Recommended
More Related Content
Viewers also liked
Similar to Ismabプレゼン（緒方）5.20
Similar to Ismabプレゼン（緒方）5.20 (7)
Recently uploaded
Recently uploaded (20)
Ismabプレゼン（緒方）5.20
- 1. Accuracy evaluation of a method to compute the area of combine- harvested field sections Mao Ogata1, Yasumaru Hirai2*, Tsuneo Nakanishi3, Takeshi Shikanai4, Eiji Inoue2, Takashi Okayasu2, Muneshi Mitsuoka2 1Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Japan 2Faculty of Agriculture, Kyushu University, Japan 3Department of Electronics Engineering and Computer Science, Fukuoka University, Japan 4Faculty of Agriculture, University of Ryukyus, Japan The 8th International Symposium on Machinery and Mechatronics for Agriculture and Biosystems Engineering at TOKI MESSE Niigata Convention Center on 23-25 May 2016, Niigata, Japan
- 3. What is this? Combine-movement traces
- 4. Combine movement traces have 2-important data Where? When? Grain elevator
- 5. informative data collected at GEs are not available Grain elevator Truckload of grain Harvested field location? Time of grain reception? ・Weight rates of brown rice and poorly ripened grain ・Estimated weight of brown rice ・Grain moisture content ・rough rice weight ・・・ Background
- 6. informative data collected at GEs are not available Background Section Harvest Area is useful for estimating mean brown rice yield Mean brown rice yield Brown rice weight Section harvest area (SHA)
- 7. Evaluation of the method to compute section harvest area Objective of study Movement traces SHA
- 8. Material & Methods GPS receiver recorded combine-movement traces Duration: October 10 to November 9, 2013 Data interval: 1 second ARN698 (KUBOTA Corporation) CD311 (CORE Corporation) 0.9 m in circular error possibility Combine 15cm
- 9. 0 10 20 30 40 0 1000 2000 3000 4000 5000 NumberofSHAs Area of SHA(m2 ) n =94 Mean: 1583 m2 Material & Methods Number of SHAs was 94 and Mean was 1583 m2 Surveyed SHAs in 59 fields
- 10. Material & Methods Calculation for SHA requires movement traces at the left and right edges of combine header GPS receiver y x O 進行方向 αt Ll Lr (xrt,yrt) (xlt,ylt) (xt-1,yt-1) (xt,yt) Ll: 165 cm Lr: 15 cm B: 135 cm B 𝑥 𝑟𝑡 = 𝑥𝑡 + 𝐿 𝑟cos(𝛼 𝑡 − 𝜋 2 ) + 𝐵𝑐𝑜𝑠𝛼 𝑡 𝑦 𝑟𝑡 = 𝑦𝑡 + 𝐿 𝑟sin(𝛼 𝑡 − 𝜋 2 ) + 𝐵𝑠𝑖𝑛𝛼 𝑡 𝑥𝑙𝑡 = 𝑥𝑡 + 𝐿𝑙cos(𝛼 𝑡 + 𝜋 2 ) + 𝐵𝑐𝑜𝑠𝛼 𝑡 𝑦𝑙𝑡 = 𝑦𝑡 + 𝐿𝑙sin(𝛼 𝑡 + 𝜋 2 ) + 𝐵𝑠𝑖𝑛𝛼 𝑡
- 11. Material & Methods The traversed cell by combine is harvested cell 0.05 m 0.05 m 0.05 m Movement traces in a target field Movement trace Traversed cell
- 12. Material & Methods Harvested area is calculated from combine header traversed cells in 1-second (a) Movement traces (a) (a) Traversed area Rt Lt -1 Rt -1 Lt Combine header
- 13. Material & Methods Locations where rice is not transplanted make untraversed gaps Untraversed gap:1 Untraversed gap:2 Truckload 1 Truckload 2 Truckload 3
- 14. Material & Methods 0 1 0 0 2 2 2 0 3 0 0 0 0 0 0 0 2 0 0 0 3 0 4 0 0 5 0 0 0 0 0 0 3 0 0 6 0 5 5 5 0 7 0 8 0 0 9 0 0 0 5 0 10 0 0 0 0 11 0 0 0 0 0 0 0 0 0 12 12 0 0 13 0 0 14 0 0 0 0 0 12 0 0 0 0 0 14 14 14 14 14 14 0 0 15 0 0 1 0 0 2 2 2 0 3 0 0 0 0 0 0 0 2 0 0 0 3 0 4 0 0 5 0 0 0 0 0 0 3 0 0 6 0 5 5 5 0 7 0 8 0 0 9 0 0 0 5 0 10 0 0 0 0 11 0 0 0 0 0 0 0 0 0 12 12 0 0 13 0 0 14 0 0 0 0 0 12 0 0 0 0 0 14 14 14 14 14 14 0 0 15 0 Traversed cell Untraversed cell Connected Component Labeling extracts untraversed gaps
- 15. Material & Methods By referring surrounding traversed cells, untraversed gap is allocated Truckload 1 Truckload 2 Truckload 3 Truckload 1 > Truckload 2
- 16. Results & Discussion 0 5 10 15 20 25 30 -25 -20 -15 -10 -5 0 5 10 15 20-25 10-15 -10 -5 0 520 15 ~~ n = 94 Relative error (% ) NumberofSHAs SHA involves ±5 %, ±10 % relative error in 64 %, 85 % of all calculations
- 17. Results & Discussion Inaccurately allocated gaps increased relative errors of SHAs Truckload 1 Truckload 2 Truckload 3 Truckload 4 234 m2 Temporary SHA(m2) SHA(m2) True value(m2) Relative error(%) 768 775 1067 -27.4 881 1250 1250 12.8
- 18. Objective of study Evaluation of the method to compute section harvest area ±5 % relative error :64 % ±10 % relative error: 85 % Accuracy Conclusion The accuracy of computing SHAs will increase by Improving precision in allocation of the untraversed gaps Untraversed gap
Editor's Notes
- Hello, everyone. My name is Mao Ogata. I am studying in Kyushu University. My study will make available the multidimensional grain data collected at grain elevator.
