Instability mechanism of mining roadway passing through fault at different angles in kilometre-deep mine and control measures of roof cutting and NPR cables

The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.

Stability control measures for roof cutting and NPR supporting of mining roadways in fault areas of kilometre-deep coal mine

The study focuses on the stability control measures for mining roadways in fault zones of deep mines,using Daqiang Coal Mine as a case study.The control system under consideration,referred to as"pre-splitting cutting roof+NPR anchor cable"(PSCR-NPR),is subjected to scrutiny through theoretical analysis,numerical modelling,and field trials.Furthermore,a comprehensive analysis is undertaken to evaluate the stability control mechanism of this particular technology.The study provides evidence that the utilization of deep-hole directional energy-concentrated blasting facilitates the attainment of directional roof cutting in roadways.The aforementioned procedure leads to the formation of a uniform structural surface on the roof of the roadway and causes modifications in the surrounding geological formation.The examination of the lateral abutment pressure and shear stress distribution,both prior to and subsequent to roof cutting,indicates that the implementation of pre-splitting techniques leads to a noteworthy reduction in pressure.The proposition of incorporating the safety factor Q for roof cutting height is suggested as a method to augment comprehension of the pressure relief phenomenon in the field of engineering.The analysis of numerical simulation has indicated that the optimal pressure relief effect of a mining roadway in a fault area is attained when the value of Q is 1.8.The NPR anchor cable exhibits noteworthy characteristics,including a high level of prestress,continuous resistance,and substantial deformation.After the excavation of the roadway,a notable reduction in radial stress occurs,leading to the reinstatement of the three-phase stress state in the surrounding rock.This restoration is attributed to the substantial prestress exerted on the radial stress.The termination point of the NPR anchor cable is strategically positioned within a stable rock formation,allowing for the utilization of the mechanical characteristics of the deep stable rock mass.This positioning serves to improve the load-bearing capacity of the surrounding rock.The mining roadway within the fault region of Daqiang Coal Mine is outfitted with the PSCR-NPR technology.The drop in shear stress experienced by the rock surrounding the roadway is estimated to be around 30%,whilst the low-stress region of the mining roadway extends by a factor of approximately 5.5.The magnitude of surface displacement convergence experiences a decrease of approximately 45%-50%.The study’s findings provide useful insights regarding the stable of mining roadway in characterized by fault zones.

Evaluation of roof cutting by directionally single cracking technique in automatic roadway formation for thick coal seam mining

Automatic roadway formation by roof cutting is a sustainable nonpillar mining method that has the potential to increase coal recovery,reduce roadway excavation and improve mining safety.In this method,roof cutting is the key process for stress relief,which significantly affects the stability of the formed roadway.This paper presents a directionally single cracking(DSC)technique for roof cutting with considerations of rock properties.The mechanism of the DSC technique was investi-gated by explicit finite element analyses.The DSC technique and roof cutting parameters were evaluated by discrete element simulation and field experiment.On this basis,the optimized DSC technique was tested in the field.The results indicate that the DSC technique could effectively control the blast-induced stress distribution and crack propagation in the roof rock,thus,achieve directionally single cracking on the roadway roof.The DsC technique for roof cutting with optimized parameters could effectively reduce the deformation and improve the stability of the formed roadway.Field engineering application verified the feasibility and effectiveness of the evaluated DSC technique for roof cutting.

Assessing cutter-rock interaction during TBM tunnelling in granite:Large-scale standing rotary cutting tests and 3D DEM simulations

The widespread utilisation of tunnel boring machines(TBMs)in underground construction engineering requires a detailed investigation of the cutter-rock interaction.In this paper,we conduct a series of largescale standing rotary cutting tests on granite in conjunction with high-fidelity numerical simulations based on a particle-type discrete element method(DEM)to explore the effects of key cutting parameters on the TBM cutter performance and the distribution of cutter-rock contact stresses.The assessment results of cutter performance obtained from the cutting tests and numerical simulations reveal similar dependencies on the key cutting parameters.More specifically,the normal and rolling forces exhibit a positive correlation with penetration but are slightly influenced by the cutting radius.In contrast,the side force decreases as the cutting radius increases.Additionally,the side force shows a positive relationship with the penetration for smaller cutting radii but tends to become negative as the cutting radius increases.The cutter's relative effectiveness in rock breaking is significantly impacted by the penetration but shows little dependency on the cutting radius.Consequently,an optimal penetration is identified,leading to a low boreability index and specific energy.A combined Hertz-Weibull function is developed to fit the cutter-rock contact stress distribution obtained in DEM simulations,whereby an improved CSM(Colorado School of Mines)model is proposed by replacing the original monotonic cutting force distribution with this combined Hertz-Weibull model.The proposed model outperforms the original CSM model as demonstrated by a comparison of the estimated cutting forces with those from the tests/simulations.The findings from this work that advance our understanding of TBM cutter performance have important implications for improving the efficiency and reliability of TBM tunnelling in granite.

