KR940004979B1 - Automatic cooking system for a range - Google Patents

Abstract

The device includes a micom (10) which controls cooking action, a key input unit (11) which selects a cooking method, a weight sensor (30), a temperature sensor (40) which senses variation of temperature, a fuzzy arithmatic inference unit (20) which computes the optimal cooking time, and a magnetron driving unit (14). The method includes a cooking selection step, a fuzzy arithmatic inference step, a heating time specifying step, and a cooking step. The fuzzy inference step includes a 1st step which saves a temperature variation in 2nd RAM (25), a 2nd step which saves a regulation and member ship function, and a 3rd step which computes an optimal cooking time.

Description

Microwave Automatic Cooking Method and Apparatus

1 is a conventional microwave circuit diagram.

2 is a microwave circuit diagram of the present invention.

3 is a detailed circuit diagram of the dose sensor of the present invention.

4 is a detailed circuit diagram of a temperature sensor of the present invention.

5 is a flowchart of a control operation of the present invention.

6 is a control flow diagram of the fuzzy computation inference unit of the present invention

7 is an exemplary view according to the operation of the fuzzy computation inference unit of the present invention.

8 is an example of calculating the heating time t _{2 according} to the sixth rule of the present invention.

* Explanation of symbols for main parts of the drawings

10: micom 11: key input unit

16: A / D Converter 20: Fuzzy Arithmetic Inference Unit

21: Fuzzy Micom 24,25: Fuzzy Memory

30: weight sensor 40: temperature sensor

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic cooking method and apparatus for a microwave oven, and more particularly, to an automatic cooking method and apparatus for a microwave oven for cooking by fuzzy theory using a dedicated fuzzy circuit.

In the conventional microwave configuration, as shown in FIG. 1, when a user manually or automatically selects a cooking type using the key input unit 11, a key signal is input to the CPU 15 of the microcomputer 10 to cook. Kind is recognized.

At the same time, the weight sensor 12 converts the weight of food into an electrical signal and inputs an analog signal to the A / D converter 16, which is an analog-digital converter of the microcomputer 10.

In addition, the temperature sensor 13 also inputs the temperature change amount of the food to the A / D converter 16 as an analog value.

At this time, the microcomputer 10 converts the analog value of the electrical signal into a digital value that can be processed by the microcomputer 10 to convert the digital value and the output of the temperature sensor 13 converted the output of the weight sensor 12 The ROM17, which stores a digital value in advance, reads the corresponding heating time data and sends a signal to the magnetron driver 14 to drive the magnetron during the heating time.

As described above, the conventional microwave cooking method is almost dependent only on the value stored in the ROM, and greatly depends on the amount of change in the weight and temperature sensor.

As a result, the heating time can be changed by slight weight difference or temperature difference in automatic cooking. In other words, if the ambient situation is not taken into account, the temperature difference loses objectivity, and the weight sensor also senses differently according to the container of the food, so that different calculation times appear for the same dish (same weight). Because of this, there is a problem that often occurs when the food is burned by less heating or overheating. Therefore, the present invention has been made to solve the above-mentioned conventional problems, an object of the present invention is to use a fuzzy theory and fuzzy microcomputer in the microwave automatic cooking method and apparatus for solving the incomplete cooking method of automatic cooking. In providing.

DETAILED DESCRIPTION Embodiments for achieving the above object of the present invention will be described in detail with reference to the accompanying drawings.

2 is a circuit diagram of the present invention, as shown therein, a key input unit 11 for selecting a cooking operation, a weight sensor 30 for detecting a weight of food, and a temperature sensor 40 for detecting a temperature change of food. And a fuzzy operation inference unit 20 for calculating an optimal cooking time by calculating the outputs of the weight sensor 30 and the temperature sensor 40 by fuzzy inference, and detecting the output of the key input unit 11 for selective cooking operation. The microcomputer 10 controls the cooking operation by controlling the magnetron driving unit 14 according to the cooking time which is the output of the fuzzy inference calculating unit 20.

