Jochen Schröder

Bio: Jochen Schröder is an academic researcher from University of Hamburg. The author has contributed to research in topics: Fault detection and isolation & Fault (power engineering). The author has an hindex of 6, co-authored 16 publications receiving 2833 citations.

Diagnosis and Fault-Tolerant Control

Abstract: This book presents model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, test fault detectability and reveal redundancies that can be used to ensure fault tolerance. Case studies demonstrate the methods presented. The second edition includes new material on reconfigurable control, diagnosis of nonlinear systems, and remote diagnosis, plus new examples and updated bibliography.

Sensor and actuator fault diagnosis of systems with discrete inputs and outputs

Abstract: The paper describes a method for detecting and identifying faults that occur in the sensors or in the actuators of dynamical systems with discrete-valued inputs and outputs. The model used in the diagnosis is a stochastic automaton. The generalized observer scheme (GOS), which has been proposed for systems with continuous-variable inputs and outputs some years ago, are developed for discrete systems. This scheme solves the diagnostic problem as an observation problem, which is set up here for discrete-event systems. As the system under consideration is described by a stochastic automaton rather than a differential equation, the mathematical background and the diagnostic algorithms obtained are completely different from the well-known observers developed for continuous-variable systems. The GOS is extended here by a fault detection module to cope with plant faults that are different from actuator or sensor faults. The diagnostic algorithm consists of two steps, the first detecting the existence of a fault and the second isolating possible sensor or actuator faults or identifying plant faults. The results are applied to quantized systems whose discrete inputs and outputs result from a quantization of the continuous-variable input and output signals. Experimental results illustrate the proposed diagnostic method.

Prozeßdiagnose mittels qualitativer Modelle am Beispiel eines Was ser Stoffverdichter s

Abstract: In diesem Beitrag werden ein Diagnoseverfahren basierend auf qualitativen Modellen und die Ergebnisse einer prakischen Anwendung auf einen Wasserstoffverdichter vorgestellt. Dazu wird sowohl ein Ansatz zur qualitativen Modellierung durch stochastische Automaten als auch eine Methode zur qualitativen Identifikation und qualitativen Prozeßdiagnose erläutert. In einem Anwendungsbeispiel wird exemplarisch gezeigt, daß diese Methoden mit Hilfe modemer Betriebsbzw. Prozeßdateninformationssysteme praktisch eingesetzt werden können.

Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools

Abstract: A most critical and important issue surrounding the design of automatic control systems with the successively increasing complexity is guaranteeing a high system performance over a wide operating range and meeting the requirements on system reliability and dependability. As one of the key technologies for the problem solutions, advanced fault detection and identification (FDI) technology is receiving considerable attention. The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers.

A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

Abstract: Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-driven methods have been receiving considerably increasing attention, particularly for the purpose of process monitoring. However, great challenges are also met under different real operating conditions by using the basic data-driven methods. In this paper, widely applied data-driven methodologies suggested in the literature for process monitoring and fault diagnosis are surveyed from the application point of view. The major task of this paper is to sketch a basic data-driven design framework with necessary modifications under various industrial operating conditions, aiming to offer a reference for industrial process monitoring on large-scale industrial processes.

A Survey of Fault Detection, Isolation, and Reconfiguration Methods

Abstract: Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.