Improving recovery in sublevel top coal caving mining by using partially reverse drawing technique

The sublevel top coal caving(SLTCC)mining technology is extensively employed in steeply inclined thick coal seams.Because of the typical characteristics of the short coal face in this mining method,a signifi-cant portion of the top coal is lost at the face end.For reducing the coal loss,the partially reverse drawing technique(PRDT)is proposed as a novel top coal drawing technique.Meanwhile,based on the Bergmark-Roos model(B-R model),a theoretical method for calculating the recovery ratio of top coal based on the top coal boundary equation and residual top coal amount is proposed.The mechanism of PRDT to reduce top coal loss at the face end is revealed by comparing with single-round sequential drawing technique(SSDT).Physical experiments and in-site observation data were used to verify the theoretical model.The results show that PRDT can effectively reduce the amount of residual coal near the roof by optimizing the shape characteristics of top coal boundary.Suggestions for improve recovery ratio in Wudong Coal Mine were given based on its face parameters.

Detection of Knowledge on Social Media Using Data Mining Techniques

In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.

Data mining techniques在冶金领域的应用

介绍了Data mining techniques产生背景、发展情况、优化过程,以及在冶金领域的应用。

Green coal mining technique integrating mining-dressing-gas draining-backfilling-mining

Aiming to address the following major engineering issues faced by the Pingdingshan No. 12 mine:(1) difficulty in implementing auxiliary lifting because of its depth(i.e., beyond 1000 m);(2) highly gassy main coal seam with low permeability;(3) unstable overlying coal seam without suitable conditions for implementing conventional mining techniques for protective coal seam; and(4) predominant reliance on ‘‘under three" coal resources to ensure production output. This study proposes an integrated, closed-cycle mining-dressing-gas draining-backfilling-mining(MDGBM) technique. The proposed approach involves the mining of protective coal seam, underground dressing of coal and gangue(UDCG), pressure relief and gas drainage before extraction, and backfilling and mining of the protected coal seam. A system for draining gas and mining the protective seam in the rock stratum is designed and implemented based on the geological conditions. This system helps in realizing pressure relief and gas drainage from the protective seam before extraction. Accordingly, another system, which is connected to the existing production system, is established for the UDCG based on the dense medium-shallow trough process. The mixed mining workface is designed to accommodate both solid backfill and conventional fully mechanized coal mining, thereby facilitating coal mining, USCG, and backfilling. The results show that: The mixed mining workface length for the Ji15-31010 protected seam was 220 m with coal production capacity 1.2 million tons per year, while the backfill capacity of gangue was 0.5 million tons per year. The gas pressure decreased from 1.78 to 0.35 MPa, and the total amount of safely mined coal was 1.34 million tons. The process of simultaneously exploiting coal and draining gas was found to be safe, efficient, and green.This process also yielded significant economic benefits.

Research on Full Space Transient Electro-magnetism Technique for Detecting Aqueous Structures in Coal Mines

Based on the transmitting theory of "smoke ring effect", the transient electromagnetism technique was used in coal mines to detect abnormal areas of aquiferous structures in both roofs and floors of coal seams and in front of excavated roadways. Survey devices, working methods and techniques as well as data processing and interpretation are discussed systematically. In addition, the direction of mini-wireframe emission electromagnetic wave of the full space transient electromagnetism technique was verified by an underground borehole for water detection and drainage. The result indicates that this technique can detect both horizontal and vertical development rules of abnormal water bodies to a certain depth below the floor of coal seams and can also detect the abnormal, low resistance water bodies within a certain distance of roofs. Furthermore, it can detect such abnormal bodies in ahead of the excavated roadway front. Limited by the underground environment, the full space transient electromagnetism technique can detect to a depth of only 120 m or so.

Passive seismic velocity tomography on longwall mining panel based on simultaneous iterative reconstructive technique (SIRT)

Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion is used to deduce the stress redistribution around the longwall mining panel. The mining-induced microseismic events were recorded by mounting an array of receivers on the surface, above the active panel. After processing and filtering the seismic data, the three-dimensional tomography images of the p-wave velocity variations by SIRT passive seismic velocity tomography were provided. To display the velocity changes on coal seam level and subsequently to infer the stress redistribution, these three-dimensional tomograms into the coal seam level were sliced. In addition, the boundary element method （BEM） was used to simulate the stress redistribution. The results show that the inferred stresses from the passive seismic tomograms are conformed to numerical models and theoretical concept of the stress redistribution around the longwall panel. In velocity tomograms, the main zones of the stress redistribution arotmd the panel, including front and side abutment pressures, and gob stress are obvious and also the movement of stress zones along the face advancement is evident. Moreover, the effect of the advance rate of the face on the stress redistribution is demonstrated in tomography images. The research result proves that the SIRT passive seismic velocity tomography has an ultimate potential for monitoring the changes of stress redistribution around the longwall mining panel continuously and subsequently to improve safety of mining operations.

