Object of this paper is the automatic supervision of an end milling operation performed on a machining center for milling and drilling. The work concerns the reliable detection of tool wear and surface quality with me...
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Object of this paper is the automatic supervision of an end milling operation performed on a machining center for milling and drilling. The work concerns the reliable detection of tool wear and surface quality with measured signals, that are easy to get. With these signals symptoms are generated using correlation functions. It will be shown, that symptoms of the main drive as well as symptoms of the x-axis feed drive can be used to monitor tool wear. Symptoms of the z-axis feed drive are correlated with surface roughness.
作者：
H. KonradR. IsermannTechnical University of Dannstadt
Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str.4 D-64283 Darmstadt Germany Phone: +49 6151 163927 Fax: +49 6151 293445
An entire model for a machining center during milling operations is presented. Existing and partly improved models of the milling process and the respective machine components are coupled together. Because of the modu...
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An entire model for a machining center during milling operations is presented. Existing and partly improved models of the milling process and the respective machine components are coupled together. Because of the modular structure single components can easily be exchanged and the entire model can be adapted to various types of machine tools. Simulation results show the usability to predict interactions in the drives caused by the intermittent cut These interactions are significantly influenced by faults in the milling process, e.g. tool breakage and cutter run-out.
作者：
Rüdiger DeibertTechnical University of Darmstadt
Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str.4 D-64283 Darmstadt Germany Phone: +49 6151 163314 Fax: +49 6151 293445
A strategy for fault detection in Fixed setpoint flow control loops is presented. First a general approach for model-based residual generation using observer based techniques is proposed. A generation of more detailed...
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A strategy for fault detection in Fixed setpoint flow control loops is presented. First a general approach for model-based residual generation using observer based techniques is proposed. A generation of more detailed symptoms by signal processing of standard control loop signals follows. The strategy is proven with both simulation examples and measured data of a water flow control loop actuated by a pneumatic driven valve. Faults in either the valve drive and the fluidic subsystem are investigated.
作者：
Rolf IsermannTechnical University of Darmstadt
Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf Georg-Straße 4 64238 Darmstadt Germany Tel.: (FRG) 6151/162114 Fax: (FRG) 6151/293445
The integration of mechanical systems and microelectronics opens new possibilities for mechanical design and automatic functions. After a discussion of the mechanical and electronic design the organization of informat...
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The integration of mechanical systems and microelectronics opens new possibilities for mechanical design and automatic functions. After a discussion of the mechanical and electronic design the organization of information processing in different levels is described. Within this frame “low-degree intelligent” mcchatronic systems can be developed which comprise adaptive control, supervision with fault diagnosis and decisions with regard to further actions. This requires the realization of knowledge based systems with learning abilities. Some aspects of the design of information processing including modeling and estimation, control and supervision methods are considered. Finally as examples the adaptive nonlinear control of a pneumatic actuator and an adaptive semiactive shock absorber for vehicle suspension systems is shown.
The estimation of the height of the centre of gravity of vehicle is significantly important for various applications in modern car management. A theoretical model of a full - scale half car including suspension and a ...
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The estimation of the height of the centre of gravity of vehicle is significantly important for various applications in modern car management. A theoretical model of a full - scale half car including suspension and a crank axle at the front and the rear axle is developed. A longitudinal model of the vehicle is described to compute the forces at the wheels curing braking and accelerating manoeuvres. Based on nonlinear spring curves and measured deflection at the front and the rear axle the centroidal height of the vehicle is estimated. Some experimental results with a space wagon are shown.
The knowledge of the friction coefficient between tyre and road surface is the central part of vehicle longitudinal and lateral control. For this purpose a friction monitoring system is developed using nonlinear and l...
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The knowledge of the friction coefficient between tyre and road surface is the central part of vehicle longitudinal and lateral control. For this purpose a friction monitoring system is developed using nonlinear and linear mathematical models to describe the /spl mu/-slip characteristics and to compute the dynamic wheel loads and longitudinal tyre forces. A recursive least squares estimator calculates the parameters of the /spl mu/-slip characteristics online and on-board for use in controlsystems.< >
The design and implementation of the heuristic knowledge base for a fuzzy logic-based technical diagnostic problem solving strategy integrated as a heuristic level within a computer assisted fault diagnosis system is ...
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The design and implementation of the heuristic knowledge base for a fuzzy logic-based technical diagnostic problem solving strategy integrated as a heuristic level within a computer assisted fault diagnosis system is considered. Based on knowledge acquisition via expert knowledge (linguistically expressed as fuzzy conditional statements);simulation-based observations of the diagnosed process (as a feature extraction technique for technical diagnostic relevant information);process history and fault statistics, a fuzzy diagnostic model is developed as a fuzzy symptoms-faults mapping and implemented within the heuristic knowledge base. Diagnostic reasoning by MATCHING the proposed fuzzy diagnostic model with the current values of the symptoms (either analytically generated or subjectively observed by the operator) is presented as well as the validation of the design method. first by illustrating it on a very simple simulated process (a low-pass filter) and then by applying it to a simulated DC motor.
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.< >
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