CN110507209B - Intelligent cooking method and intelligent cooking appliance with probe - Google Patents

Intelligent cooking method and intelligent cooking appliance with probe Download PDF

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CN110507209B
CN110507209B CN201910803153.2A CN201910803153A CN110507209B CN 110507209 B CN110507209 B CN 110507209B CN 201910803153 A CN201910803153 A CN 201910803153A CN 110507209 B CN110507209 B CN 110507209B
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food
temperature
moisture content
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CN110507209A (en
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陶敏
黄育楷
陈霞
蒋伟
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Whirlpool China Co Ltd
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    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47J—KITCHEN EQUIPMENT; COFFEE MILLS; SPICE MILLS; APPARATUS FOR MAKING BEVERAGES
    • A47J36/00—Parts, details or accessories of cooking-vessels
    • A47J36/32—Time-controlled igniting mechanisms or alarm devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K7/00—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements
    • G01K7/16—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using resistive elements
    • G01K7/22—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using resistive elements the element being a non-linear resistance, e.g. thermistor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
    • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
    • G01N27/048—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance for determining moisture content of the material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
    • G01N27/22—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
    • G01N27/223—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance for determining moisture content, e.g. humidity

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Abstract

The invention discloses an intelligent cooking method and an intelligent cooking appliance with a probe, wherein the probe is used for acquiring the resistance, the capacitance and the reactance of food, estimating the internal temperature and the moisture content of the food, judging the food category of the food and the subdivision category of the food, calculating the food maturity of the food, controlling the cooking condition and the cooking time of the food, and the intelligent cooking appliance has the advantages of accurate measurement, high efficiency and no safety risk, can simultaneously measure a plurality of foods and realizes accurate cooking.

Description

Intelligent cooking method and intelligent cooking appliance with probe
Technical Field
The invention relates to the technical field of intelligent control, in particular to an intelligent cooking method and an intelligent cooking appliance with a probe.
Background
Food will obtain good culinary art effect, and cooking utensil often needs the accurate parameter that sets up including culinary art mode, temperature, time, power, and intelligent cooking utensil utilizes intelligent control method, reduces the parameter quantity that needs set up effectively, and convenience of customers operates, lets the culinary art become simpler.
In the prior art, the intelligent cooking mainly calculates the moisture content in food through the change of the microwave propagation speed and the intensity in the process of microwave penetration of the food, so as to control the cooking condition, but the microwave can be shielded by metal, safety risks such as ignition exist in the microwave environment, and the cooking of single food cannot be accurately controlled.
Disclosure of Invention
In order to solve the technical problems, the invention provides an intelligent cooking method and an intelligent cooking appliance with a probe, which can control the cooking conditions and the cooking time of food through the temperature and the moisture content in the food obtained in real time, have accurate measurement, high efficiency and no safety risk, can simultaneously measure a plurality of foods and realize accurate cooking.
In order to solve the technical problems, the invention adopts the following technical scheme:
an intelligent cooking method realizes intelligent cooking of food through electric parameters of the food obtained by a detection device, and comprises the following steps:
1) inserting a detection device into food, and estimating the temperature T and the moisture content M inside the food through the resistance R, the capacitance C and the impedance Z of the food obtained by the detection device in real time;
2) at t0Obtaining the initial resistance R of food at any moment0Initial capacitance C0And impedance Z0And a calibrated reference impedance value Z0' make a comparison if Z0<Z0', stop cooking, if Z0≥Z0' if yes, the operation is continued until the time point t1Wherein t is1＝t0+(5s～30s)；
3) By calculating t0～t1Average temperature of the interior of the food over a period of time
Figure BDA0002182890310000011
Average value of moisture content
Figure BDA0002182890310000012
Temperature rate of change Δ T1And rate of change of moisture content Δ M1Judging the food category and continuing to operate to the time point t2Wherein t is2＝t1+(1min～5min)；
4) By calculating t0～t2Average temperature of the interior of the food over a period of time
Figure BDA0002182890310000013
Average value of moisture content
Figure BDA0002182890310000014
Temperature rate of change Δ T2And rate of change of moisture content Δ M2Judging the kind of food and the time t3And continues to run to t3Wherein t is3＝t2+(1min～5min)；
5) Calculating t0～t3Rate of change of temperature Δ T of the interior of the food over a period of time3And rate of change of moisture content Δ M3And the calibrated food reference temperature change rate delta T3' and food reference moisture content Δ M3' comparison, if Δ M3< ΔM3' and Δ T3<ΔT3', stop cooking; if the delta M3 is more than or equal to the delta M3 'or the delta T3 is more than or equal to the delta T3', the cooking is continued to the set time point T4Wherein t is4＝t3+(2min～8min)；
6) From t4Starting at a moment by calculating the temperature T inside the food4And moisture content M4Obtaining the food maturity D1And a calibrated food reference maturity D1' comparison, if D1<D1If yes, continuing to cook; if D is1≥D1', the cooking is stopped.
