【作者】 叶鲁彬；

【导师】 梁军；

【作者基本信息】 浙江大学 ， 控制科学与工程， 2011， 博士

【摘要】 在现代工业过程中,为了降低生产成本、减少排放与能耗,保持企业的竞争力,需要使过程安全、可靠、平稳地运行,其中安全问题为至关重要。过程故障是引起工业安全隐患、危险状况的重要原因,过程监控的研究致力于解决故障的检测、分离、诊断、过程恢复等,已经成为自动化领域的一个重要分支。根据过程监控模型的不同,一般可以将监控方法分为基于解析模型、数据驱动和基于知识或定性模型的方法。相比于故障检测和诊断,安全分析与评价更多地是从工艺角度具体细致地描述过程设备、运行状态的安全性。过程故障的自动恢复性控制、实时安全性评价和自动安全控制等将是过程控制今后的一个重要发展方向,而实现这工作的第一步则需要得到过程安全性的实时分析和评价结果。过程监控与故障诊断、安全性能的分析评价等研究已取得许多理论和应用成果,但同时也存在较多尚未解决的问题。本文从初步讨论控制策略对故障检测的影响出发,接着提出解决一类复杂故障的分离问题的方法,然后探索性地构造了两种安全性指数,从变量安全约束和动态稳定型两方面得到运行状态的安全性的在线评价结果。由于该领域涉及的方面较广,文中不可能巨细无遗地对所有问题进行研究,但也希望借助本文的探讨抛砖引玉,供作深入研究的引子。本文主要工作和创新结果如下：(1)针对工业过程运行中的一些复杂现象进行介绍和讨论。由于工业过程涉及到很多复杂的物质、能量交换和物理化学变化,往往具备规模大、变量多,高度非线性、强耦合性与相关性等特征。控制策略的引入改变了系统输入输出、动态关系；受到各种过程固有特征和外在因素变化的影响,工业过程会呈现出多工况或多模式的运行状态；作为非线性系统,许多工业过程存在分岔现象,影响系统的稳定性与安全性。工业过程复杂的运行状态给故障检测和诊断、安全分析和评价的研究带来了较大的困难和挑战。然后以Tennessee Eastman(TE)过程为例,初步讨论了过程控制策略对监控性能的影响。(2)基于结构化残差(Structured Residuals)的故障分离方法的原理在于为不同故障设计具有区分功能的残差响应特征,将故障特征进行解耦。工业过程中普遍存在对系统有复杂影响的故障,其解耦难度较大,甚至是不可分离性的。在过程的主成分分析(Principal Component Analysis, PCA)模型下,提出一种多层策略,去除复杂故障的共同影响特征,将其转化成简单故障。然后分配至不同层进行区分,在设计结构化残差时,每个残差被设置为对某一故障不敏感,同时最大化其对其余故障响应的敏感度。经过逐层特征抽取和结构化残差设计,最后得到表征各残差对全部故障响应特征的事件矩阵,用于分类全部简单或复杂的故障。将该方法应用于TE过程,仿真实验结果证明了其有效性。(3)为了实时地给出过程运行安全性的在线评价,提出一种基于多模式工况识别的方法。首先基于工业过程的历史运行数据,使用混合高斯模型(Gaussian Mixture Model, GMM)来表征过程的多工况状态,并在线识别当前工况。将过程变量变化至其安全边界的概率作为安全性指数(Safety Index, SI),用于描述当前工况的安全程度,该指数的构造可以视为从高维的过程变量空间至指数空间的一个映射。根据历史运行的安全性能指数值的范围进行等级划分,并在一个较低的D空间中得到与不同安全性能等级的子集(子空间)与区域边界,然后可以得到当前安全性能在子空间内的裕度。将该指数应用于TE过程和一个工业聚丙烯(Polypropylene, PP)生产过程,实验结果表明SI能够实时指示过程运行安全性的变化,并为提高过程安全性能的进一步操作提供调节方向的参考。(4)基于Hopf分岔分析,从动态稳定性方面对工业过程运行状态进行安全性评价。采用分岔方程描述过程系统的Hopf分岔点所在的临界曲面,并作为系统参数或操作变量的安全边界,然后构造了一个动态安全性指数(Dynamic Safety Index, DSI)用于综合描述各参数到其分岔点的距离。将该方法应用于一个聚乙烯(Polyethylene, PE)流化床反应器的仿真过程中,结果表明该动态安全性指数能够有效指示过程系统的运行状态至分岔现象的距离,并能提早对可能发生不稳定振荡现象进行预警。最后,对全文作出总结,归纳了研究和分析的内容及结果,指出研究成果中存在的一些未解决的问题,并展望了接下来的研究方向。更多还原

