Multiway frequency analysis for experimental psychologists.

Many research designs in experimental psychology generate data that are fundamentally discrete or categorical in nature, and produce multiway tables of frequencies. Despite an extensive and, more recently, accessible literature on the topic, multiway frequency analysis is rarely used in experimental psychology. A reason may be the form of exposition in the literature, with emphases and concerns far removed from those of the typical experimental psychologist. An approach to multiway frequency analysis for experimental psychologists is described that has the features we want: asymmetrical designs, factors assessed for their respective main and interactive effects in a manner analogous to ANOVA, and the ability to handle within-subject designs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Abstract Reachability Approach by Combining HOL Induction and Multiway Decision Graphs

In this paper, we provide a necessary infrastructure to define an abstract state exploration in the HOL theorem prover. Our infrastructure is based on a deep embedding of the Multiway Decision Graphs (MDGs) theory in HOL. MDGs generalize Reduced Ordered Binary Decision Diagrams (ROBDDs) to represent and manipulate a subset of first-order logic formulae. The MDGs embedding is based on the logical formulation of an MDG as Directed Formulae (DF). Then, the MDGs operations are defined and the correctness pro...     

基于动态MPLS的发酵过程效益函数在线预报

针对发酵过程观测数据与时序相关,提出一种动态多方向偏最小二乘回归(MPLS)方法,该方法的多模型结构解决了非线性和实时性的问题,更加适用于发酵过程的在线预报,与人工神经网络(ANN)方法相比,动态MPLS回归模型可以达到更好的拟合和预报精度.对青霉素发酵过程的效益函数拟在线预报,验证了该方法的准确性和有效性.     

Multiway independent component analysis mixture model and mutual information based fault detection and diagnosis approach of multiphase batch processes

Batch process monitoring is a challenging task, because conventional methods are not well suited to handle the inherent multiphase operation. In this study, a novel multiway independent component analysis (MICA) mixture model and mutual information based fault detection and diagnosis approach is proposed. The multiple operating phases in batch processes are characterized by non‐Gaussian independent component mixture models. Then, the posterior probability of the monitored sample is maximized to identify the operating phase that the sample belongs to, and, thus, the localized MICA model is developed for process fault detection. Moreover, the detected faulty samples are projected onto the residual subspace, and the mutual information based non‐Gaussian contribution index is established to evaluate the statistical dependency between the projection and the measurement along each process variable. Such contribution index is used to diagnose the major faulty variables responsible for process abnormalities. The effectiveness of the proposed approach is demonstrated using the fed‐batch penicillin fermentation process, and the results are compared to those of the multiway principal component analysis mixture model and regular MICA method. The case study demonstrates that the proposed approach is able to detect the abnormal events over different phases as well as diagnose the faulty variables with high accuracy. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2761–2779, 2013     

滑动模型MPCA在间歇过程故障检测与诊断中的应用

本文针对间歇生产过程复杂非线性的特点及控制系统的实时监测要求,提出了滑动模型MPCA方法。这种方法首先将三维原始数据空间按不同测量时刻切割成一系列子数据空间,然后根据选取的模型大小将各个时间段中子数据块整合成具有相同数据结构的一系列新的子数据空间,分别建立各个子MPCA模型。滑动模型MPCA方法能够在尽可能小的时间段中监测系统运行状况,能够较好解决间歇生产过程中的非线性问题,并且更好地保证数据信息抽取的完整性。仿真实例验证了该方法的有效性。     

掘进机电液双控系统的研究

 在掘进机智能化发展过程中，远程遥控和机载控制并存状态是必不可少的。掘进机一般采用电液双控系统来实现该功能，但实践中采用电液双控系统会出现液控动作缓慢的问题。当掘进机装载运输同时动作并采用液控操作时，装运马达转速缓慢甚至停转，严重影响正常工作。结合现场故障现象，分析掘进机电液双控系统的工作原理及各元件原理，排除故障并进行深入研究。基于现有技术条件，提出改造方案并选择可行方案试验，最终从根本上解决问题。     

由AT89C51/55构成的温湿度自动监测系统

介绍以AT89C51／55单片机为核心的主从机温湿度自动巡回监测系统；此系统主要由单片机、传感器、多路开关和信号处理、A／D转换子系统等组成，其中多路信号选择由CD4051和CD4052完成，电路简单可靠。     

基于滚动MPCA的青霉素发酵过程的在线监控

To reduce the variations of the production process in penicillin cultivations, a rolling multivariate statistical approach based on multiway principle component analysis （MPCA） is developed and used for fault diagnosis of penicillin cultivations. Using the moving data windows technique, the static MPCA is extended for use in dynamic process performance monitoring. The control chart is set up using the historical data collected from the past successful batches, thereby resulting in simplification of monitoring charts, easy tracking of the progress in each batch run, and monitoring the occurrence of the observable upsets. Data from the commercial-scale penicillin fermentation process are used to develop the rolling model. Using this method, faults are detected in real time and the corresponding measurements of these faults are directly made through inspection of a few simple plots （t-chart, SPE-chart, and T2-chart）. Thus, the present methodology allows the process operator to actively monitor the data from several cultivations simultaneously.     

基于多时段MFDA的水压试验机故障诊断

由于水压试验机机理建模的复杂性,很难从机理方面对其生产过程进行故障诊断,因此利用钢管水压试验系统过程变量多、打压速度快,短时间内能够产生大批数据信息的特点,提出了基于多时段多向Fisher判别分析方法用于水压试验机打压过程的故障诊断.该方法根据不同的故障在不同的时段有不同的表征,将水压机生产过程分成多个时段,对每个子时段的数据分别建立MFDA模型用于故障诊断.采用了水压试验机生产过程的几类故障数据对该方法进行验证,结果表明该方法具有很好的故障诊断性能.     

基于MKECA的非高斯性和非线性共存的间歇过程监测

多向核独立成分分析（multiway kernel independent component analysis,MKICA）在监测间歇过程非高斯性和非线性方面取得了广泛应用,其仅仅是将线性独立成分分析（independent component analysis,ICA）方法利用核主成分分析（kernel principal component analysis,KPCA）白化扩展到非线性领域,但数据经KPCA白化后只考虑数据信息最大化未考虑数据簇结构信息的不足,为解决此问题,采用核熵成分分析（kernel entropy component analysis,KECA）代替KPCA白化的过程监测方法。该方法首先利用AT展开方法将过程三维数据变为二维数据;其次用KECA进行白化处理的同时解决数据的非线性;然后建立ICA监测模型用于非高斯生产过程监测;最后将该方法应用到青霉素发酵仿真和实际的工业过程并与MKICA方法进行对比,验证该方法的有效性。