from actual system sensing,so they can’t be predicted by data-driven methods.Herein,an innovative hybrid physics-informed deep neural network(HPINN)architecture,which combines physics-based models and data-driven methods to predict dynamic load of ECS,is presented.In the proposed framework,some parts of the theoretical model are incorporated,while capturing the difficult-to-model part by training a highly expressive approximator with data.Prior physics knowledge,such as Lagrangian mechanics and the conservation of energy,is considered extra constraints,and embedded in the overall loss function to enforce model training in a feasible solution space.The satisfactory performance of the proposed framework is verified through both synthetic and actual measurement dataset.

Evaluation of rope shovel operators in surface coal mining using a Multi-Attribute Decision-Making model

Rope shovels are used to dig and load materials in surface mines. One of the main factors that influence the production rate and energy consumption of rope shovels is the performance of the operator. This paper presents a method for evaluating rope shovel operators using the Multi-Attribute Decision-Making （MADM） model. Data used in this research were collected from an operating surface coal mine in the southern United States. The MADM model consists of attributes, their weights of importance, and alter- natives. Shovel operators are considered the alternatives, The energy consumption model was developed with multiple regression analysis, and its variables were included in the MADM model as attributes. Preferences with respect to min/max of the defined attributes were obtained with multi-objective opti- mization. Multi-objective optimization was conducted with the overall goal of minimizing energy con- sumption and maximizing production rate. Weights of importance of the attributes were determined by the Analytical Hierarchy Process （AHP）, The overall evaluation of operators was performed by one of the MADM models, i.e., PROMETHEE If. The research results presented here may be used by mining professionals to held evaluate the performance of rode shovel operators in surface mining.

Underwater hydraulic shock shovel control system

The control system determines the effectiveness of an underwater hydraulic shock shovel. This paper begins by analyzing the working principles of these shovels and explains the importance of their control systems. A new type of control system’s mathematical model was built and analyzed according to those principles. Since the initial control system’s response time could not fulfill the design requirements, a PID controller was added to the control system. System response time was still slower than required, so a neural network was added to nonlinearly regulate the proportional element, integral element and derivative element coefficients of the PID controller. After these improvements to the control system, system parameters fulfilled the design requirements. The working performance of electrically-controlled parts such as the rapidly moving high speed switch valve is largely determined by the control system. Normal control methods generally can’t satisfy a shovel’s requirements, so advanced and normal control methods were combined to improve the control system, bringing good results.

Simulation Analysis of a New Type of Bionic Digging Shovel Based on DEM

The performance of a digging shovel mainly depends on the style of the shovel, while the conventional experiment methods always suffer from the problems of high lost and long period. Aiming at these problems and the characteristic that soil is composed of countless small particles, dynamic simulation analysis was performed on the resistance to a bionic digging shovel and crushing rate of the soil during the normal working process of the bionic digging shovel by EDEM through numerical simulation, calculation and comparison. The results showed that compared with the ordinary shovel, the average drag-reducing rate in the X direction was 10.41%, and the average drag-reducing rate in the Y direction was 16.28%, and the soil crushing rate was improved by 2.67%. Therefore, the bionic digging shovel has certain superiority and extension value in structure and performance. Moreover, this analysis case fully demonstrates the unique advantage of DEM method and its generalizability, and provides certain reference for similar studies.

Stress Computation of Roadheader Shovel's by using the Finite Element Method

Shovel board is an important component of the roadheader. Shovel board participate in complex and changeable tunneling work, and always under high load. In this paper, research the working condition of shovel board and analyze the shovel board by Inventor, and reach the stress and strain distribution in the shovel board bear the maximum force when working. Have some guiding on improving the shovel board structure design.

Design and experiment of an upper-side-discharge straw-returning and bundle self-unloading integrated corn residual film recycling machine