Further, the temperature T, the moisture content M, the resistance R, the capacitance C, and the impedance Z inside the food in step 1 have the following relationship:
T＝f1(R,Z)＝1/[B*ln(R/RN)]，M＝f2(C,Z)＝-42+3.81C-7.5Z+0.05C2+0.26Z2；
where B is the thermal index of the probe and RN is the resistance of the probe at 25 deg.C.
Further, when the detection device measures the resistance inside the food, the resistance set A ═ { R ═ R at different depths will be measureda，Rb，Rc，...，RnWhen the detection device measures the capacitance inside the food, the capacitance set B ═ C at different depths is measureda，Cb，Cc，...，CnWhen the detection device measures the impedance inside the food, the impedance set E ═ Z at different depths is measureda，Zb，Zc，...，ZnAnd byf1(R, Z) and f2(C, Z) obtaining a set of temperature values H ═ T at different depths within the food1a，T1b，T1c，…，T1nAnd moisture content set I ═ M1a，M1b，…，M1nAnd taking the arithmetic mean value of each element in the set H as the temperature T inside the food, and taking the arithmetic mean value of each element in the set I as the moisture content M inside the food.
Further, the reference impedance value Z in step 20' is a critical impedance value of the intelligent cooking method capable of cooking food, after the food is measured, if the impedance value is less than Z0If yes, the intelligent cooking method cannot cook; when the operation is judged to be continued, the parameter set PS is operated1Said parameter set PS1The cooking area is closed to provide full power output.
Further, in step 3, the electrical parameters of the food are measured by the detecting device every 100ms, and t is calculated0～t1Average temperature over time
Figure BDA0002182890310000021
Average value of moisture content
Figure BDA0002182890310000022
t0Time t1Rate of change of temperature Δ T at time1And rate of change of moisture content Δ M1When judging the food category, averaging the temperature
Figure BDA0002182890310000023
Average value of moisture content
Figure BDA0002182890310000024
Temperature rate of change Δ T1、Moisture content change rate Δ M1Comparing with the calibrated food database to obtain the food category of the food in the cooking area, and operating the parameter set PS corresponding to the food category2(ii) a If the food is meat in general, the parameter set PS2Closing the cooking areaProviding full power output, increasing the cooking zone temperature to 200 ℃ and t2＝t1+3 min; if the food category is bread, the parameter set PS2Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 180 ℃ and t2＝t1+4min。
Further, in step 4, the electrical parameters of the food are measured by the detecting device every 100ms, and t is calculated0～t2Average temperature over time
Figure BDA0002182890310000031
Average value of moisture content
Figure BDA0002182890310000032
t0Time t2Rate of change of temperature Δ T at time2And rate of change of moisture content Δ M2When the food is classified finely, the average temperature value is calculated
Figure BDA0002182890310000033
Average value of moisture content
Figure BDA0002182890310000034
Temperature rate of change Δ T2、Moisture content change rate Δ M2Comparing with the calibrated food database to obtain the food subdivision types in the cooking area, and operating the parameter set PS corresponding to the food subdivision types3。
Further, if the subdivided kind of food is beef, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 200 deg.C and t3＝t2+3 min; if the subdivided type of food is toasted bread, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 160 ℃ and t3＝t2+5min。
Further, when the food maturity is calculated in step 6, t4The temperature T of the interior of the food is measured every 100ms after the moment4And moistureContent M4Calculating to obtain the food maturity D1With the internal temperature T of the food4And moisture content M4Has the following relationship: d1＝f(T，M)＝3.688×(λ/(λ+c))×T4×M4Wherein λ is the thermal conductivity of the food, c is the gross calorific constant, and the food maturity D of the food1A standard food maturity D corresponding to the subdivided type of the food1' make a comparison if D1<D1If yes, continuing to cook; if D is1≥D1', the cooking is stopped.
