Conical Picks Research Articles

Microwave-Assisted Linear Cutting of Sandstone with a Conical Pick: Experimental Study

Microwave-Assisted Linear Cutting of Sandstone with a Conical Pick: Experimental Study

Hard rock fragmentation by dynamic conical pick indentation under confining pressure

Mechanical mining and excavation in deep metal mines can be regarded as the process of crushing hard rock by conical pick indentation. In this study, a confining pressure loading device was designed and used to carry out dynamic conical pick indentation crushing tests under confining pressure conditions on three types of granite with varying strengths, using the Split Hopkinson Pressure Bar (SHPB). The objective was to quantitatively investigate the effect of confining pressure and rock strength on the indentation crushing characteristics of deep hard rocks. The results indicate that as the confining pressure increases from 5 MPa to 20 MPa, the dimensional parameters such as volume, diameter and depth of the impact groove decrease linearly, while parameters such as the specific energy, indentation force, indentation index and energy utilization rate progressively increase. The increase in the confining pressure inhibits the formation of internal cracks in the rock, enhancing its resistance to pick indentation, which in turn makes rock fragmentation more difficult. This creates unfavorable conditions for efficient rock breaking. Furthermore, rock strength plays a crucial role in the pick indentation process. The higher the rock strength, the greater its resistance to pick indentation, leading to increased energy consumption, accelerated wear of the conical picks, and reduced efficiency in rock breaking.

Laboratory-Scale Limestone Rock Linear Cutting Tests with a Conical Pick: Predicting Optimal Cutting Conditions from Tool Forces

This study introduces a simplified method for predicting the optimal cutting conditions to maximize excavation efficiency based on tool forces. A laboratory-scale linear rock-cutting test was conducted using a conical pick on Finike limestone. The tool forces and their ratios were analyzed in relation to cutting parameters such as penetration depth and spacing. While the cutting force (FC) and normal force (FN) increased with the penetration depth and spacing, this relationship could not predict the optimal cutting conditions. The ratio of the mean normal force to the mean cutting force (FNm/FCm) increased with the penetration depth and the ratio of spacing to penetration depth (s/d). However, even while including this relationship, predicting optimal cutting conditions remained challenging. The ratio of the peak cutting force to the mean cutting force (FCp/FCm) reached a maximum value at a specific s/d, which is similar to the relationship between the specific energy (SE) and s/d. The optimal s/d obtained through the SE methodology was found to be between 3 and 5, and FCp/FCm reached a maximum at s/d. The error between the optimal s/d and the s/d in which FCp/FCm was maximized was less than 5%. Therefore, it was confirmed that the optimal cutting conditions could be predicted through the relationship between FCp/FCm and s/d. Additionally, by using the results from previous studies, the optimal cutting conditions obtained from the SE methodology and the proposed methodology were found to agree within a margin of error of 20%. The proposed methodology can be beneficial for the design of cutter heads and the operation of excavation machines.

A novel prediction method for peak cutting force of curved picks considering lithological tolerances

This study presents a 3D pick-rock contact calculation method for conical picks, aiming to develop a predictive method with high accuracy and lithological tolerance for peak cutting force (PCF). The method is based on the projection profile method and D. L. Sikarskie stress distribution function. By integrating Griffith’s theory with rock damage constitutive model, the energy relationship between the rock fracturing process and crack propagation process is analyzed. Furthermore, in order to accurately correct the PCF, the energy correction function (C-Kf) is proposed to calculate the damage intensity index (Ke), which accounts for the relationship between rock brittleness and rock damage elastic–plastic energy. To validate the method, it is compared with full-scale cutting tests and three existing models, and statistical analysis confirms its high lithological tolerance and accuracy, the present model has the highest R2 of 0.90404, which is at least 12.5% higher relative to the mainstream models. Moreover, incorporating Ke into the method further enhances its predictive capability.

