Development of a novel mechatronic system for mechanical weed ...

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Materials and methods 34 � Since detection is based on RGB components, it is less affected by target position and vibration. Several sensors were tested, and the CZ – H35S optical sensor head and the CZ – V21P digital fibre optic amplifier from Keyence Company have been chosen as most appropriate according to the requirements. The CZ – V21P digital fibre optic amplifier supports three different detection modes based on the combination of colour component detection and light intensity. The control interface built in to the amplifier allows the user to choose the optimal detection mode and to set up a matching rate corresponding between the calibrated target colour, as a reference, and the target colour currently being detected. The amplifier consists of four digital physical channels which can be separately calibrated with ad-hock autocalibration in few steps. Depending on the intensity and position of the illumination, some parts of the target objects can appear white as a consequence of lustre. The CZ-H35S sensor head incorporates a polarizing filter which cancels the reflection from the glossy section and only recognises targets by their colour components. Thus the CZ-H35S sensor head maintains accurate detection despite changing target conditions. Detecting range of the CZ-H35S sensor head is between 28 mm and 52 mm, with a spot diameter of 4.5 mm. The response time of the amplifier depending on the chosen detection mode lies between 200 µs and 8 ms. The sensor head and amplifier are illustrated in Figure 4.1.
Materials and methods Figure 4.1 a) RGB fibre optic sensor CZ-H35S and RGB digital fibre optic amplifier CZ – V21P b) RGB fibre optic sensor in working position with illustrated optimal detection range and spot diameter of the light source 4.1.1.2 Digital laser sensor To increase the reliability of the plant detection, the information about the objects appearing along the row line, their height and reflectance were tracked. The fact, that plants as objects are higher than the level of the soil surface, exceptions can appear only immediately after emerging when plants can have the same size as soil clumps, induced the use of additional support information for plant detection. High accuracy, area covering and short response time were the main requirements which affected the sensor selection. A hi-power definite-reflective area selection laser sensor head LV – H47 with appropriate LV- 21AP amplifier from Keyence Company, fulfilled the requirements and it was implemented in the plant detection unit. This type of sensor can be used for stable detection of the objects, even when targets have variations in shape or surface condition, which is one of the main characteristics of the plant detection. With definite-reflective type detection, the LV-H47 can ignore any influence of background conditions. Using a high-speed A/D converter, the LV-21AP amplifier substantially improves upon conventional 35
Page 1 and 2: Institut für Landtechnik der Rhein
Page 3 and 4: Development of a novel mechatronic
Page 5 and 6: Kurzfassung Entwicklung eines neuar
Page 7 and 8: Acknowledgements Acknowledgements M
Page 9 and 10: Table of contents Table of contents
Page 11 and 12: Glossary of abbreviations and symbo
Page 13 and 14: Symbol Unit Description Mmmax Nm Ma
Page 15 and 16: Symbol Unit Description Glossary of
Page 17: ωold ωout rad s -2 Latest rotatio
Page 20 and 21: Introduction The most frequently us
Page 22 and 23: Introduction application that had p
Page 24 and 25: Introduction be to go from a system
Page 26 and 27: Introduction limited and environmen
Page 28 and 29: Introduction than 40 years before g
Page 30 and 31: Introduction techniques. It is know
Page 32 and 33: Introduction Sowing and planting al
Page 34 and 35: Introduction Inter-row weeding syst
Page 36 and 37: Introduction 18 Figure 1.3 Inter-ro
Page 38 and 39: State of the art 20 Figure 2.1 a) F
Page 40 and 41: State of the art cylinder rotates a
Page 42 and 43: State of the art 1998). This device
Page 44 and 45: State of the art 26 2.2 Detection o
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Page 48 and 49: Definition of the problem and resea
Page 51: 4 Materials and methods 4.1 Detecti
Page 55 and 56: Materials and methods Figure 4.3 a)
Page 57 and 58: 4.1.2 Data acquisition 4.1.2.1 Hard
Page 59 and 60: 4.1.4 Test objects Materials and me
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Page 73: Materials and methods Another tool
Page 76 and 77: Results and discussion 58 Figure 5.
Page 82 and 83: Results and discussion objects. Acc
Page 84 and 85: Results and discussion Plant positi
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Results and discussion 84 5.2.4 Sel
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Results and discussion 86 5.2.5 Dis
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Results and discussion Conventional
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Results and discussion Since the fi
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Results and discussion To avoid con
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Results and discussion As the size
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Results and discussion 96 5.3.4 Alg
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Results and discussion 98 V = zc( t
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Results and discussion corresponds
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Results and discussion 102 5.3.6 Me
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Results and discussion hoeing accur
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Results and discussion between the
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Results and discussion distance fro
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Results and discussion Distribution
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Results and discussion cuts are ran
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Results and discussion Forward spee
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Results and discussion x [mm] Distr
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Results and discussion The experime
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6 Summary Summary Neither a mechani
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Summary The third part of the work
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7 Conclusions Conclusions The prese
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8 References References Agrios, G.
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References in California's Sacramen
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References Johnson, W C and Mullini
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References Schans, D. v. d. et al.
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List of figures List of figures Fig
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List of figures Figure 5.24 Scheme
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Plant position 9 Appendix Table 9.1
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Plant position Table 9.3 Detection
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Personal data Education About the a
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