基于AT89S51单片机的pH值控制器的设计

由于pH过程的非线性和滞后性,本文主要应用分段式变增益PID的处理方法,设计了以AT89S51单片机为主控制芯片的pH值控制器,完成了软硬件设计,有效的实现了数据处理、数据LED显示、键盘控制等功能,其电路主要由AT89S51单片机和其外围扩展电路组成。     

C616型普通车床的数控化改造

我国仍有大量的车床采用落后的手工操作方式,效率低、能耗高,工人的劳动强度大,因此,对普通车床进行技术改造是刻不容缓的事情。文章采用FANUC 0-TT数控系统对C616普通车床进行数控化改造。     

北海电厂再热烟气挡板自动调节系统改进

再热汽温调节在自动控制中占有重要的地位,而再热烟气调节挡板进行自动调节是调节再热汽温的主要手段。本文结合广西北海电厂再热汽温调节的具体情况,介绍再热烟气调节挡板自动调节的特点及逻辑实现。     

钢箱梁顶推施工技术

实践证明,钢箱梁斜拉桥采用顶推法施工时,不需大型浮吊等起吊设备,占用场地小,钢箱梁顶推、边跨支架梁段安装和塔柱的施工可同时进行,提高施工效率,节约成本,充分显示了本桥施工方法的合理性、先进性与独创性。     

Professionalism vs Commercialism: The Association Between Non-Audit Services (NAS) and Audit Independence

This paper examines the relative information content of earnings and cash flows for security returns using a methodology incorporating contextual factors which may affect earnings and cash flow response coefficients. For our UK dataset, we provide evidence that the earnings coefficient is related to earnings permanence, growth and firm size and that the cash flow coefficient may be related to growth. Although our results emphasise the value relevance of earnings, they also suggest that both contemporaneous and prior period cash flow are positively related to security returns and that market-to-book and market value of equity have predictive power for returns.     

真空烧结炉炉温控制系统关键技术研究

针对真空烧结炉温度控制过程具有大滞后、时变、非线性等特点,讨论了烧结炉炉温控制的相关关键技术,提出了自适应Fuzzy-PID复合控制算法。在算法研究的基础上,以西门子S7-200PLC为控制核心,针对真空烧结炉进行了控制器设计。     

大功率整流元件性能测试系统的研制

文章详细介绍了大功率整流元件性能测试系统的工作原理和组成,系统采用全动态测试方法测试整流元件的主要参数,利用FIR数字滤波和数字积分分离PID控制算法进行测试系统的数字采样及控制,通过专用工控机上的VisualC++6.0软件编程实现测试系统的全自动化测试。     

微控制器PID算法在风力发电变桨系统中的应用

风能作为一种清洁的可再生能源,已成为世界各国新能源供应的重要手段,发展前景非常广阔。为了克服风能稳定性差的缺点,本文设计了基于微控制器PID算法的风电变桨控制系统,实现对发电机输出功率的恒定控制。     

基于DSP的PID控制算法的研究

随着计算机和信息技术的不断进步,数字信号处理器(DSP)技术得以飞速发展,DSP凭借其高效的实时性使得其在数据信号处理方面应用有着广泛的。PID控制算法要求控制器具有快速运算、快速响应的能力,单片机在这方面处理能力远不如DSP。本文将PID控制算法和DSP技术相结合,详细阐述了基于DSP的PID控制算法,为PID控制算法在实际工程中的应用奠定了基础。     

Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?

Principal component analysis (PCA) is a method of choice for dimension reduction. In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to perform the PCA of streaming data and/or massive data. Despite the wide availability of recursive algorithms that can efficiently update the PCA when new data are observed, the literature offers little guidance on how to select a suitable algorithm for a given application. This paper reviews the main approaches to online PCA, namely, perturbation techniques, incremental methods and stochastic optimisation, and compares the most widely employed techniques in terms statistical accuracy, computation time and memory requirements using artificial and real data. Extensions of online PCA to missing data and to functional data are detailed. All studied algorithms are available in the  package onlinePCA on CRAN.