Cable Shovels Research Articles

Co-design of an unmanned cable shovel for structural and control integrated optimization: A highly heterogeneous constrained multi-objective optimization algorithm

Unmanned cable shovel is an intelligence-based large machine used for excavating in open-pit coal mines, with significant implications for the security and development of energy resources. The co-design of unmanned cable shovels, considering elements from both structural and control systems, has demonstrated superior performance in obtaining optimal solutions compared to the traditional approaches that focus on individual systems. However, the inherent complexities of diverse systems often lead to heterogeneous function evaluations, posing challenges for the existing optimization algorithms. To address highly heterogeneous multi-objective optimization problems characterized by surrogate-approximated expensive functions and explicit inexpensive functions, this study proposes a highly heterogeneous constrained multi-objective optimization (HHCMO) algorithm. Leveraging NSGA-III as an evolutionary optimizer and the Kriging model for approximating expensive functions, HHCMO strategically addresses the challenges posed by highly heterogeneous objective evaluations. A Monte Carlo sampling-based expected hypervolume improvement (EHVI) criterion, employing a new nearest point approximation method in a unified sampling space, effectively handles the impact of heterogeneous objective evaluations on the sequential infill of the Kriging model. Thorough evaluations on both unconstrained and constrained multi-objective benchmark problems validate the correctness of HHCMO and its superiority relative to state-of-the-art algorithms. Finally, the effectiveness of the proposed method is successfully demonstrated in an engineering scenario of an unmanned cable shovel, where it adeptly handles expensive functions from the structural system and inexpensive functions from the control system.

Digital twin-based excavation trajectory generation of Uncrewed excavators for autonomous mining

As modern large-capacity excavators, cable shovels provide payload capacities of more than 100-tons per scoop. The presence of a high dynamic payload combined with the self-weight may result in severe stress loading of the whole shovel front-end components during excavation. Structural performance analysis based on numerical simulations typically demands a prohibitively heavy computation, so conventional optimization-based excavation trajectory generation methods generally do not consider structural performance constraints, which may cause sudden component failure or unanticipated costly downtime. Herein, a shape–performance integrated digital twin was constructed to analyze the shape and structural performance of an uncrewed cable shovel (UCS) in real time, which was further used to support optimal excavation trajectory generation. The proposed procedure presents salient features that the time-consuming structural performance response was taken as an additional constraint, which could effectively prevent the sudden structural failures. The effectiveness and applicability were demonstrated via field tests with a UCS prototype (1:7 scale model of the WK-55 type).

Design of Unmanned Cable Shovel Based on Multiobjective Co-Design Optimization of Structural and Control Parameters

Abstract In autonomous excavation, design and optimization of the unmanned cable shovels (UCS) are important issues in the full life cycle of the equipment. However, the design of physical structure and control system of the UCS are performed at different stages, which makes it difficult for traditional sequential optimization strategy to generate global optimal solution. To enhance the working performance of the UCS, in this article, a multistage multiobjective (MSMO) co-design optimization strategy is proposed to perform global optimization considering excavation and loading processes by simultaneous optimization for the structure and control parameters of UCS. Under this framework, first, a point-to-point motion model based on 4-5-4 piecewise polynomial is proposed to describe the motion trajectory, and the dynamical model of the working device is established to predict the energy consumption in the working process. Then, the physical and geometric constraints in practical working are analyzed, and a multiobjective optimization model considering excavation and loading processes is established to improve mining efficiency and reduce energy consumption in unmanned excavation scenarios. Finally, the structural and control parameters are optimized synchronously to generate optimal physical structure, excavation, and loading trajectory. Numerical results show that the proposed MSMO co-design method can further improve the operational performance of UCS compared with the traditional optimization strategy.