Ground response and failure mechanism of gob-side entry by roof cutting with hard main roof

This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensive field measurement program was conducted to determine entry deformation,roof fracture zone,and anchor bolt(cable)loading.The results indicate that GSERC deformation presents asymmetric characteristics.The maximum convergence near roof cutting side is 458 mm during the primary use process and 1120 mm during the secondary reuse process.The entry deformation is closely associated with the primary development stage,primary use stage,and secondary reuse stage.The key block movement of roof cutting structure,a complex stress environment,and a mismatch in the supporting design scheme are the failure mechanism of GSERC.A controlling ideology for mining states,including regional and stage divisions,was proposed.Both dynamic and permanent support schemes have been implemented in the field.Engineering practice results indicate that the new support scheme can efficiently ensure long-term entry safety and could be a reliable approach for other engineering practices.

Dynamic evaluation of digital and green development policies based on text mining of the PMC framework

Aiming to identify policy topics and their evolutionary logic that enhance the digital and green development(dual development)of traditional manufacturing enterprises,address weaknesses in current policies,and provide resources for refining dual development policies,a total of 15954 dual development-related policies issued by national and various departmental authorities in China from January 2000 to August 2023 were analyzed.Based on topic modeling techniques and the policy modeling consistency(PMC)framework,the evolution of policy topics was visualized,and a dynamic assessment of the policies was conducted.The results show that the digital and green development policy framework is progressively refined,and the governance philosophy shifts from a“regulatory government”paradigm to a“service-oriented government”.The support pattern evolves from“dispersed matching”to“integrated symbiosis”.However,there are still significant deficiencies in departmental cooperation,balanced measures,coordinated links,and multi-stakeholder participation.Future policy improvements should,therefore,focus on guiding multi-stakeholder participation,enhancing public demand orientation,and addressing the entire value chain.These steps aim to create an open and shared digital industry ecosystem to promote the coordinated dual development of traditional manufacturing enterprises.

Longwall mining “cutting cantilever beam theory” and 110 mining method in China——The third mining science innovation

With the third innovation in science and technology worldwide, China has also experienced thismarvelous progress. Concerning the longwall mining in China, the ＂masonry beam theory＂ （MBT） wasfirst proposed in the 1960s, illustrating that the transmission and equilibrium method of overburdenpressure using reserved coal pillar in mined-out areas can be realized. This forms the so-called ＂121mining method＂, which lays a solid foundation for development of mining science and technology inChina. The ＂transfer rock beam theory＂ （TRBT） proposed in the 1980s gives a further understanding forthe transmission path of stope overburden pressure and pressure distribution in high-stress areas. In thisregard, the advanced 121 mining method was proposed with smaller coal pillar for excavation design,making significant contributions to improvement of the coal recovery rate in that era. In the 21st century,the traditional mining technologies faced great challenges and, under the theoretical developmentspioneered by Profs. Minggao Qian and Zhenqi Song, the ＂cutting cantilever beam theory＂ （CCBT） wasproposed in 2008. After that the 110 mining method is formulated subsequently, namely one stope face,after the first mining cycle, needs one advanced gateway excavation, while the other one is automaticallyformed during the last mining cycle without coal pillars left in the mining area. This method can beimplemented using the CCBT by incorporating the key technologies, including the directional presplittingroof cutting, constant resistance and large deformation （CRLD） bolt/anchor supporting systemwith negative Poisson＇s ratio （NPR） effect material, and remote real-time monitoring technology. TheCCBT and 110 mining method will provide the theoretical and technical basis for the development ofmining industry in China.

Optimum cutting speed of block-cutting machines in natural stones for energy saving

Energy consumption of block-cutting machines represents a major cost item in the processing of travertines and other natural stones. Therefore, determining the optimum sawing conditions for a particular stone is of major importance in the natural stone-processing industry. An experimental study was carried out utilizing a fully instrumented block-cutter to investigate the sawing performances of five different types of travertine blocks during cutting with a circular diamond saw. The sawing tests were performed in the down-cutting mode. Performance measurements were determined by measuring the cutting speed and energy consumption. Then, specific energy was determined. The one main cutting parameter, cutting speed, was varied in the investigation of optimum cutting performance. Furthermore, some physico-mechanical properties of file travertine blocks were determined in the laboratory. As a result, it is found that the energy consumption （specific energy） of block cutting machines is highly affected by cutting speed. It is determined that specific energy value usually decreases when cutting speed increases. When the cutting speed is higher than the determined value, the diamond saw can become stuck in the travertine block; this situation can be a problem for the block-cutting machine. As a result, the optimum cutting speed obtained for the travertine mines examined is approximately 1.5-2.0 m/min.

