2023
DOI: 10.3390/app13106278
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Parameter Calibration and Optimization of a Discrete Element Model of Plug Seedling Pots Based on a Collision Impact Force

Abstract: To improve the accuracy of simulation parameters used in discrete element simulation tests for the transplanting operation of the transplanting machine and to facilitate further optimization of crucial components of the transplanting machine, in this paper, the discrete element model of 50-hole plug seedling pots was calibrated and optimized based on the collision impact force between the plug seedling pot and the steel plate measured by a flexible film network tactile pressure sensor. Basic tests determined t… Show more

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Cited by 2 publications
(3 citation statements)
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“…The 5250-type flexible film network tactile pressure sensor is used in this test, as shown in Figure 2. It has a matrix-shaped sensing area (245.9 mm × 245.9 mm), a resolution of 3.2 cm −2 , and a sampling frequency of 0-100 Hz [22,23]. The specific specifications are shown in Table 1.…”
Section: Test Materials and Equipmentmentioning
confidence: 99%
See 1 more Smart Citation
“…The 5250-type flexible film network tactile pressure sensor is used in this test, as shown in Figure 2. It has a matrix-shaped sensing area (245.9 mm × 245.9 mm), a resolution of 3.2 cm −2 , and a sampling frequency of 0-100 Hz [22,23]. The specific specifications are shown in Table 1.…”
Section: Test Materials and Equipmentmentioning
confidence: 99%
“…The 5250-type flexible film network tactile pressu sensor is used in this test, as shown in Figure 2. It has a matrix-shaped sensing area (245 mm × 245.9 mm), a resolution of 3.2 cm −2 , and a sampling frequency of 0-100 Hz [22,23 The specific specifications are shown in Table 1. The experiment was carried out in the soil trench laboratory of Inner Mongolia Agr cultural University in Hohhot City, Inner Mongolia Autonomous Region.…”
Section: Test Materials and Equipmentmentioning
confidence: 99%
“…There is a large amount of sensors and artificial intelligence technology used for the modeling, simulation, and optimization of transplanting equipment in plant factory agriculture [9][10][11][12][13]. These outstanding works have greatly promoted the development of transplanting equipment technology [14][15][16][17]. Recently, driven by the rapid development of ICT such as cloud computing, IoT, big data, machine learning, augmented reality, and robotics, equipment modeling methods are becoming increasingly intelligent and data-driven [18].…”
Section: Introductionmentioning
confidence: 99%