WO2019137013A1 - 一种智能微波炉和具有食材识别的智能设备 - Google Patents

一种智能微波炉和具有食材识别的智能设备 Download PDF

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Publication number
WO2019137013A1
WO2019137013A1 PCT/CN2018/102304 CN2018102304W WO2019137013A1 WO 2019137013 A1 WO2019137013 A1 WO 2019137013A1 CN 2018102304 W CN2018102304 W CN 2018102304W WO 2019137013 A1 WO2019137013 A1 WO 2019137013A1
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WIPO (PCT)
Prior art keywords
food
heated
temperature
heating
smart
Prior art date
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PCT/CN2018/102304
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English (en)
French (fr)
Inventor
娄军
周晔
王俊
孙拥军
Original Assignee
上海达显智能科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Priority claimed from CN201820040068.6U external-priority patent/CN208124384U/zh
Priority claimed from CN201820920239.4U external-priority patent/CN208952169U/zh
Application filed by 上海达显智能科技有限公司 filed Critical 上海达显智能科技有限公司
Publication of WO2019137013A1 publication Critical patent/WO2019137013A1/zh

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
    • F24C7/00—Stoves or ranges heated by electric energy
    • F24C7/02—Stoves or ranges heated by electric energy using microwaves
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • H—ELECTRICITY
    • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
    • H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
    • H05B6/00—Heating by electric, magnetic or electromagnetic fields
    • H05B6/64—Heating using microwaves
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
    • Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Definitions

  • the utility model relates to the technical field of microwave ovens, in particular to a smart microwave oven and a smart device with food material identification.
  • microwave ovens are becoming more and more widely used. Users can heat the ingredients by selecting the heating time and heating mode. For example, the user uses a microwave oven to heat a food item for one minute. Since the heating mode is manually selected by the user, instead of the microwave oven, the heating mode is actively selected according to the weight, temperature and type of the food. If the heating time selected by the user is too long or too short, or the heating mode is not suitable, the food coke will be caused. Paste or no heat penetration occurs, so if the heated ingredients are to be heated properly, it is difficult for the novice to manually control the heating parameters of the microwave oven.
  • the present application provides a smart microwave oven including a housing, wherein a chamber is provided with a food heating placement area; and the method further includes:
  • a temperature sensor disposed on the inner wall of the casing for measuring the temperature of the food to be heated
  • a collecting device for collecting food images/food videos of the food to be heated
  • a model identification device connected to the collection device, directly receiving the food image, or converting the received food video into a food image, extracting feature points of the food image through an algorithm model, and performing feature point matching to identify the food to be heated Types of;
  • control device wherein an input end of the control device is coupled to the temperature sensor and the matching device to actively select a heating mode according to the obtained temperature and type of the food to be heated, and an output end of the control device is connected to the magnetron Controlling the magnetron to heat the foodstuff according to the actively selected heating mode or the passively selected heating mode, and during the heating process, the control device dynamically adjusts the output of the magnetron according to the current temperature of the foodstuff to be heated fed back by the temperature sensor Power or working time to achieve closed-loop control of the heating process of the food to be heated.
  • the model identification device incorporates a trained neural network model for offline recognition
  • the training set of the neural network model includes a set of food and/or food container images of big data to enable trained
  • the neural network model identifies the category attribute and/or the item volume of the item based on the feature points of the captured food image and/or the feature points of the container image.
  • the model identification device further estimates the weight of the food item based on the identified food material volume or area, and the control device actively selects the heating mode according to the temperature, category attribute, volume size and weight of the food item to be heated, and according to the category attribute
  • the volume and size control the heating time required for the actively selected or passively selected heating mode, and the heating power required to control the heating mode in a closed loop based on the feedback temperature.
  • the collecting device is a plurality of cameras, the camera is disposed inside the chamber, and the interior of the chamber is further provided with a heat-insulating, moisture-proof, transparent glass plate, the glass The board conceals the camera in a sealed cavity formed by the glass plate and the top corner of the chamber to isolate the temperature/humidity generated by the food or magnetron to be heated from the camera.
