This paper describes a new method of fault detection in milling. The presented detection algorithm is based on the estimation of particular model parameters using measured cutting force signals. By classifying the res...
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This paper describes a new method of fault detection in milling. The presented detection algorithm is based on the estimation of particular model parameters using measured cutting force signals. By classifying the resulting patterns of the estimated parameters, the conditions of the cutting teeth can be determined.
作者:
ISERMANN, RInstitute of Automatic Control
Laboratory for Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Straβe 4 D-64283 Darmstadt Germany
Beginning with classical supervision a summary is given of the main principles of model-based fault detection methods. Their basic assumptions, results from simulation and experiments allow a discussion of the feature...
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Beginning with classical supervision a summary is given of the main principles of model-based fault detection methods. Their basic assumptions, results from simulation and experiments allow a discussion of the features of the methods with regard to their applicability. The importance of realistic fault modeling is outlined. Finally the role of model-based fault detection as one information source for fault diagnosis is discussed. Several methods of fault detection have to be integrated to support a powerful diagnosis.
Selftuning of classical PI-controllers for processes without known mathematical models is achieved by applying heuristic fuzzy rules. Step changes of the reference input are used to assess control performance in terms...
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Selftuning of classical PI-controllers for processes without known mathematical models is achieved by applying heuristic fuzzy rules. Step changes of the reference input are used to assess control performance in terms of overshoot, rise time and settling time of the step response. Similar to the strategy of an experienced plant operator, a fuzzy logic ''supervision and tuning module'' can conclude from these features, which changes of the controller parameters will improve control behaviour. The concept was tested in simulation series with Matlab/Simulink. Results show the benefits of the proposed fuzzy tuning module applied to 8 different simulated test plants. Experiments with speed-regulation of a DC-servomotor indicate that the concept is suitable for processes with noisy signals as well.
An approach for supervision of vehicle dynamics is presented which may be used for intelligent vehicle control and state monitoring. In particular, an on-board process parameter estimation was implemented which allows...
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An approach for supervision of vehicle dynamics is presented which may be used for intelligent vehicle control and state monitoring. In particular, an on-board process parameter estimation was implemented which allows one to compute the physical coefficients of lateral vehicle models and their changes during operation. In addition, tire- and velocity-dependent look-up tables in presently used vehicle models were replaced by feedforward neural networks. In the phase of driving state monitoring, a set of these hybrid models-each of them trained for a special driving situation-predict the vehicle motion as a result of the actual steering angle and velocity. In a further step, suitable classification algorithms were used to detect the actual driving state by processing the residual output.
Discusses model based methods for controlling vehicle dynamics. A nonlinear model describing the longitudinal motion of a vehicle is presented. This model consists of a braking system, a powertrain and mass-damper sys...
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Discusses model based methods for controlling vehicle dynamics. A nonlinear model describing the longitudinal motion of a vehicle is presented. This model consists of a braking system, a powertrain and mass-damper system with damping from aerodynamical drag and rolling resistance. According to the most essential time constants, parameter estimation is used to determine the mass and the aerodynamical drag of the vehicle. As an example for controller design, a combination of fuzzy logic and a classical feedback linearization is presented. Furthermore, some examples of a velocity controller are shown using the described controlling techniques.
Many processes with nonlinear behaviour are difficult to model. Consequently model based approaches to fault detection can not be applied. For a certain class of these processes with mainly constant input signals a co...
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Many processes with nonlinear behaviour are difficult to model. Consequently model based approaches to fault detection can not be applied. For a certain class of these processes with mainly constant input signals a combination of parameter estimation techniques and the parity space approach allows online fault detection with small signal models. Only few knowledge of the process is required: An idea about the dynamic model order and the static nonlinear characteristic curve. Using the proposed method fault detection is performed at a flowrate control with a pneumatic driven valve.< >
In order to apply the best fault detection and diagnosis scheme, it is a must to investigate the process model profoundly and the kinds of faults to be detected. Especially the process excitation and the effect of a c...
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In order to apply the best fault detection and diagnosis scheme, it is a must to investigate the process model profoundly and the kinds of faults to be detected. Especially the process excitation and the effect of a considered fault play an important role. This is the starting point for the choice of one of the various model based fault detection methods. According to this strategy two different approaches, an observer based and a signal based approach, are selected for the two given faults of the benchmark task. Moreover it is shown that the application of adaptive thresholds can improve the performance of the fault detection scheme significantly with respect to false alarm rate and delay of detection.
作者:
R. IsermannInstitute of Automatic Control
Laboratory for Control Engineering and Process Automation Technical University Darmstadt Landgraf-Georg-Straße 4 D-64283 Darmstadt F.R. Germany
For the fault detection of technical processes different methods can be applied based on the information extracted from direct measured signals, from signal models and process models. Examples for signal model based f...
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For the fault detection of technical processes different methods can be applied based on the information extracted from direct measured signals, from signal models and process models. Examples for signal model based fault detection methods are spectral analysis or parameter estimation of ARMA models, examples for process model based methods are parameter estimation, state estimation or parity equation approaches. A comparison of these methods shows that they have different properties with regard to the detection of faults in the process, the actuators and the sensors. After a brief review of model based fault detection methods the various advantages and disadvantages of the different methods are summarized. The importance of realistic fault modeling is outlined and the suitability of model-based fault detection methods in dependence on the type of faults is discussed. By a proper integration of different fault detection methods mainly their advantages can be used and their disadvantages avoided. It will be shown which integrations of fault detection methods are appropriate to generate analytical symptoms which are then treated by methods of change detection and classification. For fault diagnosis a knowledge based procedure is required, because in addition to analytical symptoms also qualitative information in form of heuristic symptoms have to be taken into account. It will be shown how based on heuristic process knowledge as fault-symptom causalities and a unified representation of all symptoms an integrated fault diagnosis can be performed. This comprises the treatment of the symptom as uncertain facts and approximate diagnostic reasoning via if-then rules either in a probabilistic or a fuzzy-logic (possibilistic) frame. As examples for integrated fault detection and diagnosis experimental results are shown which were obtained with machine tools. In summary, the contribution shows how through proper integration of different fault detection methods and integration
Faults which appear in technical processes can often be described as additive or multiplicative faults with respect to the process model. To detect and identify these kinds of faults two model based methods, the parit...
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Faults which appear in technical processes can often be described as additive or multiplicative faults with respect to the process model. To detect and identify these kinds of faults two model based methods, the parity space approach with adaptive thresholds and the parameter estimation, are used. Starting with theoretical investigations on a simple example both schemes are applied to a ***. The results and the different properties are compared. Finally a combination of both methods is proposed to achieve optimal fault detection.
作者:
Thomas PfeuferTechnical University of Darmstadt
Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str. 4 D-64283 Darmstadt Phone: +49 6151 167405 Fax: +49 6151 293604
Automobile actuators have to work very reliable. In extension to redundancy schemes the use of model-based fault detection methods is advantageous for the early detection of incipient faults in the process or in the s...
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Automobile actuators have to work very reliable. In extension to redundancy schemes the use of model-based fault detection methods is advantageous for the early detection of incipient faults in the process or in the signals. Two different approaches, the parity-space method and the parameter estimation approach, are selected for the investigations for the example of an automobile actuator driven by a d.c. motor. After a brief description of the theoretical basis the experimental application follows to several faults.
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