Due to the arid climate,flat terrain,certain irrigation sources and high popularization of mechanical harvest in Hexi Irrigation Area of Gansu Province,the widely adopted half film-flat-mulching for corn cultivation faces serious adverse situations,such as high soil compactness,strong film-soil adhesion,significant straw stubble and thick covering accumulation on film.Therefore,a new kind of segmented combination upper-side-discharge straw-returning and bundle self-unloading integrated corn residual film recycling machine was proposed.The scheme was characterized by small volume,low resistance,low complexity and film-impurities twice separation.It is constructed based on the concept of module subsection combination.It was composed of film surface straw cleaning device and the followed residual film recycling machine,in terms of function,any usage requirements of separate and joint operations can be satisfied.The film surface straw cleaning device is responsible for the removal of vertical corn straw and ground covering beyond the film.Although its stubble cutter roller obtuse-angle Lshaped blades paired single-helix arrangement is simple,it runs smoothly and the straw crushing effect is good enough.The layout that upper-side-discharge straw-returning cross-range screw conveyor auger is back and beyond the stubble cutter roller,eliminates the common connecting transportation mechanism between crushing and straw-returning section,so that,the system structure can be optimized and the efficiency has been significantly improved.The integrated residual film recycling machine is composed of triangular pyramid arc two-stage wing(TPATSW)type film lifting shovel,rod-tooth-belt type film-impurities separation device and semi-enclosed shaftless bundle film collector.Among them,TPATSW type film lifting shovel has good corn root whisker cutting effect,low soil contact resistance and small soil congestion area,but its ability to lift film is strong,more importantly,the special segmented configuration of shovel handle and the body,shortens the overall machine length significantly.For semi-enclosed shaftless bundle film collector,however,a new scheme of eight sub-rolls rotate in the same direction,to roll the residual film into a bundle is innovatively adopted.Under its own parameters,the system has the lowest sub-roll rotation speed that can bundle the residual film without shaft inside the film collecting chamber,rather than on any subroll itself.The gap between the sub-rolls can separate impurities for the second time.After the film collection reaches the standard,the film collector can dump the residual film directly,which is simple and efficient.The field orthogonal test data of the prototype show that,the optimal parameter combination is:film lifting shovel earth angle is 30°,its operation depth is 50 mm and the machine forward speed is 5.0 km/h.The average residual film recycling rate and the crushed straw qualified rate under the optimal parameters are 84.9%and 90.3%respectively,which meet the requirements of the national and industrial standards.The research solved the passive situation that there was no matching equipment for the recycle of residual film in corn field in Hexi Irrigation Area effectively.

Characteristics of dental morphology in the Xinjiang Uyghurs and correlation with the EDARV370A variant

Teeth are one of the most important materials for anthropological studies because they are likely to be preserved in ancient remains.While the frequencies of dental characteristics can provide clues to the phylogeny of populations,genetic studies at the individual level can further reveal the biological mechanisms and evolutionary context of dental characteristics.In this study,by analyzing 38 dental characteristics of 242 Xinjiang Uyghur individuals,we found that(i)the dental characteristics of the Uyghurs showed evidence of admixture between European and East Asian populations.The admixture proportions were in line with those previously reported in population genetic studies;(ii)the Xinjiang Uyghur dental characteristics formed three clusters in pairwise correlation analysis.One of the main clusters consisted of characteristics including incisor shoveling,double shoveling and mesial ridge;and(iii)all the characteristics in this cluster were significantly correlated with the genetic variant EDARV370A.The extracted composite phenotypic factor was also significantly associated with EDARV370A,which explained 18%of the total phenotypic variance.This indicated a pleiotropic effect,i.e.,the same genetic factor affects a number of dental characteristics at the same time.Our results confirmed that EDARV370A,a genetic variant that first originated in East Asia about 30000 years ago,played an important role in incisor shoveling in East Asia.This finding suggested that incisor shoveling in modern humans in East Asia is likely to have appeared after the late Pleistocene.

Space use of wintering waterbirds in India： Influence of trophic ecology on home-range size

Relationship between species＇ home range and their other biological traits remains poorly understood, especially in migratory birds due to the difficulty associated with tracking them. Advances in satellite telemetry and remote sensing techniques have proved instrumental in overcoming such challenges. We studied the space use of migratory ducks through satellite telemetry with an objective of understanding the influence of body mass and feeding habits on their home-range sizes. We marked 26 indi- viduals, representing five species of migratory ducks, with satellite transmitters during two consecutive winters in three Indian states. We used kernel methods to estimate home ranges and core use areas of these waterfowl, and assessed the influence of body mass and feeding habits on home-range size. Feeding habits influenced the home-range size of the migratory ducks. Carnivorous ducks had the largest home ranges, herbivorous ducks the smallest, while omnivorous species had intermediate home-ranges. Body mass did not explain variation in home-range size. To our knowledge, this is the first study of its kind on migratory ducks, and it has important implications for their conservation and management [Current Zoology 60 （5）： 616-621, 2014].

