THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

计量经济分析 = Econometric analysis

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

https://www.ece.lsu.edu/mcu/lawss/add_materials/FaultDetectionPart1.pdf

A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods

A review of process fault detection and diagnosis: Part III: Process history based methods

Fault diagnosis is an important task for the safe and optimal operation of chemical processes. Hence, this area has attracted considerable attention from researchers in the past few years. A variety of approaches have been proposed for solving this problem. All approaches for fault detection and diagnosis in some sense involve the comparison of the observed hehavior of the process to a reference model. The process behavior is inferred using sensors measuring the important variables in the process. Hence, the efficiency of the diagnostic approach depends critically on the location of sensors monitoring the process variables. The emphasis of most of the work on fault diagnosis has been more on procedures to perform diagnosis given a set of sensors and less on the actual location of sensors for efficient identification of faults. A digraph-based approach is proposed for the problem of sensor location for identification of faults. Various graph algorithms that use the developed digraph in deciding the location of sensors based on the concepts of observability and resolution are discussed. Simple examples are provided to explain the algorithms, and a complex FCCU case study is also discussed to underscore the utility of the algorithm for large flow sheets. The significance and scope of the proposed algorithms are highlighted.

Locating sensors in complex chemical plants based on fault diagnostic observability criteria

Fault diagnosis is an important area in the chemical process industry and has attracted considerable attention from researchers in the recent past. All approaches for fault diagnosis depend critically on the sensors measuring the important process variables in the system. In this paper, a reliability maximization based optimization framework for sensor location from a fault diagnosis perspective is presented. The formulation is aimed toward maximizing the reliability of the fault monitoring system while satisfying the constraints imposed on the system. A minimum-cost model which minimizes the cost of the fault monitoring system while ensuring that the solution provides a minimum threshold reliability is also presented. A one-step optimization formulation which maximizes reliability and, among the various solutions with the same reliability, chooses the one with minimum cost is discussed in this paper. A methodology for obtaining the “best” sensor location irrespective of the single/multiple fault assumpti...

Comprehensive design of a sensor network for chemical plants based on various diagnosability and reliability criteria. 1. Framework

An optimally located network of sensors is a prerequisite for successful application of fault diagnosis techniques. Most of the previous work in the area of fault diagnosis deals with methodologies for identifying possible faults, given sensor data. Available literature suggests that very little work has been done on methods for optimally locating the sensors for efficient fault diagnosis. Some algorithms based on the concepts of observability and resolution were discussed in our previous work (ref 1:  Raghuraj et al. AIChE J. 1999, 45 (2), 310). These algorithms are based on a digraph (DG) representation of the process. In this article, the sensor location work is extended to use the signed directed graph (SDG) representation of the process. Various issues involved in utilizing the SDG of the process for the problem of sensor location are discussed. Algorithms for sensor network design based on the SDG of the process are detailed and applied to two chemical engineering case studies. It is shown that bett...

Mani Bhushan

Papers

Locating sensors in complex chemical plants based on fault diagnostic observability criteria

Comprehensive design of a sensor network for chemical plants based on various diagnosability and reliability criteria. 1. Framework

Design of Sensor Network Based on the Signed Directed Graph of the Process for Efficient Fault Diagnosis

Design of sensor location based on various fault diagnostic observability and reliability criteria

PHASUITE: AN AUTOMATED HAZOP ANALYSIS TOOL FOR CHEMICAL PROCESSES Part I: Knowledge Engineering Framework