The fuzzy calculation inference unit 20 stores data input from the second ROM 24, the weight sensor 30, and the temperature sensor 40, which store a type of a fuzzy rule and a membership ship function. The second RAM 25 storing the data read from the second ROM 24 and the output of the weight sensor 30 and the temperature sensor 40 are temporarily stored and stored in the second RAM 25. After storing the stored data of the second RAM (24) in the second RAM (25) and reading the stored data of the second RAM (25) to calculate the optimal cooking time through the fuzzy computation inference to output to the microcomputer 10 21, wherein the purge micom 21 receives outputs of the weight sensor 30 and the temperature sensor 40, reads the stored data of the purge memories 24 and 25, and calculates an optimal cooking time. 2 CPU 23 and the output of the weight sensor 30 and the temperature sensor 40 to the second CPU 23 and the second CP The I / O unit 22 transmits the output of the U 23 to the A / D converter 16 of the microcomputer 10.

The weight sensor 30 of the present invention is configured as shown in FIG. 3, and as shown therein, when the AC frequency 31 is supplied, the coil L ₂ is caused by resonance by the capacitor C ₂ and the coil L ₁ . The same voltage is generated in (L ₃ ) and the voltage induced in the coils (L ₂ ) and (L ₃ ) is rectified in the first bridge diode 32 and the second bridge diode 33 to operate the differential transformer. to the output terminal 36, the variable terminal of the variable resistor (VR _1), the variable resistor (VR ₂₎ appears a direct-current voltage to the variable terminal direct-current voltage is divided by a variable resistor (VR ₂₎ and resistance (R ₁₎ of the A range of voltages (eg 0-5V) are represented as analog values.

Accordingly, the output terminal 36 voltage becomes the final output value of the weight sensor 30 and is input to the I / O unit 22 of the purge micom 21.

The output value can be adjusted by the voltage organic material 35 between the coils L ₁ -L ₃ .

The temperature sensor 40 of the present invention is configured as shown in FIG. 4, and as shown therein, a resistor R ₂ and a temperature in which a supply power supply Vcc is connected in parallel to a resistor R ₁ and the resistor R ₁ . The pressure is divided by the sensor 41 and the partial pressure is output to the I / O unit 22 of the purge micom 20 through the output terminal 46.

Here, in the output terminal 46, the resistance component value is changed by the temperature sensor 41, which is a thermistor, to change the temperature of the food, thereby changing the output voltage, which is an analog value.

According to the present invention, as shown in the flowchart of FIG. 5, when the user presses the cooking selection key on the key input unit 11 by executing the cooking selection step 51, the microcomputer 10 that detects the key input 101 is automatically cooked. If it is determined 102, the automatic cooking mode 52 is set, and if the manual cooking mode 103, the manual cooking is performed.

In this case, when automatic cooking is selected, the microcomputer 10 drives the MGT by controlling the magnetron driver 14 to detect the temperature change of the food (104), and whether the constant sensing time (t ₁ ) has been reached ( 105) When the constant sensing time t ₁ is reached, the fuzzy computation inference step 53 is executed.

When the fuzzy calculation inference step 53 is executed, the fuzzy micom 21 of the fuzzy calculation inference unit 20 that detects the input value (temperature change) of the temperature sensor 40 and the input value of the weight sensor 30 is The fuzzy arithmetic reasoning is performed to calculate an optimal cooking time, and the fuzzy microcomputer 21 transmits the calculated result to the A / D converter 16 of the microcomputer 10 (108).

Accordingly, the heating time determination and cooking step 54 is executed, wherein the analog output of the purge micom 21 is converted into a digital value in the A / D converter 16 and the first input of the microcomputer 10 which has received this digital value. When the CPU 15 reads the corresponding data from the first ROM 17 and reaches the driving time t ₂ (111), the cooking is finished 112.

Here, the cooking selection step 51 is a step performed by the microcomputer 910, and the automatic cooking mode step 520 is an interchange operation between the microcomputer 10 and the fuzzy micom 21 of the fuzzy computation inference unit 20. The fuzzy arithmetic reasoning step 53 is a step performed by the fuzzy arithmetic reasoning unit 20, and the heating time determination and cooking step 54 is a step performed by the microcomputer 10.

As the above operation is performed, the fuzzy micom 21 performs fuzzy arithmetic inference. As shown in the control flowchart of FIG. 6, after determining the automatic cooking input 201 in the microcomputer 10, the fuzzy micom ( 21 receives the outputs of the weight sensor 30 and the temperature sensor 40 (202), (203) the value is stored in the second ROM (24) and the resistance (204) in the second RAM (25) The rules and membership functions as shown in FIG. 7 are read and stored in the second RAM 25 (205).

