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Equipment Limitations and Challenges in Precision N Management

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Presentation on theme: "Equipment Limitations and Challenges in Precision N Management"— Presentation transcript:

1 Equipment Limitations and Challenges in Precision N Management
R.K. Taylor, G. Dilawari, P. Bennur, J.B. Solie, N. Wang, P. Weckler, and W.R. Raun

2 Variable Rate Liquid Applicators
Direct Injection Complex Time lag Fixed orifice nozzles Flow proportional to square root of pressure Difficult to achieve range in flow rates Pulse Width Modulation Variable orifice nozzles Pressure/Flow relationship is more complex

3 Objective To determine the consistency among nozzles and repeatability of individual nozzles with respect to flow rate for commercially available variable orifice nozzles

4 Materials Nozzles: Eight of each type
TurboDrop Nozzles (GreenLeaf technologies): TDVR-02 and TDVR-03 VeriTarget Nozzles (SprayTarget )

5 Test Stand Pump Wet boom equipped with TeeJet 3 nozzle bodies
Pressure relief valve Throttling valve

6 Methodology Three nozzles were selected randomly and tested on the three nozzle boom at 20, 30, 40, 50, 60 and 80 psi 8 repetitions for each pressure Flow was adjusted to the three nozzles to achieve the desired pressure. Outflow from nozzles was calculated by measuring the volume of water collected from each nozzle over a period of 30 seconds.

7 Data analysis Analysis of Variance was performed in SAS 9.1 (SAS, Cary, NC) using PROC ANOVA to detect flow differences among nozzles. Data for each nozzle were analyzed by pressure Means were separated using the LSD option and at 0.01 level of significance Pressure-flow curves for each nozzle type were plotted and compared with the manufacturer’s pressure-flow data.

8 Results: TDVR-02 Pressure (psi) Mean (gpm) Min (gpm) Max (gpm)
Range (gpm) CV (%) 20 0.17 0.15 0.19 0.04 9.56 30 0.20 0.18 0.23 0.05 8.88 40 0.27 0.07 9.44 50 0.33 0.32 0.37 4.68 60 0.44 0.43 0.46 0.03 2.46 80 0.60 0.57 0.63 0.06 2.59

9 Results: TDVR-02

10 Results: TDVR-03 Pressure (psi) Mean (gpm) Min (gpm) Max (gpm)
Range (gpm) CV (%) 20 0.24 0.22 0.35 0.13 19.35 30 0.31 0.27 0.37 0.10 10.89 40 0.33 0.38 0.07 8.74 50 0.45 0.42 0.47 0.05 3.20 60 0.58 0.56 0.60 0.04 2.04 80 0.78 0.75 0.87 0.12 5.31

11 Results: TDVR-03

12 Results: VeriTarget Pressure (psi) Mean (gpm) Min (gpm) Max (gpm)
Range (gpm) CV (%) 20 0.17 0.16 0.22 0.06 12.34 30 0.42 0.37 0.48 0.11 7.18 40 0.81 0.76 0.89 0.13 6.65 50 1.00 0.96 1.04 0.08 2.96 60 1.12 1.10 1.16 2.32 80 1.32 1.29 1.35 1.51

13 Results: VeriTarget

14 Conclusions Inconsistent behavior was observed between the nozzles at different pressures Repeatability of a nozzle was better at pressures above 40 psi. Both the TurboDrop nozzles performed according to manufacturer’s specification CV for VeriTarget nozzles, for most of the nozzles, was around 10% which is acceptable for spraying

15 Sensor v. Map Based VRA In a map based system, the controller receives a rate change as the applicator crosses into a new zone. However, with a sensor based system the controller typically receives an updated rate every second and does not have the opportunity to stabilize.

16 Sensor Configurations

17 Accepted Resolution

18 Materials Raven 440 controller Raven Fast Close valve
Data acquisition with flow meter and pressure transducers

19 Test Stand Schematic

20 Model 1st order valve response Proportional Integral controller

21 Input Data pass Obs Mean Minimum Maximum Std dev Max rate increase
decrease - L ha-1 - 1 162 168.4 121.4 205.8 19.6 42.8 -50.6 2 162.1 18.2 58.1 -27.5 3 149 179.6 134.5 17.4 50.3 -58.6 4 150 175.7 120.1 44.0 -47.2 5 175 168.2 118.3 24.4 34.9 -44.8 6 183 165.0 22.3 44.8 -36.8 7 88 175.8 19.5 58.6 -83.6 8 85 167.8 102.9 23.8 80.1 -53.3

22 Prescribed Rate

23 Model Output

24 1 second lag

25 Output Data pass 0 sec lag 1 sec lag r2 slope Mean abs error, L ha-1 1
0.45 0.78 11.6 0.74 1.00 6.0 2 0.76 11.5 0.87 1.04 4.8 3 0.35 0.67 12.8 0.84 1.03 6.1 4 14.7 7.0 5 0.93 1.02 5.1 6 0.62 0.85 7 0.26 0.61 1.11 6.9 8 0.24 0.58 18.6 0.83 1.08 11.2

26 Conclusions The modeled results showed a mean absolute application error of 12.9 L ha-1. These results further indicate that the predicted response lagged the prescribed rate by approximately 1 second. This resulting misapplication could be reduced by half if the controller delay was reduced by 1 second.

27 Addendum

28 Improved System ??

29 Questions Randy Taylor


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