  • an illumination lamp used in conjunction with the camera is further installed in the chamber, and the installation aperture of the illumination lamp and the camera is less than 3 mm, and the illumination lamp is used when the camera is to take an image for heating the food.
  • a light source required to capture an image is supplemented to the food item to be heated.
  • the method further includes a weighing sensor for weighing the food to be heated, the weighing sensor is disposed at the bottom of the casing and below the heating placement area;
  • the load cell is coupled to an input of the control device, and the control device also actively selects a heating mode depending on the weight, temperature, and type of foodstuff to be heated.
  • a plurality of temperature/humidity sensors are further included, the temperature/humidity sensor being disposed on the inner wall of the casing to detect the temperature/humidity of the surface of the food to be heated, and/or to detect the temperature/humidity inside the chamber.
  • a humidifying portion is further disposed in the chamber, and the circuit board further controls the humidifying portion to operate according to the temperature/humidity currently detected, so that the chamber or/and the food to be heated are maintained at a set humidity.
  • the chamber is provided with an indicator light that emits a marking point to a placement area of the food item to be heated, and the indicator light has a mounting aperture of less than 3 mm, and the indicator light is used to indicate that heating and performing are required.
  • the temperature tested food material is placed at a reference position, or the placement area is provided with an identifier for indicating a food material placement reference position requiring heating and temperature testing.
  • the outer surface of the housing is provided with a human-computer interaction component, including but not limited to a touch display screen and a voice component, and the control device includes a main control panel and a human-computer interaction display.
  • a human-computer interaction component including but not limited to a touch display screen and a voice component
  • the control device includes a main control panel and a human-computer interaction display.
  • the human-machine interaction display panel actively selects a heating mode according to the obtained temperature of the food to be heated and the type of the foodstuff, or obtains a passively selected heating mode by the human-machine interaction component, and sends the heating mode to the main a control panel, wherein the main control panel controls the magnetron to heat the foodstuff according to the heating mode;
  • the human-machine interaction display board and the main control board are integrated into a single integrated structure or separated by a line, and the human-machine interaction display board also feeds back the temperature of the food to be heated to the main control in real time.
  • the plate is such that during the heating process, the main control board dynamically adjusts the output power of the magnetron according to the feedback temperature to achieve closed-loop control of the heating process of the food to be heated.
  • an intelligent sensing device is further included.
  • the smart sensing device includes a plurality of trigger circuits for detecting a state of the door switch, the trigger circuit is disposed on the door body and/or the box body, and when the door body is closed, the trigger circuit is turned on and
  • the control device, the collecting device, the related temperature sensor, the magnetron and/or the fan are activated to realize automatic recognition and automatic heating of the heated food material by the door closing operation.
  • another smart microwave oven comprising a housing, wherein a chamber of the housing is provided with a food heating placement zone; and wherein the method further comprises: but not limited to:
  • a load cell disposed at the bottom of the housing and below the placement area for weighing the food to be heated
  • a temperature/humidity sensor disposed on the inner wall of the casing for detecting the temperature of the food to be heated
  • the food identifying device is disposed on the inner wall or the outer wall of the casing for identifying the type of the food to be heated;
  • the circuit board is packaged between the inner wall and the outer wall of the casing, and is connected with a load cell, a temperature/humidity sensor, and a food identification device for selecting a heating mode according to the weight, temperature, humidity, or/and type of the food to be heated. And used to control the microwave oven to heat the food according to the heating mode.
  • the smart microwave oven is any one of a micro oven (an integrated microwave and oven function device) and a steaming oven (an integrated steamer and oven function device) or a micro steamed (integrated microwave oven, steamer and Oven function equipment) one machine.