Cutting Characteristics and Reliability Analysis of Conical Picks Containing Prefabricated Grooved Rocks

When a roadheader breaks hard rock in a roadway, the excessive cutting load causes the conical pick to experience abnormal wear, which impacts equipment stability. To improve the reliability of hard rock cutting equipment, the dynamic characteristics of prefabricated grooved rocks during cutting were investigated using a single pick cutting experimental bench in rock crushing experiments, and a conical pick cutting rock breaking finite element model was established. The rock stress state under different cutting depths and spacing conditions was analyzed, and the cutting force and the trend of the change in the specific energy consumption were elucidated. The results show that prefabricated grooves can effectively reduce the cutting load and specific energy consumption, the cutting depth and conical pick–groove spacing are the key factors affecting the cutting characteristics, and a reasonable choice of spacing and depth can help reduce the wear of conical picks and improve the working reliability of roadheaders.

Design and performance of a triaxial load cell for conical picks

Measuring the load on picks in mining operations poses a significant challenge, which hinders the optimization of cutting mechanism design. To address this issue, a unified load measurement model was initially developed using angular transformation. Subsequently, the measuring-point positions were determined based on the principles of large strain and ease of measurement, using Finite Element Analysis. By analyzing the strain law of the measuring-point positions, a sensor layout scheme was designed, which led to the development of a triaxial load cell. Utilizing the piecewise least squares method and BP neural network, the calibration and decoupling were performed. The findings indicated that the BP neural network effectively reduced the error. Finally, cutting experiments were conducted. The error was less than 8 %, effectively identifying the load variation characteristics when cutting materials with different hardness. The results demonstrate that the designed triaxial load cell can accurately and reliably capture cutting loads.

Research on the influence of cutting surface characteristics on the cutting load of the conical pick

Abstract A coal rock cutting model was established using ANSYS/LS-DYNA and the influence of different cutting surfaces was studied. By using the control variable method, simulation experiments are conducted on single and multiple conical picks cutting under the different ratios of cutting spacing to the cutting thickness. The variation pattern of the cutting correlation is obtained. The conclusion is that when the ratio is 2-2.5, there is a significant cutting correlation between adjacent picks, and the conical picks have the best cutting performance. As the ratio increases, the cutting correlation between adjacent picks weakens, which is not conducive to the cutting of the pick. This conclusion has important guiding significance for the design of cutting parameters.

Conforming Capacitive Load Cells for Conical Pick Cutters.

In underground coal mining, machine operators put themselves at risk when getting close to the machine or cutting face to observe the process. To improve the safety and efficiency of machine operators, a cutting force sensor is proposed. A linear cutting machine is used to cut two separate coal samples cast in concrete with conical pick cutters to simulate mining with a continuous miner. Linear and neural network regression models are fit using 100 random 70:30 test/train splits. The normal force exceeds 60 kN during the rock-cutting tests, and it is averaged using a low pass filter with a 10 Hertz cutoff frequency. The sensor uses measurements of the resonant frequency of capacitive cells in a steel case to determine cutting forces. When used in the rock-cutting experiments, the sensor conforms to the tooling and the stiffness and sensitivity are increased compared to the initial configuration. The sensor is able to track the normal force on the conical picks with a mean absolute error less than 6 kN and an R2 score greater than 0.60 using linear regression. A small neural network with a second-order polynomial expansion is able to improve this to a mean absolute error of less than 4 kN and an R2 score of around 0.80. Filtering measurements before regression fitting is explored. This type of sensor could allow operators to assess tool wear and material type using objective force measurements while maintaining a greater distance from the cutting interface.

Research on wear resistance of conical pick based on bionic dimple structure

Heavy equipment such as continuous mining machine and shearer are widely used in coal mining projects, and conical picks are essential cutting tools. The wear resistance of the conical picks directly affects the efficiency and reliability of the equipment. Additionally, when the conical pick cannot rotate properly, severe one-sided wear occurs and accelerates the failure of the conical pick. In this paper, a bionic dimple-structured conical pick is designed, and a mathematical model of the dimple structure is established. The self-rotation and wear resistance characteristics of the Dimple Type Pick (DTP) and the Ordinary Type Pick (OTP) are studied using the discrete element software EDEM and the dynamic analysis software ADAMS. The orthogonal experimental method is used to analyze the friction performance and mechanism of the conical pick surface from aspects such as dimple depth, number, and radius. The results show that the rotational torque of the two types of conical picks increases first and then decreases during the cutting process. The maximum torque of the DTP is 42.67% higher than that of the OTP, which indicates that DTP has better self-rotation performance than OTP. Dimple depth is the main factor affecting DTP wear, followed by the number of dimples, while the impact of dimple radius is minimal. According to the analysis on the response surface, the optimal design parameters of the dimple structure are as follows: the dimple depth is 0.3 mm, the number of dimples is 4, and the radius is 1.5 mm. The wear resistance of the optimized dimple-structured conical pick showed an improvement of 89.82% and 79.04%, compared to the OTP and the DTP. This research provides theoretical and experimental support for the development of wear-resistant and long-life conical picks.

