Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

High-Speed Permanent Magnet Electrical Machines - Applications, Key Issues and Challenges

In this paper,application examples of high-speed electrical machines are presented,and the machine structures are categorized.Key issues of design and control for the high-speed permanent magnet machines are reviewed,including bearings selection,rotor dynamics analysis and design,rotor stress analysis and protection,thermal analysis and design,electromagnetic losses analysis and reduction,sensorless control strategies,as well as comparison and selection of sine-wave and square-wave drive modes.Some challenges are also discussed,so that future studies could be focused.

Study on temperature field of the drilling machine during the course of drilling in coal mine

The working conditions of the MK-3 type full hydraulic tunnel drilling machine during the course of drilling were analyzed. Based on the energy balance governing equations for the drill rod, the temperature field of drill rod at the normal and non-normal working conditions was numerically obtained. The numerical results show that the maximum temperature at the head of drill rod under the normal working circumstance is insufficient to ignite the gas. But under the non-normal working condition, the local high temperature can ignite the gas easily and cause the fire. In order to prevent the gas fire, the occurrence of the non-normal operating condition must be prevented as far as possible during the drilling.

Calculation for Stator Loss of High-Speed Permanent Magnet Synchronous Machine in Torque-speed Envelope and Restraint Approach for Circulating Current in Windings

Iron loss and copper loss are the significant parts of electrical loss of machines,which are the major parts particularly under high frequency condition.High-speed permanent magnet synchronous machines(HS-PMSM)have the benefits of high power density,high efficiency and wide speed range.Which causes the calculation for iron loss and copper loss in whole operating range complex.By analyzing the components and influencing factors of iron loss and copper loss in stator,we have deduced the calculation formula of iron loss and copper loss in whole operating range based on the analytical solution and finite element approach(EFA)solution.According to the calculation solution,taking the influence of operating temperature on the iron loss and copper loss into account,we propose a temperature correction factor and establish the calculation method for the iron loss and copper loss with temperature influences.Finally,by the conductor transposition,we restrain the circulating current under high-frequency operating condition.

Development and Application of Complete Equipment for High-speed Tunnel Boring and Bolting Machines

With the improvement of coal mining speed and mechanization level in China,traditional tunnel boring methods can no longer meet the actual needs.In order to solve the problems of low efficiency,high labor intensity,slow tunnel boring speed,bad working environment and poor safety in traditional tunnel boring,on the basis of analyzing the development and application of coal roadway tunnel boring equipment at home and abroad,complete equipment for high-speed tunnel boring and bolting machines was developed by using the integrated technology of tunnel boring and bolting.The complete equipment for high-speed tunnel boring and bolting machines has the functions of tunnel boring and bolting synchronization,once-tunneling,negative pressure dust removal,digital guidance,independent cutting feed,digital cutting,safety monitoring and data interaction,which has the advantages of safety in use,reliability and efficiency.

Continuous prediction method of earthquake early warning magnitude for high-speed railway based on support vector machine

Purpose–Using the strong motion data ofK-net in Japan,the continuous magnitude prediction method based on support vector machine(SVM)was studied.Design/methodology/approach–In the range of 0.5–10.0 s after the P-wave arrival,the prediction time window was established at an interval of 0.5 s.12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning(EEW)magnitude prediction model(SVM-HRM)for high-speed railway based on SVM.Findings–The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm.Results show that at the 3.0 s time window,themagnitude prediction error of the SVM-HRMmodel is obviously smaller than that of the traditionalτc method and Pd method.The overestimation of small earthquakes is obviously improved,and the construction of the model is not affected by epicenter distance,so it has generalization performance.For earthquake events with themagnitude range of 3–5,the single station realization rate of the SVM-HRMmodel reaches 95%at 0.5 s after the arrival of P-wave,which is better than the first alarm realization rate norm required by“The TestMethod of EEW andMonitoring Systemfor High-Speed Railway.”For earthquake eventswithmagnitudes ranging from3 to 5,5 to 7 and 7 to 8,the single station realization rate of the SVM-HRM model is at 0.5 s,1.5 s and 0.5 s after the P-wave arrival,respectively,which is better than the realization rate norm of multiple stations.Originality/value–At the latest,1.5 s after the P-wave arrival,the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate,which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction.

