Cooking by utilizing a cluster analysis and cooking utensils therefor

• US 20060112833A1
• Filed: 01/07/2004
• Published: 06/01/2006
• Est. Priority Date: 01/09/2003
• Status: Abandoned Application

• Current Assignee: Rational AG
• Original Assignee: Rational AG
• Inventors: Blaschke, Gunter
• Application Number:
  US10/541,816
• Publication Number:
  US 20060112833A1
• Time in Patent Office: Days
• US Class Current: 99/325
• CPC Class Codes: F24C 7/08 Arrangement or mounting of control or safety devices
• CPC Class Codes: G05B 21/02 electric

Abstract

The invention relates to a method for cooking items that are to be cooked in a cooking chamber of a cooking utensil comprising a control and/or regulating mechanism which has access to primary, chronologically arranged measured data and secondary measured data of a state variable regarding at least one item that is to be cooked and/or a state variable regarding a cooking utensil, said secondary measured data not being chronologically arranged. The cooking process is carried out in the following steps according to said state variable/s: an actual cooking curve of the measured data Z, of the item (i) that is to be cooked is detected up to a specific point in time t<SB>M</SB> before the final cooking point t<SB>E</SB> is reached; the detected actual cooking curve Z_i is associated with a representative cooking profile X_n that is determined via a cluster analysis; and the cooking process is carried out according to the determined representative cooking profile X_n, wherein i and n∈|N. Also disclosed is a cooking utensil comprising a cooking chamber for receiving items that are to be cooked, a measuring device for detecting measuring data, a device for storing measured data and variables that are determined therefrom, and a control and/or regulating mechanism for directing the cooking process according to the inventive method.

Claims

1. Method for cooking of items in a cooking chamber of a cooking apparatus with a control or regulation device, which has access to primary measured data arranged in time as well as to secondary measured data which are not arranged in time, of at least one state variable of an item to be cooked or of the cooking apparatus, the method comprising:

acquiring an actual course of a cooking process of the measured data Z_i of the item to be cooked i up to a predefined time t_M before a cooking completion time t_E,

assigning the acquired actual course of cooking process Z_i to a representative cooking profile X_n determined through cluster analysis, where the cluster analysis includes standardization of the actual cooking courses or making them comparable, and

guiding the cooking process as a function of the determined representative cooking profile X_n, where i and n∈

|N.

2. Method according to claim 1, wherein the cluster analysis includes at least one of a regression analysis, or a similarity comparison, or a coefficient comparison, or a formation of a range, or an interpolation or an extrapolation.

3. Method according to claim 1, wherein the actual cooking courses are standardized or made comparable, by determining an accumulated percentage Y_i from the 100% end value of the measured data Z_i at the cooking completion time t_E as a function of time t_j with j∈

|N, where the 100% end value is defined as a target quantity Z_i(t_E) at the cooking completion time t_E.

4. Method according to claim 3, wherein the target quantity Z_i(t_E) is adjusted or taken from a stored representative cooking profile X_n.

5. Method according to claim 1, wherein the cluster analysis includes classifying actual courses of the cooking process made comparable, including,

determining the sums of the squares of a distance A_il to the end time of cooking t_E with l∈

|N, where

$A_{\mathrm{il}}<br><br>\left(t_E\right)=\underset{j=0}{\overset{E}{\sum <br><br>}}<br><br>{\left(Y_i<br><br>\left(t_j\right)-Y_i<br><br>\left(t_j\right)\right)}^2,$

determining a number N of classes K_n with n={1, 2 . . . N}, and

defining each class K_n through a single or a respective maximum value of the sum of the squares of the distance A_ii(t_E).

6. Method according to claim 5, wherein the cluster analysis includes the assignment of a representative cooking profile X_n(t_j) to each class K_n.

7. Method according to claim 6, wherein the assignment of an actual course of the cooking process Z_i to a representative cooking profile X_n(t_j) of a class K_n includes:

determining a value of deviation S_in(t_M) for each class K_n within a time interval t_M, where

$S_{\mathrm{in}}<br><br>\left(t_M\right)=\underset{j=0}{\overset{M}{\sum <br><br>}}<br><br>{\left(\left(\frac{Y_i<br><br>\left(t_j\right)}{X_n<br><br>\left(t_j\right)}\right)-\left(\frac{Y_i<br><br>\left(t_{j+1}\right)}{X_n<br><br>\left(t_{j+1}\right)}\right)\right)}^2<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{with}<br><br>\text{\hspace{1em}<br><br>}<br><br>X_n><br><br>0,\mathrm{and}$

obtaining the value of deviation S_in(t_M) with the value of the smallest magnitude for the percentage Y_i(t_M) at time t_M.