Investigation of combined rock-breaking ability of sawblade and conical pick

To solve the problem of severe wear and low rock-breaking efficiency of a conical pick during rock cutting, a method of rock-breaking using a sawblade and conical pick is proposed, which can improve the rock-breaking ability and efficiency. Test benches for the sawblade rock cutting and conical-pick breaking were established to verify the numerical simulation model and improve the numerical simulation accuracy. The numerical simulation model of sawblade and conical-pick rock-cutting was used to investigate the effect of the cutting parameters on cutting performance. Based on the numerical simulation results of rock-breaking, a prediction model of the cutting force and specific cutting energy consumption for combined rock-breaking with a sawblade and conical pick was developed. This provides a comparative analysis basis for the combined rock-breaking capacity of sawblades and conical picks as well as traditional conical-pick rock-breaking. The results indicate that the cutting force, specific cutting energy consumption, and rock-breaking efficiency of combined rock-breaking with a sawblade and conical pick are better than those of the traditional conical pick. The research results provide a theoretical foundation for applying a combined rock-breaking method to sawblades and conical picks in engineering practice.

Introducing a New Model for Prediction of Mean Cutting Forces Acting on Conical Pick Cutters

Introducing a New Model for Prediction of Mean Cutting Forces Acting on Conical Pick Cutters

Experimental investigation of the failure of conical picks under thermal and abrasive effects

Conical picks are widely used in fields such as tunnel excavation, and high temperatures often occur on the surfaces of conical picks during the hard rock cutting process. To explore the influence of temperature on the wear of conical picks, a rotary cutting test was arranged. The cutting head torque, heat distribution and wear on the conical pick at different rotating speeds and cutting depths were explored. Moreover, the working process with and without cooling liquid was taken into consideration, and the mass losses of the conical pick under those conditions were analyzed. The experimental results showed that under cooling liquid conditions, the maximum temperature on the conical pick decreased by 230°C, and the mean mass loss of the conical pick decreased by 15.8 g. Therefore, high temperature could not be ignored in hard rock cutting. On the basis of these findings, a method for the measurement of rock abrasiveness was proposed in this paper, and different from previous research, the thermal effect was taken into consideration. A test bed for rock abrasiveness measurement was assembled in which a sintered WC-Co rod was used for rotary grinding on the rock sample, and the mass loss of the grinding rod was determined to evaluate the rock abrasiveness. The loading force between the grinding rod and rock sample was considered in the measurement of rock abrasiveness. The results showed that the mass losses of sintered WC-Co rods increased with the loading force. In addition, the characteristics of oxygen found from scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS) showed that peeling and cracking could be found at distances of 5 mm and 10 mm from the end face of the grinding rod, and the increased oxygen content suggested obvious oxidization at those regions as well.

Structure design and service performance of bionic conical pick

Heavy equipment such as continuous mining machines and shearers are widely used in coal mining projects, and conical picks are essential cutting tools. During the cutting process, different conical pick structures can have significant impacts on the cutting performance of the equipment, and the wear resistance of the conical picks will directly affect the efficiency and reliability of the equipment. In this paper, a bionic dimple-structured conical pick is designed, and a mathematical model of the dimple structure is established. The cutting performance, self-rotation performance, and wear resistance of dimple-type picks (DTPs) and ordinary-type picks (OTPs) are studied using the discrete element software EDEM and the dynamic analysis software ADAMS. The results show that during the cutting process, the trend of rotational torque over time for both types of conical picks first increases and then decreases, with the maximum rotational torque of DTP being greater than that of OTP, indicating that the self-rotation performance of DTP is superior to OTP. Compared with OTP, DTP exhibits a smaller total wear amount and better wear resistance performance. When comparing end plates equipped with DTP to those with OTP, the end plates with DTP have a smaller load fluctuation coefficient, lower cutting resistance, lower specific energy consumption for cutting, and greater total coal mass.

