This page has only limited features, please log in for full access.
In the field of agricultural machinery, various empirical field tests are performed to measure the design load for optimal design of tractors and implement. However, field test performance is costly, time-consuming, and there are many constraints on weather and field soil conditions, requiring simulation utilization studies to overcome these shortcomings. Therefore, the objectives of this study are to perform agricultural soil modeling, draft force prediction simulation in function of tillage depth using discrete element method (DEM) software, and to verify the prediction accuracy by comparing with field test results. In this study, soil property measurement test was performed by soil depth considering target tillage depth (0–200 mm) using soil mechanical properties measurement system for DEM soil modeling. DEM soil model calibration was performed using virtual vane shear test and cone penetration test values instead of the repose angle test. In addition, field tests to verify the accuracy of draft force prediction simulation were performed using a measuring tractor equipped with a draft force measurement system, a tillage depth measurement system and an RTK-GPS (travel speed). As a result of the DEM simulation, it was found that the prediction accuracy of the draft force was within 7.5% (5.1–9.9%) when compared to the measured draft force through field test. In addition, it was confirmed that the result was 5.3–61.6% more accurate than those obtained through existing theoretical methods used to predict draft force. On the other hand, the error of draft force prediction using DEM simulation considering only topsoil properties showed 20.3% lower prediction accuracy than the DEM soil model considering the soil properties of different soil layer. This study provides useful information for the DEM soil modeling process that consider the change in soil properties according to the tillage depth from the perspective of agricultural machinery research and it is expected to be utilized in agricultural machinery design research.
Yeon-Soo Kim; Abu Ayub Siddique; Wan-Soo Kim; Yong-Joo Kim; Sang-Dae Lee; Dong-Keun Lee; Seok-Joon Hwang; Ju-Seok Nam; Seong-Un Park; Ryu-Gap Lim. DEM simulation for draft force prediction of moldboard plow according to the tillage depth in cohesive soil. Computers and Electronics in Agriculture 2021, 189, 106368 .
AMA StyleYeon-Soo Kim, Abu Ayub Siddique, Wan-Soo Kim, Yong-Joo Kim, Sang-Dae Lee, Dong-Keun Lee, Seok-Joon Hwang, Ju-Seok Nam, Seong-Un Park, Ryu-Gap Lim. DEM simulation for draft force prediction of moldboard plow according to the tillage depth in cohesive soil. Computers and Electronics in Agriculture. 2021; 189 ():106368.
Chicago/Turabian StyleYeon-Soo Kim; Abu Ayub Siddique; Wan-Soo Kim; Yong-Joo Kim; Sang-Dae Lee; Dong-Keun Lee; Seok-Joon Hwang; Ju-Seok Nam; Seong-Un Park; Ryu-Gap Lim. 2021. "DEM simulation for draft force prediction of moldboard plow according to the tillage depth in cohesive soil." Computers and Electronics in Agriculture 189, no. : 106368.
Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to agriculture. For this reason, this study proposes weakly supervised crop area segmentation (WSCAS) to identify the uncut crop area efficiently for path guidance. Weakly supervised learning has advantage for training models because it entails less laborious annotation. The proposed method trains the classification model using area-specific images so that the target area can be segmented from the input image based on implicitly learned localization. This way makes the model implementation easy even with a small data scale. The performance of the proposed method was evaluated using recorded video frames that were then compared with previous deep-learning-based segmentation methods. The results showed that the proposed method can be conducted with the lowest inference time and that the crop area can be localized with an intersection over union of approximately 0.94. Additionally, the uncut crop edge could be detected for practical use based on the segmentation results with post-image processing such as with a Canny edge detector and Hough transformation. The proposed method showed the significant ability of using automatic perception in agricultural navigation to infer the crop area with real-time level speed and have localization comparable to existing semantic segmentation methods. It is expected that our method will be used as essential tool for the automatic path guidance system of a combine harvester.
Wan-Soo Kim; Dae-Hyun Lee; Taehyeong Kim; Hyunggun Kim; Taeyong Sim; Yong-Joo Kim. Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester. Sensors 2021, 21, 4801 .
AMA StyleWan-Soo Kim, Dae-Hyun Lee, Taehyeong Kim, Hyunggun Kim, Taeyong Sim, Yong-Joo Kim. Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester. Sensors. 2021; 21 (14):4801.
Chicago/Turabian StyleWan-Soo Kim; Dae-Hyun Lee; Taehyeong Kim; Hyunggun Kim; Taeyong Sim; Yong-Joo Kim. 2021. "Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester." Sensors 21, no. 14: 4801.
This study is focused on the estimation of fuel consumption of the power-shift transmission (PST) tractor based on PTO (power take-off) dynamometer test. The simulation model of PST tractor was developed using the configurations and powertrain of the real PST tractor. The PTO dynamometer was installed to measure the engine load and fuel consumption at various engine load levels (40, 50, 60, 70, 80, and 90%), and verify the simulation model. The axle load was also predicted using tractor’s specifications as an input parameter of the simulation model. The simulation and measured results were analyzed and compared statistically. It was observed that the engine load, as well as fuel consumption, were directly proportional to the engine load levels. However, it was statistically proved that there was no significant difference between the simulation and measured engine torque and fuel consumption at each load level. The regression equations show that there was an exponential relationship between the fuel consumption and engine load levels. However, the specific fuel consumptions (SFC) for both simulation and measured were linear relationships and had no significant difference between them at each engine load level. The results were statistically proved that the simulation and measured SFCs were similar trends. The plow tillage operation could be performed at the gear stage of 7.65 km/h with higher working efficiency at low fuel consumption. The drawback of this study is to use a constant axle load instead of dynamic load. This study can provide useful information for both researchers and manufacturers related to the automated transmission of an agricultural tractor, especially PST tractor for digital farming solutions. Finally, it could contribute to the manufacturers developing a new agricultural tractor with higher fuel efficiency.
