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 tem...
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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 temperature, pressure, vibration and to generate alarms if certain limits are exceeded. 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 analytical symptoms. Heuristic symptoms observed by the operator or based on, e.g. the process history are another source for fault diagnosis. Both kinds of symptoms are weighted by confidence measures and are fed into a knowledge based fault diagnosis procedure. The diagnosis is performed by forward and backward chaining according to causal fault-symptom trees. 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. As one example, experimental results are shown for a DC motor powered feed drive of a machine tool. A summary of practical results with other machines is also given.
The integration of microelectronics within the actuator allows not only replacement of the analog position controller but addition of several functions which give the actuator more intelligent functions. The actuator ...
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The integration of microelectronics within the actuator allows not only replacement of the analog position controller but addition of 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. After a short review of important actuator principles and their properties, 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. 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.
The development of technical diagnostic systems has shown that the time has come to bridge the gap between the process-oriented engineering approach and the reasoning-oriented approach. As a contribution to this on-go...
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The development of technical diagnostic systems has shown that the time has come to bridge the gap between the process-oriented engineering approach and the reasoning-oriented approach. As a contribution to this on-going task, the paper proposes a unified frame for integration of different fault detection and decision techniques via approximate reasoning on analytical and heuristic fuzzy symptoms.< >
Beginning with classical supervision a summary is given on 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 on 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 perform a powerful diagnosis.
A parameter-adaptive controller to control the simulated plant of the "1993 IFAC World Congress Bench Mark Design Example" is presented. To cope with the rather fast time-varying process parameters a set of ...
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A parameter-adaptive controller to control the simulated plant of the "1993 IFAC World Congress Bench Mark Design Example" is presented. To cope with the rather fast time-varying process parameters a set of parallel estimators is used. Due to a cyclic restart procedure each of these estimators is working with another time window. For the controller itself an algorithm is used that realizes a controller with variable robustness. Simulation results are presented.
As many faults induce parameter variations, it is important for detection and diagnosis to observe their timely development. One possibility is to estimate the parameters directly by well-known least squares methods f...
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As many faults induce parameter variations, it is important for detection and diagnosis to observe their timely development. One possibility is to estimate the parameters directly by well-known least squares methods for dynamic systems, but this requires some computational effort at each sampling step. The proposed method uses the easy to calculate parity space equations with special, parameter-sensitive features and state variable filters to generate signal derivatives. Different to previous approaches here parity equations are used in the continuous time domain. Then the connection between physical and model parameters is direct and eases a fault diagnosis. A parameter classification table can be derived from the according pattern of the obtained set of residuals. This table enables to localize which physical parameter has been affected. Furthermore well known parity space design methods can be included for the detection of sensor faults.
This approach describes a methodology for the fault detection in machine tools by using few robust sensors and dynamic process models. Two different model based methods, parameter estimation and state estimation, are ...
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This approach describes a methodology for the fault detection in machine tools by using few robust sensors and dynamic process models. Two different model based methods, parameter estimation and state estimation, are used for the detection of tool wear and tool breakage in the drilling process.< >
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 t...
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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.
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 t...
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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.
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 i...
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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.
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