大断面切眼支护技术研究与实践

针对古城煤矿S1303综采工作面切眼的地质构造与施工条件,提出了大断面切眼采用“锚网索+π型梁棚+预注浆”联合支护方案,有效地控制了大断面切眼留顶煤施工期间的支护难题,保障了S1303综采面切眼能够满足设计要求和如期完成施工,为同类条件下的切眼施工提供了一定参考。     

爆炸载荷下空孔缺陷与爆生裂纹扩展行为研究

空孔在岩石巷道直眼掏槽爆破中具有重要作用,为研究空孔及其缺陷在爆炸荷载作用下的扩展行为和作用机理,以PMMA代替岩石材料,利用预制裂纹代替空孔缺陷,借助动态焦散线系统和理论分析为手段,研究不同间距下空孔、空孔处预制裂纹、爆生裂纹动态扩展规律及机理,分析不同"径距比"与掏槽效果的关系。研究结果表明:在装药量一定的情况下,随着炮孔与空孔距离的变化,爆生裂纹扩展距离呈现递增而预制裂纹扩展距离呈现递减的趋势,但都存在极值;当炮孔与空孔距离较小时,爆生裂纹和预制裂纹扩展及相互作用最复杂,爆生裂纹扩展经历由压缩应力波为主,表现为直线的前期扩展;由空孔处发射应力波和压缩应力波共同作用下,爆生裂纹偏离炮孔与空孔连心线的中期扩展,以及由空孔应力集中区作用使爆生裂纹向空孔方向偏移的后期阶段;预制裂纹扩展经历由空孔处应力集中作用下,表现为直线的前期扩展,以及由爆生裂纹处反射拉伸波作用使其向爆生裂纹发展的后期阶段;当炮孔与空孔距离较大时,反射应力波及应力集中效应对爆生裂纹和预制裂纹扩展在减弱,爆生裂纹与预制裂纹扩展行为仅有前期直线扩展阶段。"径距比"的大小对爆破效果影响较大,直眼掏槽爆破应以最优"径距比"作为掏槽爆破参数设计的依据。     

TBP/煤油热解焚烧装置的改进及冷试验证

国内低放废液磷酸三丁酯/煤油(TBP/煤油)热解焚烧处理设施的主要核心设备——热解炉是从国外某公司引进的,在工程系统冷调试过程发生了热解炉的搅拌桨卡死和高温气体过滤器严重堵塞的情况,导致系统不能稳定运行。经对热解炉检查,发现国外引进热解炉存在设计和制造缺陷,不能满足系统稳定运行。通过系统分析研究,国内自主设计一套磁力驱动搅拌桨转动装置和烧结金属高温气体过滤器,在后续调试过程中取得了比国外某公司原设计更好的运行效果,使得我国TBP-煤油热解处理设施顺利调试成功。     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

生物氧化预处理中进气量实时预测数学模型研究

精准预测生物氧化预处理中的进气量对提高黄金提取率和节能降耗具有重要意义。以气体管流连续性方程和运动方程为控制方程，采用Preissmann隐格式法作为差分方法。同时，根据集合卡尔曼滤波(Ensemble Kalman filter，EnKF)算法原理，构造进气量、压强的状态空间模型。结果表明，基于气体管流控制方程建立的进气量模型预测结果与实际进气量观测值具有较好的一致性；与传统静态预测方法相比，EnKF同化方法引入实时观测值和模型参数的更新，有效提高了进气量的预测精度，其平均绝对误差、平均相对误差和均方根误差有明显的降低。可见，基于气体管流控制方程建立的预测模型结合EnKF同化方法是提高生物氧化槽进气量预测精度的有效手段。     

一种射频抗电磁干扰的矿用红外温度传感器

设计了一种适用于复杂条件下实施井下温度探测的射频式红外温度传感器。借助于光学系统、光电探测器实时感应井下温度并提取温度信号,同时在DC-DC电源隔离模块中实施EMI滤波以抗电磁干扰,处理后的信号经过A/D转换、运算器放大后显示在LCD上,实施读取数据并记录在传感器的存储片上,实现了矿井复合灾害条件下的温度测试,测试精度控制在±2%。     

燃煤锅炉除尘专用滤料的开发

介绍机械制造厂燃煤锅炉的烟尘特点,分析滤料失效的原因,提出一套针对该工况的滤料解决方案。介绍针对复杂工况条件所选用的纤维种类以及复合面层原料成分配比的确定,最终选用针刺工艺加工并对该新产品的基本性能进行了测试分析。     

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.