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Examples for fault detection in closed loops

Annual Review in Automatic Programming 1992年 17卷 235-240页

作者： R. Deibert R. Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Landgraf-Georg-Str. 4 D-6100 Darmstadt Germany

Fault diagnosis of closed control loops and its components is a topic which requires deeper investigation. Main problems are the different targets of control and fault diagnosis. control loops are designed to reduce the influence of deviations of controller, actuator, the process itself and the sensors with regard to the desired input/output behaviour. On the other hand, the aim of fault diagnosis procedures is to detect these deviations in order to decide whether they cause a failure, damage or not allowed process behaviour, and to arrange appropriate actions. State space approaches are first investigated for fault detection in control loops because they need not necessarily excitation, a cirumstance which is given in many control loops. As a first stage of the current investigations, control loops with linear components will be examined.

关键词： control loop model-based state estimation parameter estimation

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Examples for Fault Detection in Closed Loops

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IFAC Proceedings Volumes 1992年第10期25卷 235-240页

作者： R. Deibert R. Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Landgraf-Georg-Str.4 D-6100 Darmstadt Germany

关键词： control loop model-based state estimation parameter estimation

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Intelligent Actuators - Ways to Autonomous Actuating Systems

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IFAC Proceedings Volumes 1992年第6期25卷 13-26页

作者： R. Isermann U. Raab Technical University of Darmstadt Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf Georg Str. 4. D-6100 Darmstadt Germany

The integration of microelectronics within the actuator allows to not only replace the analog position controller but to add several functions which give the actuator more intelligent functions. The actuator control is performed in different levels and includes adaptive nonlinear control, optimization of speed and precision, supervision and fault diagnosis. The actuator knowledge base comprises actuator models based on parameter estimation, controller design and a storage of the learned behavior. An inference mechanism makes decisions for control and fault diagnosis and a communication module operates internally and externally. As examples electromagnetic and pneumatic actuators are considered and it is shown how the control can be improved considerably by model based nonlinear control, taking into account time varying nonlinear characteristics and hysteresis effects. The supervision with fault detection indicates faults in the electrical and mechanical subsystems of the actuator. Several experimental results are shown including the implementation on a low-cost microcontroller.

关键词： Actuators intelligent control functions nonlinear adaptive control supervision fault diagnosis

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Model-Based Fault Diagnosis of Industrial Robots: A Comparison of Different Methods

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IFAC Proceedings Volumes 1992年第28期25卷 251-255页

作者： Rüdiger Deibert Thomas Höfling Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Landgraf-Georg-Str.4 D-6100 Darmstadt Phone: +49 6151 163314 Fax : +49 6151 293445

In modern manufacturing systems it is very important to increase the safety, reliability and availability of the involved components, e.g. industrial robots. Downtime of the entire production line as a result of a single component breakdown will cause high costs which have to be avoided. Hence automatic controlled systems of high complexity should be supervised by automatic means and supplemented by appropriate diagnosis methods. Continuous time model-based procedures have been proven to present powerful tools for this purpose. In the present contribution specific approaches of parameter estimation and state estimation are applied to the mechanical components of an industrial robot. Several changes which represent typical mechanical faults were established artificially to the robot. Finally the different approaches are compared.

关键词： Model-based fault diagnosis parameter estimation fault sensitive filter industrial robot

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Model-Based Force Sensing for an Industrial Robot by Using Drive Signals

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IFAC Proceedings Volumes 1991年第9期24卷 129-134页

作者： J. Böhm Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Landgraf-Georg-Strasse 4 D-6100 Darmstadt Germany

A model—based method for sensing external forces between a workpiece and the robot’s end-effector from drive current signals will be presented. To estimate these active forces only the natural process signals (armature current and actual joint position) of the robot are used. These signals are usually available in the control system of the robot. So no additional sensor is required. The force signal in the armature current will be interpreted as a disturbing torque which is estimated by a third order adaptive disturbance observer based on mathematical dynamic models for the robot. Finally first experimental results will be presented which were obtained with an industrial robot with six degrees of freedom.

关键词： Industrial robots Modelling Disturbance observers process monitoring Force sensing

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Fault Diagnosis of Machines via Parameter Estimation and Knowledge processing

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IFAC Proceedings Volumes 1991年第6期24卷 43-55页

作者： R. Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Landgraf Georg Straße 4 D-6100 Darmstadt Germany

For further improvement of the reliability and safety of machines the automatic early detection and localization of faults is of high interest. The conventional approach is to monitor some important variables like temperatures, pressures, vibrations and to generate alarms if certain limits are exeeded. However, developing internal faults are in this way only detected at a rather late stage. By applying static and dynamic process models and common process input and output measurements the inherent relationships and redundancies can be used to detect faults earlier and to localize them better. Changes in process and signal parameters are very well suited for fault detection. The paper describes a general methodology for machines and other processes by using few measurements, dynamic process and signal models and parameter estimation to generate symptoms. The detected symptoms are fed into a knowledge based fault diagnosis procedure. Analytical and heuristic knowledge is treated via fault-symptom trees, process history and plausibility measures. The considered machines consist of a motor, a drive chain and a working process or load. They may be electrical motor or combustion engine driven pumps, fans or machine tools with gear or belt drive chains. The described methodology was developed and tested experimentally for several machines. As one example, experimental results are shown for a d.c. motor powered feed drive of a machine tool.