Mining Machines for Comprehensive Mechanized Mining of Bauxite

The mining machine for bauxite is the key equipment for the mechanized mining of underground bauxite ore. The mining machines for shearing and loading bauxite ore have been studied in this paper from three aspects: the determination of key technical parameters, the in-situ tests, optimization, and improvement. Mechanical and physical parameters of bauxite ore, such as high tensile strength, no-cleavage, and abrasion properties, have a great impact on the determination of key technical parameters of the mining machine. The conventional conical picks which are widely used in mining equipment drums for soft rock, such as coal mines, are not suitable for bauxite and other high-abrasion ore rocks. The chisel pick is theoretically a better choice. The main faults of the mining machine for bauxite during the in-situ tests are closely related to the high abrasion of bauxite rock, especially for the abrasion of conical picks and the walking actuator of the traction part. So the second-generation mining machine should be optimized from the selection of types, linear speed, and cutting depth of picks, from selecting wear-resistance material for the walking actuator of the traction part and designing a more suitable structure for the walking actuator of the traction part. The research results have important theoretical significance for the design of mining machines for bauxite.

Low-Profile Capacitive Load Cells for Underground Mining Material and Wear Classification to Promote Worker Safety

This work proposes a capacitive load cell for conical picks to enable underground continuous mining machine operators to perform their roles away from known hazardous regions near the machine. The load cell is embedded in commercially available flexible printed circuit board, integrates with the target tooling, and demonstrates in situ force sensing of vibration signatures for continuous mining cutting tools. Changes in material constitution, tool mass, and tool geometry cause modal variations in vibrational response measurable with force sensors at the cutting interface. Time-series measurements are captured during rock cutting tests using a linear cutting machine. These measurements are segmented into small windows, less than 0.25 s, and are preprocessed using the fast Fourier transform, which highlights the modal variations. The transformed measurements are then classified into different material and wear categories using support-vector machines with the radial basis function kernel. Different normalization schemes and Fourier transform methods are tested for signal preprocessing. Results show that the power spectral density measurements with normally distributed coefficients give good results for material classification, while the normalized time-domain measurements give better results for wear classification. Under laboratory conditions, this technique is shown to classify material and wear categories with F1 score above 0.85 out of 1.0 for our experiment. This technology could be used to assist operators in assessing material and wear conditions from a safer distance. It has applications in the coal mining industry as well as other applications which use conical picks such as road milling.

A novel method for reducing the amount of dust produced by roadheaders based on the numerical simulation of coal breakage

Dust pollution is a serious environmental hazard during the tunneling in coal mines. Despite the presented dust control technologies, the method of reducing dust production has not been adequately investigated. This paper conducted cutting tests with various tip angles and attack angles using numerical models. A novel method for reducing the production of dust, based on the simulation results, was proposed and verified in the field experiments. The cutting force, work and crack extensions were analyzed. The concentrations of dust in laboratory tests were linked to the simulation results. The simulated results showed that the conical pick with a large tip angle could increase the cutting force and work and cause more cracks. The attack angle had a negative relation with the cutting force and work. The field experiments suggested that the amount of dust could be significantly reduced by using conical picks with a small tip angle. A slower rotation speed of the cutting head could alleviate dust hazards. The results are of momentous relevance for mine managers and researchers to reduce the production of dust during tunneling and control the dust more efficient.

Estimating the mean cutting force of conical picks using random forest with salp swarm algorithm