A probe into“mining technique in the condition of floor failure”for coal seam above longwall goafs

Targeting at the coal seam with useful value discarded above goafs,attempted to explore the feasibility of'mining technique in the condition of floor failure' from theoretical point of view,and predicted.It indicated that mining technique in the condition of floor failure used above Longwall Goafs in Baijiazhuang Mining is totally feasible.At law,the deformation of the floor in the mining technique by means of probability-integral method.And it is discov- ered that deformed basin can emerge in the footwall of No.6 coal seam and its maximum subsidence was possibly 1 633 mm or so and its maximum positive curvature is 61.74/10^(-3). At last,it therefore suggests appropriate ground pressure control measures as strengthening observation of ground pressure and adopting false slope for exploitation and strengthening support for reasonable push and slide based on the adverse ground pressure behaviors possibly occurring in the mining technique.This serves to gather data and lay sturdy founda- tion for further probe into the mining technique,and offers theoretical and technical grounds for concrete implementation of the mining technique.

Study on the Safety and Prevention Technology of Coal Mining under the River in Xingyuan Coal Mine

Coal mining-induced surface subsidence poses significant ecological and infrastructural challenges, necessitating a comprehensive study to ensure safe mining practices, particularly in underwater conditions. This project aims to address the extensive impact of coal mining on the environment, infrastructure, and overall safety, focusing on the Shigong River area above the working face. The study employs qualitative and quantitative analyses, along with on-site engineering measurements, to gather data on crucial parameters such as coal seam characteristics, roof rock lithology, thickness, water resistance, and structural damage degree. The research encompasses a multidisciplinary approach, involving mining, geology, hydrogeology, geophysical exploration, rock mechanics, mine surveying, and computational mathematics. The importance of effective safety measures and prevention techniques is emphasized, laying the foundation for research focused on the Xingyun coal mine. The brief concludes by highlighting the potential economic and social benefits of this project and its contribution to valuable experience for future subsea coal mining.

Data Mining as a Technique for Healthcare Approach

Data Mining, also known as knowledge discovery in data (KDC), is the process of uncovering patterns and other valuable information from large data sets. According to https://www.geeksforgeeks.org/data-mining/, it can be referred to as knowledge mining from data, knowledge extraction, data/pattern analysis, data archaeology, and data dredging. With advance research in health sector, there is multitude of Data available in healthcare sector. The general problem then becomes how to use the existing information in a more useful targeted way. Data Mining therefore is the best available technique. The objective of this paper is to review and analyse some of the different Data Mining Techniques such as Application, Classification, Clustering, Regression, etc. applied in the Domain of Healthcare.

Stress Measurement with an Improved Hollow Inclusion Technique In Jinchuan Nickel Mine

Borehole overcoring stress measurement with an improved hollow inclusion technique was carried out at 10 points on 3 levels in Jinchuan nickel mine which is situated in north-west of China. Through the measurement, 3-D in situ stress state at the measuring points and distribution characteristics of the stress field in the mine were obtained. The stress state in Jinchuan mine is dominated by the horizontal tectonic stress field. The maximum principal stress is horizontal which is about twice the weight of the overburden and its orientation is approximately vertical to the regional tectonic line. The difference between two horizontal principal stresses is quite large which is an important reason to cause failure of underground excavations.

Application of DEM overlaying technique in surface subsidence identification─a case study in Ruqigou coal mining area of Ningxia,China

Subsidence occurred in many parts of the world. particularly in densely populated deltaic regions, causing extremely expensive damage. It can be resulted from natural causes. man-made induced causes, or other mixed causes. For identifying surface subsidence, many techniques have been employed, for example, geodetic monitoring, airborne laser subsidence measurement system,differential S.A.R., interferometry DGPS, and satellite radar measurements. However. all these methods require large time span and a large amount of field work. With the development of GIS techniques, identification of surface subsidence is becoming a relative easy problem. Ruqigou coal mining area was selected as a case study to identify the surface subsidence with DEM (digital elevation model) overlaying techniques. The result shows that DEM overlaying technique is a very useful method on surface subsidence identification. The accuracy of the results are largely dependent on the precision of the data-input.

Linking Competitors’ Knowledge and Developing Innovative Products Using Data Mining Techniques

In this article, the relationship between the knowledge of competitors and the development of new products in the field of capital medical equipment has been investigated. In order to identify the criteria for measuring competitors’ knowledge and developing new capital medical equipment products, marketing experts were interviewed and then a researcher-made questionnaire was compiled and distributed among the statistical sample of the research. Also, in order to achieve the goals of the research, a questionnaire among 100 members of the statistical community was selected, distributed and collected. To analyze the gathered data, the structural equation modeling (SEM) method was used in the SMART PLS 2 software to estimate the model and then the K-MEAN approach was used to cluster the capital medical equipment market based on the knowledge of actual and potential competitors. The results have shown that the knowledge of potential and actual competitors has a positive and significant effect on the development of new products in the capital medical equipment market. From the point of view of the knowledge of actual competitors, the market of “MRI”, “Ultrasound” and “SPECT” is grouped in the low knowledge cluster;“Pet MRI”, “CT Scan”, “Mammography”, “Radiography, Fluoroscopy and CRM”, “Pet CT”, “SPECT CT” and “Gamma Camera” markets are clustered in the medium knowledge. Finally, “Angiography” and “CBCT” markets are located in the knowledge cluster. From the perspective of knowledge of potential competitors, the market of “angiography”, “mammography”, “SPECT” and “SPECT CT” in the low knowledge cluster, “CT scan”, “radiography, fluoroscopy and CRM”, “pet CT”, “CBCT” markets in the medium knowledge cluster and “MRI”, “pet MRI”, “ultrasound” and “gamma camera” markets in the high knowledge cluster are located.