关键词： Fault detection supervision monitoring safety parameter estimation knowledge base diagnostics fault-trees inference mechanism

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Multivariable Constrained Predictive control (With Application to High Performance Distillation)

Multivariable Constrained Predictive Control (With Applicati...

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American control Conference (ACC)

作者： D.J. Wilkinson M.T. Tham A.J. Morris Automation & Control Group Manufacturing Services Division Shell International Petroleum Company Limited The Hague Netherlands Department of Chemical and Process Engineering University of Newcastle Newcastle-Upon-Tyne UK

A multivariable constrained predictive controller is briefly described. Its objective function is solved via Singular Value Decomposition (SVD). Apart from being a numerically robust solution technique, the approach also provides useful on-line information which can be used to enhance the stability of the closed loop system. The performance characteristics of the algorithm are illustrated by applications to nonlinear simulations of two high purity distillation columns.

关键词： Predictive control Manufacturing automation Robust stability Cost function Automatic control Petroleum Chemical processes Chemical engineering Feedback control PROM

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Interactive power system data preparation and verification using a pc‐editor

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European Transactions on Electrical Power 1991年第3期1卷 149-152页

作者： Linke, K. Rumpel, D. Dip1.-Ing. Klaus Linke (1939) VDEis the director of the department "load dispatching and network operation" of Vereinigte Elektrizitatswerke Westfalen AG (VEW). DortmundGermany. After the study of electrical engineering at the Technical University of KarlsruhdGermany he started his professional career in an engineering-concern where he was responsible among others for investigations concerning the installation of process-computers in chemical plants. In 1968 he changed to VEW. Here in 1984 he took over his present position in which he is mainly engaged with the tasks of the management of the HV and EHV network and the power system control together with the problems concerning network automation incident to it. (Vereinigte Elektrizitatswerke Westfalen AG Hauptverwaltung Rheinlanddamm 24 W-4600 Dortmund 1 T +49 23 114 38-42 41) Dr.-Ing. Dieter Rumpel (1932) VDE is full professor and since 1978 head of the Power Systems Institute of Duisburg University Germany. He got his DiplAng. degree from the Technical University Munich and his Dr.-Ing. degree from the Technical University Berlin. Before his call to Duisburg he worked at Siemens AG for 23 years. (Universiiit-GHDuisburg Fachbereich Elektrotechnik PF 10 15 03 W-4100 Duisburg T 4 9 20 313 79-34 37)

For computerized power system operation, all objects of the network must be mapped in a data‐model. For this task, the „Grid Data Language” (GDL) does not apply format‐bound source data, but describes the objects using a format‐free source text. To handle such texts, an editing‐ and verification‐system was implemented. This paper reports its application when describing an extra‐high voltage network for use in a training simulator. In that way, the full content of a dispatcher EHV data‐model could be converted to GDL, requiring a work of 15 to 20 man‐days. Copyright © 1991 John Wiley & Sons, Ltd.

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Model Based Fault Diagnosis and Supervision of Machines and Drives

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IFAC Proceedings Volumes 1990年第8期23卷 1-12页

作者： R. Isermann W. Appel B. Freyermuth A. Fuchs W. Janik D. Neumann Th. Reiss P. Wanke Institute for Control Engineering Laboratory of Control Techniques and Process Automation Technical University Darmstadt Landgraf Georg Straβe 4 D-6100 Darmstadt FRG

The early detection and localization of faults in machines and drives is of primary interest to make further improvements of the reliability and safety. The conventional way is to monitor some important variables like temperatures, pressures, vibrations and to generate alarms if certain limits are exceeded. However, developing internal process faults are only detected at a rather late stage. In recent years research has shown that many process faults can be detected earlier and localized better by using static and dynamic models together with some definite robust sensors. For machines and drives many faults appear as process and signal parameter changes. The contribution describes a general methodology for the fault diagnosis of machines and drives by using few sensors, dynamic process and signal models and parameter estimation. Changes of process and signal parameters are then symptoms, which are fed into a knowledge based fault diagnosis component. Then analytical and heuristic knowledge is treated via fault trees and plausibility measures. The results were obtained in several research projects with machine tools and robots driven by d. c., a.c. and synchroneous motors. Examples show some experimental results.

关键词： Fault detection process monitoring reliability expert system knowledge base parameter estimation industrial robot machine tool feed drive

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A Knowledge Based Fault Diagnosis System for the Supervision of Periodically and Intermittent Working Machine Tools

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IFAC Proceedings Volumes 1990年第8期23卷 89-94页

作者： D. Neumann Technical University of Darmstadt Inst. of Control Engineering Laboratory for Automatic Control and Process Automation Landgraf-Georg-Str. 4 D-6100 Darmstadt FRG

The paper describes a personal-computer-based fault diagnosis system, which is designed for the analysis of periodically working machine tools. The used algorithms are described from signal analysis to the diagnosis system including some tests with real machines. The system was synthesized modularly. so that it can easily be adapted to other processes. Only few standard signals are needed. which have to be measured for controlling purposes anyway. so normally no special sensors have to be added. The knowledge based diagnosis system uses furtheron heuristic knowledge from machine history and expert knowledge. which is not exactly quantifiable.

关键词： machine tools modeling failure detection signal processing identification frequency domain

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