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1.
针对目前工业CT图像转换为3D打印G代码方法效率低的问题,提出一种基于邻层数据匹配的工业CT图像直接转换成G代码的方法。首先采用Canny算子提取工业CT图像的轮廓,然后处理轮廓分叉问题,实现邻层间几何信息数据匹配,其次进行邻层间轮廓插值以满足3D打印层间厚度要求,从而避免"阶梯效应",最后通过填充编码得到用于3D打印的G代码。使用本文提出的方法,轮毂CT图像转换为G代码的时间为10.5 s,耗时远小于其他间接转换方法;3D打印出的轮毂无"阶梯效应",平均尺寸误差率为0.25%。实验结果表明,该方法不涉及中间格式,转换效率高,转换误差与传统方法相当,适用于具有复杂内腔结构的零件。 相似文献
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Tao TIAN Chao-lan ZHANG Feng ZHU Shan-xin YUAN Ying GUO Sheng-guo XUE 《中国有色金属学会会刊》2021,31(5):1484-1495
A column experiment was conducted to investigate the effect of phosphogypsum (PG) on the saline- alkalinity, and aggregate stability of bauxite residue. Results showed that: with increasing leaching time, the concentrations of saline-alkali ions decreased while the concentration increased in bauxite residue leachate; compared with CK (control group) treatment, pH, electric conductivity (EC), exchangeable sodium percentage (ESP), sodium absorption ratio (SAR), and exchangeable Na+ content of bauxite residue were reduced following PG treatment; average particle sizes in aggregates following CK and PG treatments were determined to be 155 and 193 nm, respectively. SR-μCT test results also confirmed that bauxite residue following PG treatment acquired larger aggregates and larger pore diameter. These results indicate that the PG treatment could significantly modulate the saline-alkalinity, and simultaneously enhance aggregate stability of bauxite residue, which provides a facile approach to reclaim bauxite residue disposal areas. 相似文献
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为缓解我国水、能源和粮食资源紧张问题,促进资源可持续利用,构建水-能源-粮食系统,利用耦合协调度模型对我国的30个省(自治区、直辖市)进行测算,并利用空间杜宾模型分析主要影响因素。结果表明:2003—2017年,我国能源、粮食评价[JP]指数高于水资源评价指数,系统综合评价指数逐年递增;大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势,个别省份耦合协调度濒临失调;耦合协调度空间自相关性较强,虽有明显波动,但是呈现逐年加强的态势;影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。 相似文献
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《International Journal of Hydrogen Energy》2022,47(100):42280-42292
In this study, the separation of hydrogen from gas mixtures using a palladium membrane coupled with a vacuum environment on the permeate side was studied experimentally. The gas mixtures composed of H2, N2, and CO2 were used as the feed. Hydrogen permeation fluxes were measured with membrane operating temperature in the range of 320–380 °C, pressures on the retentate side in the range of 2–5 atm, and vacuum pressures on the permeate side in the range of 15–51 kPa. The Taguchi method was used to design the operating conditions for the experiments based on an orthogonal array. Using the measured H2 permeation fluxes from the Taguchi approach, the stepwise regression analysis was also employed for establishing the prediction models of H2 permeation flux, followed by the analysis of variance (ANOVA) to identify the significance and suitability of operating conditions. Based on both the Taguchi approach and ANOVA, the H2 permeation flux was mostly affected by the gas mixture composition, followed by the retentate side pressure, the vacuum degree, and the membrane temperature. The predicted optimal operating conditions were the gas mixture with 75% H2 and 25% N2, the membrane temperature of 320 °C, the retentate side pressure of 5 atm, and the vacuum degree of 51 kPa. Under these conditions, the H2 permeation flux was 0.185 mol s?1 m?2. A second-order normalized regression model with a relative error of less than 7% was obtained based on the measured H2 permeation flux. 相似文献
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Aggregate question answering essentially returns answers for given questions by obtaining query graphs with unique dependencies between values and corresponding objects. Word order dependency, as the key to uniquely identify dependency of the query graph, reflects the dependencies between the words in the question. However, due to the semantic gap caused by the expression difference between questions encoded with word vectors and query graphs represented with logical formal elements, it is not trivial to match the correct query graph for the question. Most existing approaches design more expressive query graphs for complex questions and rank them just by directly calculating their similarities, ignoring the semantic gap between them. In this paper, we propose a novel Structure-sensitive Semantic Matching(SSM) approach that learns aligned representations of dependencies in questions and query graphs to eliminate their gap. First, we propose a cross-structure matching module to bridge the gap between two modalities(i.e., textual question and query graph). Then, we propose an entropy-based gated AQG filter to remove the structural noise caused by the uncertainty of dependencies. Finally, we present a two-channel query graph representation that fuses the semantics of abstract structure and grounding content of the query graph explicitly. Experimental results show that SSM could learn aligned representations of questions and query graphs to eliminate the gaps between their dependencies, and improves up to 12% (F1 score) on aggregation questions of two benchmark datasets. 相似文献
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为解决矿山充填体强度的设计问题,提高矿山充填体的强度动态调整能力,本文通过调查国内百座矿山现场充填体强度实际数据,采用SVM方法建立充填体强度智能预测模型,对70组训练样本数据进行训练,采用BP神经网络模型与SVM模型的预测结果进行比较。结果表明:SVM预测模型的最大误差为3.52%,平均误差为2.41%。BP预测模型的最大误差为10.98%,平均误差为7.01%。SVM模型比BP模型预测精度更高,误差更小。采用SVM模型对三山岛金矿充填体强度进行预测,一步骤回采矿房充填体强度1.02MPa,推荐灰砂比1:12,二步骤回采矿房充填体强度0.86MPa,推荐灰砂比1:16。现场采场充填效果良好,未发生充填体失稳现象。基于SVM的充填体强度智能匹配模型能够在满足采场稳定性的前提下,减少充填成本,提高矿山的经济效益。 相似文献