An Optimal Feed Interpolator Based on G^2 Continuous Bézier Curves for High-Speed Machining of Linear Tool Path

A numerical control (NC) tool path of digital CAD model is widely generated as a set of short line segments in machining. However, there are three shortcomings in the linear tool path, such as discontinuities of tangency and curvature, huge number of line segments, and short lengths of line segments. These disadvantages hinder the development of high speed machining. To smooth the linear tool path and improve machining efficiency of short line segments, this paper presents an optimal feed interpolator based on G^2 continuous Bézier curves for the linear tool path. First, the areas suitable for fitting are screened out based on the geometric characteristics of continuous short segments (CSSs). CSSs in every area are compressed and fitted into a G^2 Continuous Bézier curve by using the least square method. Then a series of cubic Bézier curves are generated. However, the junction between adjacent Bézier curves is only G^0 continuous. By adjusting the control points and inserting Bézier transition curves between adjacent Bézier curves, the G^2 continuous tool path is constructed. The fitting error is estimated by the second-order Taylor formula. Without iteration, the fitting algorithm can be implemented in real-time environment. Second, the optimal feed interpolator considering the comprehensive constraints (such as the chord error constraint, the maximum normal acceleration, servo capacity of each axis, etc.) is proposed. Simulation and experiment are conducted. The results shows that the proposed method can generate smooth path, decrease the amount of segments and reduce machining time for machining of linear tool path. The proposed research provides an effective method for high-speed machining of complex 2-D/3-D profiles described by short line segments.

A BiGRU joint optimized attention network for recognition of drilling conditions

The identification and recording of drilling conditions are crucial for ensuring drilling safety and efficiency. However, the traditional approach of relying on the subjective determination of drilling masters based on experience formulas is slow and not suitable for rapid drilling. In this paper, we propose a drilling condition classification method based on a neural network model. The model uses an improved Bidirectional Gated Recurrent Unit (BiGRU) combined with an attention mechanism to accurately classify seven common drilling conditions simultaneously, achieving an average accuracy of 91.63%. The model also demonstrates excellent generalization ability, real-time performance, and accuracy, making it suitable for actual production. Additionally, the model has excellent expandability, which enhances its potential for further application.

Machine learning for fault diagnosis of high-speed train traction systems: A review

High-speed trains(HSTs)have the advantages of comfort,efficiency,and convenience and have gradually become the mainstream means of transportation.As the operating scale of HSTs continues to increase,ensuring their safety and reliability has become more imperative.As the core component of HST,the reliability of the traction system has a substantially influence on the train.During the long-term operation of HSTs,the core components of the traction system will inevitably experience different degrees of performance degradation and cause various failures,thus threatening the running safety of the train.Therefore,performing fault monitoring and diagnosis on the traction system of the HST is necessary.In recent years,machine learning has been widely used in various pattern recognition tasks and has demonstrated an excellent performance in traction system fault diagnosis.Machine learning has made considerably advancements in traction system fault diagnosis;however,a comprehensive systematic review is still lacking in this field.This paper primarily aims to review the research and application of machine learning in the field of traction system fault diagnosis and assumes the future development blueprint.First,the structure and function of the HST traction system are briefly introduced.Then,the research and application of machine learning in traction system fault diagnosis are comprehensively and systematically reviewed.Finally,the challenges for accurate fault diagnosis under actual operating conditions are revealed,and the future research trends of machine learning in traction systems are discussed.

Heterogeneity identification method for surrounding rock of large-section rock tunnel faces based on support vector machine

Purpose–The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.Design/methodology/approach–Relying on the support vector machine(SVM)-based classification model,the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face,and the identification calculation was carried out for the five test tunnels.Then,the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.Findings–The results show that compared with the two classification models based on neural networks,the SVM-based classification model has a higher classification accuracy when the sample size is small,and the average accuracy can reach 87.9%.After the samples are replaced,the SVM-based classification model can still reach the same accuracy,whose generalization ability is stronger.Originality/value–By applying the identification method described in this paper,the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified,and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting,and can provide a basis for local optimization of support parameters.

Development of High-speed Machining Database with Case-based Reasoning

Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very important role in the implementation of high-speed machining technology. The case-based reasoning is used in the developing of high-speed machining database to overcome the shortage of available high-speed cutting parameters in machining data handbooks and shop floors. The high-speed machining database developed in this paper includes two main components: the machining database and the case-base. The machining database stores the cutting parameters, cutting tool data, work pieces and their materials data, and other relative data, while the case-base stores mainly the successfully solved cases that are problems of work pieces and their machining. The case description and case retrieval methods are described to establish the case-based reasoning high-speed machining database. With the case retrieval method, some succeeded cases similar to the new machining problem can be retrieved from the case-base. The solution of the most matched case is evaluated and modified, and then it is regarded as the proposed solution to the new machining problem. After verification, the problem and its solution are packed up into a new case, and are stored in the case-base for future applications.