Abu Ayub Siddique; Seung-Min Baek; Seung-Yun Baek; Wan-Soo Kim; Yeon-Soo Kim; Yong-Joo Kim; Dae-Hyun Lee; Kwan-Ho Lee; Joon-Yeal Hwang. Simulation of Fuel Consumption Based on Engine Load Level of a 95 kW Partial Power-Shift Transmission Tractor. Agriculture 2021, 11, 276 .
AMA StyleAbu Ayub Siddique, Seung-Min Baek, Seung-Yun Baek, Wan-Soo Kim, Yeon-Soo Kim, Yong-Joo Kim, Dae-Hyun Lee, Kwan-Ho Lee, Joon-Yeal Hwang. Simulation of Fuel Consumption Based on Engine Load Level of a 95 kW Partial Power-Shift Transmission Tractor. Agriculture. 2021; 11 (3):276.
Chicago/Turabian StyleAbu Ayub Siddique; Seung-Min Baek; Seung-Yun Baek; Wan-Soo Kim; Yeon-Soo Kim; Yong-Joo Kim; Dae-Hyun Lee; Kwan-Ho Lee; Joon-Yeal Hwang. 2021. "Simulation of Fuel Consumption Based on Engine Load Level of a 95 kW Partial Power-Shift Transmission Tractor." Agriculture 11, no. 3: 276.
The objective of this study was to develop a model to estimate the axle torque (AT) of a tractor using an artificial neural network (ANN) based on a relatively low-cost sensor. ANN has proven to be useful in the case of nonlinear analysis, and it can be applied to consider nonlinear variables such as soil characteristics, unlike studies that only consider tractor major parameters, thus model performance and its implementation can be extended to a wider range. In this study, ANN-based models were compared with multiple linear regression (MLR)-based models for performance verification. The main input data were tractor engine parameters, major tractor parameters, and soil physical properties. Data of soil physical properties (i.e., soil moisture content and cone index) and major tractor parameters (i.e., engine torque, engine speed, specific fuel consumption, travel speed, tillage depth, and slip ratio) were collected during a tractor field experiment in four Korean paddy fields. The collected soil physical properties and major tractor parameter data were used to estimate the AT of the tractor by the MLR- and ANN-based models: 250 data points were used for developing and training the model were used, the 50 remaining data points were used to test the model estimation. The AT estimated with the developed MLR- and ANN-based models showed agreement with actual measured AT, with the R2 value ranging from 0.825 to 0.851 and from 0.857 to 0.904, respectively. These results suggest that the developed models are reliable in estimating tractor AT, while the ANN-based model showed better performance than the MLR-based model. This study can provide useful results as a simple method using ANNs based on relatively inexpensive sensors that can replace the existing complex tractor AT measurement method is emphasized.
Wan-Soo Kim; Dae-Hyun Lee; Yong-Joo Kim; Yeon-Soo Kim; Seong-Un Park. Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network. Sensors 2021, 21, 1989 .
AMA StyleWan-Soo Kim, Dae-Hyun Lee, Yong-Joo Kim, Yeon-Soo Kim, Seong-Un Park. Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network. Sensors. 2021; 21 (6):1989.
Chicago/Turabian StyleWan-Soo Kim; Dae-Hyun Lee; Yong-Joo Kim; Yeon-Soo Kim; Seong-Un Park. 2021. "Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network." Sensors 21, no. 6: 1989.
The purpose of this study is to evaluate the performance of a robot combine harvester by comparing the Centimeter Level Augmentation Service (CLAS) and the Multi-Global Navigation Satellite System (GNSS) Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) from the Quasi-Zenith Satellite System (QZSS) by using the Real Time Kinematic (RTK) positioning technique as a reference. The first section of this study evaluates the availability and the precision under static conditions by measuring the activation time, the reconnection time, and obtaining a Twice Distance Root Mean Square (2DRMS) of 0.04 m and 0.10 m, a Circular Error Probability (CEP) of 0.03 m and 0.08 m, and a Root Mean Square Error (RMSE) of 0.57 m and 0.54 m for the CLAS and MADOCA, respectively. The second section evaluates the accuracy under dynamic conditions by using a GNSS navigation-based combine harvester running in an experimental field. The results show that the RMSE of the lateral deviation is between 0.04 m and 0.69 m for MADOCA and between 0.03 m and 0.31 m for CLAS; which suggest that the CLAS positioning augmentation system can be utilized for the robot combine harvester if the user considers these accuracy and dynamic characteristics.
Kannapat Udompant; Ricardo Ospina; Yong-Joo Kim; Noboru Noguchi. Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester. Agronomy 2021, 11, 483 .
AMA StyleKannapat Udompant, Ricardo Ospina, Yong-Joo Kim, Noboru Noguchi. Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester. Agronomy. 2021; 11 (3):483.
Chicago/Turabian StyleKannapat Udompant; Ricardo Ospina; Yong-Joo Kim; Noboru Noguchi. 2021. "Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester." Agronomy 11, no. 3: 483.