  • a smart device having a food material identification, comprising a housing, wherein the chamber is provided with a food heating placement area, and further comprising:
  • a temperature sensor disposed on an inner wall of the casing for detecting a temperature of the foodstuff/chamber to be heated
  • a collecting device for collecting food images/food videos of the food to be heated
  • a model identification device connected to the collection device, directly receiving the food image, or converting the received food video into a food image, extracting feature points of the food image through an algorithm model, and performing feature point matching to identify the food to be heated Types of;
  • control device wherein an input end of the control device is coupled to the temperature sensor and the model identification device to actively select a heating mode according to the obtained temperature/humidity and type of the foodstuff/chamber to be heated, the output of the control device Connecting with the heating component, controlling the smart device to heat the foodstuff according to the actively selected heating mode or the passively selected heating mode, and during the heating process, the control device feeds back the current temperature of the foodstuff/chamber to be heated according to the temperature sensor Dynamically adjust the output power or working time of the smart device to achieve closed-loop control of the heating process of the food to be heated.
  • the model identification device incorporates a trained neural network model for offline recognition
  • the training set of the neural network model includes a set of food and/or food container images of big data to enable trained
  • the neural network model identifies the category attribute and/or the item volume of the item based on the feature points of the captured food image and/or the feature points of the container image.
  • the model identification device further estimates the weight of the food material based on the identified food material volume or area, and the control device actively selects the heating mode according to the temperature/humidity, category attribute, volume size, and weight of the foodstuff/chamber to be heated. And the heating time required to control the active or passively selected heating mode according to the category attribute and volume, and the heating power required to control the heating mode in a closed loop according to the feedback temperature.
  • the method further includes an intelligent sensing device, the smart sensing device includes a plurality of trigger circuits for detecting a state of the door switch, the trigger circuit is disposed on the door body and/or the box, the door When the body is closed, the trigger circuit turns on and activates the control device, the collecting device, the related sensor, the heating component and/or the fan, so that the smart device automatically recognizes and automatically heats the food to be heated by closing the door.
  • the smart sensing device includes a plurality of trigger circuits for detecting a state of the door switch, the trigger circuit is disposed on the door body and/or the box, the door When the body is closed, the trigger circuit turns on and activates the control device, the collecting device, the related sensor, the heating component and/or the fan, so that the smart device automatically recognizes and automatically heats the food to be heated by closing the door.
  • the heating mode is actively selected according to the type of identification, so that the smart microwave oven can realize automatic heating without the user manually selecting the heating mode, and whether it is actively selecting heating or user selection.
  • Heating through the real-time feedback of the temperature of the food in the heating process, dynamically adjust the output power or working time of the magnetron to achieve closed-loop control of the heating process of the food to be heated, improve the taste of the food through closed-loop control, and improve the use of the microwave oven Experience and reduce the skills and experience of novices using microwave ovens to heat ingredients.
  • 1 is a schematic structural view of a smart microwave oven
  • FIG. 2 is a schematic diagram of a smart microwave oven circuit of the first embodiment
  • FIG. 3 is a schematic diagram of a smart microwave oven circuit of the second embodiment.
  • Embodiment 1 is a diagrammatic representation of Embodiment 1:
  • This example provides a smart microwave oven, the structure shown in Figure 1, including the housing 1, the temperature sensor 2, the acquisition device 3, the model identification device and the control device (not shown), the structure of each component and the functions realized
  • the details are as follows.
  • a food heating placing area 11 is arranged in the chamber of the casing 1 to place the food to be heated in the heating placing area 11.
  • a reference position can be set in the heating placing area 11.
  • An identification line such as a circular reference position identification line, to indicate that the food to be heated is placed in the reference position identification line; in another embodiment, the marking may be emitted into the heating placement area 11 in the chamber.
  • Point indicator light which is used to indicate the reference position of the food to be heated and temperature tested. To prevent microwave leakage, the indicator light has a mounting aperture of less than 3 mm.
  • the temperature sensor 2 is disposed on the inner wall of the casing 1, and the inner wall refers to the inner wall of the casing 1, and may be an inner side wall, an inner top wall, an inner top angle, etc., depending on the type of the temperature sensor 2 and the temperature to be detected.
  • the temperature sensor 2 is disposed at a corresponding position inside the casing 1.
