Method of estimating crop yields

• US 7,089,117 B2
• Filed: 11/22/2001
• Issued: 08/08/2006
• Est. Priority Date: 11/24/2000
• Status: Expired due to Term

• Current Assignee: Blue Leaf IP Incorporated (CNH Industrial N.V.)
• Original Assignee: CNH Industrial America LLC (CNH Industrial N.V.)
• Inventors: Maertens, Koen
• Primary Examiner(s): MCELHENY JR, DONALD E
• Application Number:
  US10/476,328
• Publication Number:
  US 20040194442A1
• Time in Patent Office: 1,720 Days
• Field of Search: 702/2, 702/5, 701/50
• US Class Current: 702/5
• CPC Class Codes: A01B 79/005 Precision agriculture
• CPC Class Codes: A01D 41/127 Control or measuring arrangements specially adapted for combines

Abstract

A method of estimating the instantaneous crop yield ŷ₂(t) at time t in a field, during harvesting with a harvesting machine that operates by cutting and/or controlling the crop and has a crop mass flow sensor that measures the mass flow rate of crop processed by the machine at a location remote from that at which the harvesting machine cuts the crop and generates a signal {dot over ({circumflex over (m)}_out(t) indicative thereof, including the steps of: generating a mass flow rate signal {dot over ({circumflex over (m)}_out(t) using the sensor;generating an area rate signal ŝ(t) indicative of time domain variations in the area of the field harvested per time unit;filtering the area rate signal ŝ(t) using a function P(s) representative of the dynamics of the harvesting machine to generate a filtered area rate signal ŝ₂(t); andusing the filtered area rate signal ŝ₂(t) for deriving from the mass flow rate signal {dot over ({circumflex over (m)}_out(t) a yield per area unit ŷ₂(t).

Claims

1. A method of estimating the instantaneous crop yield ŷ

₂(t) at time t in a field, during harvesting with a harvesting machine that operates by cutting and/or collecting the crop and has a crop mass flow sensor that measures the mass flow rate {dot over (m)}_out(t) of crop processed by the machine at a location remote from that at which the harvesting machine cuts the crop and generates a signal {dot over ({circumflex over (m)}_out(t) indicative thereof, the method comprising the steps of;

(i) generating a said mass flow rare signal {dot over ({circumflex over (m)}_out(t) using said mass flow sensor; and

(ii) generating an area rate signal ŝ

(t) indicative of time domain variations in the area of the field harvested per time unit;

characterized in that it comprises the further steps of;

(iii) filtering said area rate signal ŝ

(t) using a function P(s) representative of the dynamics of the harvesting machine to generate a filtered area rate signal ŝ

₂(t); and

(iv) using said filtered area rate signal ŝ

₂(t) for deriving from said mass flow rate signal in {dot over ({circumflex over (m)}_out(t) a yield per area unit ŷ

₂(t).

2. A method according to claim 1, characterized in that the instantaneous yield ŷ

₂(t) is estimated according to the expression;

${\hat{y}}_2<br><br>\left(t\right)=\frac{{\stackrel{\widehat{.}}{m}}_{\mathrm{out}}<br><br>\left(t\right)}{L^{-1}<br><br>\left(P<br><br>\left(s\right)<br><br>\hat{S}<br><br>\left(s\right)\right)}$

3. A method according to claim 1, characterized in that it includes the further step of (v) shifting the resulting estimated yield value ŷ

₂(t) by a time interval Δ

t representative of a delay between cutting and/or collecting of the crop by the harvesting machine and measurement of the mass flow rate by the crop mass flow sensor.

4. A method according to claim 3, characterized in that it includes the further step of (vi) mapping the time shifted crop yield values for a range of values of t whereby to obtain a yield map of a field or part thereof.

5. A method according to claim 3, characterized in that the steps (ii)–

(iv) are carried out in real time by a computer carried by or operatively connected to the harvesting machine.

6. A method according to claim 1, characterized in that it includes the step of (vii) recording a series of crop yield values in a memory.

7. A method according to claim 4, characterized in that it includes the step of (vii) recording a series of crop yield values in a memory, wherein the mapping step (vi) takes place offline from said computer using the crop yield values stored in said memory.

8. A method according to claim 1, characterized in that the function P(s) includes functions F₁(s), F₂(s) and F₃(s) that respectively model the dynamics of different subsystems in the forward path of crop via the harvesting machine.

9. A method according to claim 1, characterized in that it includes the further steps of:

(a) monitoring a machine condition;

(b) automatically adapting the function P(s) to a changing machine condition.

10. A method according to claim 9, characterized in that said machine condition is a machine setting.

11. A method according to claim 10, characterized in that said machine condition is chosen from threshing drum or cleaning fan speeds, concave setting or sieve setting.

12. A method according to claim 9, characterized in that said machine condition is a distribution of crop flow over the machine.

13. A method according to claim 12, characterized in that said monitoring step includes monitoring a crop flow at a particular location of the machine.

14. A method according to claim 12, characterized in that said machine condition is the ratio (ρ

) of a return crop flow to a full crop flow.

15. A method according to claim 9, characterized in that the sub-step of automatically adapting the function P(s) includes:

(c) filtering the area rate signal ŝ

(t) using a function that simulates the influence of the machine dynamics at zero return flow; and

, as necessary.

