An intelligent cooking method based on weight sensor and NTC temperature sensor

Abstract

The present invention discloses an intelligent cooking method based on a weight sensor and an NTC temperature sensor, and belongs to the field of kitchenware cooking. First, the ambient temperature fed back by the NTC temperature sensor is used to calibrate the gravity sensor; secondly, the food quality and the ambient temperature of the NTC temperature sensor are obtained, and the food type is judged by these two data; finally, according to the food type and food weight, the database gives the cooking temperature and cooking time. The present invention utilizes the ambient temperature, and performs weight calibration on the gravity sensor feedback data at a specified ambient temperature, thereby realizing a method for measuring and obtaining accurate food weight in a complex temperature environment such as an oven or an air fryer. At the same time, the food weight measured by the weight sensor and the temperature rise rate at a specified ambient temperature are used to judge the food type through the database, and the food type and food weight are used to automatically give the food cooking temperature and time, thereby realizing intelligent cooking.

Description

Technical Field

[0001] The invention relates to the technical field of kitchenware cooking, and in particular to an intelligent cooking method based on a weight sensor and an NTC temperature sensor. Background Art

[0002] With the development of intelligent control technology, home appliances and kitchen appliances have entered the era of intelligence. Smart ovens have changed the traditional oven method of manually setting temperature and time or manually selecting food type and quality. They use weight sensors to collect food weight and NTC temperature sensors to collect oven cavity temperature. They judge the type of ingredients by food weight and cavity temperature, realizing an intelligent cooking method with automatic temperature and time settings.

[0003] The principle of weight sensor for measuring weight is: metal deforms under a certain weight, causing the voltage analog quantity at both ends of the metal to change. By measuring this changed voltage analog quantity, the specific weight is calculated. However, the ambient temperature will also affect the deformation of the metal, causing the voltage analog quantity to change. For traditional ovens and air fryers, the role of the NTC temperature sensor is only to react to the real-time temperature of the oven cavity to control the cooking temperature. In traditional ovens and air fryers, due to the special environment of ovens, air fryers and other kitchen utensils, the ambient temperature changes frequently and widely. When the user adds food, it may be at room temperature or in a hot pot environment that has just been cooked, which makes it difficult to measure the weight of food. Summary of the invention

[0004] The object of the present invention is to provide an intelligent cooking method based on a weight sensor and an NTC temperature sensor to solve the problems in the background technology.

[0005] In order to solve the above technical problems, the present invention provides an intelligent cooking method based on a weight sensor and an NTC temperature sensor, comprising:

[0006] Use the ambient temperature fed back by the NTC temperature sensor to calibrate the gravity sensor;

[0007] Get the food quality and the ambient temperature of the NTC temperature sensor, and use these two data to determine the type of food;

[0008] Based on the type and weight of ingredients, the database gives the cooking temperature and cooking time.

[0009] In one embodiment, calibrating the gravity sensor using the ambient temperature fed back by the NTC temperature sensor includes:

[0010] The ingredients are judged by their weight. First, the ingredients database is analyzed. The cooking temperature of the ingredients in the database needs to be higher than the ambient temperature T0 fed back by the NTC temperature sensor. The ambient temperature T0 is consistent with the lowest cooking temperature T of various ingredients.min Correspondingly, the ambient temperature T0 fed back by the NTC temperature sensor is selected as the standard temperature of the gravity sensor;

[0011] After each heating, the oven and air fryer need to be cooled down briefly to ensure user safety. This operation ensures that even if the user cooks with a hot pot, the initial ambient temperature of the NTC temperature sensor is lower than the selected ambient temperature T0;

[0012] The gravity sensor is installed at the bottom of the kitchenware, and a baking tray and grill are placed on top. The weight analog quantity of each ingredient is measured, and linear interpolation is performed on all voltage analog quantity nodes to accurately obtain the accurate weight of the ingredient at ambient temperature T0.

[0013] During the actual cooking process of food, the ambient temperature T0 fed back by the NTC temperature sensor reaches the specified temperature T0, and the weight sensor voltage analog quantity is measured to calculate the food mass M.

[0014] In one embodiment, the weight simulation amount of each food material is measured by the following method:

[0015] The empty plate measures the sensor analog quantity U at the ambient temperature T0, and obtains the weight analog quantity U0 of the food 0g; a xg weight is placed on the baking tray, and the sensor analog quantity U at the ambient temperature T0 is measured, and the weight analog quantity U of the xg food is obtained. x ; By analogy, each time you add xg weights to measure, you can get the weight voltage analog value U at each xg interval m , where x is greater than 0.

