Showing papers by "Raghunathan Rengaswamy published in 2003"
TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
2,263 citations
TL;DR: This final part discusses fault diagnosis methods that are based on historic process knowledge that need to be addressed for the successful design and implementation of practical intelligent supervisory control systems for the process industries.
1,902 citations
TL;DR: This part of the paper reviews qualitative model representations and search strategies used in fault diagnostic systems and broadly classify them as topographic and symptomatic search techniques.
1,415 citations
TL;DR: A fuzzy-reasoning approach is proposed to ensure robustness to the inherent uncertainty in the identified trends and to provide succinct mapping in fault diagnosis of an exothermic reactor case study.
125 citations
TL;DR: In this paper, the authors focus on the systematic development of graph models and the conceptual relationship between the analysis of graph model and the underlying mathematical description and the analysis procedures for the graph model.
Abstract: In the recent past, graph-based approaches have been proposed by various researchers for safety analysis and fault diagnosis of chemical process systems. Though these approaches have shown promise, there are a number of important issues that have not been adequately addressed in the literature. The issue of systematic development of graph representations for chemical processes has not been addressed in the literature. This is an important issue because the development of digraphs is error-prone and time-consuming. Further, little attention has been paid toward understanding the conceptual relationship between the underlying mathematical description and the analysis procedures for the graph model. Also, the utility of these graph-based approaches at a flowsheet level has not been studied. With these issues in perspective, in this first part of the two-part paper, we focus on the systematic development of graph models and the conceptual relationship between the analysis of graph models and the underlying ma...
124 citations
TL;DR: In this paper, the authors present a signed digraph (SDG) model for control loops and discuss a framework for application of graph-based approaches at a flowsheet level.
Abstract: The objectives of this part of the two part paper are (i) development of signed digraph (SDG) models for control loops and (ii) discussion of a framework for application of graph-based approaches at a flowsheet level. Further, two case studies are used to explain the methods developed in part 11 (Ind. Eng. Chem. Res. 2003, 42, in press) and this paper. The first case study (continuous stirred tank reactor case study) explains the basic concepts of the generate and test method for SDG analysis, generation of redundant equations using algebraic manipulation, and analysis of systems with a single control loop. Case study 2 (flash vaporizer case study) deals with different methods of generating redundant equations and the analysis of systems with multiple interacting control loops.
78 citations
TL;DR: In this paper, a unified multi-objective formulation for the input design is proposed, where the input can be evaluated as a solution to a constrained multiobjective optimization problem.
10 citations
TL;DR: This paper presents a PCA-QTA technique for fault diagnosis (FD) in large-scale plants that is applied on the principal components rather than on the sensor data and reduces computational complexity in trend-extraction by about 40%.
6 citations
TL;DR: In this article, a unified signed directed graph (SDG) model for control loops is proposed, in which both disturbances (sensor bias etc.) as well as structural faults can be easily modeled.
Abstract: Though signed directed graphs (SDG) have been widely used for modeling control loops, due to lack of adequate understanding of SDG-based steady state process modeling, special and cumbersome methods are used to analyze control loops. In this article, we discuss a unified SDG model for control loops (proposed by Maurya et al. (2002 b ) ), in which both disturbances (sensor bias etc.) as well as structural faults (sensor failure etc.) can be easily modeled. Various fault scenarios such as external disturbances, sensor bias, controller failure etc. have been discussed. Two case studies are presented to show the utility of the SDG model for fault diagnosis. A tank-level control system is used as first case study. The second case study deals with fault diagnosis of a multi-stream controlled CSTR.
3 citations
TL;DR: In this paper, the authors presented a PCA-QTA technique for fault diagnosis in large-scale plants to reduce the computation time, which is applied on the principal components rather than on the sensor data.
Abstract: Quick fault detection and diagnosis is very important for effective process operations management. Qualitative trend analysis (QTA), a data-driven semiquantitative technique, has been widely used for fault diagnosis (FD). Though QTA provides quick and accurate diagnosis - the increase in computational complexity of QTA with the increase in the number of sensors used for diagnosis - may prohibit its real-time application for very large-scale plants. In most of the chemical plants, the measurements are highly redundant and this redundancy can be exploited by performing principal component analysis (PCA) on the measured data. In this paper, we present a PCA-QTA technique for fault diagnosis in large-scale plants to reduce the computation time. Essentially, QTA is applied on the principal components rather than on the sensor data. The results are quite promising for the Tennessee Eastman (TE) process
2 citations