Abstract
This paper proposed a new digital twin method to effectively, accurately and in real-time in-situ track machine dynamic error using accelerometer data. The digital twin tracked the positioning data measured by its built-in encoders and superimposes it with displacement data obtained from the accelerometers for more accurate positioning, resulting in micrometre level improvements. In this paper, the digital twin dynamic error tracking approach was implemented on a collaborative robot. Ball-bar tests were conducted to evaluate the effectiveness of the proposed digital twin dynamic error tracking approach. The results show a significantly improved position tracking accuracy of up to 75%, compared with using the collaborative robot’s built-in encoders. The digital twin provides a cost-effective solution to track machine dynamic errors. This method could also be expanded to work on other CNC machines and robots, making it a universal solution for improving machine dynamic measurement accuracy.
Original language | English |
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Number of pages | 4 |
Publication status | Published - 12 Jun 2023 |
Event | Euspen's 23rd International Conference & Exhibition, Copenhagen, Denmark - Copenhagen, Denmark Duration: 12 Jun 2023 → 16 Jun 2023 |
Conference
Conference | Euspen's 23rd International Conference & Exhibition, Copenhagen, Denmark |
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Country/Territory | Denmark |
City | Copenhagen |
Period | 12/06/23 → 16/06/23 |
Keywords
- digital twin
- dynamic error
- accelerometer