Method of estimating crop yields

• US 20040194442A1
• Filed: 05/05/2004
• Published: 10/07/2004
• Est. Priority Date: 11/24/2000
• Status: Active Grant

• Current Assignee: Blue Leaf IP Incorporated (CNH Industrial N.V.)
• Original Assignee: Blue Leaf IP Incorporated (CNH Industrial N.V.)
• Inventors: Maertens, Koen
• Granted Patent: US 7,089,117 B2
• Time in Patent Office: Days
• US Class Current: 56/10.20R
• 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

1-28. -28 (Canceled)

29. 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 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).

30. A method according to claim 29, characterized in that the instantaneous yield ŷ

₂(t) is estimated according to the expression;

31. A method according to claim 29, 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.

32. A method according to claim 31, 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.

33. A method according to claim 31, 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.

34. A method according to claim 29, characterized in that it includes the step of (vii) recording a series of crop yield values in a memory.

35. A method according to claim 32, 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.

36. A method according to claim 29, 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.

37. A method according to claim 29, 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.

38. A method according to claim 37, characterized in that said machine condition is a machine setting.

39. A method according to claim 38, characterized in that said machine condition is chosen from threshing drum or cleaning fan speeds, concave setting or sieve setting.

40. A method according to claim 37, characterized in that said machine condition is a distribution of crop flow over the machine.

41. A method according to claim 40, characterized in that said monitoring step includes monitoring a crop flow at a particular location of the machine.

42. A method according to claim 40, characterized in that said machine condition is the ratio (ρ

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

43. A method according to claim 37, 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

.

44. A method according to claim 29, 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.

45. A method according to claim 44, characterized in that the function R(s) is substantially non-dynamic.

46. A method according to claim 45, 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.

47. A method according to claim 29, characterized in that it includes the step of (viii) repeating the method a plurality of times at a sampling frequency of 1 Hz.

48. A method according to claim 29, 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.

49. 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;

(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; and

(xiii) if the result of said assessment is negative carrying out the method steps (i) to (iv) of the method according to claim 29.

50. A method according to claim 49, characterized in that ŷ

₁(t) is determined by the expression;

51. A method according to claim 49, characterized in that the cut-off frequency of the low pass filter F(s) is 0.2 Hz.

52. A method according to claim 49, characterized in that it includes carrying out the method steps of claim 31, if the result of said assessment is negative.

53. 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, characterized in that it includes a computer programmed to carry out the method steps (i) to (iv) of claim 29.

54. 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, characterized in that it includes a computer programmed to carry out the method of claim 49.