Multi-disciplinary Conceptual Design Knowledge of Multi-stage Hybrid Rocket Using Data Mining Technique

This paper deals with the application of data mining techniques to the conceptual design knowledge for a LV （launch vehicle） with a HRE （hybrid rocket engine）. This LV is a concept of the space transportation, which can deliver micro-satellite to the SSO （sun-synchronous orbit）. To design the higher performance LV with HRE, the optimum size of each component, such as an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle, should be acquired. The Kriging based ANOVA （analysis of variance） and SOM （self-organizing map） are employed as data mining techniques for knowledge discovery. In this study, the paraffin （FT-0070） is used as a propellant of HRE. Then, the relationship among LV performances and design variables are investigated through the analysis and the visualization. To calculate the engine performance, the regression rate is computed based on an empirical expression. The design knowledge is extracted for the design knowledge of the multi-stage LV with HRE by analysis using ANOVA and SOM. As a result, the useful design knowledge on the present design problem is obtained to design HRE for space transportation.

Theories and techniques of coal bed methane control in China

Coal bed methane control with low permeability is a hot issue at present. The current status of coal bed methane control in China is introduced. The government-support policies on coal bed methane control are presented. This paper proposes the theories of methane control in depressurized mining, including methane extraction in depressurized mining, simultaneous mining technique of coal and methane without coal pillar, and circular overlying zone for high-efficiency methane extraction in coal seams with low permeability. The techniques of methane control and related instruments and equipments in China are introduced. On this basis, the problems related to coal bed methane control are addressed and further studies are pointed out.

Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

传统资源储量估算在QuantyMine数字矿山软件中的实现及关键技术

根据我国传统资源储量估算方法特点,以地矿点源数据库为基础,以矿山日常勘探与储量估算及开发工作流程为主线,在QuantyMine数字矿山软件中开发了实现传统资源储量估算的功能。解决了多源地矿勘查数据一体化管理与应用、资源储量估算与地矿勘查图件报表编制一体化、多金属矿山资源储量动态估算与管理、资源储量估算成果共享等关键技术问题。结合传统储量估算工作特点,采用智能化与人机交互相结合的方式实现了多金属矿山资源储量多维空间一体化与可视化动态估算与管理功能,可有效提高储量估算科学性和可靠性。相对传统手工储量估算,采用本系统可提高5倍以上的工作效率。在紫金矿业集团所属多个矿山的应用表明,结果偏差在10%以内,估算准确率明显提高。

基于变化参与实例的空间并置模式增量挖掘方法

空间并置模式是一组空间特征的子集,它们的实例在空间中频繁关联。空间并置模式挖掘是空间数据挖掘的一个重要分支。然而,空间数据库随时间不断变化,高效的空间并置模式增量挖掘显得尤为重要。提出基于变化参与实例的空间并置模式增量挖掘方法,相比传统的增量挖掘算法,不进行耗时的变化表实例生成操作,直接搜索变化参与实例。为加速变化参与实例搜索过程,提出了实例级搜索优化策略、启发式模式剪枝技术,进而提出了IMCP-CPI,讨论了算法的复杂度、正确性和完备性。在真实和模拟数据集上进行了大量实验验证IMCP-CPI的性能。结果表明IMCP-CPI远优于当前已知的5个空间并置模式增量挖掘算法,其效率提升数倍甚至数个量级。在变化数据占比为原数据集5%的新数据集中,当距离阈值d很大或者参与度阈值min_prev很小时,IMCP-CPI的性能比当前并置模式挖掘较优算法CPM-Col及改进算法CPM-iCol提升2~3倍。此外,当变化数据占比分别小于等于原数据集的25%和50%时,无论在参数变化还是可扩展性方面,IMCP-CPI均优于CPM-iCol和CPM-Col,这对具体实践中的方法选取给与了参考意见。

故障诊断技术在煤矿机械设备中的应用

随着煤矿需求的不断增长,煤矿机械设备的应用也非常广泛。但是在实际生产过程中,煤矿机械设备往往会出现各种各样的故障,不仅会大幅度降低生产效率,而且还有可能出现严重安全事故。因此应当针对故障诊断技术在煤矿机械设备中的应用进行深入分析,确保煤矿机械设备可以稳定运行。