- I know this is sudden, what is this? These 2 pictures are related to this one (movement traces). 少し間をおいて This is combine-movement traces in harvesting. The movement traces have 2-important information.
- One is the location of harvested field. The other one is the time of grain reception at Grain elevator. Farmers harvest the fields and take the harvested grain to GE when truckload becomes full. GEs collect multidimensional informative data.
- What are informative data? I will show you right now. In Japan, GEs collect these informative data in each truckload, such as weight rates of brown rice and poorly ripened grain, estimated weight of brown rice, grain moisture content and rough rice weight. However, these grain data are not related to the harvested field and time of grain reception at GEs. Thus, these informative grain data are not available.
- Do you remember that combine-movement traces contain the information, such as, the location of harvested fields and the time of grain reception. Movement traces make the informative grain data collected at GEs available. For example, Brown rice yield is divided by the area of these movement traces, we can get mean brown rice yield. The area of combine movement traces means Section Harvest Area (SHA) in this study. Of course, there is such kind of SHA which consist of the movement traces in completely harvested field.
- So then, the objective of this study is to evaluate the method developed to compute section harvest area (SHA) from combine-movement traces.
- We mounted GPS receiver on the combine cabin roof. We exploited this GPS receiver to record the combine-movement traces in harvesting. The nominal accuracy of this GPS receiver was 0.9 m in circular error possibility. The Experiment duration was from October 10 to November 9, 2013. The movement traces was measured at 1-second intervals.
- We surveyed SHAs in 59 fields, but the number of SHAs was 94. This is because when truckload becomes full, farmers stop harvesting and take the harvested grain to GEs, although harvesting in the field is still halfway. Here is the histogram of surveyed SHAs. The mean of this was 1583 m2.
- We assumed the SHA, namely, combine-harvested area is the same to the area traversed by a combine header. Thus, we calculate the movement traces at the left and right edges of a combine header. We applied these formulas for the calculation based on the movement traces at the GPS receiver mounted position.
- From this slide, I will show you a flow of computing SHAs. This is target field contain 3 SHAs. These SHAs are related to truckload numbers, from 1 to 3. At first, we put the grid area. (Animation) This grid area covers the all movement traces in this target field. It consists of 0.05 m square cells. When a cell includes the movement trace, this cell is regarded as traversed cell. The sum of the traversed cells means harvested area, in other words, temporary SHA.
- The traversed cells are judged from the movement traces at the left and right edges of combine header at 1-second intervals.
- Do you remember the sum of traversed cells means temporary SHA? There are some gaps which are not transplanted. The cells in the gaps have no movement trace, such as, untraversed gap1 and 2, we assumed that SHA should include these untraversed gaps. To add the area of untraversed gaps, at first, we need extract them.
- We applied the Connected Component Labeling to extract the untraversed gaps. This method judges the continuously connected cells by referring surrounding cells in these 4 directions and labels the same number, except for the traversed cells. For other continuously connected cells, this method labels different numbers. As a result, the method extracted the all of cells in each untraversed gap. Finally, we allocated the untraversed gaps to temporary SHAs.
- By referring the number of surrounding traversed cells in this quadrangle, we decided to the target SHA for the allocation. In this case, the number of cells in truckload 1 is larger, so this untraversed gap was allocated to the SHA corresponding to truckload 1. The flow of computing SHA is finished. I will talk about results.
- This is a histogram of relative errors of SHA. The relative errors ranged from -27.4 to 17.1 %. SHAs involved ±5 % and ±10 % relative errors in 64 % and 85 % of all calculation, respectively. Most cases of beyond ±10 % relative error were observed in the field which consist of more than 2 SHAs. I will show you the example.
- Like this. This field consists of 4 SHAs related to each truckload, from 1 to 4. In this case, SHA in truckload 2 was underestimated and in truckload 4 was overestimated. (Animation) This untraversed gap was allocated to the SHA in truckload 4. This untraversed gap should be allocated to the SHA in truckload 2 or 3 theoretically, but this quadrangle contained the cells of all SHAs and out of field. Besides, in this quadrangle, the number of cells in truckload 4 was the largest and this untraversed gap was allocated to inappropriate SHA. Therefore, it is clear that misjudgement in the allocation made bud influence to the accuracy of computing SHAs.
- The objective of this study was to evaluate the method to compute SHA. The accuracy of the computing was like this. The cases of ± 5 % relative error was 64 % and ± 10 % relative error was 85 % in all of calculation, 94 cases. On the other hand, some untraversed gaps were allocated to inappropriate SHA. Therefore, we concluded the accuracy of computing SHAs will increase by modifying the algorism of the allocation.