Further, when two or more foods are present in the cooking area, and when it is determined in step 3 that the food categories of the foods in the cooking area are different, or when it is determined in step 4 that the subdivided categories of the foods in the cooking area are different, the intermediate step is skipped, and step 6 is directly performed, and the maturity D of each food is measured every 100ms2Calculating when the maturity D of each food2In the interval of comprehensive maturity [ DDa,DDb]When it is inside, the cooking is stopped, wherein DDaIs the food reference maturity, DD, of the smallest value among the foods in the cooking areabThe food reference maturity with the largest value among the foods in the cooking area.
An intelligent cooking appliance using the intelligent cooking method is provided with a probe, wherein the intelligent cooking appliance comprises an energy source, a cooking cavity, a control system and the probe is used for measuring resistance, capacitance and impedance of food.
Compared with the prior art, the invention has the beneficial technical effects that:
1. can obtain the temperature and the moisture content in the food in real time, and can cook the food
Time control, accurate measurement, high efficiency, no safety risk, capability of simultaneously measuring a plurality of foods,
accurate cooking is achieved.
Drawings
FIG. 1 is a schematic flow chart of a control method according to the present invention;
fig. 2 is a schematic structural diagram of the present invention.
1. Control system, 2, energy source, 3, cooking chamber, 4, probe, 5, food.
Detailed Description
A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, an intelligent cooking method for intelligently cooking food by using an electrical parameter of the food obtained by a detection device includes the following steps:
s1: inserting the detection device into the food, and estimating the temperature T and the moisture content M inside the food through the resistance R, the capacitance C and the impedance Z of the food acquired by the detection device in real time.
Specifically, the temperature T, the moisture content M, the resistance R, the capacitance C, and the impedance Z inside the food in step 1 have the following relationship:
T＝f1(R,Z)＝1/[B*ln(R/RN)]，M＝f2(C,Z)＝-42+3.81C-7.5Z+0.05C2+0.26Z2；
where B is the thermal index of the probe and RN is the resistance of the probe at 25 deg.C.
Specifically, when the detection device measures the resistance inside the food, the resistance set A ═ { R ═ R at different depths will be measureda， Rb，Rc，...，RnWhen the detection device measures the capacitance inside the food, the capacitance set B ═ C at different depths is measureda，Cb，Cc，...，CnWhen the detection device measures the impedance inside the food, the impedance set E ═ Z at different depths is measureda，Zb，Zc，...，ZnAnd through f1(R, Z) and f2(C, Z) obtaining a set of temperature values H ═ T at different depths within the food1a，T1b，T1c，…，T1nAnd moisture content set I ═ M1a，M1b，…，M1nTaking the arithmetic mean value of each element in the set H as the temperature T inside the food, and taking the arithmetic mean value of each element in the set I as the water content inside the foodThe amount M.
S2 at t0Obtaining the initial resistance R of food at any moment0Initial capacitance C0And impedance Z0And a calibrated reference impedance value Z0' make a comparison if Z0<Z0', stop cooking, if Z0≥Z0' if yes, the operation is continued until the time point t1Wherein t is1＝t0+(5s～30s)。
Specifically, the reference impedance value Z in step 20' is a critical impedance value of the intelligent cooking method capable of cooking food, after the food is measured, if the impedance value is less than Z0If yes, the intelligent cooking method cannot cook; when the operation is judged to be continued, the parameter set PS is operated1Said parameter set PS1The cooking area is closed, full power output is provided, the cookability of the food can be detected, and if the food placed in the cooking area does not belong to the food which can be cooked by the intelligent cooking method, the cooking cannot be continued.
