Journal ArticleDOI
Process fault detection based on modeling and estimation methods-A survey
TLDR
This contribution presents a brief summary of some basic fault detection methods, followed by a description of suitable parameter estimation methods for continuous-time models.About:
This article is published in Automatica.The article was published on 1984-07-01. It has received 2367 citations till now. The article focuses on the topics: Fault detection and isolation & Process modeling.read more
Citations
More filters
Journal ArticleDOI
Actuator fault diagnosis: an adaptive observer-based technique
Hong Wang,S. Daley +1 more
TL;DR: A novel approach for the fault diagnosis of actuators in known deterministic dynamic systems by using an adaptive observer technique under the assumption that the system state observer can be designed such that the observation error is strictly positive real (SPR).
Journal ArticleDOI
Multimode process monitoring with Bayesian inference‐based finite Gaussian mixture models
Jie Yu,S. Joe Qin +1 more
TL;DR: The proposed multimode process monitoring approach based on finite Gaussian mixture model (FGMM) and Bayesian inference strategy is superior to the conventional PCA method and can achieve accurate and early detection of various types of faults in multimode processes.
Journal ArticleDOI
Reconstruction-based contribution for process monitoring
Carlos F. Alcala,S. Joe Qin +1 more
TL;DR: The lack of diagnosability of traditional contributions is analyzed for the case of single sensor faults with large fault magnitudes, whereas for the same case the proposed reconstruction-based contributions guarantee correct diagnosis.
Journal ArticleDOI
Brief paper: Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems
Zhiwei Gao,Steven X. Ding +1 more
TL;DR: A robust state-space observer is proposed to simultaneously estimate descriptor system states, actuator faults, their finite times derivatives, and attenuate input disturbances in any desired accuracy by using the linear matrix inequality (LMI) technique.
Journal ArticleDOI
Effect of model uncertainty on failure detection: the threshold selector
TL;DR: In this paper, the authors present a framework to incorporate a knowledge of modeling error in the analysis and design of failure detection systems, called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals and identifies the optimal threshold to be used in innovations-based DIA algorithms.
References
More filters
Journal ArticleDOI
Paper: A survey of design methods for failure detection in dynamic systems
TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
Book
Digital Control Systems
TL;DR: This chapter introduces the z-Transform, a new type of transform that combines Laplace Transforms, z-Transforms and Modified Z-TRANSFORMS with Convolution Integral to achieve state-of-the-art control of Discrete-Data Systems.
Journal ArticleDOI
Correspondence item: An innovations approach to fault detection and diagnosis in dynamic systems
R. K. Mehra,J. Peschon +1 more
TL;DR: A general approach to fault detection, diagnosis and prognosis in systems describable by mathematical models is outlined, based on System Theory and Statistical Decision Theory.
Dissertation
Failure accomodation in linear systems through self-reorganization.
TL;DR: In this article, the authors present a model for the first unmanned aerial vehicle (UAV) and demonstrate its performance in the first flight test of the UAV-A1.
Journal ArticleDOI
Parameter estimation for continuous-time models-A survey
TL;DR: The paper reviews the progress of research on parameter estimation for continuous-time models of dynamic systems over the period 1958-1980 and includes a classification system which conforms as closely as possible to that which has arisen naturally over the past two decades.