The development of an automatic walking-type pepper transplanter could be effective in improving the mechanization rate in pepper cultivation, where the dibbling mechanism plays a vital role and determines planting performance and efficiency. The objective of this research was to determine a suitable working speed for a gear-driven dibbling mechanism appropriate for a pepper transplanter, while considering agronomic transplanting requirements. The proposed dibbling mechanism consisted of two dibbling hoppers that simultaneously collected free-falling seedlings from the supply mechanism and dibbled them into soil. To enable the smooth collection and plantation of pepper seedlings, analysis was carried out via a mathematical working trajectory model of the dibbling mechanism, virtual prototype simulation, and validation tests, using a physical prototype. In the mathematical model analysis and simulation, a 300 mm/s forward speed of the transplanter and a 60 rpm rotational speed of the dibbling mechanism were preferable in terms of seedling uprightness and low mulch film damage. During the field test, transplanting was conducted at a 40 mm planting depth, using different forward speed levels. Seedlings were freely supplied to the hopper from a distance of 80 mm, and the success rate for deposition was 96.79%. A forward speed of 300 mm/s with transplanting speed of 120 seedlings/min was preferable in terms of achieving a high degree of seedling uprightness (90 ± 3.26), a low rate of misplanting (8.19%), a low damage area on mulch film (2341.95 ± 2.89 mm2), high uniformity of planting depth (39.74 ± 0.48 mm), and low power consumption (40.91 ± 0.97 W).
Zafar Iqbal; Nafiul Islam; Milon Chowdhury; Sumaiya Islam; Tusan Park; Yong-Joo Kim; Sun-Ok Chung. Working Speed Analysis of the Gear-Driven Dibbling Mechanism of a 2.6 kW Walking-Type Automatic Pepper Transplanter. Machines 2021, 9, 6 .
AMA StyleZafar Iqbal, Nafiul Islam, Milon Chowdhury, Sumaiya Islam, Tusan Park, Yong-Joo Kim, Sun-Ok Chung. Working Speed Analysis of the Gear-Driven Dibbling Mechanism of a 2.6 kW Walking-Type Automatic Pepper Transplanter. Machines. 2021; 9 (1):6.
Chicago/Turabian StyleZafar Iqbal; Nafiul Islam; Milon Chowdhury; Sumaiya Islam; Tusan Park; Yong-Joo Kim; Sun-Ok Chung. 2021. "Working Speed Analysis of the Gear-Driven Dibbling Mechanism of a 2.6 kW Walking-Type Automatic Pepper Transplanter." Machines 9, no. 1: 6.
Conventional tractor transmission spiral bevel gears are designed and evaluated based on the engine rated load, which is significantly higher than the load conditions in the field. In this study, the fatigue life of a spiral bevel gear is evaluated to obtain data for design optimization. The equivalent load was calculated using the field load data, and the integrated equivalent load was calculated based on the annual usage of major field operations in Korea. The fatigue life of three spiral bevel gear samples was evaluated using the accelerated life test (ALT) under an engine rated load condition of 120%. It was also evaluated under engine rated, plow equivalent, and integrated equivalent load. Fatigue life was estimated using the ALT results and the fatigue damage exponent based on the ALT equation. We observed that the fatigue life of the spiral bevel gear under the plow equivalent and integrated equivalent loads is higher than that under the rated load by 214 and 9,400 times, respectively. The results of this study can provide useful information for the design optimization of tractor transmission spiral bevel gears considering the field equivalent load.
Wan-Soo Kim; Yong-Joo Kim; Yeon-Soo Kim; Seong-Un Park; Kyeong-Hwan Lee; Dong-Hyuck Hong; Chang-Hyun Choi. Evaluation of the fatigue life of a tractor’s transmission spiral bevel gear. Journal of Terramechanics 2020, 94, 13 -22.
AMA StyleWan-Soo Kim, Yong-Joo Kim, Yeon-Soo Kim, Seong-Un Park, Kyeong-Hwan Lee, Dong-Hyuck Hong, Chang-Hyun Choi. Evaluation of the fatigue life of a tractor’s transmission spiral bevel gear. Journal of Terramechanics. 2020; 94 ():13-22.
Chicago/Turabian StyleWan-Soo Kim; Yong-Joo Kim; Yeon-Soo Kim; Seong-Un Park; Kyeong-Hwan Lee; Dong-Hyuck Hong; Chang-Hyun Choi. 2020. "Evaluation of the fatigue life of a tractor’s transmission spiral bevel gear." Journal of Terramechanics 94, no. : 13-22.
The objective of this study is the simulation of the most affected design factors and variables of the clutch pack for the power-shift transmission (PST) of a tractor based measured data. The simulation model, the mathematical model of sliding velocity, a moment of inertia, and clutch engagement pressure of clutch pack were developed using the powertrain and configurations of the real PST tractor. In this study, the sensor fusion method was used to precisely measure the proportional valve pressure by test bench, which was applied to the simulation model. The clutch engagement times were found 1.20 s at all temperatures for determined factors. The engagement pressures have a significant difference at various temperatures (25 to 100 °C) of the hydraulic oils after the 1.20 s but the most affected factors were satisfied with the simulation conditions that ensure the clutch engagement on time. Finally, this sensor fusion method is believed to be helpful in realizing precision agriculture through minimization of power loss and maximum energy efficiency of tractors.