S3: by calculating t0～t1Average temperature of the interior of the food over a period of time
Figure BDA0002182890310000051
Average value of moisture content
Figure BDA0002182890310000052
Temperature rate of change Δ T1And rate of change of moisture content Δ M1Judging the food category and continuing to operate to the time point t2Wherein t is2＝t1+(1min～5min)。
Specifically, in step 3, the electrical parameters of the food are measured by the detection device every 100ms, and t is calculated0～t1Average temperature over time
Figure BDA0002182890310000053
Average value of moisture content
Figure BDA0002182890310000054
t0Time t1Rate of change of temperature Δ T at time1And rate of change of moisture content Δ M1When judging the food category, averaging the temperature
Figure BDA0002182890310000055
Average value of moisture content
Figure BDA0002182890310000056
Temperature rate of change Δ T1、Moisture content change rate Δ M1Comparing with the calibrated food database to obtain the food category of the food in the cooking area, and operating the parameter set PS corresponding to the food category2(ii) a If the food is meat in general, the parameter set PS2Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 200 deg.C and t2＝t1+3 min; if the food category is bread, the parameter set PS2Sealing the cooking area, injecting steam into the cooking area to provide full power output, and increasing the temperature of the cooking area to 180 deg.C and t2＝t1+4min。
S4 by calculating t0～t2Average temperature of the interior of the food over a period of time
Figure BDA0002182890310000057
Average value of moisture content
Figure BDA0002182890310000058
Temperature rate of change Δ T2And rate of change of moisture content Δ M2Judging the kind of food and the time t3And continues to run to t3Wherein t is3＝t2+(1min～5min)。
Specifically, in step 4, the electrical parameters of the food are measured by the detecting device every 100ms, and t is calculated0～t2Average temperature over time
Figure BDA0002182890310000059
The water content is flatMean value
Figure BDA00021828903100000510
t0Time t2Rate of change of temperature Δ T at time2And rate of change of moisture content Δ M2When the food is classified finely, the average temperature value is calculated
Figure BDA00021828903100000511
Average value of moisture content
Figure BDA00021828903100000512
Temperature rate of change Δ T2、Moisture content change rate Δ M2Comparing with the calibrated food database to obtain the food subdivision types in the cooking area, and operating the parameter set PS corresponding to the food subdivision types3。
In particular, if the subdivided type of food is beef, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 200 deg.C and t3＝t2+3 min; if the subdivided type of food is toasted bread, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 160 ℃ and t3＝t2+5 min; for different kinds of food, the corresponding parameter set can be calibrated, and the personalized cooking of the food is realized.
In particular, the parameter set PS3Providing full or 90% power output, run time t3＝t2+[(λ/(λ +c))×ΔT2×ΔM2×t2]λ is the thermal conductivity of the food, and c is the gross calorific constant.
S5 calculating t0～t3Rate of change of temperature Δ T of the interior of the food over a period of time3And rate of change of moisture content Δ M3And the calibrated food reference temperature change rate delta T3' and food reference moisture content Δ M3' comparison, if Δ M3< ΔM3' and Δ T3<ΔT3', stop cooking; if Δ M3 ≧ Δ M3' or Δ T3 ≧ Δ MΔ T3', then cooking is continued to the set time point T4Wherein t is4＝t3+(2min～8min)。
S6 starting from the time T4, by calculating the temperature T of the inside of the food4And moisture content M4Obtaining the food maturity D1And a calibrated food reference maturity D1' comparison, if D1<D1If yes, continuing to cook; if D is1≥D1', the cooking is stopped.
Specifically, when the food maturity is calculated in step 6, t4The temperature T of the interior of the food is measured every 100ms after the moment4And moisture content M4Calculating to obtain the food maturity D1With the internal temperature T of the food4And moisture content M4Has the following relationship: d1＝f(T，M)＝3.688×(λ/(λ+c))×T4×M4Wherein λ is the thermal conductivity of the food, c is the gross calorific constant, and the food maturity D of the food1A standard food maturity D corresponding to the subdivided type of the food1' make a comparison if D1<D1If yes, continuing to cook; if D is1≥D1', stop cooking; for beef, the food maturity is controlled to be above 80; for bread, the maturity value should be controlled to be above 95; the food maturity is monitored, and when the food maturity reaches the standard, the cooking is stopped, so that the food is guaranteed to be mature, excessive cooking is avoided, and the intelligent cooking of the food is realized.