Support Vector Machines(SVM)-Markov Chain Prediction Model of Mining Water Inflow

This study was conducted to establish a Support Vector Machines(SVM)-Markov Chain prediction model for prediction of mining water inflow. According to the raw data sequence, the Support Vector Machines(SVM) model was built, and then revised by means of a Markov state change probability matrix. Through dividing the state and analyzing absolute errors and relative errors and other indexes of the measured value and the fitted value of SVM, the prediction results were improved. Finally,the model was used to calculate relative errors. Through predicting and analyzing mining water inflow, the prediction results of the model were satisfactory. The results of this study enlarge the application scope of the Support Vector Machines(SVM) prediction model and provide a new method for scientific forecasting water inflow in coal mining.

Evaluating performance of cutting machines during sawing dimension stones

The performance of cutting machines in terms of energy consumption and vibration directly affects the production costs. In this work, our aim was to evaluate the performance of cutting machines using hybrid intelligent models. For this purpose, a systematic experimental work was performed. A database of the carbonate and granite rocks was established, in which the physical and mechanical properties of these rocks (i.e., UCS, elastic modulus, Mohs hardness, and Schmiazek abrasivity factor) and the operational parameters (i.e., depth of cut and feed rate) were considered as the input parameters. The predictive models were developed incorporating a combination of the multi-layered perceptron artificial neural networks and genetic algorithm (GANN-BP) and the support vector regression method and Cuckoo optimization algorithm (COA-SVR). The results obtained indicated that the performance of the developed GANN-BP and COA-SVR models was close to each other and that these models had good agreements with the measured values. These results also showed that these proposed models were suitable tools in evaluating the performance of cutting machines.

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.

Analysis of the dominant diseases and clinical application characteristics of traditional Chinese cutting therapy based on data mining technology

Objective: To analyze the advantages of Traditional Chinese Cutting Therapy at the present stage and the characteristics of clinical research and application, so as to provide a basis for clinical treatment and research. Methods: Search the Chinese and English databases of relevant literatures on Traditional Chinese Cutting Therapy, and make statistics and Analysis on the distribution, types, distribution, indications and dominant diseases, the number of cases, clinical efficiency, intervention measures and operation sites of the published literatures. Results: A total of 311 articles were included. There are 40 indications for Traditional Chinese Cutting Therapy at this stage. The dominant diseases are psoriasis, asthma, facial paralysis, rhinitis, neurodermatitis, facial neuritis, chloasma, acne, migraine and insomnia. Traditional Chinese Cutting Therapy is closely related to meridian theory. At present, there are few theoretical and basic studies, the quality of relevant clinical studies is low, and the writing standard of research reports is inadequate. Conclusion: At present, the indications of Traditional Chinese Cutting Therapy are extensive, and the dominant diseases are concentrated, with dermatological diseases and neurological diseases as the main diseases. In the future, we should increase theoretical research and basic research, attach importance to the combination of meridian theory and Traditional Chinese Cutting Therapy, and standardize the implementation of clinical research and the writing of reports.

Cutting Force Fluctuation Suppression and Error Homogenization of Noncircular Gear Hobbing Based on the Tool Shifting Method

The current research on noncircular hobbing mainly focuses on the linkage model and motion realization.However,the intermittent cutting characteristics of hobbing would increase uncertainties in the manufacturing process.In this paper,a hobbing machining model with tool-shifting characteristics was proposed to solve the problems of cutting force fluctuation and inconsistency of tooth profile envelope accuracy at different positions of the pitch curve in noncircular gear hobbing.Based on the unit cutting force coefficient method,the undeformed chip volume generated by interrupted cutting was used to characterize the fluctuation trend of the hobbing force.The fluctuation characteristics of the cutting force generated by different hobbing models were compared and analyzed.Using the equivalent gear tooth and hob slotting numbers,an analysis model of the tooth profile envelope error of the noncircular gear was constructed.Subsequently,the tooth profile envelope errors at different positions of the pitch curve were compared and analyzed based on the constructed model.The transmission structure of the electronic gearbox was constructed based on the proposed hobbing model,and the hobbing experiment was conducted based on the selfdeveloped noncircular gear CNC hobbing system.This paper proposes a hobbing method that can effectively suppress the fluctuation of the peak and whole circumference cutting force and reduce the maximum envelope error of the whole circumference gear teeth.