  • the temperature sensor 2 may be an infrared temperature sensor to measure the temperature of the surface of the food to be heated; in other embodiments, the temperature sensor may also be a thermistor, Thermocouples, MEMS temperature sensors, etc., can collect the internal temperature of the chamber and measure the temperature inside the food to be heated.
  • the collecting device 3 can be disposed in the chamber 11 or outside the chamber 11.
  • the collecting device 3 is used to collect the food image or the food video of the food to be heated.
  • two methods for collecting the image of the food to be heated are provided.
  • the food image is directly collected from the food to be heated, and the collected food image is a fixed angle static image; the other way is to directly collect the food video of the food to be heated, and then cut and integrate the video to obtain Multi-angle image of the food, because the latter way to obtain a multi-angle food image, by identifying the multi-angle image of the food can get a more accurate food type.
  • the collecting device 3 of this example is a plurality of cameras, and a plurality of cameras are disposed inside the chamber of the casing 1.
  • the camera of this example is preferably a wide-angle camera.
  • the position of the camera is set at the top corner of the top of the microwave oven, and the camera can obtain a larger shooting angle at the top corner, so the number can be at least one, and of course, two or three as needed.
  • a camera is arranged at the vertex position to achieve the purpose of obtaining the image of the food in multiple directions, thereby improving the accuracy of the parameter.
  • the interior of the chamber is also provided with a heat-insulating, moisture-proof and transparent glass plate, and the glass plate hides the camera in a sealed cavity formed by the glass plate and the chamber, so that The temperature/humidity generated by the microwave material to be heated or the temperature/humidity generated by the magnetron is isolated from the camera, that is, the camera separates the camera from the inside of the chamber through the insulated transparent glass plate; A fan component is added to the sealed cavity to dissipate heat generated by the camera during operation.
  • An illumination lamp is further disposed in the chamber, preferably disposed on the same side of the camera or at the top of the cabinet.
  • the illumination lamp is activated together with the camera to extract a clear picture of the food material for the camera, and when the camera is to take an image for heating the food,
  • the illuminator supplements the food to be heated with the light source required to capture the image.
  • the illumination lamp is preferably a white light, although other colors can also be used for illumination purposes, but it will affect the judgment of the ingredients.
  • the position of the camera is not limited to the internal vertices in the above, and may be disposed at the top or the side wall, and the specific position is not specifically limited.
  • the position of the illumination lamp is set on the camera side or the top of the microwave oven. The purpose is to prevent backlighting or shadowing of the food material when the camera is photographed. Therefore, the position of the lamp and the camera can be appropriately adjusted without affecting the photographing effect.
  • the camera is connected to the control unit using interfaces such as MIPI or USB.
  • the position of the camera in the present embodiment is not limited to the vertex position in the above embodiment, and the position thereof may be set on the inner wall or the top of the microwave oven.
  • the camera When the camera is set on the outer wall, it is mainly for the consumer to conveniently call the relevant recipes and related knowledge and cloud interaction by recognizing the ingredients.
  • the lamp used in conjunction with the camera is preferably an LED light source with a color temperature of about 5000K to 6500K, so that the light can be uniformly irradiated on the surface of the food, and the lamp needs to be insulated with 1-3 layers of high temperature glass, the outermost layer. The glass also needs to be scattered.
  • the system needs to correct the color temperature by software. It can also be modified by adding a filter. If the correction is not good, the accuracy of the identification of the ingredients will be reduced.
  • the specific solution is set according to the specific product.
  • the lights can be placed near the camera or on the top plate.
  • the lights can also be used in one to three, depending on the specific product requirements and configuration.
  • an LED light source with a color temperature of 6500K was used and insulated.
  • the model identification device of the present example is connected to the acquisition device 3, directly receives the food image collected by the collection device 3 or directly receives the food video collected by the collection device 3, and then converts the food video into a corresponding food image (eg, in the video)
  • Each N frame is converted into an image to obtain a plurality of food images of different angles.
  • the feature points of the food image are extracted by the algorithm model and the feature points are matched to identify the type of the food to be heated.
  • the model identification device has a built-in neural network model for offline recognition.
  • the training set of the neural network model includes a set of food and/or food containers for big data, so that the trained neural network model is based on the characteristics of the collected food images.