A Novel Half-Bridge Power Supply for High Speed Drilling Electrical Discharge Machining

High Speed Drilling Electrical Discharge Machining (HSDEDM) uses controlled electric sparks to erode the metal in a work-piece. Through the years, HSDEDM process has widely been used in high speed drilling and in manufacturing large aspect ratio holes for hard-to-machine material. The power supplies of HSDEDM providing high power applica-tions can have different topologies. In this paper, a novel Pulsed-Width-Modulated (PWM) half-bridge HSDEDM power supply that achieves Zero-Voltage-Switching (ZVS) for switches and Zero-Current-Switching (ZCS) for the dis-charge gap has been developed. This power supply has excellent features that include minimal component count and inherent protection under short circuit conditions. This topology has an energy conservation feature and removes the need for output bulk capacitors and resistances. Energy used in the erosion process will be controlled by the switched IGBTs in the half-bridge network and be transferred to the gap between the tool and work-piece. The relative tool wear and machining speed of our proposed topology have been compared with that of a normal power supply with current limiting resistances.

Evaluation of the local inflammatory stress response and pain mediator secretion after impacted wisdom tooth extraction with high-speed turbine drill combined with original luxator

Objective: To study the local inflammatory stress response and pain mediator secretion after impacted wisdom tooth extraction with high-speed turbine drill combined with original luxator. Methods: Patients who received impacted wisdom tooth extraction in the First People's Hospital ofYunnan Province between March 2014 and June 2017 were selected as the research objects and randomly divided into the observation group who accepted impacted wisdom tooth extraction with high-speed turbine drill combined with original luxator and the control group who accepted impacted wisdom tooth extraction with traditional chisel. The contents of inflammatory mediators, stress mediators and pain mediators in gingival crevicular fluid were measured before surgery and 3 days after surgery. Results: Three days after surgery, PTX3, ICAM1, MPO, PGE2, PPARγ, ROS, MDA, 5-HT, CGRP, SP, Gal and ATP contents in gingival crevicular fluid of both groups were higher than those before surgery whereas GPx and T-AOC contents were significantly lower than those before surgery, and PTX3, ICAM1, MPO, PGE2, PPARγ, ROS, MDA, 5-HT, CGRP, SP, Gal and ATP contents in gingival crevicular fluid of observation group were lower than those of control group whereas GPx and T-AOC contents were significantly higher than those of control group. Conclusions: The impacted wisdom tooth extraction with high-speed turbine drill combined with original luxator can reduce the local inflammatory stress response and inhibit the secretion of pain mediators.

Evaluation of the energy efficiency of rotary percussive drilling using dimensionless energy index

This paper sets forth a geomechanics framework for assessing the energy efficiency of rotary percussive drilling using the energy criterion, which has been proposed by Victor Oparin for volumetric destruction of high-stress rocks having nonuniform physico-mechanical properties. We review the long-term research and development in the specified area of science and technology, including research and development projects implemented at the Institute of Mining, Siberian Branch of the Russian Academy of Sciences. A new modified expression of Oparin’s dimensionless energy criterion of volumetric rock destruction k is introduced. The range of in situ values is determined for the energy criterion of volumetric rock destruction at the optimized energy efficiency of rotary percussive drilling. The temporospatial intervals of geotechnical monitoring are found to control pneumatic drilling energy efficiency at subsoil use objects in Russia. The integrated experimental, theoretical and geotechnical approach to the comprehensive investigation of real-time processes of rock fracture in rotary percussive drilling using the energy concept possesses the necessary geomechanical performance-and-technology potential to create the next level geotechnical monitoring of drilling systems for various purposes, including determination of physico-mechanical properties and the stress-strain analysis of rock mass in full-scale drilling.