【Abstract】 In modern industry, in order to lower the production cost, reduce the emission and energy consumption, it is necessary to keep the process operations in safe, reliable and steady states. In all of them, the safety issue is the most important. In practical industries, process faults or malfunctions are the main causes of unsafe threats and hazardous situations. The research of process monitoring is focused on the solution of fault detection, isolation, diagnosis, process recovery, etc. And it is now more of the important branch of industry automation. According to different monitoring models, the methodology of process monitoring can be usually classified into three categories:the approaches based on analytical models, data-driven, and based on knowledge or qualitative models. Compared with the fault detection and diagnosis, the approaches of safety analysis and assessment provide more particular descriptions on process operation or equipment safety degree based on the process characterizations. The automation in fault diagnosis, fault-recovery control, online safety assessment, and safety control is one of the future directions in process automation. And the step to achieve these is to obtain the online assessment results of operation safety.The studies on process monitoring & fault diagnosis, safety assessment have developed greatly, both on theories and practical applications. However, there are many unsolved issues. In this thesis, the impact of control strategy on the fault detection performance is discussed firstly. Then, a method is proposed to address the issue of complex fault isolation based on structured residuals. As an explorative work, two types of safety index are then constructed, characterizing the operation safety based on the process variable constraints and dynamic stability properties. Since the area of process monitoring & fault diagnosis and safety assessment is very vast, it is impossible to list and discuss all issues detailedly in the thesis. The main innovative work of this paper is as follows.(1) Some introductory discussions on the complex phenomena in the industrial processes. The practical industries are always involved with complicated mass and energy exchanges and meanwhile accompanied with physical or chemical reactions. And the process systems usually have the features like large-scale, high dimension of variables, nonlinearity, strong coupling, and correlation. The introduction of process control loops changes the input-output relations and dynamic characterizations of the system. The process operations may have multiple modes in practical situations due to parametric drifts, disturbance, feedstock, and environmental impacts. For nonlinear systems, there might be some complex phenomena, like bifurcation, which may have impacts on the system stability properties. It is stated that the complexity operation states in industrial process bring a great of difficulties and challenges to study and application of the process monitoring and safety assessment. Taking the Tennessee Eastman (TE) process as an example, some preliminary discussions on the impact of control strategies on the fault detection performance.(2) The principle of fault isolation approach based on structured residuals lies in the decoupling of the fault features by designing appropriate structured residuals. However, many faults in industry processes are too complicated to be decomposed. Under the principal component analysis (PCA) model, a multi-level strategy is proposed to extract the complex fault features, and assign the faults on different levels, where the structured residuals are designed to achieve best isolation performance. Each residual is expected to be insensitive to one fault and most sensitive to others. Lastly, a general incidence matrix is obtained to represent all residual response to faults, based on which all faults are isolated. The approach is applied in the TE process simulation results, which demonstrates the effectiveness.(3) A method based on multiple-mode identification is proposed in order to give an online assessment on the process operation. The Gaussian Mixture Model (GMM) is adopted to characterize the historical operation modes and identify the current state. A probabilistic safety index (SI) is constructed to denote the distance from the current operation to the safety limits. The calculation of the SI can be seen as two successive mappings. The original process variable space can be segmented into several subspaces, which are corresponding to different SI levels. In the D space, which have lower dimensions, the boundaries between different subspaces are obtained, and the current operation margin in a certain SI level can be calculated. The method is applied to the TE process and an industrial polypropylene (PP) process, and the results show that the SI can effectively show the variations in the operation safety, and provide preliminary advice on the manipulating directions to improve the process operation safety.(4) Considering the dynamic stability of process system, an approach is proposed to assess the process operation safety based on Hopf bifurcation analysis. Hopf bifurcation equations are adopted to characterize the curved surface of the Hopf points in the parameter space. A dynamic safety index (DSI) is constructed to represent the distance of the current operation state to the safety limits, i.e., the Hopf surface. The DSI is applied in a simulated gas-phase fluidized polyethylene reactor process. The results demonstrate that the DSI can effectively characterize the distance of the operation state to the Hopf bifurcation, and it is also able to give alerts on the unstable oscillations in advance, which is very beneficial to the practical maintenance of process operation.In the last chapter, conclusions of the thesis are summarized. Some unsolved problems and the prospects on the future study areas are pointed out and preliminarily discussed.更多还原