[0016] In one embodiment, after obtaining the food mass M and the specified minimum cooking temperature T of the food min , the types of food judged by these two data include:

[0017] By detecting the ambient temperature, the time t required for the ambient temperature T0 to reach T0+10℃ is obtained T0 ;

[0018] First, the database stores the t values ​​of various foods at various weight points. T0 Data, through linear interpolation method to fit the food quality M-time t T0 The curve of

[0019] During the heating process, after collecting the current weight of the food, substitute the food mass M-time t of food A T0 The theoretical heating time t of various ingredients can be calculated by A ; At the same time, the time t0 required for the ambient temperature T0 to reach T0+10℃ during the current food heating process is collected, and the food membership F is further calculated A =|t0-tA |;

[0020] Calculate the food membership F of other ingredients in the database, and the type of ingredient being cooked is the one with the smallest food membership F value.

[0021] In the intelligent cooking method based on weight sensors and NTC temperature sensors provided by the present invention, weight sensors are introduced into kitchen appliances in high-temperature environments such as traditional ovens and air fryers. In an environment where the temperature will change significantly and frequently, the weight of food can be measured. Combined with the change in furnace temperature, the type of ingredients being cooked can be judged, and the cooking temperature and cooking time can be automatically given, thereby realizing one-click start of intelligent cooking. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of the principle architecture structure of an intelligent cooking method based on a weight sensor and an NTC temperature sensor provided by the present invention;

[0023] Figure 2 It is a flow chart of an intelligent cooking method based on a weight sensor and an NTC temperature sensor provided by the present invention. DETAILED DESCRIPTION

[0024] The following is a further detailed description of an intelligent cooking method based on a weight sensor and an NTC temperature sensor proposed by the present invention in combination with the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer according to the following description. It should be noted that the accompanying drawings are in a very simplified form and are not in precise proportions, and are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention.

[0025] The present invention provides an intelligent cooking method based on a weight sensor and an NTC temperature sensor. Figure 1 The control architecture diagram shown includes two steps: measuring the weight of food and intelligently cooking the ingredients.

[0026] like Figure 2 As shown, the first step is a method for measuring food weight: the present invention also utilizes the ambient temperature fed back by the NTC temperature sensor to calibrate the gravity sensor.

[0027] The ingredients are judged by their weight. First, the ingredients database is analyzed. The cooking temperature of the ingredients in the database needs to be higher than the ambient temperature T0 fed back by the NTC temperature sensor. The ambient temperature T0 is consistent with the lowest cooking temperature T of various ingredients. minCorrespondingly, the ambient temperature T0 fed back by the NTC temperature sensor is selected as the standard temperature of the gravity sensor. If the cooking temperature of food A is 200 degrees, the cooking temperature of food B is 180 degrees, and the cooking temperature of food C is 160 degrees; then the weight of the three ingredients A, B, and C are determined at 160 degrees. This T min The lowest cooking temperature of the three ingredients is 160 degrees. After each heating, the oven and the air fryer need to be cooled down briefly to ensure the safety of the user. This operation can also ensure that even if the user cooks with a hot pot, the initial ambient temperature of the NTC temperature sensor is lower than the selected ambient temperature T0.

[0028] The gravity sensor is installed at the bottom of the kitchenware, and a baking tray and grill are placed on top. The empty tray measures the sensor analog value U at the ambient temperature T0, and the weight analog value U0 of 0g of the food is obtained; a 50g weight is placed on the baking tray, and the sensor analog value U at the ambient temperature T0 is measured, and the weight analog value U of 50g of the food is obtained. 50 ; By analogy, each time a 50g weight is added for measurement, the weight voltage analog value U can be obtained at every 50g interval m By performing linear interpolation on all voltage analog nodes, the exact weight of the food at ambient temperature T0 can be accurately obtained.

[0029] During the actual cooking process of the food, the ambient temperature T0 fed back by the NTC temperature sensor reaches the specified minimum cooking temperature T min , measure the analog value of the weight sensor voltage and calculate the food mass M.

[0030] Please continue reading Figure 2 The second step is the intelligent cooking method for ingredients: after obtaining the ingredient mass M and the specified minimum cooking temperature T min , you can judge the type of food through two pieces of data.

[0031] By detecting the ambient temperature, we can get the time t required for the ambient temperature T0 to T0+10℃ T0 Different ingredients of the same weight will have different time t due to the influence of different factors such as the water content, volume, and initial temperature of the ingredients. T0 The data is different.

