The scope of this paper relates to sensor fault detection in intelligent early failure warning sensors system for safety critical single throw mechanical equipment, using Vapor's Train Rotary Door Operator (TRDO) ...
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The scope of this paper relates to sensor fault detection in intelligent early failure warning sensors system for safety critical single throw mechanical equipment, using Vapor's Train Rotary Door Operator (TRDO) as a first case study. Work carried out at The University of Birmingham includes design and development of state-of-the-art control and data acquisition system for Vapor's TRDO using Lab Windows/CVI. Fault diagnosis of engineering systems involves identification of components that cause variations from usual healthy behaviour. When observed abnormal behaviour crosses certain threshold a warning is initiated for failure. Neural networks are being used for system identification and modelling of healthy behaviour of equipment using various sensors. Failures are predicted from deviation of any sensor's data from its healthy model. Faulty component is identified after analysis of information from all sensors and using database available from fault modes and effects criticality analysis (FMECA) of the TRDO. Sensor failure detection and sensor value validation has also been investigated. Different types of sensors are employed for monitoring various parameters used in electro-pneumatic operation of train door. These parameters include air flow, air pressure, angular displacement, lateral displacement, opening and closing time. These parameters relate to one another and this property is exploited to detect sensor failures. Detection of sensor failures using analytical redundancy is also discussed.
This paper describes the use of Prolog in the implementation of a Knowledge-based Environment for modelling and simulation (KEMS). The basis of the implementation is the AI frame paradigm which provides a conceptual f...
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This paper describes the use of Prolog in the implementation of a Knowledge-based Environment for modelling and simulation (KEMS). The basis of the implementation is the AI frame paradigm which provides a conceptual foundation for the design of the model Base, the simulation Code Generator and the Knowledge Acquisition Module which are the Prolog-based components of KEMS. The experiences derived from KEMS provide a springboard from which the wider applications of Logic programming in control Engineering are discussed. Six application areas are identified, including modelling, the design of from-ends for CAD packages, the design of object-oriented databases, the prototyping of engineering concepts, knowledge-based control and the design of decision-support systems.
The paper describes a framework for the modelling and simulation of hybrid systems and the implementation of the strategy in the real-time Expert system tool, G2. The strategy is predicated on three key notions: hybri...
The paper describes a framework for the modelling and simulation of hybrid systems and the implementation of the strategy in the real-time Expert system tool, G2. The strategy is predicated on three key notions: hybrid model base, interactions between dissimilar model elements, and hybrid simulation. The combination of a hybrid model structure, incorporating Grafcets, equations, rules and objects, with the real-time features of G2 is shown to be an efficient vehicle for the integration of process functions such as supervisory control, sequential control, scheduling, fault monitoring and optimisation.
ANDECS belongs to the new generation of open CAE systems for computational experimenting in controlled dynamics systems simulation, analysis, and multi-objective optimization. Strict databased function modularization ...
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ANDECS belongs to the new generation of open CAE systems for computational experimenting in controlled dynamics systems simulation, analysis, and multi-objective optimization. Strict databased function modularization with neutral object-oriented data- and model interfaces allows a flexible configuration of computational chains and loops. Function modules are available for basic mathematical methods, control methods, simulation, parameter- and trajectory optimization and interactive visualisation for result- and algorithm animation. ANDECS supports interoperability by exchanging both commands and data via interprocess communication with: MATLAB and Xmath for system dynamics analysis and synthesis; KHOROS and Data Explorer for versatile result visualisation; KISMET as robot animation package; and the like.
Summary form only given. The scope of this paper relates to sensor fault detection in intelligent early failure warning sensors system for safety critical single throw mechanical equipment, using Vapor's train rot...
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Summary form only given. The scope of this paper relates to sensor fault detection in intelligent early failure warning sensors system for safety critical single throw mechanical equipment, using Vapor's train rotary door operator (TRDO) as a first case study. Work carried out at The University of Birmingham includes design and development of state-of-the-art control and data acquisition system for Vapor's TRDO using Lab Windows/CVI. Fault diagnosis of engineering systems involves identification of components that cause variations from usual healthy behaviour. When observed abnormal behaviour crosses certain threshold a warning is initiated for failure. Neural networks are being used for system identification and modelling of healthy behaviour of equipment using various sensors. Failures are predicted from deviation of any sensor's data from its healthy model. Faulty component is identified after analysis of information from all sensors and using database available from fault modes and effects criticality analysis (FMECA) of the TRDO. Sensor failure detection and sensor value validation has also been investigated. Different types of sensors are employed for monitoring various parameters used in electro-pneumatic operation of train door. These parameters include air flow, air pressure, angular displacement, lateral displacement, opening and closing time. These parameters relate to one another and this property is exploited to detect sensor failures. Detection of sensor failures using analytical redundancy is also discussed.
The main objective of the INSYDE project is to define, implement, and demonstrate a comprehensive methodology for the design of hybrid hardware/software systems. Stages in the INSYDE methodology are analysis, system d...
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The main objective of the INSYDE project is to define, implement, and demonstrate a comprehensive methodology for the design of hybrid hardware/software systems. Stages in the INSYDE methodology are analysis, systemdesign, detailed design, and validation. The functional requirements analysis results, after some iterations, in a conceptual model in OMT. The systemdesign, which iterates over the OMT structure classification and the transition from OMT to OMT*, produces an OMT* systemdesignmodel. This systemdesignmodel is transformed into SDL/VDL automatically as far as possible, and partially by the user. Additional information for the further specification development can be taken from the OMT* systemdesignmodel.
At idle the engine throttle is closed and the airflow into the engine is typically controlled by the opening of a simple electromechanical valve actuated by the engine's electronic engine management system. This p...
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At idle the engine throttle is closed and the airflow into the engine is typically controlled by the opening of a simple electromechanical valve actuated by the engine's electronic engine management system. This provides the principal means to control engine speed. It is commonly supplemented by control of the spark advance to modulate engine torque production. This is an input which acts quickly but is limited in authority. The MATLAB/SIMULINK engine model and its role in control law development are described.
The use of model-based approaches is proposed to improve the control performance of an industrial polymerization reactor. This involves the development of a process model using system identification techniques, the si...
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The use of model-based approaches is proposed to improve the control performance of an industrial polymerization reactor. This involves the development of a process model using system identification techniques, the simulation of the plant within the Simulink environment to allow for the design and validation of control strategies. From these studies a Smith Predictor was implemented to significantly improve the polymer viscosity control. A hardware platform is developed to facilitate the implementation of sophisticated algorithms such as recursive least squares, that could not be accommodated on the existing DCS.
For a water distribution systemsimulation, the three main causes of uncertainty are: an inaccurate network model, inaccurate consumption predictions and errors associated with measurements (random and systematic). Th...
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For a water distribution systemsimulation, the three main causes of uncertainty are: an inaccurate network model, inaccurate consumption predictions and errors associated with measurements (random and systematic). The paper presents calculations using the ellipsoid algorithm in order to provide confidence limits on state estimates in the nonlinear water system state estimation process.
The paper discusses the benefits of systemmodelling for safety and fault analysis. It aims to show that by using a graphical approach, formal methods can be introduced into the design process along with other methods...
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The paper discusses the benefits of systemmodelling for safety and fault analysis. It aims to show that by using a graphical approach, formal methods can be introduced into the design process along with other methods and not require specialist software knowledge. Also, it discusses that once a systemmodel has been developed not only can the design safety issues be studied but failure mode analysis be undertaken.
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