Abstract:The internal channel networks embedded within a soft structure can be a fruitful mechanism to create and activate actuators in the research fields of soft robotics. The deformation of the supporting elastic structure from the pressurized viscous fluid into the channels needs an accurate investigation. In this paper, accurate modeling and dynamic analysis of this nonlinear soft actuator is our goal. In this modeling, the soft actuator is considered the Euler–Bernoulli beam with large deflection and nonlinear st… Show more
“…where mv a = mass of the piston and the double derivative of the piston displacement, respectively. This represents a dynamic model of the actuator, which contains pressure derivative equations from two chambers expressed by a continuity mass equation and a double derivative equation for the motion of the actuator piston [36].…”
Section: Simulations Of Model In a Transient Statementioning
Many different types of aircraft designs have flight control systems (FCS) powered by hydraulic systems. With respect to the torques, moments, surface areas, and opposing forces to be acted upon, components introduce faults into the hydraulic system when these components are aging or degrading. The diagnostics of a hydraulically powered flight control actuation system (HPFCAS) rely on the faults produced within the subsystem components as well as the entire system’s mechanism itself. In this paper, a model for an HPFCAS is developed to analyze faults where the HPFCAS was approached as a system of systems (SOS). The identified faults were injected into the system. It is established that some of the faults from the different subsystems had similar characteristic effects and were propagated with attendant consequences. For instance, a measured decrease in the pressure value is observed because of the decrease in the pump speed. A similar characteristic is observed if there is leakage on the line or if there is a clogging valve. These form complex integrated responses in determining where the fault is coming from if only one component is analyzed since it involves components serving different subsystems. Results show that only models that can describe the real characteristics or attributes of the specific systems, due to their defined components, are sufficient for effective diagnostics. This is because the data obtained are more accurate at predicting the behavior of components.
“…where mv a = mass of the piston and the double derivative of the piston displacement, respectively. This represents a dynamic model of the actuator, which contains pressure derivative equations from two chambers expressed by a continuity mass equation and a double derivative equation for the motion of the actuator piston [36].…”
Section: Simulations Of Model In a Transient Statementioning
Many different types of aircraft designs have flight control systems (FCS) powered by hydraulic systems. With respect to the torques, moments, surface areas, and opposing forces to be acted upon, components introduce faults into the hydraulic system when these components are aging or degrading. The diagnostics of a hydraulically powered flight control actuation system (HPFCAS) rely on the faults produced within the subsystem components as well as the entire system’s mechanism itself. In this paper, a model for an HPFCAS is developed to analyze faults where the HPFCAS was approached as a system of systems (SOS). The identified faults were injected into the system. It is established that some of the faults from the different subsystems had similar characteristic effects and were propagated with attendant consequences. For instance, a measured decrease in the pressure value is observed because of the decrease in the pump speed. A similar characteristic is observed if there is leakage on the line or if there is a clogging valve. These form complex integrated responses in determining where the fault is coming from if only one component is analyzed since it involves components serving different subsystems. Results show that only models that can describe the real characteristics or attributes of the specific systems, due to their defined components, are sufficient for effective diagnostics. This is because the data obtained are more accurate at predicting the behavior of components.
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