浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。     

基于数据拼接的金刚石刀具刃口三维形貌表征技术

原子力显微镜(AFM)是获取金刚石刀具刃口纳米级三维形貌的重要手段,但其存在测量范围小,难以表征参与切削区域整段刃口形貌特征的问题。采用基于迭代最近点法的刃口AFM测量数据拼接算法,获得了由多组数据拼接得到的刃口纳米级三维形貌,并进行了切削实验验证。实验结果表明,采用的数据拼接方法可较好地用于表征刀具刃口三维形貌。     

A Unified Analysis of Structured Sonar-Terrain Data Using Bayesian Functional Mixed Models

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. Although existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this article, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. Supplementary materials for this article are available online.     

手机信令数据在地质灾害预警中的应用

本文是在地质灾害监测预警项目的实践基础上,结合移动运营商对手机信令数据的侦测应用,提出了基于手机信令数据的地质灾害预警发布的解决方案。该方案可实现地质灾害隐患点威胁区域的人员实时统计、预警信息发布、预警效果判断等功能,弥补了现有基于短信和大喇叭预警发布解决方案的不足。它能有效降低地质灾害发生时造成的人员伤亡,并且适用于我国所有的地质灾害影响区域。     

基于街景地图数据的北京市东城区 街道绿色空间正义评估研究

绿色空间正义是城市空间正义的典型代表，意为在人群中公平分配维护绿色空间的责任和享有绿色空间的权益。根据其定义，以北京市东城区为例，从责任和权益2个角度着眼，一方面基于百度街景地图数据提炼街道空间绿视率的空间分布特点，表征街道绿色空间的客观可感知水平；另一方面将街道绿视率和实时人口热力叠加，探讨街道绿色空间的实际被感知程度，从而完成对北京市东城区街道绿色空间维护和享有情况的评估。发现邻近使用者维护街道绿色空间的责任对绿化客观可感知水平的重要性，以及合理的道路断面设计对同时提升街道空间活力和绿视率即绿化实际被感知程度的有效性。由此总结出2点街道绿色空间规划设计建议，即明晰权责边界并保证公共权益优先级，以及加强落地性设计导则中对绿色空间正义问题的关注，并对未来研究提出展望。     

基于流数据聚类算法的电力大数据异常检测

针对电力大数据流的异常检测问题,该文将流数据聚类算法与电力大数据相结合,针对现有流数据聚类算法不易存储全部数据、断电数据易丢失等问题,以及流数据聚类算法对于离线阶段聚类算法实时应答的要求,从数据的完整性、安全性以及流数据聚类算法的低时间复杂度的角度出发,对CluStream流数据聚类算法进行改进,提出流式K-means聚类算法。对在线阶段,使用Redis集群进行流数据的缓冲,并设计节点时间衰减策略,增大心跳消息中有效消息所占比例;对离线阶段聚类算法进行优化,使用最佳距离法确定初始聚类中心,减少迭代次数;最后,使用所提出的流式K-means聚类算法进行用户用电异常行为检测,实验结果表明,该算法能够很好的发现用户用电异常行为。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

煤田地震勘探中多井组合爆炸法浅析

地震勘探中炸药作为激发震源的激发条件多样,采用有效的震源激发方式,才能取得高信噪比的地震原始数据。本文依据有关爆破原理,理论结合实践经验,提出在厚黄土区采用多井组合的激发方式,能有效压制噪声,增强性噪比,提高数据质量。     

Identification of digital technologies and digitalisation trends in the mining industry

Digitalisation in mining refers to the use of computerised or digital devices or systems and digitised data that are to reduce costs, improve business productivity, and transform mining practices. However, it remains increasingly difficult for mining companies to decide which digital technologies are most relevant to their needs and individual mines. This paper provides an overview of digital technologies currently relevant to mining companies as presented and discussed by mining journals, the media and insight reports of leading consultancy agencies. Relevant technologies were systematically identified using text-mining techniques, and network analyses established the relations between significant technologies. Results demonstrated that currently 107 different digital technologies are pursued in the mining sector. Also, an analysis of the actual implementation of digital technologies in 158 active surface and underground mines reveals a limited uptake of digital technologies in general and that the uptake increases with the run-of-mine production. Large-scale mining operations appear to select and apply digital technologies suitable to their needs, whereas operations with lower production rates do not implement the currently available digital technologies to the same extent. These minor producers may require other digital transformation solutions tailored to their capabilities and needs and applicable to their scale of operations.     

某能源公司安全管理效率评价

某能源股份有限公司是我国上市煤炭公司,为评价其安全管理效率,采用数据包络(DEA)分析方法,以员工人数、资产总额、安全生产费为投入指标,以原煤产量、百万吨煤死亡率为产出指标,对其2007—2018年间的安全管理效率进行了评价。结果显示,某能源公司在研究期间的安全管理效率较为低下,但近5年来有提升的趋势,2018年安全管理实现DEA有效;安全管理无效的主要原因为纯技术效率和规模效率低下。为提高安全管理效率,该企业应在安全投入资源的匹配性和安全投入规模的合理性两个方面采取针对性措施。