Continuous measurement method and mathematical model for soil compactness

With the continuous improvement of agricultural mechanization,soil compaction becomes more and more serious.Serious soil compaction has been considered as an important negative factor affecting crop growth and yield.The measurement of soil compactness is a common method to measure the soil compaction level.In order to solve the problems of discontinuous sampling,time-consuming and poor real-time soil compactness measurement,a real-time measurement method of soil compactness based on fertilizing shovel was proposed,and the mathematical model between fertilizing shovel arm deformation and soil compactness was established.Based on the interaction mechanism between fertilizing shovel and soil,through the force analysis of fertilizing shovel,it was found that the deformation of fertilizing shovel arm was positively correlated with the sum of soil compactness(SSC)within the range of tillage depth.In order to verify the theoretical analysis results and the detection accuracy of strain gauge,the static bench test was carried out.The test results showed that the strain gauge signal for measuring the deformation of the fertilizing shovel arm was significantly correlated with the applied force.The fitting curve of the linear correlation coefficient was 0.999,the maximum detection error was 0.68 kg,and the detecting accuracy was within the tolerance of 0.57%.Through field orthogonal experiments with four working depths and four compaction levels,a mathematical model of the strain gauge signal and the SSC within the range of tillage depth was established.The experiment showed that compared with the other three depths,the linear correlation coefficient at the tillage depth of 5 cm(TD5)was the lowest,and the slope of the fitting curve was obviously different from the other three depths,so the 5 cm data were excluded when modeling.The model between mean signal value and mean SSC within the range of tillage depth was established based on the data of sampling points with tillage depths of 7.5 cm(TD7.5),10 cm(TD10),and 12.5 cm(TD12.5).The linear correlation coefficient(R^(2))of the model between mean signal value and mean SSC which eliminated 5 cm data was 0.980 and the root mean square error(RMSE)was 143.57 kPa.Compared with the linear model before averaging,the R^(2) was improved by 8.65%,and the RMSE was reduced by 52.39%.This system can realize the real-time and continuous measurement of soil compactness and provide data support for follow-up intelligent agricultural operations.

Multiobjective trajectory optimization of intelligent electro-hydraulic shovel

Multiobjective trajectory planning is still face challenges due to certain practical requirements and mul-tiple contradicting objectives optimized simultaneously.In this paper,a multiobjective trajectory optimization approach that sets energy consumption,execution time,and excavation volume as the objective functions is presented for the electro-hydraulic shovel(EHS).The proposed cubic polynomial S-curve is employed to plan the crowd and hoist speed of EHS.Then,a novel hybrid constrained multiobjective evolutionary algorithm based on decomposition is proposed to deal with this constrained multiobjective optimization problem.The normalization of objectives is introduced to minimize the unfavorable effect of orders of magnitude.A novel hybrid constraint handling approach based onε-constraint and the adaptive penalty function method is utilized to discover infeasible solution information and improve population diversity.Finally,the entropy weight technique for order preference by similarity to an ideal solution method is used to select the most satisfied solution from the Pareto optimal set.The performance of the proposed strategy is validated and analyzed by a series of simulation and experimental studies.Results show that the proposed approach can provide the high-quality Pareto optimal solutions and outperforms other trajectory optimization schemes investigated in this article.

Toward autonomous mining:design and development of an unmanned electric shovel via point cloud-based optimal trajectory planning

With the proposal of intelligent mines,unmanned mining has become a research hotspot in recent years.In the field of autonomous excavation,environmental perception and excavation trajectory planning are two key issues because they have considerable influences on operation performance.In this study,an unmanned electric shovel(UES)is developed,and key robotization processes consisting of environment modeling and optimal excavation trajectory planning are presented.Initially,the point cloud of the material surface is collected and reconstructed by polynomial response surface(PRS)method.Then,by establishing the dynamical model of the UES,a point to point(PTP)excavation trajectory planning method is developed to improve both the mining efficiency and fill factor and to reduce the energy consumption.Based on optimal trajectory command,the UES performs autonomous excavation.The experimental results show that the proposed surface reconstruction method can accurately represent the material surface.On the basis of reconstructed surface,the PTP trajectory planning method rapidly obtains a reasonable mining trajectory with high fill factor and mining efficiency.Compared with the common excavation trajectory planning approaches,the proposed method tends to be more capable in terms of mining time and energy consumption,ensuring high-performance excavation of the UES in practical mining environment.