Abu Ayub Siddique; Wan-Soo Kim; Yeon-Soo Kim; Seung-Yun Baek; Seung-Min Baek; Yong-Joo Kim; Seong-Un Park; Chang-Hyun Choi. Simulation of Design Factors of a Clutch Pack for Power-Shift Transmission for an Agricultural Tractor. Sensors 2020, 20, 7293 .
AMA StyleAbu Ayub Siddique, Wan-Soo Kim, Yeon-Soo Kim, Seung-Yun Baek, Seung-Min Baek, Yong-Joo Kim, Seong-Un Park, Chang-Hyun Choi. Simulation of Design Factors of a Clutch Pack for Power-Shift Transmission for an Agricultural Tractor. Sensors. 2020; 20 (24):7293.
Chicago/Turabian StyleAbu Ayub Siddique; Wan-Soo Kim; Yeon-Soo Kim; Seung-Yun Baek; Seung-Min Baek; Yong-Joo Kim; Seong-Un Park; Chang-Hyun Choi. 2020. "Simulation of Design Factors of a Clutch Pack for Power-Shift Transmission for an Agricultural Tractor." Sensors 20, no. 24: 7293.
The spiral bevel gear in a tractor, unlike the other gears in the transmission, is one of the most vulnerable gears in terms of fatigue life, as it is consistently driven throughout the operations of the tractor. Conventional fatigue life tests of transmission gears require expensive equipment and repeated tests, and do not reflect dynamic field loads. The aim of this study is to develop a simulation model which can replace conventional fatigue life tests for actual gears, in order to evaluate the fatigue life of a tractor using dynamic field load data. A transmission simulation model including a spiral bevel gear was developed using commercial software. In order to measure the dynamic load of the tractor according to various field operations, an axle torque measurement system was developed, and field experiments were performed for major agricultural operations occurring in the field. Fatigue life was calculated using Rainflow cycle counting (RFC), the Smith–Watson–Topper (SWT) model, and S–N curves based on torque data measured in the field. The fatigue life under moldboard plow tillage, subsoiler tillage, rotary tillage, and baler operation were 13,599, 285, 278,884, and 525,977 h, respectively. The fatigue life of the tractor, according to subsoiler tillage and baler operation, was 0.104 and 192 times the service life, respectively, where the difference between these two operations was about 1846 times. The fatigue life of the tractor, according to the attached implement type, was significantly different. Therefore, it can be seen that the fatigue life of a tractor can be significantly different, depending on agricultural operation type which the farmer uses most often; this can be used as basic data for tractor design and evaluation. In addition, it is considered that the developed simulation model can be applied to fatigue life evaluation using dynamic field load data.
Wan-Soo Kim; Yong-Joo Kim; Seung-Min Baek; Seok-Pyo Moon; Nam-Gyu Lee; Yeon-Soo Kim; Seong-Un Park; Yong Choi; Young-Keun Kim; Il-Su Choi; Duck-Kyu Choi; Chang-Hyun Choi. Fatigue Life Simulation of Tractor Spiral Bevel Gear According to Major Agricultural Operations. Applied Sciences 2020, 10, 8898 .
AMA StyleWan-Soo Kim, Yong-Joo Kim, Seung-Min Baek, Seok-Pyo Moon, Nam-Gyu Lee, Yeon-Soo Kim, Seong-Un Park, Yong Choi, Young-Keun Kim, Il-Su Choi, Duck-Kyu Choi, Chang-Hyun Choi. Fatigue Life Simulation of Tractor Spiral Bevel Gear According to Major Agricultural Operations. Applied Sciences. 2020; 10 (24):8898.
Chicago/Turabian StyleWan-Soo Kim; Yong-Joo Kim; Seung-Min Baek; Seok-Pyo Moon; Nam-Gyu Lee; Yeon-Soo Kim; Seong-Un Park; Yong Choi; Young-Keun Kim; Il-Su Choi; Duck-Kyu Choi; Chang-Hyun Choi. 2020. "Fatigue Life Simulation of Tractor Spiral Bevel Gear According to Major Agricultural Operations." Applied Sciences 10, no. 24: 8898.
Pepper is one of the most vital agricultural products with high economic value, and pepper production needs to satisfy the growing worldwide population by introducing automatic seedling transplantation techniques. Optimal design and dimensioning of picking device components for an automatic pepper transplanter are crucial for efficient and effective seedling transplantation. Therefore, kinematic analysis, virtual model simulation, and validation testing of a prototype were conducted to propose a best-suited dimension for a clamp-type picking device. The proposed picking device mainly consisted of a manipulator with five grippers and a picking stand. To analyze the influence of design variables through kinematic analysis, 250- to 500-mm length combinations were considered to meet the trajectory requirements and suit the picking workspace. Virtual model simulation and high-speed photography tests were conducted to obtain the kinematic characteristics of the picking device. According to the kinematic analysis, a 350-mm picking stand and a 380-mm manipulator were selected within the range of the considered combinations. The maximum velocity and acceleration of the grippers were recorded as 1.1, 2.2 m/s and 1.3, 23.7 m/s2, along the x- and y-axes, respectively, for 30 to 90 rpm operating conditions. A suitable picking device dimension was identified and validated based on the suitability of the picking device working trajectory, velocity, and acceleration of the grippers, and no significant difference (p ≤ 0.05) occurred between the simulation and validation tests. This study indicated that the picking device under development would increase the pepper seedling picking accuracy and motion safety by reducing the operational time, gripper velocity, acceleration, and mechanical damage.
