Abstract
In sheet-forming process, we are dealing with a two-dimensional product, rolls of paper or metal, polymer films etc. The control objective is to maintain product quality, e.g., thickness, uniformity during continuous production. Despite recent advances in measurement technology, it is difficult to measure all points on the entire sheet. Therefore, we have a two-dimensional product with scattered measurements. The location of measurement points not only decides the correctness of the estimation, it also affects the control performance. Previous study shows that, in the temporal mode, the optimal estimation implies equally spaced measurement updates. In this article, an image-based approach is proposed to evaluate the appropriateness of measurement patterns for interactive spatio-temporal systems. The method is based on the concept of time to the next nearest neighbor(s) and the mean and standard deviation are utilized to discriminate among measurement patterns. It is useful in arranging multiple scanning sensors. The proposed approach is employed for the evaluation of multi-sensor arrangement for typical sheet-forming processes. Results show that the image-based analysis is effective for the design of sensor trajectories for manufacturing of two-dimensional products.
| Original language | English |
|---|---|
| Pages (from-to) | 5709-5717 |
| Number of pages | 9 |
| Journal | Chemical Engineering Science |
| Volume | 56 |
| Issue number | 20 |
| DOIs | |
| State | Published - 16 10 2001 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Kalman filter
- LQG
- Nearest neighbor
- Sensor arrangement
- Sheet-forming process
- State estimation
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