The fuzzy microcomputer 21 reads the values stored in the second RAM 25, which is a fuzzy memory, and applies the output value of the weight sensor 30 and the output value of the temperature sensor 40 to each rule and membership function. Calculates the time t ₂ for optimum cooking (206) and transmits the calculated analog value t ₂ to the A / D converter 16 of the microcomputer 10 through the I / O unit 22. (207).

Accordingly, when the microcomputer 10 reaches 210 the driving time t ₂ , the microcomputer 10 terminates the operation 211.

FIG. 7 illustrates an embodiment of the operation of the fuzzy computation inference unit 20.

FIG. 7A is an exemplary diagram of a rule stored in the second ROM 25 of the purge unit 20 and outputs a heating time t ₂ calculated by receiving values of the weight sensor 30 and the temperature sensor 40 as inputs. One embodiment of the fuzzy rule.

7B and 7C are exemplary embodiments of a membership function according to input variables of the weight sensor 30 and the temperature sensor 40 stored in the second ROM 25.

7d shows an example in which the weight is 500 g and the temperature change is 3 ° C., and the input weight is 500 g, and the voltage is 1,2 volts (V) as an analog value, and the temperature change 3 ° C is 3.4 volt as the analog voltage value. (V) is shown in Figure 8 the process of inferring the calculated heating time (t ₂ ) at this time.

In other words, by applying the six rules (R1-R6) to the input values 1.2V and 3.4V, the smallest values are taken to select the smallest part, and then the six rules (R1-R6) are taken as the maximum values, and finally the area of the final inference The heating time t ₂ is calculated by calculating the area and the heating time t ₂ is obtained as an analog value by the following equation.

Accordingly, the calculation result t ₂ , which is the output of the fuzzy microcomputer 21 according to the above formula, is converted into a digital value by the A / D converter 16 of the microcomputer 10, and the corresponding data is output to the magnetron driver 14. Done.

As described in detail above, the present invention accurately calculates inaccurate and unintentional heating time (t ₂ ) of automatic cooking occurring in a conventional microwave oven using a fuzzy microcomputer employing a fuzzy theory, and thus cooks well and prevents overheating. The burning of the cooking fire solved the problem, and at the same time has an excellent effect of improving the quality of automatic cooking.

Claims (4)

A key input unit 11 for selecting a cooking operation, a weight sensor 30 for detecting the weight of food, a temperature sensor 40 for detecting a temperature change of food, the weight sensor 30 and a temperature sensor 40 The fuzzy operation inference unit 20 calculates an optimal cooking time by applying fuzzy arithmetic by applying a fuzzy rule to the output of the and the output of the key input unit 11 to determine the selected cooking operation. Automatic cooking apparatus for a microwave oven, characterized in that configured to control the cooking operation by controlling the magnetron drive unit 14 according to the cooking time calculated by the fuzzy calculation inference unit (20). A cooking selection step of determining whether the cooking is automatic according to the cooking selection key input is set to automatic cooking mode if automatic cooking, and manual cooking mode if not automatic cooking, and temperature change of food when automatic cooking mode is set at the cooking selection step. In order to detect the minute, the magnetron is driven and reaches a predetermined sensing time (t ₁ ). The heating time determination step of determining the heating time (t ₂ ) according to the data by digitally converting the time (t ₂ ) calculated in the step, and the cooking step of driving the magnetron for the time determined in the heating time determination step to perform cooking Automatic cooking of the microwave, characterized in that to perform the cooking by sequentially Way. The method of claim 2, wherein the fuzzy arithmetic inference step detects and stores the weight sensing value and the temperature sensing change after a predetermined time t ₁ when the automatic cooking is set and stores in the second RAM 25. The second process of storing the rules and membership functions stored in 24) in the second RAM 25 and the fuzzy operation according to the applied weight values and temperature changes stored in the first process are applied to the second process. An automatic cooking method of a microwave oven comprising a third process of performing inference to calculate an optimum heating time. According to claim 1, Fuzzy calculation inference unit 20 temporarily stores the data input from the second ROM 24, the weight sensor 30 and the temperature sensor 40 to store the type of fuzzy (Fuzzy Rule) The second RAM 25 stores data read from the second ROM 24, the outputs of the weight sensor 30 and the temperature sensor 40 are received in the second RAM 25, and are stored in the second RAM 25. After storing the stored data in the 2RAM (24) in the second RAM (25), the fuzzy micom (21) for calculating the optimum cooking time through the fuzzy calculation inference to output the stored data of the second RAM (25) to the microcomputer (10) Automatic cooking apparatus of the microwave, characterized in that consisting of).