地面直井大液量水力压裂消突技术在石港矿的应用

针对山西石港煤业有限责任公司煤与瓦斯突出制约安全生产的问题,采用了地面直井大液量水力压裂消突技术,有效解决了问题,实现了安全高效生产,可为类似条件的矿井提供借鉴。     

基于W77E58单片机无抖动误差深度测量系统的设计

使用新型W77E58高速单片机并运用先进的鉴相和消抖算法,设计了用于测井深度测量子系统,完全消除了编码器引起的抖动误差,给出该系统硬件的设计方案。系统已成功应用于测井仪中,表明该系统具有很高的测量精度和稳定性。     

多个粗差剔除前后的平差值转换

本文从观测值中含有多个粗差的平差值入手，采用文献[1]中的F－T检验法剔除多个粗差，导出了剔除多个粗差后的平差值转换公式．与文献[2]中的转换公式比较可知，本文所提出的是一通用公式，而文献[2]中转换公式仅是文中的特冽。文中的其例说明，这一转换公式在理论上是严密的，实用起来方便、可行．     

遥控传输系统中的调制和解调技术

介绍了高稳定锁相调制和高灵敏度的接收解调.对其进行了理论分析,描述了调制速度和锁定时间的确定问题,解调单元中接收灵敏度的提高和静噪电路的设计.     

新型电气火灾消烟剂的研制

针对电气火灾中产生的大量有毒烟雾，研制一种细水雾型消烟剂，能够通过润湿、凝并、粘结等物理作用以及化学反应沉降烟尘，去除有毒气体，达到快速消烟目的，平均消烟效率达85％以上。该消烟剂为绿色无污染产品，不会造成消烟范围内设备、装置的短路和腐蚀，火灾现场容易清洁。     

联苯锅炉预抽真空技术

介绍一种联苯锅炉预抽真空技术,即在室温和低温离加热(70℃或50℃)过程中对联苯锅炉抽真空,然后加热至联苯气化温度,最后用联苯蒸气对生产设备进行升温。使用该方法降低了联苯气化温度,缩短了联苯加热时间,消除了联苯拔气造成的环境污染,开车升温耗电节约60%。     

Alternative Hotelling's T2 Charts using Winsorized Modified One‐Step M‐estimator

Hotelling's T² chart is a popular tool for monitoring statistical process control. However, this chart is sensitive in the presence of outliers. To alleviate the problem, this paper proposed alternative Hotelling's T² charts for individual observations using robust location and scale matrix instead of the usual mean vector and the covariance matrix, respectively. The usual mean vector in the Hotelling T² chart is replaced by the winsorized modified one‐step M‐estimator (MOM) whereas the usual covariance matrix is replaced by the winsorized covariance matrix. MOM empirically trims the data based on the shape of the data distribution. This study also investigated on the different trimming criteria used in MOM. Two robust scale estimators with highest breakdown point, namely S_n and T_n were selected to suit the criteria. The upper control limits for the proposed robust charts were calculated based on simulated data. The performance of each control chart is based on the false alarm and the probability of outlier's detection. In general, the performance of an alternative robust Hotelling's T² charts is better than the performance of the traditional Hotelling's T² chart. Copyright © 2012 John Wiley & Sons, Ltd.     

An adaptive normal estimation method for scanned point clouds with sharp features

Normal estimation is an essential task for scanned point clouds in various CAD/CAM applications. Many existing methods are unable to reliably estimate normals for points around sharp features since the neighborhood employed for the normal estimation would enclose points belonging to different surface patches across the sharp feature. To address this challenging issue, a robust normal estimation method is developed in order to effectively establish a proper neighborhood for each point in the scanned point cloud. In particular, for a point near sharp features, an anisotropic neighborhood is formed to only enclose neighboring points located on the same surface patch as the point. Neighboring points on the other surface patches are discarded. The developed method has been demonstrated to be robust towards noise and outliers in the scanned point cloud and capable of dealing with sparse point clouds. Some parameters are involved in the developed method. An automatic procedure is devised to adaptively evaluate the values of these parameters according to the varying local geometry. Numerous case studies using both synthetic and measured point cloud data have been carried out to compare the reliability and robustness of the proposed method against various existing methods.     

一种基于GPU的大规模地形绘制算法

利用Geometry Clipmap算法的基本思想,对原算法进行简化与改进。在预处理阶段,对地形数据的存储方式进行简化,并采用Clipmap结构进行组织和管理;在绘制阶段,重点针对不同分辨率层次之间的裂缝问题进行分析和处理,提出了一种引入过渡带的方法有效消除了裂缝。实验表明,该方法有效提高渲染速率,并充分发挥GPU的优势,实现了大规模地形数据的实时可视化。     

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

This paper proposes a new modeling approach that is experimentally validated on piezoelectric systems in order to provide a black‐box pseudolinear model for complex systems control. Most of the time, one uses physical based approaches. However, sometimes complex phenomena occur in the system due to atypical changes of the process behavior, output noise or some hard nonlinearities. Therefore, we adopt identification methods to achieve the modeling task. The microdisplacements of the piezoelectric systems generate atypical data named outliers, leading to large estimated prediction errors. Since these errors disturb the classical normal probability density function, we choose here, as corrupted distribution model, the gross error model (GEM). In order to deal more efficiently with the outliers, we use the Huber's function, as mixed L₂/L₁ norms in which the tuning threshold named scaling factor is extended. From this function, a cost function also named PREC as parameterized robust estimation criterion is established. The identification is performed by choosing an Output Error model structure. In order to express the asymptotic covariance matrix of the robust estimator, we present a L finite Taylor's expansion to linearize the gradient and the hessian of the PREC. Experimental results are presented and discussed. Copyright © 2014 John Wiley & Sons, Ltd.