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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Tran, Nhut-Thanh
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Computer Science & IT Electrical & Electronics Engineering

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Towards optimal fillet portioning: a computer vision system for determining the fish fillet volume Nguyen, Chanh-Nghiem; Vo, Ngọc-Tan; Nguyen, Ngoc-Thanh; Tran, Nhut-Thanh; Nguyen, Chi-Ngon
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp550-558

Abstract

Portioning large fish fillets for packaging is usually performed manually by skilled workers. Automating this process and obtaining packaged products with attractive shapes and affordable weights will be beneficial for promoting purchase decisions. Towards developing an automated fish fillet portioning system, this study investigated a computer vision approach for determining the fillet volume. A belt conveyor would transport a fish fillet to the image capture booth, where its cross-section areas would be calculated for volume determination. The developed system could be operated with a conveyor speed ranging from 7.5 to 30.6 mm/s. The system performance was evaluated at a conveyor speed of 7.5 mm/s using small catfish fillets from 142.2 to 225.4 cm3. A mean percent error of 9.2% was observed, and the smallest percent error of 3.8% was obtained with a 225.4 cm3 fillet. With minor measurement errors obtained for larger fillets, the proposed computer vision system showed great potential for developing a cost-effective automated system for customized fish fillet partitioning to accelerate purchase decisions and also for quality control and classification of the fish fillets.
Analysis and modeling of a pneumatic artificial muscle system Tran, Vinh-Phuc; Tran, Nhut-Thanh; Nguyen, Chi-Ngon; Nguyen, Chanh-Nghiem
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp874-884

Abstract

Hysteresis is a common challenge in achieving precise position control of pneumatic artificial muscles (PAMs). Accurate modeling of this phenomenon is essential for the development of efficient PAM control systems. This study evaluates four mathematical models for modeling PAM dynamics: Nonlinear AutoRegressive with eXogenous inputs (NARX), BoxJenkins (BJ), Prandtl-Ishlinskii (PI), and second-order underdamped system and one zero (P2UZ). To assess the effectiveness of these models, experiments were conducted with reference input signals of varying amplitudes. The accuracy and goodness of fit of these models were evaluated based on root mean square error (RMSE) and coefficient of determination. Results show that the P2UZ model achieved the highest fitness (97.15%) and the lowest RMSE (1.80 mm), followed closely by the NARX model with 96.83% fitness and an RMSE of 1.90 mm. The PI and BJ models demonstrated lower performance, with the BJ model showing the lowest fitness (90.79%) and the highest RMSE (3.25 mm). These findings provide valuable insights for improving PAM control and PAM-based automation systems by highlighting the strengths and limitations of each model.
Co-Authors Nguyen, Chanh-Nghiem Nguyen, Chi-Ngon Nguyen, Ngoc-Thanh Tran, Vinh-Phuc Vo, Ngọc-Tan