Some Engineering Factors Affecting the Performance of an Automatic Sugarcane Seed Cutting Machine | ||
| Aswan University Journal of Environmental Studies | ||
| Article 6, Volume 5, Issue 1, March 2024, Pages 87-100 PDF (1.07 M) | ||
| Document Type: Original Research | ||
| DOI: 10.21608/aujes.2024.259084.1206 | ||
| Authors | ||
| Abdallah E. Elwakeel* 1; Loai s. Nasrat2; Mohamed E. Badawy3; Manar A. Ourapi1 | ||
| 1Agricultural Engineering Department, Faculty of Agriculture and Natural Resources, Aswan University, Aswan 81528, Egypt | ||
| 2Electrical Power Engineering Department, Faculty of Engineering, Aswan University, Aswan 81528, Egypt | ||
| 3Agricultural Engineering Research Institute - Dokki – Giza 12611, Egypt | ||
| Abstract | ||
| The current study aimed to study some engineering factors affecting the performance of a new automatic sugarcane seed cutting machine based on an RGB color sensor and internet of things technology assisted by sugarcane seed monitoring and a counter-remote system. In the current study, we evaluated the performance of the developed machine using two saw knives with different tooth numbers (80 teeth and 30 teeth), five different cutting times (t1 = 1000 ms, t2 =1500 ms, t3 =2000 ms, t4 =2500 ms, and t5 =3000 ms), and four different sugarcane stalk diameters (d1 = 2.03 cm, d2 = 2.72 cm, d3 = 3.42 cm, and d4 = 3.94 cm). The obtained results showed that the invisible losses and cutting efficiency decreased with the decrease in the diameter of the sugarcane stalks, the increase in the cutting time, and the increase in the number of teeth of the rotary saw knife. While machine productivity took the opposite trend. Where it decreased with increasing cutting time and increasing the diameter of the sugarcane stalks, while the number of teeth of the rotary saw knife had no significant difference. | ||
| Keywords | ||
| sugarcane; PV system; Machine vision, Internet of things (IoT); machine learning | ||
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