  • the feature points of the dots and/or receptacle images identify the category attributes of the ingredients and/or the volume of the ingredients.
  • the training includes the collection, cleaning and use of big data, as well as the influence of the use environment and equipment, such as the different conditions of various containers. Impact, training through relevant data to ensure that the final neural network model can be used for food identification and food identification under different containers, so even if the food video or food image collected includes food for itself, it further includes food for storage.
  • the appliance such as the tray for storing food, can also identify the corresponding type of food material according to the collected food image or appliance image.
  • the model recognition device realizes the recognition of the liquid by recognizing the cup.
  • the model recognition device of this example is offline image recognition, so that the recognition speed of the smart microwave oven is faster when used locally, and the influence of wireless network transmission on image recognition is minimized.
  • the neural network model can be updated online in real time according to changes in the type of ingredients, improvement in accuracy, and the like.
  • the input end of the control device is connected with the temperature sensor 2 and the matching device to actively select the heating mode according to the obtained temperature and type of the food to be heated, and the output of the control device is connected with the magnetron according to the actively selected heating mode or passive
  • the selected heating mode controls the magnetron to heat the food to be heated, and during the heating process, the control device dynamically adjusts the output power or working time of the magnetron according to the current temperature of the food to be heated fed back by the temperature sensor to realize the food to be heated. Closed loop control of the heating process. Even if the same food material is different in volume and temperature, the required heating mode and heating time are different.
  • the model identification device estimates the weight of the food material according to the identified food material volume or area, and the control device according to the temperature of the food to be heated,
  • the category attribute, volume size and weight actively select the heating mode, and the heating time required to control the active or passively selected heating mode according to the category attribute and volume, and the heating power or heating required to control the heating mode based on the feedback temperature. time.
  • model identification device may be integrated with the collection device 3, or may be integrated with the control device, or may be used independently, in which manner, according to the specific requirements of the product. This example does not make special requirements.
  • this example in order to directly weigh the food, for example, to directly weigh the food in the standard appliance, this example also includes a load cell, and the weighing sensor directly weighs the food to be heated, and is set at The bottom of the casing 1 is located below the heating placement zone 11, and the load cell is connected to the input end of the control device.
  • the control device also actively selects the heating mode according to the weight, temperature and type of the foodstuff to be heated.
  • this example also includes several temperature/humidity sensors, temperature/humidity.
  • the sensor can be used in several ways, can be used at the same time or can be combined according to different product requirements.
  • thermocouple thermistor and MEMS temperature sensor, etc.
  • a method for measuring the temperature of the surface of a foodstuff using a non-contact infrared sensor, etc., while giving a reference mark for placing the position of the foodstuff); one for measuring the temperature inside the foodstuff (using thermocouples, thermistors, and MEMS temperature)
  • the temperature/degree sensor can be placed anywhere inside the cavity to detect the temperature/humidity of the surface of the food to be heated, and/or to detect the cavity Temperature/humidity of the interior; in a preferred embodiment, the temperature/humidity sensor is disposed in the inner side wall of the housing a portion below the middle to detect the temperature/humidity of the surface of the food to be heated, and/or to detect the temperature/humidity inside the chamber, the chamber is further provided with
  • the outer surface of the housing 1 is provided with a human-computer interaction component, including but not limited to the touch display screen 4 and the voice component 5, wherein the touch display screen 4 is intuitive
  • the current working mode and working time of the microwave oven are displayed.
  • the user can directly modify the current working mode of the microwave oven through the touch display screen 4, for example, switching from the high fire mode to the low fire mode, and the user can also pass the touch display screen 4
  • the voice component 5 of the present example includes a microphone and a horn, and the voice component 5 performs sound identification on the inside and outside of the microwave oven to realize an automatic heating process of an edible material and external voice control.
  • the microwave oven can issue a corresponding voice prompt through the voice component 5, or the user can select the heating mode of the microwave oven through the voice component 5 voice.
