共查询到13条相似文献,搜索用时 62 毫秒
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《工矿自动化》2021,47(3)
基于振动信号辨识是实现综放开采煤矸识别的有效手段,现有方法在识别准确性和有效性方面有待进一步研究。提出了一种基于经验模态分解(EMD)特征提取与随机森林(RF)的煤矸识别方法。采用加速度传感器及数据采集仪采集了某综放工作面煤和矸石冲击液压支架尾梁产生的振动信号,分别对2种信号进行EMD,得到一系列本征模态函数(IMF);根据EMD结果选取有效IMF,分别提取IMF能量、峭度、矩阵奇异值及对应熵作为特征向量,采用各特征向量独立训练RF模型,根据各RF模型对测试样本的识别结果筛选特征向量,并建立特征数据集;采用特征数据集训练RF模型,采用训练好的RF模型实现煤矸识别。测试结果表明:该方法对200组煤矸测试样本的识别准确率达96.5%,且当RF模型中决策树数量设置为100或150时识别准确率最高,对测试样本进行特征提取与识别的耗时不超过0.2s,满足综放工作面煤矸识别准确性和实时性要求。 相似文献
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针对目前液压支架直线度测量方法存在测量维度低、误差较大、易受粉尘影响等问题,提出了一种基于架间行走机器人的液压支架直线度测量方法。该方法主要用于支撑掩护式支架,在架间行走机器人上布置传感器,用于直接测量液压支架底座的横向偏移、纵向偏移、横向斜角和纵向倾角等多维位置偏移信息,从而通过支架位置偏移量表征液压支架的直线度信息。试验结果表明,相邻两架偏移误差值在0.2cm以内,相邻两架角度误差在10′以内;当模型增加到100架支架,依据常规液压支架1.5m的中心距计算,在工作面长度为150m时,预计会产生位置偏移累计误差10cm,角度累计误差8°20′,对于长度不超过150m的短距离综采工作面,这个累计误差在可接受的范围内,可满足液压支架直线度的测量需求。相比于传统的一维测量信息,该方法通过4维位置偏移信息可为液压支架群的控制提供参考。 相似文献
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支持向量回归估计性能分析 总被引:3,自引:2,他引:3
本文对支持向量机用于回归估计进行了详细的性能分析,得出了不敏感系数、惩罚因子和核函数及其参数是影响支持向量机回归估计性能的主要因素。不敏感系数可控制模型的泛化推广能力,其值的确定应考虑样本可能带有的噪声分布状况,惩罚因子可控制拟合曲线复杂性,核函数宽度系数可影响回归曲线光滑程度。因此,在采用支持向量机回归建模时,应根据建模对象选定合适的参数值,以保证回归建模效果。最后通过对原油实沸点蒸馏曲线的拟合问题验证了分析结果,为进一步研究确定SVM参数的优化方法打下了基础。 相似文献
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This paper describes a procedure for optimal determination of two groups of parameters of a hydraulic support employed in
the mining industry. The procedure is based on mathematical programming methods. In the first step, the optimal values of
some parameters of the leading four-bar mechanism are found in order to ensure the desired motion of the support with minimal
transversal displacements. In the second step, maximal tolerances of the optimal values of the leading four-bar mechanism
are calculated, so the response of hydraulic support will be satisfying.
Received April 13, 1999 相似文献
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针对液压支架稳态支护对液压支架控制器自适应控制快速性和强抗干扰能力要求,以ZY10800/28/63支顶掩护式液压支架为研究对象,建立了液压支架运动学模型和阀控液压缸液压系统传递函数,设计了一种包含速度补偿的RBF神经网络控制器,基于该控制器提出了一种液压支架顶梁位姿调控系统,通过控制立柱和平衡千斤顶长度,保证支护状态下液压支架顶梁高度和姿态角稳定。在Matlab/Simulink中建立了液压支架顶梁位姿调控系统仿真模型并进行实验,结果表明:RBF神经网络控制器对阶跃信号的响应时间短,未出现超调现象;在施加顶梁冲击力情况下,RBF神经网络控制器较PID控制器和滑模控制器具有更快的响应速度、更小的超调量和更强的抗干扰能力,能维持支架顶梁位姿处于目标位置,具有良好的稳定性。 相似文献
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Shield tunneling performance depends mainly on changes in geological conditions and machine working status. Understanding its characteristics is the key to operating and controlling shield machine during the metro construction. Despite the large set of shield tunneling data in having been a big challenge in interpreting the underlying meaning, a systematical view of the shield tunneling performance has not yet been identified. In this study, a methodology for the modeling and analysis of shield tunneling performance network is proposed which aims at integrating the high dimensional data mining and the complex network approaches for shield performance evaluation. It is tested by analyzing the heterogeneous data of shield tunneling performance acquired from in the first Yangtze river crossing metro tunnel project in China. Each segment ring tunneling cycle in the construction were considered to be nodes of the network mapped while edges are determined by nodes having the similarity greater than an optimal threshold value. The construct network exhibits high clustering coefficient combined with comparatively short path lengths, which demonstrates a small world topology feature. Communities in the performance network with different size based on the complex network are detected, which provides the vital decision information for geological conditions identification and shield tunneling performance risk evaluation. 相似文献
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