基于GPS的变形监测数据处理时间间隔的合理确定

应用概率统计原理,分析研究变形监测精度、数据处理时间间隔及位移速度3者之间的关系,给出其应满足的理论关系式,为合理确定变形监测数据处理时间间隔和监测精度提供理论依据;在此基础上,具体分析了地壳板块运动、滑坡和周期性变形监测数据处理的合理时间间隔,结果对实际工作具有指导意义.

一种缩短某型飞行器飞控组件测试数据处理时间的方法

某型飞行器的飞控组件测试数据量大,处理这些测试数据需要耗费大量的时间,造成产品交付进度慢。为解决这个问题,文章首先分析了造成某型飞控组件测试数据处理时间长的主要原因,通过建立理论模型、优化试验流程、开发数据处理软件等手段进行控制,缩短了产品试验数据处理时间。结果表明,与改进前对比,使用该方法后飞控组件测试数据处理时间明显缩短。

基于腔式探头的束团到达时间测量算法优化

腔式探头具有高信噪比和高灵敏度的特性,TM_(010)模式下在近轴附近的腔体输出信号与束流横向位置无关,信号幅度与电荷量呈正比,信号相位由束团到达时间决定,因此非常适用于高分辨率的束团到达时间测量。上海硬X射线自由电子激光装置(SHINE)对束团到达时间的测量精度要求非常高,期望运用基于谐振腔的束团到达时间监测系统,可实现在100 pC电荷量下分辨率好于25 fs的技术指标。对于高Q的谐振腔信号,单点采样的信噪比随信号的衰减而降低,因此肯定存在一最佳的信号处理窗口。为分析最佳处理窗口与相关参数的定量关系,采用数值仿真和束流实验相结合的办法来研究这个问题。分析发现,存在最佳数据处理时间窗口,该参数只与信号衰减时间常数有关,而与系统采样率、系统信噪比、系统模拟带宽无关。在最佳数据处理时间窗口条件下,束流到达时间测量不确定性可获得最佳值。

基于LSTM模型的量化投资时间序列数据处理研究

长短期记忆网络(LSTM)因其强大的序列建模能力,成为时间序列预测任务中的主流深度学习模型。然而,股票数据作为典型的时间序列数据,常常面临数据格式多样、内容错误、非线性和非平稳性、模型数据要求格式高等问题。该文详细阐述了针对LSTM的时间序列数据处理方法,并基于Python语言进行了实证检验。实验证明,经过优化的数据处理流程不仅减少了模型训练过程中的错误,还显著提升了预测精度。

啤酒发酵中温度的测控方法

结合集散控制系统的特点,设计了一种嵌入式啤酒发酵控制系统。该系统采用自主研发的智能化SOC(System on Chip)嵌入式数据终端处理器作为控制终端;通过差动中值定标的方法实现现场高精度检测;使用固定周期预测增量控制方法对啤酒发酵的温度进行控制;采用时间隧道数据处理器处理的方法而使数据处理系统化,提高了系统的稳定性和连贯性;数据终端处理器配置通用串行口,与工控计算机组成局域网实现集散式控制。实践证明,该系统不仅成本低、功能强,而且灵活、可靠。

影响频谱分析仪测量速度的因素

频谱分析仪是射频无线产品性能测量不可缺少的设备,它的操作比较复杂和花费时间,工程技术人员往往处理不当而影响完成项目的进度,特别是频谱分析仪的测量时间,搞不好要等待几十分钟才获得测量结果.扫描时间在频谱分析仪中占有很大份额,对于采用模拟的分辨率滤波器的仪器来说,扫描时间可表示为:

Scheduling transactions in mobile distributed real-time database systems

A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments. At the mobile hosts, all transactions perform local pre-validation. The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle. Transactions that survive in local pre-validation must be submitted to the server for local final validation. The new protocol eliminates conflicts between mobile read-only and mobile update transactions, and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly shortened. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants. The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate, restart rate, commit rate. Under high work load （think time is ls） the miss rate of DMVOCC-MVDA is only 14.6%, is significantly lower than that of other protocols. The restart rate of DMVOCC-MVDA is only 32.3%, showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions. And the commit rate of DMVOCC-MVDA is up to 61.2%, which is obviously higher than that of other protocols.

Combined GPS/GLONASS Data Processing

To obtain the GLONASS satellite position at an epoch other than reference time,the satellite’s equation of motion has to be integrated with broadcasting ephemerides.The iterative detecting and repairing method of cycle slips based on triple difference residuals for combined GPS/GLONASS positioning and the iterative ambiguity resolution approach suitable for combined post processing positioning are discussed systematically.Experiments show that millimeter accuracy can be achieved in short baselines with a few hours’ dual frequency or even single frequency GPS/GLONASS carrier phase observations,and the precision of dual frequency observations is distinctly higher than that of single frequency observations.

The Application of Multiquadric Function Fitting to Borehole Strain Time Series Data Processing

Based on the existing continuous borehole strain observation,the multiquadric function fitting method was used to deal with time series data. The impact of difference kernel function parameters was discussed to obtain a valuable fitting result,from which the physical connotation of the original data and its possible applications were analyzed.Meanwhile,a brief comparison was made between the results of multiquadric function fitting and polynomial fitting.

A Contraction-expansion Helical Mixer in the Laminar Regime

A contraction-expansion helical mixer which combines several features, viz. helical pipes for induction of secondary flows and sudden expansion and contraction array tor expansion vortices, has been designed to en- hance flow mixing. A fast competitive-consecutive diazo coupling reaction is used to test the mixing efficiency of contraction-expansion helical mixer. Furthermore, an image processing technique is applied for data visualization and monitoring the extent of mixing. The mixing performance is found to be superior in comparison to the regular helical mixer in the range of Reynolds number from 170 to 1540. Moreover, the mixing time of contraction-expansion helical mixer was found to be reduced by more than 25% compared to the regular helical pipe. Finally, a simple correlation is proposed for predicting the mixing time.