Machine Vision Based Fish Cutting Point Prediction for Target Weight

Food processing companies pursue the distribution of ingredientsthat were packaged according to a certain weight. Particularly, foods like fishare highly demanded and supplied. However, despite the high quantity offish to be supplied, most seafood processing companies have yet to installautomation equipment. Such absence of automation equipment for seafoodprocessing incurs a considerable cost regarding labor force, economy, andtime. Moreover, workers responsible for fish processing are exposed to risksbecause fish processing tasks require the use of dangerous tools, such aspower saws or knives. To solve these problems observed in the fish processingfield, this study proposed a fish cutting point prediction method based onAI machine vision and target weight. The proposed method performs threedimensional(3D) modeling of a fish’s form based on image processing techniquesand partitioned random sample consensus (RANSAC) and extracts 3Dfeature information. Then, it generates a neural network model for predictingfish cutting points according to the target weight by performing machinelearning of the extracted 3D feature information and measured weight information.This study allows for the direct cutting of fish based on cutting pointspredicted by the proposed method. Subsequently, we compared the measuredweight of the cut pieces with the target weight. The comparison result verifiedthat the proposed method showed a mean error rate of approximately 3%.

Prediction of Wearing of Cutting Tools Using Real Time Machining Parameters and Temperature Using Rayleigh-Ham Method

Wear of cutting tools is a big concern for industrial manufacturers, because of their acquisition cost as well as the impact on the production lines when they are unavailable. Law of wear is very important in determining cutting tools lifespan, but most of the existing models don’t take into account the cutting temperature. In this work, the theoretical and experimental results of a dynamic study of metal machining against cutting temperature of a treated steel of grade S235JR with a high-speed steel tool are provided. This study is based on the analysis of two complementary approaches, an experimental approach with the measurement of the temperature and on the other hand, an approach using modeling. Based on unifactorial and multifactorial tests (speed of cut, feed, and depth of cut), this study allowed the highlighting of the influence of the cutting temperature on the machining time. To achieve this objective, two specific approaches have been selected. The first was to measure the temperature of the cutting tool and the second was to determine the wear law using Rayleigh-Ham dimensional analysis method. This study permitted the determination of a law that integrates the cutting temperature in the calculations of the lifespan of the tools during machining.

Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

Opinion Mining(OM)studies in Arabic are limited though it is one of the most extensively-spoken languages worldwide.Though the interest in OM studies in the Arabic language is growing among researchers,it needs a vast number of investigations due to the unique morphological principles of the language.Arabic OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic features.The comparative OM studies in the English language are wide and novel.But,comparative OM studies in the Arabic language are yet to be established and are still in a nascent stage.The unique features of the Arabic language make it essential to expand the studies regarding the Arabic text.It contains unique featuressuchasdiacritics,elongation,inflectionandwordlength.Thecurrent study proposes a Political Optimizer with Probabilistic Neural Network-based Comparative Opinion Mining(POPNN-COM)model for the Arabic text.The proposed POPNN-COM model aims to recognize comparative and non-comparative texts in Arabic in the context of social media.Initially,the POPNN-COM model involves different levels of data pre-processing to transform the input data into a useful format.Then,the pre-processed data is fed into the PNN model for classification and recognition of the data under different class labels.At last,the PO algorithm is employed for fine-tuning the parameters involved in this model to achieve enhanced results.The proposed POPNN-COM model was experimentally validated using two standard datasets,and the outcomes established the promising performance of the proposed POPNN-COM method over other recent approaches.

Cutting Experiment of Fraxinus mandshurica UsingWaterjet-Assisted CO_(2)Laser

High-quality wood products and valuable wood crafts receive everyone’s favor with the rapid development of the economy.In order to improve the cutting surface quality of wood forming parts,the cutting experiment of renewable Fraxinus mandshurica was conducted by waterjet-assisted CO_(2)laser(WACL)technology.A quadratic mathematical model for describing the relationship between surface roughness changes and cutting parameters was established.The effects of cutting speed,flow pressure and laser power on the kerf surface roughness of Fraxinus mandshurica when cutting transversally were discussed by response surface method.The experimental results showed that kerf surface roughness decreased under a lower laser power,higher cutting speed and higher flow pressure.When the cutting speed was 30 mm/s,flow pressure was 1.58 MPa and laser power was 45 W,the actual surface roughness of the optimized Fraxinus mandshurica was 2.41μm,and it was in accord with the theoretically predicted surface roughness value of 2.54μm,so the model fitted the actual situation well.Through the analysis of 3D profile morphology and micromorphology,it was concluded that the optimized kerf surface of Fraxinus mandshurica was smoother,the cell wall was not destroyed and the tracheid was clear.It provides the theoretical basis for wood micromachining.