Conical picks are widely used as cutting tools in shearers and roadheaders, and the mean cutting force (MCF) is one of the important parameters affecting conical pick performance. As MCF depends on a number of parameters and due to that the existing empirical and theoretical formulas and numerical modelling are not sufficient enough and reliable to predict MCF in a proficient manner. So, in this research, a novel intelligent model based on a random forest algorithm (RF) and a heuristic algorithm called the salp swarm algorithm (SSA) have been applied to determine the optimal hyper-parameters in RF, and root mean square error is used as a fitness function. A total of 188 data samples including 50 rock types and seven parameters (tensile strength of the rock σt, compressive strength of the rock σc, cone angle θ, cutting depth d, attack angle γ, rake angle α and back-clearance angle β) were collected to develop an SSA-RF model for mean cutting force prediction. The prediction results of the SSA-RF model were compared with seven influential formulas and four classical models, such as random forest, extreme learning machine, support vector machine and radial basis function neural network. The mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and Pearson correlation coefficient (R2) were employed as evaluation indexes to compare the capability of different predicting models. The MAE (0.509 and 0.996), RMSE (0.882 and 1.165), MAPE (0.146 and 0.402) and R2 (0.975 and 0.910) values between measured and predicted MCF for training and testing phases of the SSA-RF model clearly demonstrate the superiority in prediction compared to the other tools. A sensitivity analysis has also been performed to understand the influence of each input parameter on MCF, which indicates that σc, d and σt are the most important variables for MCF prediction.

Mass and Volumetric Abrasive Wear Measurements of the Mining Conical Picks

The wearing of cutting tools is a bottleneck of many branches in the industry. However, the tools used in the mining sector are extraordinarily prone to rapid deterioration since many rocks exhibit aggressive abrasive properties. A typical example of a fast wearing cutting tool is a conical pick. It is used in the mining industry and other businesses requiring rock cutting, such as in roadworks and tunnelling. Both manufacturers and users attempt to find a way to enhance the lifespan of the working surface of conical picks via different approaches, namely heat treatment, chemical treatment, work hardening, and hardfacing, etc. To correctly estimate the resistance to abrasive wear for a particular conical pick, one must select appropriate procedures and methods. By this time, the most common estimation method is to measure the mass loss before and after cutting, preserving the specified and constant conditions. This method was developed for users (mines) and manufacturers of cutting tools, especially conical picks. Alternative methods of assessing the picks’ wear are also sought. In this paper, the authors perform additional volumetric loss measurements via a photogrammetric approach, which results in a 3D scan of brand-new and exploited conical pick. Three different sets of four picks were measured both in the domain of mass loss and volume loss, and the results were compared. Slight differences in parameters C2 and C3 were found. Additionally, the authors enclose recommendations regarding the proper use of the methods mentioned above, mainly focusing on the ability to perform linear and angular measurements of the tool performed on the 3D scan.

Methods and Test Benches for Cutting Tools Testing—A Review

Mechanical mining is a widely used method of separating materials from the face to obtain a useful mineral (e.g., coal, metal ores, salts, and diamonds), to make underground workings (e.g., mine galleries, tunnels, and underground garages), level roads, shape slopes, or to dig ditches. Mechanical mining is applied in the mining branch, tunnelling, road, and construction industries. Depending on the mechanical properties of the rocks, most frequently described by uniaxial compression strength, various machines and tools are used. The methods of mining high-strength abrasive rocks that have been used and developed in recent years are particularly applicable to the mining of copper, gold, tungsten, platinum ores, diamond deposits, and tunnelling. In addition to rock strength, the effectiveness of the mining process is affected by abrasiveness, which influences the rate of abrasive tool wear. Therefore, in various research and development centres, but also in production companies, tools are tested on unique stands. Tests are carried out to determine the cutting resistance and assess the wear rate. This article reviews methods and benches for testing mining tools, conical picks, and discs. Various solutions for testing single tools and cutting heads have been presented. The analysis conducted has revealed that despite the large number and great diversity of different test benches, there are no appropriate methods and stands for testing the wear rate of materials intended for mining tools.

Investigation of the Influence of Cutting Parameters on Conical Pick Cutting Performance and Rock Damage

Conical picks are applied to rock breaking, and the cutting parameters greatly influence cutting performance and rock damage. A conical pick rock-cutting numerical simulation model and software to provide a quantitative analysis of rock damage are established to research the influence of cutting parameters on cutting force and rock damage. The research results indicated that the average peak cutting force decreases with an increased cutting angle, and the average peak cutting force increases with a decreased cutting speed. The average peak cutting force of the second conical pick increases as the distance between double conical picks increases in the process of rock-cutting with double conical picks. There is a positive correlation between the volume of rock damage, the volume of rock breaking, and the cutting force of the conical pick. The research results provide a reference for optimizing the cutting parameters of conical picks.