Online Tuning of Structured Fabric Vibration Absorber

This paper presents a new tunable vibration absorber, which is made by a beam-like composite structure with a post in the middle section. The low-frequency vibration response of this system is controlled by the fundamental flapping bending mode of the composite beam such that it’s dynamics resembles that of a mass-spring-damper vibration absorber, which can be used to control either the time-harmonic or resonant vibrations of structures/machines. The beam is formed by a single or a double layer of structured fabric core material wrapped in a deflated plastic bag, which works as the outer skin of the composite material. The fabrics are formed by chain mails made with a) cubic, b) spherical-octahedral, c) octahedral truss-like particles. The post has been conceived in such a way as it works both as a mechanical joint and a vacuum connector, which is linked to a vacuum control platform. The platform is formed by a miniature diaphragm pump, four electro-mechanical valves and a pressure error sensor. Also, the beam-like structure is equipped with three accelerometers: one positioned in the middle section and the other two at the outer sections. In this way they can be suitably used to detect the vibration energy absorbed by the system. The pump and the electromechanical valves are commanded by a dSpace digital controller. The pressure output signal from the error sensor is also feed to the controller together with the output signals from three accelerometer error sensors. The pressure sensor is used in a single channel feedback control loop to regulate the vacuum in the bag. The output signals from the accelerometer sensors are instead employed to detect the vibration absorption of the system and thus to implement a feedback loop that sets the vacuum level in the bag in such a way as the system maximizes the vibration absorption from the hosting machine/structure. The paper presents preliminary results on the design and development of a prototype control platform and on the implementation of the pressure feedback regulator and tuning feedback approach, which is based on a model-free extremum seeking algorithm