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以某注塑产品为实例,针对实际生产出现的制品缺陷,利用Moldflow模拟分析软件MPI,对不同浇日位置进行了流动模拟分析.提出流动成型改进方案,并最终选定符合实际的优化成型方案.实践证明,利用优化方案改进模具进行注塑生产,得到了合格的制件. 相似文献
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如何保障φ800氨合成塔电加热器的长周期运行,本文对其电炉丝部分的结构进行了生产分析并提出了改进方案。该厂自行设计、制造的电炉丝投运二年多来,取得了预期效果。文章对改造前的电炉丝结构及存在问题、改进方案、投运情况等进行了叙述。 相似文献
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《工程塑料应用》2020,(5)
为解决因注塑模推杆设计不合理而导致的注塑件脱模变形严重问题,以底座注塑件为例,通过利用Moldflow结合Workbench进行成型收缩翘曲分析和脱模分析,获得塑件收缩阻碍脱模的翘曲变形特性,以及脱模阻力引起的塑件应变与变形量分布,为推杆配置优化提供依据,最后在脱模阻力明显区域设置6根推杆,并在脱模分析应变较大区域确立了3个顶出镶块搭配推杆的方案。基于模流分析和推杆配置结果,采用侧向进料偏心注塑模,其中塑件卡扣由斜顶内抽及斜导柱外抽成型,有效地解决了底座成型可能引起的质量问题。实践证明,应用该方法能使注塑模推出机构设计过程数据化,能在模具制造之前发现和解决问题,从而提高推出设计精度,缩短研发周期,为同类注塑模具设计提供参考。 相似文献
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针对一次法载重子午胎成型机主轴箱在轮胎生产厂家所出现的主轴轴承磨损严重问题进行改进,主轴支撑由单轴承改进为双轴承支撑.从生产中遇到的问题入手,分析了问题产生的原因,提出了改进方案,通过理论计算和有限元分析为改进的设计方案奠定了理论基础,同时也是对改进设计的有效验证. 相似文献
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针对山东东华水泥有限公司5000t/d新型干法水泥熟料生产线在调试和生产运行中遇到的一些电气问题进行分析,并相应地提出了解决措施。如:对电液动推杆进行的无触点开关改造、对石灰石厂内供料系统进行的连锁保护改造以及电气接口改造等。实践表明,对于生产中出现的问题,必须仔细检查,综合分析判断,才能准确排除。 相似文献
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酒瓶顶盖注塑模具设计 总被引:4,自引:0,他引:4
分析了酒瓶顶盖的结构,提出了模具设计的关键点,设计了模具的整体结构。根据塑件分型面的位置,设计了推件板和推杆的二次推出机构,在型芯紧固螺钉中心钻孔,解决了推杆的安装问题。多个分型面处采用了锥面配合,解决了导向件磨损的问题,提高了模具的精度,延长了模具的寿命。经过生产验证,该摸具结构合理、动作可靠。 相似文献
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研究碎屑沉积和碎屑岩的粒度大小和各种粒级的分布特征的方法称为粒度分析。粒度分析是判别沉积环境和水动力条件的重要物理标志,而且对碎屑岩系油气储层评价也极为重要[3]。选取适合勘探区域内储层特征的粒度分析方法,方能更好地为油田勘探以及后续的开发生产提供更准确的信息。目前,长庆油田和延长油田在研究"三低"储层(低孔、低渗、低产)的物性时,实验室粒度分析主要依靠图像粒度法和激光粒度法。本文以鄂尔多斯盆地坪桥区北部为研究区块,就上述两种检测方法在陕北斜坡中部长6油层中的适应性展开讨论。 相似文献
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仪器分析枝术引入复混肥生产控制分析中,以自动电位滴定仪、分光光度计、火焰光度计为测试工具测定氮、磷、钾的含量,耗时短,可以满足生产控制分析对时效性方面的要求。 相似文献
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针对新疆某矿的红柱石矿物组成,选择了HF─HNO3为溶剂,有效地分离了对红柱石矿含量测定有干扰的脉石矿物,建立了以铝量法为基础的物相分析方法。该法分析结果的准确性和精密度都达到了分析要求。 相似文献
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The kernel principal component analysis (KPCA) method employs the first several kernel principal components (KPCs), which indicate the most variance information of normal observations for process monitoring, but may not reflect the fault information. In this study, sensitive kernel principal component analysis (SKPCA) is proposed to improve process monitoring performance, i.e., to deal with the discordance of T2 statistic and squared prediction error δSPE statistic and reduce missed detection rates. T2 statistic can be used to measure the variation directly along each KPC and analyze the detection performance as well as capture the most useful information in a process. With the calculation of the change rate of T2 statistic along each KPC, SKPCA selects the sensitive kernel principal components for process monitoring. A simulated simple system and Tennessee Eastman process are employed to demonstrate the efficiency of SKPCA on online monitoring. The results indicate that the monitoring performance is improved significantly. 相似文献
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I. J. Wesley F. Pacheco A. E. J. McGill 《Journal of the American Oil Chemists' Society》1996,73(4):515-518
The application of discriminant analysis for identifying and quantifying adulterants in extra virgin olive oils is presented.
Three adulterants were used (sunflower oil, rapessed oil, and soybean oil) and were present in the range 5–95%. Near-infrared
spectroscopy and principal components analysis were used to develop a discriminant analysis equation that could identify correctly
the type of seed oil present in extra virgin olive oil in 90% of cases. Partial least squares analysis was used to develop
a calibration equation that could predict the level of adulteration. Cross validation suggested that it was possible to measure
the level of adulteration to an accuracy of ±0.9%. External validation of the derived calibation equation gave a standard
error of performance of ±2.77%. 相似文献
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Uwe Kruger David Antory Juergen Hahn George W. Irwin Geoff McCullough 《Computers & Chemical Engineering》2005,29(11-12):2355
Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process. 相似文献