Research Progress of Key Technology of High-Speed and High Precision Motorized Spindles

High speed machining and high precision machining are two tendencies of themanufacturing technology worldwide. The motorized spindle is the core component of the machine toolsfor achieving the high speed and high precise machining, which affects the general developmentlevel of the machine tools to a great extent. Progress of the key techniques is reviewed in thispaper, in which the high speed and high precision spindle bearings, the dynamical and thermalcharacteristics of spindles, the design technique of the high frequency motors and the drivers, theanti-electromagnetic damage technique of the motors, and the machining and assembling technique areinvolved. Finally, tha development tendencies of the motorized spindles are presented.

Failure mode change and material damage with varied machining speeds:a review

High-speed machining(HSM) has been studied for several decades and has potential application in various industries, including the automobile and aerospace industries. However,the underlying mechanisms of HSM have not been formally reviewed thus far. This article focuses on the solid mechanics framework of adiabatic shear band(ASB) onset and material metallurgical microstructural evolutions in HSM. The ASB onset is described using partial differential systems. Several factors in HSM were considered in the systems, and the ASB onset conditions were obtained by solving these systems or applying the perturbation method to the systems. With increasing machining speed, an ASB can be depressed and further eliminated by shock pressure. The damage observed in HSM exhibits common features. Equiaxed fine grains produced by dynamic recrystallization widely cause damage to ductile materials, and amorphization is the common microstructural evolution in brittle materials. Based on previous studies, potential mechanisms for the phenomena in HSM are proposed. These include the thickness variation of the white layer of ductile materials. These proposed mechanisms would be beneficial to deeply understanding the various phenomena in HSM.

Energy field-assisted high-speed dry milling green machining technology for difficult-to-machine metal materials

Energy field-assisted machining technology has the potential to overcome the limitations of machining difficult-to-machine metal materials,such as poor machinability,low cutting efficiency,and high energy consumption.High-speed dry milling has emerged as a typical green processing technology due to its high processing efficiency and avoidance of cutting fluids.However,the lack of necessary cooling and lubrication in high-speed dry milling makes it difficult to meet the continuous milling requirements for difficult-to-machine metal materials.The introduction of advanced energy-field-assisted green processing technology can improve the machinability of such metallic materials and achieve efficient precision manufacturing,making it a focus of academic and industrial research.In this review,the characteristics and limitations of high-speed dry milling of difficult-to-machine metal materials,including titanium alloys,nickel-based alloys,and high-strength steel,are systematically explored.The laser energy field,ultrasonic energy field,and cryogenic minimum quantity lubrication energy fields are introduced.By analyzing the effects of changing the energy field and cutting parameters on tool wear,chip morphology,cutting force,temperature,and surface quality of the workpiece during milling,the superiority of energy-field-assisted milling of difficult-to-machine metal materials is demonstrated.Finally,the shortcomings and technical challenges of energy-field-assisted milling are summarized in detail,providing feasible ideas for realizing multi-energy field collaborative green machining of difficult-to-machine metal materials in the future.

Optimization of Parameters CO<SUB>2</SUB>Laser for Drilling Different Types of Glass

The aim of this work is to study in detail the drilling process on glass by CO2 laser. The study parameters considered in the present experiments are based on the laser beam power of range (30% - 80% of 25 W) and an exposure time for drilling (2 - 8 s). The measured diameters of holes by optical methods are between [300 - 800 μm]. The results obtained by optical observations suggest that ordinary and mineral glasses cannot withstand to a contact of the laser beam and crack during the formation of the drilling hole. The minimum power and duration of exposure are the optimal parameters for drilling the organic glass, we observe no micro-cracks, and again we see that the edges of the holes have a good surface quality with a high aspect ratio.

Positioning of Screw Holes Group Based on Digital Camera and Digital Control Drilling

Positioning of screw holes is an important production procedure for steel construction connecting with bolts. In this paper, a new production method is presented, in which the digital camera is used for taking pictures of screw holes and other techniques are advanced. This paper also indicates that the pixels of CCD chip in photogrammetry should be chosen as all geometric units in an image, such as interior elements and all kinds of distortions. The measure can also simplify the camera calibration for determining the size of non-square pixel.

RESEARCH ON THE ADAPTIVE CONTROL OF DRILLING PROCESS

A self-tuning adaptive controller is presented which is used for the adaptive control (AC) of drlling process. The parameters of the controller can be regulated in-processly by on line system identification, so as to fit the variation of the cutting conditions. This control method has been successfully applied to the adaptive control of drilling process. The experimental results indicate that the controller has the ability to adapt to the variation of the cutting process parameters and is good in performance.