Nafiul Islam; Zafar Iqbal; Mohammod Ali; Milon Chowdhury; Shaha Nur Kabir; Tusan Park; Yong-Joo Kim; Sun-Ok Chung. Kinematic Analysis of a Clamp-Type Picking Device for an Automatic Pepper Transplanter. Agriculture 2020, 10, 627 .
AMA StyleNafiul Islam, Zafar Iqbal, Mohammod Ali, Milon Chowdhury, Shaha Nur Kabir, Tusan Park, Yong-Joo Kim, Sun-Ok Chung. Kinematic Analysis of a Clamp-Type Picking Device for an Automatic Pepper Transplanter. Agriculture. 2020; 10 (12):627.
Chicago/Turabian StyleNafiul Islam; Zafar Iqbal; Mohammod Ali; Milon Chowdhury; Shaha Nur Kabir; Tusan Park; Yong-Joo Kim; Sun-Ok Chung. 2020. "Kinematic Analysis of a Clamp-Type Picking Device for an Automatic Pepper Transplanter." Agriculture 10, no. 12: 627.
The Internet of Things (IoT) is a network of devices for communicating machine to machine (M2M) based on wired and wireless Internet. IoT in agriculture is a revolutionary technology that can be applied to agricultural production year-round. The aim of this study is to summarize cases of IoT being applied to agricultural automation in the agricultural sector and to discuss the limitations and prospects for expanding the application of IoT technology in Korea. The application of IoT in agriculture was classified and analyzed based on previous data, and the sensors and communication technologies used were compared. Based on the analysis results, the limitations of and prospects for IoT in agriculture were discussed. IoT was widely used in agriculture, such as management systems, monitoring systems, control systems, and unmanned machinery. In addition, the various wireless communication technologies used in agriculture, such as Wi-Fi, long-range wide area network (LoRaWAN), mobile communication (e.g., 2G, 3G, and 4G), ZigBee, and Bluetooth, were also used in IoT-based agriculture. With the development of various communication technologies, such as 5G, it is expected that faster and broader IoT technologies will be applied to various agricultural processes in the future. IoT-based agriculture equipped with a communication system suitable for each agricultural environment can contribute to agricultural automation by increasing crop quality and production and reducing labor.
Wan-Soo Kim; Won-Suk Lee; Yong-Joo Kim. A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation. Journal of Biosystems Engineering 2020, 45, 385 -400.
AMA StyleWan-Soo Kim, Won-Suk Lee, Yong-Joo Kim. A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation. Journal of Biosystems Engineering. 2020; 45 (4):385-400.
Chicago/Turabian StyleWan-Soo Kim; Won-Suk Lee; Yong-Joo Kim. 2020. "A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation." Journal of Biosystems Engineering 45, no. 4: 385-400.
Machine-vision-based crop detection is a central issue for digital farming, and crop height is an important factor that should be automatically measured in robot-based cultivations. Three-dimensional (3D) imaging cameras make it possible to measure actual crop height; however, camera tilt due to irregular ground conditions in farmland prevents accurate height measurements. In this study, stereo-vision-based crop height was measured with compensation for the camera tilt effect. For implementing the tilt of the camera installed on farm machines (e.g., tractors), we developed a posture tilt simulator for indoor testing that could implement the camera tilt by pitch and roll rotations. Stereo images were captured under various simulator tilt conditions, and crop height was measured by detecting the crop region in a disparity map, which was generated by matching stereo images. The measured height was compensated for by correcting the position of the region of interest (RoI) in the 3D image through coordinate transformation between camera coordinates and simulator coordinates. The tests were conducted by roll and pitch rotation around the simulator coordinates. The results showed that crop height could be measured using stereo vision, and that tilt compensation reduced the average error from 15.6 to 3.9 cm. Thus, the crop height measurement system proposed in this study, based on 3D imaging and a tilt sensor, can contribute to the automatic perception of agricultural robots.
Wan-Soo Kim; Dae-Hyun Lee; Yong-Joo Kim; Yeon-Soo Kim; Taehyeong Kim; Seong-Un Park; Sung-Soo Kim; Dong-Hyuck Hong. Crop Height Measurement System Based on 3D Image and Tilt Sensor Fusion. Agronomy 2020, 10, 1670 .
AMA StyleWan-Soo Kim, Dae-Hyun Lee, Yong-Joo Kim, Yeon-Soo Kim, Taehyeong Kim, Seong-Un Park, Sung-Soo Kim, Dong-Hyuck Hong. Crop Height Measurement System Based on 3D Image and Tilt Sensor Fusion. Agronomy. 2020; 10 (11):1670.
Chicago/Turabian StyleWan-Soo Kim; Dae-Hyun Lee; Yong-Joo Kim; Yeon-Soo Kim; Taehyeong Kim; Seong-Un Park; Sung-Soo Kim; Dong-Hyuck Hong. 2020. "Crop Height Measurement System Based on 3D Image and Tilt Sensor Fusion." Agronomy 10, no. 11: 1670.
In this paper, the effects of sputter-deposited silicon oxide (SiOx) passivation on p-type tin monoxide (SnO) semiconductor are investigated. X-ray photoelectron spectroscopy analyses indicate that the relative oxygen content decreases when a SiOx passivation layer is applied, thus inducing an oxygen deficient stoichiometry which promotes the delocalization of the valence band, thus improving hole transport. As a result, SnO thin-film transistors (TFTs) with a SiOx protective layer exhibit much higher field-effect mobility of 1.40 cm2/Vs compared to devices without passivation (6.23 × 10−2 cm2/Vs).