Specifically, when two or more foods are present in the cooking area, and when it is determined in step 3 that the food categories of the respective foods in the cooking area are different, or when it is determined in step 4 that the subdivided categories of the respective foods in the cooking area are different, the intermediate step is skipped, and step 6 is directly performed, and the maturity D of the respective foods is determined every 100ms2Calculating when the maturity D of each food2In the interval of comprehensive maturity [ DDa,DDb]When it is inside, the cooking is stopped, wherein DDaIs the food reference maturity, DD, of the smallest value among the foods in the cooking areabThe food with the largest value in each food in the cooking areaStandard maturity of the material; each food corresponds to one detection device, the detection devices are used for acquiring the electric parameters of the food, the maturity of the food is calculated, and the accurate control of the single food is realized.
An intelligent cooking appliance using the above intelligent cooking method with a probe for measuring the resistance, capacitance and impedance of food 5 comprises an energy source 2, a cooking cavity 3, a control system 1 and a probe 4.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein, and any reference signs in the claims are not intended to be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (9)

1. An intelligent cooking method for realizing intelligent cooking of food through electric parameters of the food obtained by a detection device is characterized by comprising the following steps:
1) inserting a detection device into food, and estimating the temperature T and the moisture content M inside the food through the resistance R, the capacitance C and the impedance Z of the food obtained by the detection device in real time;
2) at t0Obtaining the initial resistance R of food at any moment0Initial capacitance C0And impedance Z0And a calibrated reference impedance value Z0' make a comparison if Z0<Z0', stop cooking, if Z0≥Z0' if yes, the operation is continued until the time point t1Wherein t is1＝t0+(5s～30s)；
3) By calculating t0～t1Average temperature of the interior of the food over a period of time
Figure FDA0003272762210000011
Average value of moisture content
Figure FDA0003272762210000012
Temperature rate of change Δ T1And rate of change of moisture content Δ M1Judging the food category and continuing to operate to the time point t2Wherein t is2＝t1+(1min～5min)；
4) By calculating t0～t2Average temperature of the interior of the food over a period of time
Figure FDA0003272762210000013
Average value of moisture content
Figure FDA0003272762210000014
Temperature rate of change Δ T2And rate of change of moisture content Δ M2Judging the kind of food and the time t3And continues to run to t3Wherein t is3＝t2+(1min～5min)；
5) Calculating t0～t3Rate of change of temperature Δ T of the interior of the food over a period of time3And rate of change of moisture content Δ M3And the calibrated food reference temperature change rate delta T3' and food reference moisture content Δ M3' comparison, if Δ M3<ΔM3' and Δ T3<ΔT3', stop cooking; if the delta M3 is more than or equal to the delta M3 'or the delta T3 is more than or equal to the delta T3', the cooking is continued to the set time point T4Wherein t is4＝t3+(2min～8min)；
6) From t4Starting at a moment by calculating the temperature T inside the food4And moisture content M4Obtaining the food maturity D1And a calibrated food reference maturity D1' comparison, if D1<D1If yes, continuing to cook; if D is1≥D1', the cooking is stopped.
2. The intelligent cooking method according to claim 1, wherein: in the step 1, the following relations exist among the temperature T, the moisture content M, the resistance R, the capacitance C and the impedance Z inside the food: t ═ f1(R,Z)＝1/[B*ln(R/RN)]，M＝f2(C,Z)＝-42+3.81C-7.5Z+0.05C2+0.26Z2Wherein B is the thermal sensitivity index of the probe device and RN is the resistance value of the probe device at 25 ℃.