  • the heating mode of the microwave oven of the present example may be that the control device independently selects a corresponding heating mode according to the acquired temperature, the type of the foodstuff, and the size of the foodstuff. From the perspective of the microwave oven, the heating mode is actively selected by the microwave oven, instead of being artificially selected. In addition, by setting the human-computer interaction component, the user can select the heating mode through the touch display screen 4 or through the voice component 5. From the perspective of the microwave oven, the heating mode is passively selected by the microwave oven.
  • the example further includes an intelligent sensing device, and the intelligent sensing device includes a plurality of trigger circuits for detecting the state of the door switch, and the trigger circuit is disposed on the door body and/or the box body, and the door body is closed.
  • the trigger circuit is turned on and the control device, the collecting device, the related sensor, the magnetron and/or the fan are activated, the smart microwave oven automatically recognizes and automatically heats the food to be heated by closing the door.
  • the trigger circuit is a gate switch, which can be in various forms such as a mechanical switch, an electronic switch and an optical switch.
  • the installation position can be on a suitable position such as a door or a door frame to ensure that the door closing signal can be timely, reliable and safe. Transmission. When the door is closed, the door switch is closed and the closing signal is transmitted to the smart sensing device and subsequent operations are initiated.
  • the utility model comprises a plurality of sensors for detecting parameters inside the chamber, a plurality of sensors are connected with the control device, and a switch is arranged at the door body, and the switch is automatically triggered when the door body is closed, and the control device is closed by the switch.
  • the microwave oven and various sensors are automatically activated.
  • the heating time and heating temperature are automatically set according to the data detected by the sensor and the type of the food, and the automatic heating function is realized, thereby avoiding the inaccurate setting caused by the artificial setting.
  • the problem of overcooking or cooking is not in place.
  • control device comprises a main control board and a human-computer interaction display board, and the human-computer interaction display control board actively selects the heating mode according to the obtained temperature of the food to be heated and the type of the foodstuff, or obtains the passively selected heating mode through the human-computer interaction component. And sending the heating mode to the main control board, the main control board controls the magnetron to heat the food according to the heating mode; the human-computer interaction display panel and the main control board are integrated or connected by a line, and The human-computer interaction display panel also feeds the temperature of the food to be heated to the main control board in real time, so that during the heating process, the main control board dynamically adjusts the output power of the magnetron according to the feedback temperature to realize the heating process of the food to be heated. Closed loop control.
  • the basic principle block diagram of the smart microwave oven is shown in Figure 2 and Figure 3.
  • the example further includes a wireless communication module, and the wireless communication module is connected with the human-machine interaction display board signal, and the wireless communication module can It is a wifi module, it can also be a Bluetooth module, a 2G/3G/4G/5G module, or a combination of several modules.
  • the cloud module can be connected to the cloud to upload the heating process and results of the smart microwave oven to the cloud or
  • the external terminal in addition, can also wirelessly control the heating mode of the microwave oven through the external terminal, and can also download the recipe to the touch display screen 5 in the cloud through the wireless communication module, and then control the microwave oven according to the downloaded recipe through the human-computer interaction display panel. Heating mode.
  • the various cameras, infrared sensors, and lamp devices selected in this example need, but are not limited to, components having a diameter of less than 3 mm to prevent microwave leakage.
  • Embodiment 2 is a diagrammatic representation of Embodiment 1:
  • the present application provides a specific application of the smart microwave oven, the structure of which can refer to FIG. 1 , including the housing 1 , and includes but is not limited to: load cell, temperature / humidity sensor, food identification device, slave control a circuit board and a main control circuit board; wherein the chamber 1 has a food heating placement area 11 in the chamber, the load cell is disposed at the bottom of the housing 1 and is located below the food heating placement area, and the load cell is used for heating the food.
  • the food to be heated carried on the area 11 is weighed; the temperature/humidity sensor is disposed on the inner wall of the casing 1, the temperature/humidity sensor is used to detect the temperature of the food to be heated; and the food identification device is disposed inside the chamber of the casing 1.