Song-Yi Ahn; Seong Cheol Jang; Aeran Song; Kwun-Bum Chung; Yong Joo Kim; Hyun-Suk Kim. Performance enhancement of p-type SnO semiconductors via SiOx passivation. Materials Today Communications 2020, 26, 101747 .
AMA StyleSong-Yi Ahn, Seong Cheol Jang, Aeran Song, Kwun-Bum Chung, Yong Joo Kim, Hyun-Suk Kim. Performance enhancement of p-type SnO semiconductors via SiOx passivation. Materials Today Communications. 2020; 26 ():101747.
Chicago/Turabian StyleSong-Yi Ahn; Seong Cheol Jang; Aeran Song; Kwun-Bum Chung; Yong Joo Kim; Hyun-Suk Kim. 2020. "Performance enhancement of p-type SnO semiconductors via SiOx passivation." Materials Today Communications 26, no. : 101747.
The cone index (CI), as an indicator of the soil strength, is closely related to the traction performance of tractors. This study evaluates the traction performance of a tractor in terms of the CI during tillage. To analyze the traction performance, a field site was selected and divided into grids, and the CI values at each grid were measured. The CI maps of the field sites were created using the measured CI. The traction performance was analyzed using the measured traction load. The traction performance was grouped at CI intervals of 400 kPa to classify it in terms of the CI. When the CI decreased, the engine speed and tractive efficiency (TE) decreased, while the engine torque, slip ratio, axle torque, traction force, and dynamic traction ratio (DTR) increased. Moreover, the DTR increased up to approximately 13%, and the TE decreased up to 9%. The maximum TE in the DTR range of 0.45–0.55 was higher than approximately 80% for CI values above 1500 kPa. The DTR and TE results obtained in terms of the CI can help efficiently design tractors considering the soil environmental conditions.
Wan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Yong Choi; Young-Keun Kim; Il-Su Choi. Traction performance evaluation of a 78-kW-class agricultural tractor using cone index map in a Korean paddy field. Journal of Terramechanics 2020, 91, 285 -296.
AMA StyleWan-Soo Kim, Yong-Joo Kim, Seung-Yun Baek, Yeon-Soo Kim, Yong Choi, Young-Keun Kim, Il-Su Choi. Traction performance evaluation of a 78-kW-class agricultural tractor using cone index map in a Korean paddy field. Journal of Terramechanics. 2020; 91 ():285-296.
Chicago/Turabian StyleWan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Yong Choi; Young-Keun Kim; Il-Su Choi. 2020. "Traction performance evaluation of a 78-kW-class agricultural tractor using cone index map in a Korean paddy field." Journal of Terramechanics 91, no. : 285-296.
In order to optimize tractor design and optimize efficiency during tillage operation, it is essential to verify the impact through field tests on factors affecting the tractor load. The objectives of this study were to investigate the effect of tillage depth on power transmission efficiency of 42 kW power agricultural tractor during moldboard plowing. A load measurement system and a tillage depth measurement system were configured for field tests. To analyze the effect of tillage depth on power transmission efficiency and fuel consumption, the data measured in the three-repeated field test were classified according to tillage depth. As the tillage depth increased from 11 cm at the top of the hardpan to 23 cm at the deepest, the required power of the engine increased by approximately 13% from 35.48 kW to 40.11 kW, and the power transmission efficiency also increased significantly from 66% to 95%. Among them, the power transmission efficiency of the rear axle was significantly increased from 38% to 59%, which was the most affected. As the tillage depth increased, the overall power requirement is greatly increased due to the resulting workload, but the fuel consumption and the specific fuel consumption are reduced because the engine speed of the tractor is reduced. As the tillage depth increased from 11 cm to 23 cm, the fuel consumption rate was rather reduced by 13.5% as the engine rotational speed decreased 11.3% due to the increase work load of tractor. In addition, the specific fuel consumption decreased from 302.44 g/kWh to 236.93 g/kWh, showing a fuel consumption saving of up to 21.7% during moldboard plow. In addition, as the tillage depth increased, the ratio of the value excluding the mechanical and hydraulic power requirements has significantly decreased from 34% to 5% as the power transmission efficiency increases. This study considers the soil properties according to the soil depth, as well as the power transmission efficiency and fuel consumption rate. The research results can provide useful information for research on power transmission efficiency and selection of an appropriate power source of agricultural tractor according to tillage depth during moldboard plowing and are expected to be used in various ways as basic studies of digital farming research in agricultural machinery.
Yeon-Soo Kim; Wan-Soo Kim; Abu Ayub Siddique; Seung-Yun Baek; Seung-Min Baek; Su-Hwan Cheon; Sang-Dae Lee; Kyeong-Hwan Lee; Dong-Hyuck Hong; Seong-Un Park; Yong-Joo Kim. Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing. Agronomy 2020, 10, 1263 .
AMA StyleYeon-Soo Kim, Wan-Soo Kim, Abu Ayub Siddique, Seung-Yun Baek, Seung-Min Baek, Su-Hwan Cheon, Sang-Dae Lee, Kyeong-Hwan Lee, Dong-Hyuck Hong, Seong-Un Park, Yong-Joo Kim. Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing. Agronomy. 2020; 10 (9):1263.