Digging Trajectory Optimization for Cable Shovel Robotic Excavation Based on a Multi-Objective Genetic Algorithm

As one of the most essential earth-moving equipment, cable shovels significantly influence the efficiency and economy in the open-pit mining industry. The optimal digging trajectory planning for each cycle is the base for achieving effective and energy-saving operation, especially for robotic excavation, in which case, the digging trajectory can be precisely tracked. In this paper, to serve the vision of cable shovel automation, a two-phase multi-objective genetic algorithm was established for optimal digging trajectory planning. To be more specific, the optimization took digging time and energy consumption per payload as objects with the constraints of the limitations of the driving system and geometrical conditions. The WK-55-type cable shovel was applied for the validation of the effectiveness of the multi-objective optimization method for digging trajectories. The digging performance of the WK-55 cable shovel was tested in the Anjialing mining site to establish the constraints. Besides, the digging parameters of the material were selected based on the tested data to make the optimization in line with the condition of the real digging operations. The optimization results for different digging conditions indicate that the digging time decreased from an average of 20 s to 10 s after the first phase optimization, and the energy consumption per payload reduced by 13.28% after the second phase optimization, which validated the effectiveness and adaptivity of the optimization algorithm established in this paper.

Digging force and power consumption during robotic excavation of cable shovel: experimental study and DEM simulation

ABSTRACT Cable shovels are on the top priority of the most widely used machinery in open-pit mining industry, the automation of which offers great potential to improve both production efficiency and equipment reliability. Rational evaluations of digging force and power consumption serve as one of the fundamental techniques of realising autonomous operation of cable shovels. In this study, because of the wide range of digging parameters in theoretical calculation, the method of simulation is used to narrow the range of digging parameters in theoretical calculation, so that the digging force can be accurately and efficiently predicted by the method of theoretical calculation. Furthermore, scale-model-based experiments were taken in order to validate the effectiveness of the simulation results. Conclusively, although the theoretical calculation can numerically predict the power consumption in an acceptable extent (), the fitted value of unit resistance to excavation for the theoretical calculation was out of its empirical value range according to the classical theory applied to the prediction of digging resistance in the design of cable shovel. On the other hand, the simulation results were shown to be highly consistent with the experimental results (), which demonstrate the efficiency of the simulation method in evaluating dynamic working performance of cable shovels.

Study on theory and methods of payload online estimation for cable shovels

Cable shovels are one of the most widely used machines in open-pit mining industry. Precise estimation of payload can effectively avoid overload and underload for each dump, significantly improve the working performance of cable shovels and reduce the maintenance costs of haul trucks. In this research, an algorithm based on static analysis for payload online estimation was established, which took hoist force, crowd force and geometrical parameters of the working device as input variables for the situation when both hoist and crowd motors were hovering during the digging process. More specifically, the torque balance function was applied for payload calculation on the basis of the kinematic model built for evaluating the length of different force arms when the dipper handle stayed in different positions. In order to verify the efficiency of the payload online estimation algorithm, six different working positions and four different fullness states of the dipper were chosen for testing. And a testing system consisting of a 1/35 scale model of cable shovel, software of LabVIEW, hardware of cRIO and multi-types of sensors was designed and set up. Testing results show that the relative error between the theoretically calculated value and the real weight of payload is averagely less than 6% when the dipper was 40% fully filled and averagely less than 3% when the fullness reached 100%, which has proved the efficiency of the payload online estimation theory and methods established in this research.

Particle flow mechanism into cable shovel dippers

Electric cable (or rope) shovels are critical equipment in the surface mining industry. An improved understanding of the factors which affect the flow of broken material into the dipper during loading can help to evaluate the performance of the excavator, define the criteria for equipment selection and develop ways to mitigate equipment damage caused by broken particles. In this paper, the mechanism of granular material flow was investigated through a series of laboratory tests by moving 1:32 and 1:20 (cube root scale) models of a 44m3 dipper through a test bin filled with angular crushed limestone. It was found that neither dipper angle nor hoist speed has significant influence on the general flow pattern. It was also found that the general flow mechanism is independent on the size of the dipper. Quantitatively, it was determined that hoist speed and pitch angle affect the productivity of the machine with lower pitch angle resulting in higher payload, and faster hoist speed results in shorter dig time. While both lower pitch angle and faster hoist speeds also produce a higher rate of energy consumption, overall both contribute to improved machine productivity.