  • the food material identification device is used for identifying the type of the food to be heated; the slave control circuit board and the main control circuit board are respectively packaged between the inner wall and the outer wall of the casing 1, and the communication connection between the slave control circuit board and the main control circuit board
  • the slave control board is connected with a load cell, a temperature/humidity sensor, and a food identification device for selecting a heating mode according to the weight, temperature, humidity, or/and type of the food to be heated, and
  • the heating mode is transmitted to the main control circuit board, and the main control circuit board actively controls the microwave oven to heat the foodstuff according to the heating mode; the smart microwave oven of the present example can realize the fully automatic control heating of the food to be heated, without the user manually operating the heating, thereby Improve the experience of the microwave oven.
  • the slave control circuit board of this example is essentially the human-machine interaction display board of the first embodiment.
  • the main control circuit board of this example is essentially the main control board of the first embodiment, and only the description on the text of the name is different. The working principle is the same.
  • the human control circuit board can also be called the human-computer interaction display board, and the main control circuit board is called the main control board.
  • the food material identifying device of the present example integrates the functions of the collecting device and the matching device in the first embodiment, that is, the food material identifying device has the function of acquiring an image and recognizing an image. Further, the food material identifying device includes a plurality of cameras, and the plurality of cameras are disposed at Any position inside the chamber of the casing 1 can be collected as long as the food can be collected.
  • the camera of this example is preferably a wide-angle camera, and the wide-angle camera integrates a circuit board of the image recognition algorithm (the circuit board and the model identification device of the first embodiment)
  • the image recognition algorithm the image of the food to be heated collected by the wide-angle camera is intelligently identified offline, and the types of food materials to be heated, such as buns, steamed buns, liquids, chicken legs, fish, and the like, are commonly recognized;
  • Image recognition algorithms can use the wireless network to perform online model updates from the cloud (such as models that increase the variety of ingredients or improve recognition accuracy).
  • the image recognition algorithm adopts artificial intelligence technology, uses neural network and big data to train the model, and then uses the offline model for local use, that is, offline image recognition, so that the recognition speed of the smart device is faster when used locally. Minimize the impact of wireless network transmission on image recognition.
  • the model can be updated online in real time based on changes in the type of ingredients and improvement in accuracy.
  • the ingredients are automatically heated according to the obtained temperature and weight of the ingredients (controlling the power and time of heating), and the ingredients to be processed can enter the automatic control process after being placed in the smart device and closed, so that the cooking experience is made.
  • intelligent devices can be controlled by interactive methods such as voice and touch display.
  • the camera can also identify the two-dimensional code or barcode on the package to identify the type of the food, and then automatically control the heated food according to the corresponding program; please refer to the first embodiment for the specific installation of the camera. I will not repeat them here.
  • the number of the temperature/humidity sensors of the present example is several, and the number of the temperature/humidity sensors of the present example is two, which are respectively disposed in the casing 1
  • the temperature/humidity sensor may be installed in other arrangements as long as the accurate detection of the food to be heated and the cavity is achieved. Temperature / humidity can be.
  • the temperature/humidity sensor can be used in several ways, and can be used at the same time or in combination according to different product requirements.
  • One is used to measure the temperature inside the cavity of the smart microwave oven (using thermocouples, thermistors, MEMS temperature sensors, etc.) a method for measuring the temperature of the surface of the food (using a non-contact infrared sensor, etc., while giving a reference mark for placing the position of the food); one for measuring the temperature inside the food (using thermocouple, thermal Various methods, such as resistors and MEMS temperature sensors, where temperature sensitive components need to be inserted into the food to be tested).
  • the control circuit board selects the heating mode according to the weight, temperature, humidity and type of the food to be heated, and then transmits the heating mode to the main control circuit board, and the main control circuit board controls the operation of the magnetron assembly according to the heating mode to be heated.
  • the ingredients are actively heated.
  • sensors such as an odor sensor
  • the slave control board is based on the overall sense and The results of the measurement are combined to select the best heating mode to achieve optimal heating of the ingredients in the microwave oven.
  • the various cameras, infrared sensors, and lamp devices selected in this example need, but are not limited to, components having a diameter of less than 3 mm to prevent microwave leakage.