Chicago/Turabian StyleYeon-Soo Kim; Wan-Soo Kim; Abu Ayub Siddique; Seung-Yun Baek; Seung-Min Baek; Su-Hwan Cheon; Sang-Dae Lee; Kyeong-Hwan Lee; Dong-Hyuck Hong; Seong-Un Park; Yong-Joo Kim. 2020. "Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing." Agronomy 10, no. 9: 1263.
In general, the tractor axle torque is used as an indicator for making various decisions when engineers perform transmission fatigue life analysis, optimal design, and accelerated life testing. Since the existing axle torque measurement method requires an expensive torque sensor, an alternative method is required. Therefore, the aim of this study is to develop a prediction model for the tractor axle torque during tillage operation that can replace expensive axle torque sensors. A prediction model was proposed through regression analysis using key variables affecting the tractor axle torque. The engine torque, engine speed, tillage depth, slip ratio, and travel speed were selected as explanatory variables. In order to collect explanatory and dependent variable data, a load measurement system was developed, and a field experiment was performed on moldboard plow tillage using a tractor with a load measurement system. A total of eight axle torque prediction regression models were proposed using the measured calibration dataset. The adjusted coefficient of determination (R2) of the proposed regression model showed a range of 0.271 to 0.925. Among them, the prediction model E showed an adjusted R2 of 0.925. All of the prediction models were verified using a validation set. All of the axle torque prediction models showed an mean absolute percentage error (MAPE) of less than 2.8%. In particular, Model E, adopting engine torque, engine speed, and travel speed as variables, and Model H, adopting engine torque, tillage depth and travel speed as variables, showed MAPEs of 1.19 and 1.30%, respectively. Therefore, it was found that the proposed prediction models are applicable to actual axle torque prediction.
Wan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Seong-Un Park. Development of a Prediction Model for Tractor Axle Torque during Tillage Operation. Applied Sciences 2020, 10, 4195 .
AMA StyleWan-Soo Kim, Yong-Joo Kim, Seung-Yun Baek, Yeon-Soo Kim, Seong-Un Park. Development of a Prediction Model for Tractor Axle Torque during Tillage Operation. Applied Sciences. 2020; 10 (12):4195.
Chicago/Turabian StyleWan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Seong-Un Park. 2020. "Development of a Prediction Model for Tractor Axle Torque during Tillage Operation." Applied Sciences 10, no. 12: 4195.
This study was conducted to develop a simulation model of a 50 kW class hydro mechanical transmission (HMT) tractor and to verify the model by comparing the measured and simulated data, including the axle torque, rotational speed, and power transmission efficiency. The platform of the HMT was composed of the engine, hydrostatic unit (HSU), compound planetary gear, range shift, spiral bevel gear, and final reduction gear. The HMT had three gear stages and a maximum forward speed of 40 km/h. To evaluate the performance of the HTM, a test bench was installed based on the engine of the HMT platform, and a simulation model was developed using 3D simulation software. To compare the results of the simulation, a bench test using the platform was performed according to the gear stages. The similarities between the measured and simulated data were analyzed using the t-test. As a result, there were no significant differences for the axle torque, rotational speed, and power transmission efficiency. Finally, the power transmission efficiency between the measured and simulated results was compared and analyzed using linear regression analysis to validate the accuracy of the simulation model. The trend of the power transmission efficiency between the measured and simulated results appeared to be similar in all sections, and we obtained a simulation model with the accuracy of an R-squared value of more than 0.97. In conclusion, the measured and simulated results were similar to each other. Considering the results of this study, it will be useful to develop the HMT tractor and to improve the power transmission efficiency for the optimal design.
Seung-Min Baek; Wan-Soo Kim; Yeon-Soo Kim; Yong-Joo Kim. Development of a Simulation Model for HMT of a 50 kW Class Agricultural Tractor. Applied Sciences 2020, 10, 1 .
AMA StyleSeung-Min Baek, Wan-Soo Kim, Yeon-Soo Kim, Yong-Joo Kim. Development of a Simulation Model for HMT of a 50 kW Class Agricultural Tractor. Applied Sciences. 2020; 10 (12):1.
Chicago/Turabian StyleSeung-Min Baek; Wan-Soo Kim; Yeon-Soo Kim; Yong-Joo Kim. 2020. "Development of a Simulation Model for HMT of a 50 kW Class Agricultural Tractor." Applied Sciences 10, no. 12: 1.
This study was conducted to develop a simulation model of a 120 kW class electric all-wheel-drive (AWD) tractor and verify the model by comparing the measurement and simulation results. The platform was developed based on the power transmission system, including batteries, electric motors, reducers, wheels, and a charging system composed of a generator, an AC/DC converter, and chargers on each axle. The data measurement system was installed on the platform, consisting of an analog (current) and a digital part (rotational speed of electric motors and voltage and SOC (state of charge) level of batteries) by a CAN (controller area network) bus. The axle torque was calculated using the current and torque curves of the electric motor. The simulation model was developed by 1D simulation software and used axle torque and vehicle velocity data to create the simulation conditions. To compare the results of the simulation, a driving test using the platform was performed at a ground speed of 10 km/h in off- and on-road conditions. The similarities between the results were analyzed using statistical software and we found no significant difference in axle torque data. The simulation model was considered to be highly reliable given the change rate and average value of the SOC level. Using the simulation model, the workable time of driving operation was estimated to be about six hours and the workable time of plow tillage was estimated to be about 2.4 h. The results showed that the capacity of the battery is slightly low for plow tillage. However, in future studies, the electric AWD tractor performance could be improved through battery optimization through simulation under various conditions.
