Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers

Johannes Maierhofer; Daniel J. Rixen

doi:10.1007/978-3-031-37007-6_8

Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers

Johannes Maierhofer, Daniel J. Rixen

Chair of Applied Mechanics

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Automatic impulse hammers have proven their advantages in experimental testing. Up to now, adjusting the resulting peak force is a cumbersome hand-tuning of the parameters of the hammer electronic. As the hammer is equipped with a high-quality force sensor anyway, the idea is close to utilize that force sensor signal to control the hammer. Usually these sensors are ICP-Sensors that are directly connected to the data acquisition system that is used to perform the desired measurements. This contribution shows a way to interpose the controller of the hammer and so allow the usage of the measured force. This is used in combination with an iterative learning control scheme to find the best parameters to achieve the desired impact force on the structure in a repeatable and convenient way.

Original language	English
Title of host publication	Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023
Editors	Matthew Allen, Jason Blough, Michael Mains
Publisher	Springer
Pages	65-77
Number of pages	13
ISBN (Print)	9783031370069
DOIs	https://doi.org/10.1007/978-3-031-37007-6_8
State	Published - 2024
Event	Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023 - Austin, United States Duration: 13 Feb 2023 → 16 Feb 2023

Publication series

Name	Conference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)	2191-5644
ISSN (Electronic)	2191-5652

Conference

Conference	Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023
Country/Territory	United States
City	Austin
Period	13/02/23 → 16/02/23

Keywords

AMimpact
Automatic modal hammer
Experimental dynamic
Non-linear testing
Testing equipment

Access to Document

10.1007/978-3-031-37007-6_8

Cite this

Maierhofer, J., & Rixen, D. J. (2024). Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers. In M. Allen, J. Blough, & M. Mains (Eds.), Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023 (pp. 65-77). (Conference Proceedings of the Society for Experimental Mechanics Series). Springer. https://doi.org/10.1007/978-3-031-37007-6_8

Maierhofer, Johannes ; Rixen, Daniel J. / Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers. Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. editor / Matthew Allen ; Jason Blough ; Michael Mains. Springer, 2024. pp. 65-77 (Conference Proceedings of the Society for Experimental Mechanics Series).

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title = "Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers",

abstract = "Automatic impulse hammers have proven their advantages in experimental testing. Up to now, adjusting the resulting peak force is a cumbersome hand-tuning of the parameters of the hammer electronic. As the hammer is equipped with a high-quality force sensor anyway, the idea is close to utilize that force sensor signal to control the hammer. Usually these sensors are ICP-Sensors that are directly connected to the data acquisition system that is used to perform the desired measurements. This contribution shows a way to interpose the controller of the hammer and so allow the usage of the measured force. This is used in combination with an iterative learning control scheme to find the best parameters to achieve the desired impact force on the structure in a repeatable and convenient way.",

keywords = "AMimpact, Automatic modal hammer, Experimental dynamic, Non-linear testing, Testing equipment",

author = "Johannes Maierhofer and Rixen, {Daniel J.}",

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series = "Conference Proceedings of the Society for Experimental Mechanics Series",

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Maierhofer, J & Rixen, DJ 2024, Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers. in M Allen, J Blough & M Mains (eds), Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. Conference Proceedings of the Society for Experimental Mechanics Series, Springer, pp. 65-77, Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023, Austin, United States, 13/02/23. https://doi.org/10.1007/978-3-031-37007-6_8

Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers. / Maierhofer, Johannes; Rixen, Daniel J.
Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. ed. / Matthew Allen; Jason Blough; Michael Mains. Springer, 2024. p. 65-77 (Conference Proceedings of the Society for Experimental Mechanics Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Automatic impulse hammers have proven their advantages in experimental testing. Up to now, adjusting the resulting peak force is a cumbersome hand-tuning of the parameters of the hammer electronic. As the hammer is equipped with a high-quality force sensor anyway, the idea is close to utilize that force sensor signal to control the hammer. Usually these sensors are ICP-Sensors that are directly connected to the data acquisition system that is used to perform the desired measurements. This contribution shows a way to interpose the controller of the hammer and so allow the usage of the measured force. This is used in combination with an iterative learning control scheme to find the best parameters to achieve the desired impact force on the structure in a repeatable and convenient way.

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Maierhofer J, Rixen DJ. Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers. In Allen M, Blough J, Mains M, editors, Special Topics in Structural Dynamics and Experimental Techniques, Volume 5 - Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023. Springer. 2024. p. 65-77. (Conference Proceedings of the Society for Experimental Mechanics Series). doi: 10.1007/978-3-031-37007-6_8

Iterative Learning Control Based on Force Measurements for Automatic Impulse Hammers

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