Domenico Manzari
Enhancing Tracking Algorithm Performance in a 2D Laser Cutting Machine through Z-Axis Modelling and Validation.
Rel. Alessandro Rizzo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024
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Abstract: |
This work arises from the need to solve the problem of tracking the signal from a capacitive sensor and was promoted by Prima Industrie, a leader in the production of laser cutting machines for sheet metal. The quality of laser cutting significantly depends on the distance between the cutting head and the sheet. An algorithm controls this distance in real time by tracking the capacitive sensor signal to ensure the correct standoff. To compensate for system delays and optimize cutting performance, the system, particularly the Z-axis, was modeled using a data-driven approach based on experimental tests, exciting the system with white noise added to the different control loops. Data processing and analysis led to the development of a model using MATLAB® System Identification Toolbox. The search for and use of new components to be integrated into the machine to enhance performance necessitated the creation of a model based on physics, adopting a first-principles approach through the Bond Graph Approach. Both models were implemented in MATLAB and Simulink. The modeling allowed for the identification, validation, and optimization of the dynamic response parameters of the system, improving signal tracking and cutting quality. |
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Relators: | Alessandro Rizzo |
Academic year: | 2023/24 |
Publication type: | Electronic |
Number of Pages: | 92 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica) |
Classe di laurea: | New organization > Master science > LM-25 - AUTOMATION ENGINEERING |
Aziende collaboratrici: | Prima Industrie SpA |
URI: | http://webthesis.biblio.polito.it/id/eprint/31781 |
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