Seung-Yun Baek; Yeon-Soo Kim; Wan-Soo Kim; Yong-Joo Kim. Development and Verification of a Simulation Model for 120 kW Class Electric AWD (All-Wheel-Drive) Tractor during Driving Operation. Energies 2020, 13, 2422 .
AMA StyleSeung-Yun Baek, Yeon-Soo Kim, Wan-Soo Kim, Yong-Joo Kim. Development and Verification of a Simulation Model for 120 kW Class Electric AWD (All-Wheel-Drive) Tractor during Driving Operation. Energies. 2020; 13 (10):2422.
Chicago/Turabian StyleSeung-Yun Baek; Yeon-Soo Kim; Wan-Soo Kim; Yong-Joo Kim. 2020. "Development and Verification of a Simulation Model for 120 kW Class Electric AWD (All-Wheel-Drive) Tractor during Driving Operation." Energies 13, no. 10: 2422.
We fabricated and evaluated four types of Li batteries, in this case a LTO/liquid electrolyte/Li battery, a LTO/LiPON/Li all-solid-state battery, and LTO/LiPON + liquid electrolyte/Li batteries with and without a separator to investigate and clarify the effects of each interface. Through the present research, it was found that a conventional polymer-based separator increases the impedance in the middle frequency region, resulting in an increase in the total cell resistance. After replacing the polymer-based separator with a thin-film solid electrolyte, the cycleability and capacity of the cell were comparable to those of a conventional Li-ion battery with a polymer separator. The all-solid-state Li thin-film battery without a liquid electrolyte exhibits the lowest capacity due to the large interfacial resistance between the Li metal and the LiPON solid electrolyte. However, we found that the insertion of an Al2O3 interlayer between the Li and LiPON improves the capacity.
Jong Heon Kim; Cheng-Fan Xiao; Jonghyun Han; Yong Joo Kim; Shunsuke Yagi; Hyun-Suk Kim. Interface control for high-performance all-solid-state Li thin-film batteries. Ceramics International 2020, 46, 19960 -19965.
AMA StyleJong Heon Kim, Cheng-Fan Xiao, Jonghyun Han, Yong Joo Kim, Shunsuke Yagi, Hyun-Suk Kim. Interface control for high-performance all-solid-state Li thin-film batteries. Ceramics International. 2020; 46 (12):19960-19965.
Chicago/Turabian StyleJong Heon Kim; Cheng-Fan Xiao; Jonghyun Han; Yong Joo Kim; Shunsuke Yagi; Hyun-Suk Kim. 2020. "Interface control for high-performance all-solid-state Li thin-film batteries." Ceramics International 46, no. 12: 19960-19965.
This study was conducted to analyze the effects of tillage depth and gear selection on the mechanical load and fuel efficiency of an agricultural tractor during plow tillage. In order to analyze these effects, we developed an agricultural field measuring system consisting of a load measurement part (wheel torque meter, proximity sensor, and real-time kinematic (RTK) global positioning system (GPS)) and a tillage depth measurement part (linear potentiometer and inclinometer). Field tests were carried out using moldboard plows with a maximum tillage depth of 20 cm and three gear selections (M2H, M3L, and M3H) in a rice stubble paddy field for plow tillage. The average travel speed and slip ratio had the lowest M2H and the highest M3L. M3H had the highest theoretical speed, but the travel speed was 0.13 km/h lower than M3L due to the reduction in the axle rotational speed at deep tillage depth. Regarding engine load, the higher the gear, the greater the torque and the lower the axle rotation speed. The front axle load was not significantly affected by the tillage depth as compared to other mechanical parts, except for the M3H gear. The rear axle load generated about twice the torque of the front wheel and overall, it tended to show a higher average rear axle torque at higher gear selection. The rear axle load and fuel rate were found to be most affected by the combination of the tillage depth and gear selection combination. Overall, field test results show that the M3H had the highest fuel efficiency and a high working speed while overcoming high loads at the same tillage depth. In conclusion, M3H is the most suitable gear stage for plow cultivation, and the higher the gear stage and the deeper the tillage depth during plowing, the higher the fuel efficiency. The results of this study will be useful for analyzing mechanical load and fuel efficiency during farm operations. In a future study, we will conduct load analysis studies in other farming operations that consider various soil mechanics factors as well as tillage depths and gear selections.
Yeon-Soo Kim; Wan-Soo Kim; Seung-Yun Baek; Young-Joo Kim; Sang-Dae Lee. Analysis of Tillage Depth and Gear Selection for Mechanical Load and Fuel Efficiency of an Agricultural Tractor Using an Agricultural Field Measuring System. Sensors 2020, 20, 2450 .
AMA StyleYeon-Soo Kim, Wan-Soo Kim, Seung-Yun Baek, Young-Joo Kim, Sang-Dae Lee. Analysis of Tillage Depth and Gear Selection for Mechanical Load and Fuel Efficiency of an Agricultural Tractor Using an Agricultural Field Measuring System. Sensors. 2020; 20 (9):2450.
Chicago/Turabian StyleYeon-Soo Kim; Wan-Soo Kim; Seung-Yun Baek; Young-Joo Kim; Sang-Dae Lee. 2020. "Analysis of Tillage Depth and Gear Selection for Mechanical Load and Fuel Efficiency of an Agricultural Tractor Using an Agricultural Field Measuring System." Sensors 20, no. 9: 2450.