Supervision, fault-detection and fault-diagnosis methods — An introduction

Isermann, Rolf

doi:10.1016/s0967-0661(97)00046-4

Cited by 792 publications

(332 citation statements)

References 14 publications

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“…Take a Fault Detection Isolation and Recovery (FDIR) application for example; it reuses process data from different aspects of the test systems network to detect faulty operation of systems; learning signature patterns and their eventual failure modes [2]. This function could then be used to automatically manage moderate faults or activate an alarm before a failure occurs.…”

Section: Requirements Of Data Dependent Applicationsmentioning

confidence: 99%

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An `on-demand' data communication architecture for supplying multiple applications from a single data source: an industrial application case study

Azolibe

McGookin

2015

7th EVI-GTI International Gas Turbine Instrumentation Conference

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A key aspect of automation is the manipulation of feedback sensor data for the automated control of particular process actuators. Often in practice this data can be reused for other applications, such as the live update of a graphical user interface, a fault detection application or a business intelligence process performance engine in real-time. In order for this data to be reused effectively, appropriate data communication architecture must be utilised to provide such functionality. This architecture must accommodate the dependencies of the system and sustain the required data transmission speed to ensure stability and data integrity. Such an architecture is presented in this paper, which shows how the data needs of multiple applications are satisfied from a single source of data. It shows how the flexibility of this architecture enables the integration of additional data sources as the data dependencies grow. This research is based on the development of a fully integrated automation system for the test of fuel controls used on civil transport aircraft engines.

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Section: Requirements Of Data Dependent Applicationsmentioning

confidence: 99%

“…For example to determine the health of systems through analysis of process data which contains insights about the operating conditions of different components. This could be the basis for a preventative datadriven maintenance strategy that involves fixing faults before they become failures that could cost substantial amounts of money [2].…”

Section: Introductionmentioning

confidence: 99%

An `on-demand' data communication architecture for supplying multiple applications from a single data source: an industrial application case study

Azolibe

McGookin

2015

7th EVI-GTI International Gas Turbine Instrumentation Conference

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“…The residual for each healthy sensor is typically produced by means of dedicated observers [38]. Therefore, for each sensor set there are one controller and one observer.…”

Section: Sensor Fault Tolerance Via Lsdp Design and Robustness Assessmentioning

confidence: 99%

“…The sensor fault modelling can be done in three ways [38]: (i) abrupt fault (stepwise) (i) incipient fault (drift-like) and (iii) intermittent fault. For the simulation tests the first case is assumed in this paper.…”

Section: Framework Assessment and Data Analysismentioning

confidence: 99%

Optimised sensor selection for control and fault tolerance of electromagnetic suspension systems: A robust loop shaping approach

2014

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This paper presents a systematic design framework for selecting the sensors in an optimised manner, simultaneously satisfying a set of given complex system control requirements, i.e. optimum and robust performance as well as fault tolerant control for high integrity systems. It is worth noting that optimum sensor selection in control system design is often a non-trivial task. Among all candidate sensor sets, the algorithm explores and separately optimises system performance with all the feasible sensor sets in order to identify fallback options under single or multiple sensor faults. The proposed approach combines modern robust control design, fault tolerant control, multiobjective optimisation and Monte Carlo techniques. Without loss of generality, it's efficacy is tested on an electromagnetic suspension system via appropriate realistic simulations.Keywords: Optimised sensor selection, Robust control, Fault tolerant control, Magnetic levitation, Multi-objective optimisation, Electromagnetic Suspension IntroductionOptimum sensor selection in practical control system design can be complex process especially if the selection is done with respect to a number of properties in order to achieve robust optimum performance and reliability properties.A typical closed-loop control system is shown in Fig. 1. Typically, a system to be controlled has a number of candidate control inputs (actuators) and outputs (sensors) that could be used to control it by proper controller design using one of the existing modern control methods. Moreover the system suffers from input disturbances and uncertainties or model inaccuracies. Additionally, faults highly The problem of sensor/actuator selection has been addressed before in the literature [5] but none of the methods consider simultaneous satisfaction of the aforementioned properties except in [6] where the authors have consider both optimum performance and sensor fault tolerance using Linear Quadratic Gaussian (LQG) control. Therefore the problem is to find the 'best' set of sensors, Y o , subject to the aforementioned control properties i.e. optimum performance, robustness, fault tolerance and minimum number of sensors.The novelty in this paper relies in the fact that optimum robust performance with sensor fault tolerance is achieved by combining robust control methods, Fault Tolerant Control (FTC), MultiObjective OPtimisation (MOOP) and Monte Carlo (MC) method as illustrated in Fig. 2.Robust control design in a practical control system has a vital role because real systems have

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“…Although a number of detection algorithms might be sufficiently local to locate a specific fault, in general less is available to isolate (Chow & Willsky, 1984;Basseville & Nikiforov, 1993;Gertler, 1993Gertler, , 1998Himmelblau, 1978;Isermann, 1984Isermann, , 1997. Based on qualitative reasoning, the proposed approach has been developed, in part, by referring to SDG representations of control systems and their interactions.…”

Section: Introductionmentioning

confidence: 99%

Towards distributed diagnosis of the Tennessee Eastman process benchmark

Chen

Howell

2002

Control Engineering Practice

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A distributed hybrid strategy is outlined for the isolation of faults and disturbances in the Tennessee Eastman Process, which would build on existing structures for distributed control systems, so should be easy to implement, be cheap and be widely applicable. The main emphasis in the paper is on one component of the strategy, a steady state based approach. Results obtained by applying this approach are presented and knowledge limitations are discussed. In particular a way in which a knowledge-base might evolve to improve isolation capabilities is suggested and the role of the operator is briefly discussed.

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Supervision, fault-detection and fault-diagnosis methods — An introduction

Cited by 792 publications

References 14 publications

An `on-demand' data communication architecture for supplying multiple applications from a single data source: an industrial application case study

An `on-demand' data communication architecture for supplying multiple applications from a single data source: an industrial application case study

Optimised sensor selection for control and fault tolerance of electromagnetic suspension systems: A robust loop shaping approach

Towards distributed diagnosis of the Tennessee Eastman process benchmark

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