The technology of swarm intelligence has been applied to a mechanical vibration monitoring system composed of a network of units equipped with sensors and actuators. The expression of “swarm intelligence” was first used in 1988 in the context of cellular robotic systems, where lots of simple agents may generate self-organized patterns through mutual interactions. There are various examples of the swarm intelligence in the natural environment, a swarm of ants, birds or fish. In this sense, the network of agents in a swarm may have some kind of intelligence or higher function than those appeared in a simple agent, which is defined as the swarm intelligence. The concept of swarm intelligence may be applied in diverse engineering fields such as flexible pattern recognition, adaptive control system, or intelligent monitoring system, because some kind of intelligence may emerge on the network without any special control system. In this study, a simulation model of a five degree-of-freedom lumped mass-spring system was prepared as an example of a mechanical dynamic system. Five units composed of a displacement sensor and a variable damper as actuator were assumed to be placed on each mass of the system. Each unit was connected to each other to exchange the information of state variables measured by sensors on each unit. Because the network of units configured as a mutual connected neural network, a kind of artificial intelligence, the network of units may memorize the several expected vibration-controlled patterns and may produce the signal to the actuators on the unit to reduce the vibration of target system. The simulation results showed that the excited vibration was reduced autonomously by selecting the position where the damping should be applied.
Skip Nav Destination
ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 18–20, 2017
Snowbird, Utah, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5826-4
PROCEEDINGS PAPER
Application of Swarm Intelligence to a Vibration Monitoring System
Takuya Hiura,
Takuya Hiura
Yokohama National University, Yokohama, Japan
Search for other works by this author on:
Shin Morishita
Shin Morishita
Yokohama National University, Yokohama, Japan
Search for other works by this author on:
Takuya Hiura
Yokohama National University, Yokohama, Japan
Shin Morishita
Yokohama National University, Yokohama, Japan
Paper No:
SMASIS2017-3734, V002T03A004; 6 pages
Published Online:
November 9, 2017
Citation
Hiura, T, & Morishita, S. "Application of Swarm Intelligence to a Vibration Monitoring System." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring. Snowbird, Utah, USA. September 18–20, 2017. V002T03A004. ASME. https://doi.org/10.1115/SMASIS2017-3734
Download citation file:
18
Views
Related Proceedings Papers
Related Articles
Model Following Adaptive Sliding Mode Tracking Control Based on a Disturbance Observer for the Mechanical Systems
J. Dyn. Sys., Meas., Control (May,2018)
Vibration Suppression in Cutting Tools Using a Collocated Piezoelectric Sensor/Actuator With an Adaptive Control Algorithm
J. Vib. Acoust (October,2010)
Experiments on Active Vibration Control of a Flexible Four-Bar Linkage Mechanism
J. Vib. Acoust (January,2000)
Related Chapters
Spiking Neural Networks on Self-Updating System-on-Chip for Autonomous Control
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
An Adaptive Fuzzy Control for a Multi-Degree-of-Freedom System
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Cognitive Science as Natural Computational Metaphor
International Conference on Software Technology and Engineering, 3rd (ICSTE 2011)