基于独立元的k近邻故障检测策略

k近邻故障检测(fault detection based on k nearest neighbors,FD–k NN)方法能够提高具有非线性和多模态特征过程的故障检测率.由于系统故障通常由潜隐变量异常变化引起,而该类型故障并不能被观测数据直观表现,因此直接在观测变量上执行FD–k NN方法,其故障检测率降低.本文旨在提高FD–k NN方法针对潜隐变量故障的检测能力,提出基于独立元的k近邻故障检测方法.首先,通过对观测数据应用独立元分析(independent component analysis,ICA)方法,获得独立元矩阵;接下来在独立元矩阵中应用FD–k NN方法进行故障检测.这等同于直接监控过程潜隐变量的变化,可以提高过程故障检测率.通过非线性实例仿真实验,证明本文方法检测潜隐变量故障是有效的;同时,在半导体蚀刻工艺过程的仿真实验中,与主元分析(principal component analysis,PCA)方法、核主元分析(kernel principal component analysis,KPCA)方法、基于主元分析的k近邻故障检测(principal component–based k nearest neighbor rule for fault detection,PC–k NN)方法和FD–k NN方法进行对比,实验结果进一步验证了本文方法的有效性.

基于k近邻主元得分差分的故障检测策略

针对具有非线性和多模态特征过程的故障检测问题,本文提出一种基于k近邻主元得分差分的故障检测策略.首先,通过主元分析(Principal component analysis,PCA)方法计算样本的真实得分.然后,应用样本的k近邻均值计算样本估计得分.接下来,通过上述两种得分计算样本的得分差分矩阵和残差矩阵,其中残差矩阵由样本的估计得分计算得到,这区别于传统方法.最后,在差分子空间和残差子空间中分别建立新的统计指标进行故障检测.值得注意的是本文的得分差分方法能够消除数据结构对过程故障检测的影响,同时,新的统计量能够提高过程的故障检测率.将本文方法在两个模拟例子和Tennessee Eastman(TE)过程中进行测试,并与传统方法如PCA、KPCA、DPCA和FD-k NN等进行对比分析,测试结果证明了本文方法的有效性.

Multiple fault diagnosis of down-hole conditions of sucker-rod pumping wells based on Freeman chain code and DCA

It is important to achieve continuous, stable and efficient pumping well operation in actual oilfield operation. Down-hole pumping well working conditions can be monitored in real-time and a reasonable production scheme can be designed when computer diagnosis is used. However, it is difficult to make a comprehensive analysis to supply efficient technical guidance for operation of the pumping well with multiple faults of down-hole conditions, which cannot be effectively dealt with by the common methods. To solve this problem, a method based on designated component analysis （DCA） is used in this paper. Freeman chain code is used to represent the down-hole dynamometer card whose important characteristics are extracted to construct a designated mode set. A control chart is used as a basis for fault detection. The upper and lower control lines on the control chart are determined from standard samples in normal working conditions. In an incompletely orthogonal mode, the designated mode set could be divided into some subsets in which the modes are completely orthogonal. The observed data is projected into each designated mode to realize fault detection according to the upper and lower control lines. The examples show that the proposed method can effectively diagnose multiple faults of down-hole conditions.

带有执行器饱和的变时滞Markovian跳变系统的DOBC控制

针对一类转移概率部分未知的Markovian跳变系统,考虑系统中存在时变时滞以及执行器饱和的情况,研究此类系统基于干扰观测器的抗干扰控制(Disturbance-observer-based-control, DOBC)问题.首先,分析带有扰动估计误差的闭环系统的随机稳定性,通过构建适当的模态依赖型Lyapunov-Krasovskii(L-K)泛函并引入自由权矩阵,给出闭环系统的随机稳定性判据;然后,将控制器增益以及观测器增益的求解问题转化为带有线性矩阵不等式约束的可行性问题,并通过迭代优化算法得到最大吸引域的估计值;最后,通过仿真算例,验证所提出方法的正确性和有效性.

Approach of Synthesizing Model Predictive Control and Its Applications for Rotary Kiln Calcination Process

An actual control demand of rotary kiln is taken as background. By analyzing and improving approach of MPC （synthesizing model predictive control）, an effective strategy which applies complex S-MPC in actual industrial process is designed. Firstly, after analyzing the main components technology and calcination reaction mechanism in detail, the calcining belt state-space model of rotary kiln is built using PO-Moesp （past-output multivariable output error state space model identification） method. Then, calcining belt temperature predictive control system is de signed. The control system combines time-delay gain scheduled, output-tracking, recursive subspace adaptive and other methods, and forms the off-line/on-line predictive controller of rotary kiln. At last, MATLAB is applied for simulation, experiments run in constant value tracking and servo tracking situation. Simulation results show its ef- fectiveness and feasibility.