[0032] First, the database stores the t values ​​of various foods at various weight points (100g, 150g, etc.). T0 Data, through linear interpolation method to fit the food quality M-time t T0 curve.

[0033] During the heating process, after collecting the current weight of the food, substitute the food A weight M-time t T0The theoretical heating time t of various ingredients can be calculated by A At the same time, the time t0 required for the ambient temperature T0 to reach T0+10℃ during the current food heating process is collected, and the food membership F can be further calculated. A =|t0-t A |, where food membership refers to a calculated value of the probability that the currently cooked food belongs to a certain ingredient in the database. Similarly, the food membership F of other ingredients in the database is calculated, and the type of ingredient being cooked has the smallest food membership F value.

[0034] Finally, based on the determined type and weight of the ingredients, the database automatically gives the cooking temperature and cooking time. The database is empirical data pre-stored in the software, including theoretical cooking temperatures and theoretical cooking times for ingredients of various weights.

[0035] Traditional ovens use the ambient temperature fed back by the NTC temperature sensor to control the cooking temperature. The present invention uses the ambient temperature to calibrate the weight of the gravity sensor feedback data at a specified ambient temperature, thus realizing a method for measuring the accurate weight of ingredients in complex temperature environments such as ovens and air fryers. At the same time, the weight of the ingredients measured by the weight sensor and the temperature rise rate at a specified ambient temperature are used to determine the type of ingredients through the database. The type of ingredients and the weight of the ingredients are used to automatically give the cooking temperature and time of the ingredients, thus realizing intelligent cooking.

[0036] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.

Claims

1. An intelligent cooking method based on a weight sensor and an NTC temperature sensor, characterized in that: include: Use the ambient temperature fed back by the NTC temperature sensor to calibrate the gravity sensor; Get the food quality and the ambient temperature of the NTC temperature sensor, and use these two data to determine the type of food; Based on the type and weight of ingredients, the database gives the cooking temperature and cooking time; Using the ambient temperature feedback from the NTC temperature sensor to calibrate the gravity sensor includes: The ingredients are judged by their weight. First, the ingredients database is analyzed. The cooking temperature of the ingredients in the database needs to be higher than the ambient temperature T0 fed back by the NTC temperature sensor. The ambient temperature T0 is consistent with the lowest cooking temperature T of various ingredients. min Correspondingly, the ambient temperature T0 fed back by the NTC temperature sensor is selected as the standard temperature of the gravity sensor; After each heating, the oven and air fryer need to be cooled down briefly to ensure user safety. This operation ensures that even if the user cooks with a hot pot, the initial ambient temperature of the NTC temperature sensor is lower than the selected ambient temperature T0; The gravity sensor is installed at the bottom of the kitchenware, and a baking tray and grill are placed on top. The weight analog quantity of each ingredient is measured, and linear interpolation is performed on all voltage analog quantity nodes to accurately obtain the accurate weight of the ingredient at ambient temperature T0. During the actual cooking process of the food, the ambient temperature T0 fed back by the NTC temperature sensor reaches the specified minimum cooking temperature T min , measure the analog value of the weight sensor voltage and calculate the food mass M.

2. The intelligent cooking method based on weight sensor and NTC temperature sensor as claimed in claim 1, characterized in that: The weight simulation amount of each ingredient is measured by the following method: The empty plate measures the sensor analog quantity U at the ambient temperature T0, and obtains the weight analog quantity U0 of the food 0g; a xg weight is placed on the baking tray, and the sensor analog quantity U' is measured at the ambient temperature T0, and the weight analog quantity U of the xg food is obtained. x ; By analogy, each time you add xg weights to measure, you can get the weight voltage analog value U at each xg interval m , where x is greater than 0.

3. The intelligent cooking method based on weight sensor and NTC temperature sensor as claimed in claim 2, characterized in that: After obtaining the food mass M and the specified minimum cooking temperature T min , the types of food judged by these two data include: By detecting the ambient temperature, we can get the ambient temperature from T0 to T0+10 o The time required for C T0 ; First, the database stores the t values ​​of various foods at various weight points. T0 Data, through linear interpolation method to fit the food quality M-time t T0 The curve of During the heating process, after collecting the current weight of the food, substitute the food mass M-time t of food A T0 The theoretical heating time t of various ingredients can be calculated by A ; At the same time, the ambient temperature T0 to T0+10 during the current food heating process is collected o The time required for C is t0, and the food membership F is further calculated. A =|t0-t A |; Calculate the food membership F of other ingredients in the database, and the type of ingredient being cooked is the one with the smallest food membership F value.

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