3. The intelligent cooking method according to claim 2, wherein: when the detection device measures the resistance inside the food, the resistance set A ═ R at different depths is measureda，Rb，Rc，...，RnWhen the detection device measures the capacitance inside the food, the capacitance set B ═ C at different depths is measureda，Cb，Cc，...，CnWhen the detection device measures the impedance inside the food, the impedance set E ═ Z at different depths is measureda，Zb，Zc，...，ZnAnd through f1(R, Z) and f2(C, Z) obtaining a set of temperature values H ═ T at different depths within the food1a，T1b，T1c，...，T1nAnd moisture content set I ═ M1a，M1b，...，M1nAnd taking the arithmetic mean value of each element in the set H as the temperature T inside the food, and taking the arithmetic mean value of each element in the set I as the moisture content M inside the food.
4. The intelligent cooking method according to claim 1, wherein: reference impedance value Z in step 20' is a critical impedance value of the intelligent cooking method capable of cooking food, after the food is measured, if the impedance value is less than Z0If yes, the intelligent cooking method cannot cook; when the operation is judged to be continued, the parameter set PS is operated1Said parameter set PS1The cooking area is closed to provide full power output.
5. The intelligent cooking method according to claim 1, wherein: measuring the electrical parameters of the food by a detection device every 100ms in the step 3, and calculating to obtain t0～t1Average temperature over time
Figure FDA0003272762210000021
Average value of moisture content
Figure FDA0003272762210000022
t0Time t1Rate of change of temperature Δ T at time1And rate of change of moisture content Δ M1When judging the food category, averaging the temperature
Figure FDA0003272762210000023
Average value of moisture content
Figure FDA0003272762210000024
Temperature rate of change Δ T1Moisture content change rate Δ M1Comparing with the calibrated food database to obtain the food category of the food in the cooking area, and operating the parameter set PS corresponding to the food category2(ii) a If the food is meat in general, the parameter set PS2Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 200 deg.C and t2＝t1+3 min; if the food category is bread, the parameter set PS2Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 180 ℃ and t2＝t1+4min。
6. The intelligent cooking method according to claim 1, wherein: measuring the electrical parameters of the food by a detection device every 100ms in the step 4, and calculating to obtain t0～t2Average temperature over time
Figure FDA0003272762210000025
Average value of moisture content
Figure FDA0003272762210000026
t0Time t2Rate of change of temperature Δ T at time2And rate of change of moisture content Δ M2When the food is classified finely, the average temperature value is calculated
Figure FDA0003272762210000027
Average value of moisture content
Figure FDA0003272762210000028
Temperature rate of change Δ T2、Moisture content change rate Δ M2Comparing with the calibrated food database to obtain the food subdivision types in the cooking area, and operating the parameter set PS corresponding to the food subdivision types3。
7. The intelligent cooking method according to claim 6, wherein: if the subdivided type of food is beef, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 200 deg.C and t3＝t2+3 min; if the subdivided type of food is toasted bread, the parameter set PS3Sealing the cooking area, providing full power output, increasing the temperature of the cooking area to 160 ℃ and t3＝t2+5min。
8. The intelligent cooking method according to claim 1, wherein: when food maturity is calculated in step 6, t4Every 100ms after the momentInternal temperature T4And moisture content M4Calculating to obtain the food maturity D1With the internal temperature T of the food4And moisture content M4Has the following relationship: d1＝f(T，M)＝3.688×(λ/(λ+c))×T4×M4Wherein λ is the thermal conductivity of the food, c is the gross calorific constant, and the food maturity D of the food1A standard food maturity D corresponding to the subdivided type of the food1' make a comparison if D1<D1If yes, continuing to cook; if D is1≥D1', the cooking is stopped.
9. The intelligent cooking method according to claim 8, wherein: when two or more foods are present in the cooking area and it is determined in step 3 that the food categories of the foods in the cooking area are different or it is determined in step 4 that the subdivided categories of the foods in the cooking area are different, the intermediate step is skipped and the process proceeds directly to step 6, and the maturity D of each food is measured every 100ms2Calculating when the maturity D of each food2In the interval of comprehensive maturity [ DDa,DDb]When it is inside, the cooking is stopped, wherein DDaIs the food reference maturity, DD, of the smallest value among the foods in the cooking areabThe food reference maturity with the largest value among the foods in the cooking area.
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