(d) simulating the influence of a return flow ratio ρ

.

16. A method according to claim 1, characterized in that the function P(s) includes a function R(s) that models the flow of incompletely processed crop, via a return path defined in the harvesting machine, for further processing.

17. A method according to claim 16, characterized in that the function R(s) is substantially non-dynamic.

18. A method according to claim 17, characterized in that it is carried out using a particular algebraic solution of R(s) that is based on a discrete approximation of the proportion of the crop in the harvesting machine that flows via said return path.

19. A method according to claim 1, characterized in that it includes the step of (viii) repeating the method a plurality of times at a sampling frequency of 1 Hz.

20. A method according to claim 1, characterized in that it includes the further steps of:

(ix) assessing whether variations in the flow of crop through the harvesting machine derive predominantly from time domain variations in the area of the field harvested at time t; and

(x) carrying out said method if the result of said assessment is affirmative.

21. A method of estimating the instantaneous crop yield in a field during harvesting using a harvesting machine that operates by cutting and/or collecting the crop and has a crop mass flow sensor that measures the mass flow rate {dot over (m)}_out(t) of crop passing through the harvesting machine and generates a signal {dot over ({circumflex over (m)}_out(t) indicative thereof, the method including the steps of:

(xi) assessing whether variations in the flow of crop through the harvesting machine derive predominantly from time domain variations in the field conditions; and

(xii) if the result of said assessment is affirmative, generating a said mass flow rate signal {dot over ({circumflex over (m)}_out(s) using said sensor, filtering said signal using a function P<sup>−

1</sup>(s) that models the inverse dynamics of the flow of crop through the harvesting machine and additionally filtering said signal using a function F(s) that is a low pass filter to generate an estimate ŷ

₁(t) of the instantaneous crop yield at time t.

22. A method according to claim 21, characterized in that ŷ

₁(t) is determined by the expression;

${\hat{y}}_1<br><br>\left(t\right)=\frac{L^{-1}<br><br>\left(P^{-1}<br><br>\left(s\right)<br><br>F<br><br>\left(s\right)<br><br>{\stackrel{\widehat{.}}{m}}_{\mathrm{out}}<br><br>\left(s\right)\right)}{\hat{s}<br><br>\left(t\right)}$

wherein ŝ

(t) is the measured field surface harvested at instant t.

23. A method according to claim 21, characterized in that the cut-off frequency of the low pass filter F(s) is 0.2 Hz.

24. A method according to claim 21, wherein if the result of said assessment is negative then the method includes the further step of shifting the resulting estimated yield value ŷ

₂(t) by a time interval Δ

t representative of a delay between cutting and/or collecting of the crop by the harvesting machine and measurement of the mass flow rate by the crop mass flow sensor.

27. A method according to claim 21, characterized in that if the result of said assessment is negative, that the method further comprises:

(i) generating a said mass flow rate signal {dot over ({circumflex over (m)}_out(t) using said mass flow sensor; and

(ii) generating an area rate signal ŝ

(t) indicative of time domain variations in the area of the field harvested per time unit;

characterized in that it comprises the further steps of;

(iii) filtering said area rate signal ŝ

(t) using a function P(s) representative of the dynamics of the harvesting machine to generate a filtered area rate signal ŝ

₂(t); and

(iv) using said filtered area rate signal ŝ

₂(t) for deriving from said mass flow rate signal {dot over ({circumflex over (m)}_out(t) a yield per area unit ŷ

₂(t).

25. A harvesting machine that operates by cutting and/or collecting crop and has a crop mass flow sensor that measures the mass flow rate of crop processed by the machine at a location remote from that at which the harvesting machine cuts and/or collects the crop, wherein a computer is programmed to carry out a method comprising the steps of:

(i) generating a said mass flow rate signal {dot over ({circumflex over (m)}_out(t) using said mass flow sensor; and

(ii) generating an area rate signal ŝ

(t) indicative of time domain variations in the area of the field harvested per time unit;

characterized in that it comprises the further steps of;

(iii) filtering said area rate signal ŝ

(t) using a function P(s) representative of the dynamics of the harvesting machine to generate a filtered area rate signal ŝ

₂(t); and

(iv) using said filtered area rate signal ŝ

₂(t) for deriving from said mass flow rate signal {dot over ({circumflex over (m)}_out(t) a yield per area unit ŷ

₂(t).

26. A harvesting machine that operates by cutting and/or collecting the crop and has a crop mass flow sensor that measures the mass flow rate of crop processed by the machine at a location remote from that at which the harvesting machine cuts the crop, wherein a computer is programmed to carry out a method including the steps of:

(i) assessing whether variations in the flow of crop through the harvesting machine derive predominantly from time domain variations in the field conditions; and

(ii) if the result of said assessment is affirmative, generating a said mass flow rate signal {dot over ({circumflex over (m)}_out(s) using said sensor, filtering said signal using a function P<sup>−

1</sup>(s) that models the inverse dynamics of the flow of crop through the harvesting machine and additionally filtering said signal using a function F(s) that is a low pass filter to generate an estimate ŷ

₁(t) of the instantaneous crop yield at time.