智能采煤机器人关键技术

采煤机是综采工作面的核心装备,研发智能采煤机器人是实现综采工作面智能化的关键。综合分析当前采煤机机器人化研究进程中的传感检测、位姿控制、速度控制、截割轨迹规划与跟踪控制等技术的研究现状,提出研发智能采煤机器人必须破解的“智能感知、位姿控制、速度控制、截割轨迹规划与跟踪控制、位-姿-速协同控制”五大关键技术,并给出解决方案。针对智能感知问题,提出了构建智能感知系统思路,给出了智能采煤机器人智能感知系统的架构,实现对运行状态、位姿、环境等全面感知,为智能采煤机器人安全、可靠运行提供保障;针对位姿控制问题,提出了智能PID位姿控制思路,给出了改进遗传算法的PID位姿控制方法,实现了智能采煤机器人位姿精准控制;针对速度控制问题,提出了融合“力-电”异构数据的截割载荷测量思路,给出了基于神经网络算法的截割载荷测量方法,实现了截割载荷的精准测量;提出牵引与截割速度自适应控制思路,给出了人工智能算法牵引与截割速度决策方法和滑模自抗扰控制的牵引与截割速度控制方法,实现了智能采煤机器人速度精准自适应控制;针对截割轨迹规划与跟踪控制问题,提出了截割轨迹精准规划思路,给出了融合地质数据和历史截割数据的截割轨迹规划模型,实现了截割轨迹的精准规划;提出了截割轨迹精准跟踪控制思路,给出了智能插补算法的截割轨迹跟踪控制方法,实现了智能采煤机器人截割轨迹高精度规划与精准跟踪控制;针对“位-姿-速”协同控制问题,提出了“位-姿-速”协同控制参数智能优化思路,给出了基于多系统互约束的改进粒子群“位-姿-速”协同控制参数优化方法,实现了智能采煤机器人智能高效作业。深入研究五大关键技术破解思路,有利于加快推动研发高性能、高效率、高可靠的智能采煤机器人。

切削速度对某新型易切削钢切屑形态及加工表面形貌影响

为了明确切削速度对某新型易切削钢切屑形态及加工表面形貌的影响规律,开展了不同切削速度下某新型易切钢的切削试验,研究切屑形态和已加工表面形貌并分析其产生原因。结果表明:宏观上,在切削速度大于150 m/min时,该易切削钢切屑以短管螺旋状为主,当切削速度小于150 m/min时,切屑以发条状和破断弧形为主,形成锯齿形切屑的临界切削速度大约在200 m/min;切削速度影响切屑底面形貌,在低速切削时,切屑底面较多大小不一的撕裂状凹坑、沟槽,当切削速度增大至200 m/min时,能够形成表面较光滑的切屑底面;低速切削该易切削钢时,工件表面粗糙度较大,3D形貌显示波峰高度、波谷深度也均较大,随着切削速度的增加,粗糙度减小,3D形貌亦趋于平缓。

基于样本嵌入的挖矿恶意软件检测方法

加密货币挖矿恶意软件的高盈利性和匿名性,对计算机用户造成了巨大威胁和损失。为了对抗挖矿恶意软件带来的威胁,基于软件静态特征的机器学习检测器通常选取单一类型的静态特征,或者通过集成学习来融合不同种类静态特征的检测结果,忽略了不同种类静态特征之间的内在联系,其检测率有待提升。文章从挖矿恶意软件的内在层级联系出发,自下而上提取样本的基本块、控制流程图和函数调用图作为静态特征,训练三层模型以将这些特征分别嵌入向量化,并逐渐汇集从底层到高层的特征,最终输入分类器实现对挖矿恶意软件的检测。为了模拟真实环境中的检测情形,先在一个小的实验数据集上训练模型,再在另一个更大的数据集上测试模型的性能。实验结果表明,三层嵌入模型在挖矿恶意软件检测上的性能领先于近年提出的机器学习模型,在召回率和准确率上相比其他模型分别提高了7%和3%以上。