Contact and Joint Forces Modeling and Simulation of Crawler-formation Interactions

Cable shovels are used in surface mining operations to achieve economic bulk production capacities. The service life of the rawlers and their shoes define shovel reliability, maintainability, availability and efficiency. The crawler track-terrain interaction generates high time-fluctuating contact forces that result in stress buildup, crack and fatigue failure of wler shoes. In addition, the link pins that connect two crawler shoes can exert large fluctuating pin loads on shoe lugding to shoe breakage. This paper addresses fundamental research into contact forces acting on crawler shoes, joint forces generated in the link pin and total deformation of the formation during shovel propel. During propel, the crawler track is controlled by two drive constraints that cause the crawler to follow straight or turning motions. A virtual prototype simulator of the crawler-terrain interaction dynamics is developed and simulated within the MSC ADAMS environment. The simulation results show that the average penetration depth for different crawler shoes is within the range of 5.9 and 6.7 cm for both types of driving constraints. During translation, the maximum magnitude of contact forces along vertical, longitudinal and lateral directions have respective values of 5.9 × 105 N, 5.5 × 105 N and 1.7 × 105 N. During turning, the crawler track experiences varying bouncing and rolling motions causing maximum magnitude of vertical and lateral contact forces on the crawler shoes to increase 1.15 and 1.42 times the maximum translation values. The total deformation of oil sand terrain for the two motions fluctuates between -0.24 and 0.26 cm and between -1.03 and 1.33 cm, respectively. This study provides solid foundation for further studies on dynamic stress and fatigue failure analysis of crawler shoes during shovel propel and loading operations.

Correspondence analysis of repair data: a case study for electric cable shovels

In mining operation, effective maintenance scheduling is very important because of its effect on the performance of equipment and production costs. Classifying equipment on the basis of repair durations is considered one of the essential works to schedule maintenance activities effectively. In this study, repair data of electric cable shovels used in the Western Coal Company, Turkey, has been analyzed using correspondence analysis to classify shovels in terms of repair durations. Correspondence analysis, particularly helpful in analysing cross-tabular data in the form of numerical frequencies, has provided a graphical display that permitted more rapid interpretation and understanding of the repair data. The results indicated that there are five groups of shovels according to their repair duration. Especially, shovels numbered 2, 3, 7, 10 and 11 required a repair duration of<1 h and maintained relatively good service condition when compared with others. Thus, priority might be given to repair them in maintenance job scheduling even if there is another failed shovel waiting to be serviced. This type of information will help mine managers to increase the number of available shovels in operation.

Fatigue life prediction of heavy mining equipment. Part 2: Behaviour of corner crack in steel welded box section and remaining fatigue life determination

Frequent fatigue failure of mining equipment has created a need for fatigue life prediction of several components that suffer from frequent recurrence of fatigue cracking. The focus of this paper is the frequent occurrence of fatigue cracks in the boom of cable shovels, which consists of a twin box girder joining together near both extremities. After the determination of load spectrum and the material fatigue properties by field monitoring and material testing, the fatigue behaviour of a cracked shovel boom was investigated. Two-tip corner cracks were of particular interest since they are commonly observed in the field. These cracks typically initiate in the flange at the toe of web to flange or flange to diaphragm welds and propagate into the web. Detailed finite element models with corner cracks were developed for the boom and stress intensity factors for various crack configurations were evaluated from the finite element analysis results. The growth behaviour of corner cracks was studied and a simplified method is presented for the fatigue life prediction. Fracture toughness tests were conducted on single edge notch bend specimens at room temperature and low temperature (−50 ∘C). The remaining life of a cracked boom is then determined based on brittle fracture or unstable crack growth.