8. Method according to claim 1, wherein the guiding of the cooking process includes predicting measured data Z_i(t_E) at an end of cooking time t_E through the determined representative cooking profile X_n(t_j).

9. Method according to claim 8, wherein predicting includes:

assigning the accumulated percentages Y_i(t_j) to a class K_n and thus to a representative cooking profile X_n(t_j),

obtaining a multiplier P_in at time t_M where

$P_{\mathrm{in}}=\frac{Z_i<br><br>\left(t_M\right)}{X_n<br><br>\left(t_M\right)},\text{\hspace{1em}<br><br>}<br><br>\mathrm{where}<br><br>\text{\hspace{1em}<br><br>}<br><br>X_n><br><br>0<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{and}$

extrapolating by multiplication of the end value X_n(t_E) of the representative cooking profile with the multiplier P_in, where

X_n(t_E)P_in=Z_i(t_E)

10. Method according to claim 1, wherein a state variable of the item to be cooked obtained from the primary measured data includes one or more of the weight loss of the item to be cooked, the core temperature of the item to be cooked, the diameter of the item to be cooked, the density of the item to be cooked, the type of item to be cooked, the degree of ripeness of the item to be cooked, the pH value of the item to be cooked, the consistency of the item to be cooked, the state of storage of the item to be cooked, the odor of the item to be cooked, the taste of the item to be cooked, the quality of the item to be cooked, the browning of the item to be cooked, the crust formation of the item to be cooked, the vitamin degradation of the item to be cooked, the formation of carcinogenic substances in the item to be cooked, the hygiene of the item to be cooked, the water activity of the item to be cooked, the moisture content of the item to be cooked, the protein content of the item to be cooked, or the thermal conductivity of the item to be cooked.

11. Method according to claim 1, wherein a cooking apparatus state variable determined from the primary measured data includes one or more of the temperature in the cooking chamber, or the moisture in the cooking chamber or the air movement rate in the cooking chamber.

12. Method according to claim 1, including determining, as secondary measured data, at least one apparatus input by a user.

13. Method according to claim 1, wherein each measured actual course of the cooking process Z_i, each determined accumulated percentage Y_i or each determined representative cooking profile X_n is stored in a memory device, automatically or optionally.

18. Method according to claim 1, wherein the cluster analysis includes classifying actual cooking courses made comparable.

19. Method according to claim 1 wherein the cluster analysis includes a standardization of actual courses of the cooking process or making them comparable by determining an accumulated percentage Y_i from the 100% end value of the measured data Z_i(t_E) at the cooking completion time t_E as a function of time t_j with j∈

|N.

20. Method according to claim 6, wherein a representative cooking profile X_n(t_j) is determined by calculating a mean value or a centroid of the accumulated percentages Y_i(t_j) per class K_n or the representative cooking profile X_n(t_j) is recalled from a memory device.

21. Method according to claim 12, wherein the at least one apparatus input by a user includes the selection of a cooking program or a state variable of an item to be cooked at the end of the cooking, time or a state variable of the cooking apparatus at the end time of cooking time.

22. Method according to claim 12, wherein the external factor includes one or more of a date, or a time, or a season, or a weather or a geographical location.

14. Cooking apparatus with a cooking chamber for holding an item to be cooked, comprising:

a measuring device for determining measured data,

a memory device for storing measured data and quantities determined from the measured data, and

a control or regulation device for guiding a cooking process by,

acquiring an actual course of a cooking process of measured data of the item to be cooked up to a predefined time before a cooking completion time,

assigning the acquired actual course of the cooking process to a representative cooking profile determined through cluster analysis, and

guiding the cooking process as a function of the determined representative cooking profile.

15. Cooking apparatus according to claim 14, wherein the measuring device and the control or regulation device are constructed as one.

16. Cooking apparatus according to claim 15, wherein the memory device is integrated with the measuring device and the control or regulation device.

17. Cooking apparatus according to claim 16, wherein the memory device, the measuring device and the control or regulation device are integrated in a cooking process sensor.