Cable shovel digging optimization for energy efficiency

Abstract Operator practices have long been suspected to contribute towards the inefficient use of cable shovels. The objective of this work is to find the optimal crowd arm and hoist rope speeds for given initial conditions, material properties and uncertain bulk densities. The excavation process has been modeled using shovel kinematics and dynamics and includes dynamic shovel payload and material cutting resistance models using geometric simulation and passive soil pressure techniques. The models have been used to simulate the energy per unit loading rate of the P&H 2100BL shovel. Extended simulations were carried out for crowd arm and hoist rope speeds ranging from 0.25 to 0.5 m s −1 and 0.5 to 0.7 m s −1 , respectively. From the results, the optimal crowd arm and hoist rope speeds were found to be 0.25 and 0.7 m s −1 , respectively. The objective function value was 0.2111 kJ s/kg with a standard deviation of 0.0161 kJ s/kg. At 95% confidence, the energy per unit loading rate lies within 0.1795 and 0.2428 kJ s/kg. The study also shows that the optimal operating conditions yield an average of 2.5 million tonnes/annum more than the non-optimal conventional operation.

Stress loading of the cable shovel boom under in-situ digging conditions

Cable shovels are capital-intensive equipment, whose operations are characterized by high stress loading and fatigue failure resulting in high maintenance costs. The operating environment and the stress fields on the boom must continually be monitored to avoid random fatigue failure to achieve reliability, longevity and economic usage. In this paper, the authors develop dynamic models for real-time stress monitoring using a combination of flexible and rigid body approach. A virtual prototype simulator is developed to simulate the cable shovel excavation in oil sands and to examine the motion, stress and local deformation of the boom. The P&H 4100A cable shovel, deployed in the Athabasca oil sands formation, is used to examine the cable shovel boom durability using stress fields simulation. The results show that high stresses occur at regions around the joint between the upper body and the boom, resulting in large deformations. In hard formations, the results show that the stress fields in this region exceed the Von Mises yield strength of steel used in making the shovel boom components. The results also show that the FE nodes of 178, 168, 120, 63, 127 and 84 for 10 MPa modulus of elasticity and 127, 61, 126, 45, 60 and 39 nodes for 20 MPa modulus of elasticity are the highly stressed nodes with high degree of boom deformation and fatigue failure. The study provides a solid foundation for further study of failure life analysis of the cable shovel components.

Performance monitoring of electric cable shovels

A shovel performance monitoring study at an oil sands mine used current and voltage data from hoist, crowd and swing motors of P&H 4100 series electric cable shovels. The goal was to identify key shovel performance indicators using only data from the motors. It was found that hoist and crowd motor responses can be used to identify different shovel activities, especially the dig cycle. Some key shovel performance indicators examined are the dig cycle time, digging energy and digging power. By averaging the hoist power over a number of dig cycles, the average hoist power is less sensitive to digging trajectory and could be a useful parameter for assessing ground diggability characteristics. Analysis of performance indicators showed that the shovel performance can be significantly influenced by the operator. The study revealed that freezing temperatures can have a minor and localized influence on shovel performance.

97/01696 A year of GPS at Fording Coal Limited, Green-hills operations

Fording Greenhills first acquired GPS (Global Positioning System) technology with the commissioning of a GPS-based dispatch system in December 1994. The second exposure to satellite technology came with the conversion of the conventional optical survey system to a high-resolution GPS system in June 1995. In September 1995, a GPS-based grade control system was tested on the largest shovel (Marion 301 - 58 cubic yard). In January 1996, the system was added to all of the cable shovels (2 P&H 2800s). All three applications of GPS at Greenhills are fully operational and producing positive results. This paper will focus on the practical application of GPS in a mining environment and the effect that GPS technology has had on the Greenhills Mine.

Performance assessment of hydraulic and cable shovels

Abstract In this paper, performance assessment studies for hydraulic and cable shovels carried out on a nationwide scale in the surface lignite mines of Turkish Coal Enterprises are explained. The work was involved manual stopwatch surveys of shovel dig cycle times, estimation of bucket filling and hourly excavation capacity of shovels. The accumulated data is compared with the literature values in order to be evaluated in terms of ease of digging. The observed bucket size ranges of hydraulic and cable shovels varied from 2,5 to 10.5 and 4.5 to 25 yd respectively. The work efficiencies were established by considering observed and net outputs. Furthermore, the performance results were cooperated with geotechnical data to define the ease of digging.