  • the slave control circuit board and the main control circuit board of this example are two independent circuit boards, and are connected by line communication, and can expand the other function design of the slave control circuit board according to actual needs. So that the smart microwave oven can achieve intelligent control of the corresponding functions.
  • the main control circuit board and the slave control circuit board are also integrated design.
  • the main control circuit board and the slave control circuit board are integrated design or separate design according to the research and development design of the microwave oven and the actual needs of the user. Settings are not specifically limited.
  • the intelligent control of the microwave oven can also be implemented by a person skilled in the art.
  • the smart microwave oven may not be provided with a load cell and a temperature/humidity sensor, for example,
  • the smart microwave oven may only include the food material identification device, that is, the control panel selects the heating mode by type; or, in other embodiments, the smart microwave oven may be provided with a load cell or a temperature/humidity sensor, such that the slave circuit board passes the weight and Type or temperature, humidity and type select heating mode.
  • the utility model provides a smart device with food material identification, which comprises but is not limited to any one of a micro oven and a micro steamer or a micro steaming and baking machine, and the intelligent device automatically recognizes the food and heats the food.
  • food material identification comprises but is not limited to any one of a micro oven and a micro steamer or a micro steaming and baking machine, and the intelligent device automatically recognizes the food and heats the food.
  • the intelligent device automatically recognizes the food and heats the food.
  • the chamber of the housing of the smart device is provided with a food heating placement area, which further comprises:
  • the temperature sensor is disposed on the inner wall of the casing for detecting the temperature of the foodstuff/chamber to be heated.
  • the inner wall of the present example also refers to the wall of the inner cavity of the casing, and is not limited to the inner side wall or the inner wall.
  • the top wall, that is, the temperature sensor is disposed inside the casing to reach the detection temperature.
  • the type of the temperature sensor and the temperature measurement method of the present example refer to the first embodiment, and the details of the temperature of the heated food are detected.
  • the temperature in the chamber is determined according to the specific type of smart device. For example, if the smart device is an oven, only the temperature in the oven chamber needs to be detected. If the smart device is a micro-steamer, it can be detected. Heating the temperature of the ingredients;
  • the collecting device is configured to collect food images and/or food videos of the food to be heated;
  • the collecting device of the present example is a plurality of cameras.
  • the interior of the chamber is further provided with heat insulation and moisture isolation.
  • a transparent glass plate the glass plate conceals the camera in a sealed cavity formed by the glass plate and the chamber, so as to isolate the temperature/humidity generated by the food or heating component to be heated from the camera; the specific working mode of the collecting device of this example
  • For the installation method please refer to the first embodiment, which is not described here.
  • the model identifying device is connected to the collecting device signal, directly receives the food image, or converts the received food video into a food image, extracts feature points of the food image through an algorithm model, and performs feature point matching to identify the type of the food to be heated;
  • control device the input end of the control device is connected with the temperature sensor and the model identification device to actively select the heating mode according to the obtained temperature/humidity and type of the foodstuff/chamber to be heated, and the output end of the control device is connected with the heating component, according to The actively selected heating mode or the passively selected heating mode controls the smart device to heat the heated foodstuff, and during the heating process, the control device dynamically adjusts the output power of the smart device according to the current temperature of the foodstuff/chamber to be heated fed back by the temperature sensor or Working time to achieve closed-loop control of the heating process of the food to be heated.
  • the model identification device has a built-in neural network model for offline recognition, and the training set of the neural network model includes a large data set of food and/or food containers, so that the trained neural network model is based on the collected food image.
  • the feature points and/or feature points of the container image identify the category attribute of the item and/or the item volume.
  • the model identification device also estimates the weight of the food according to the identified food volume or area, and the control device actively selects the heating mode according to the temperature, category attribute, volume and weight of the food/chamber to be heated, and controls the active selection according to the category attribute and the volume size or The heating time required for the passively selected heating mode, and the heating power or heating time required to control the heating mode in a closed loop based on the feedback temperature.
  • the example further includes an intelligent sensing device, the smart sensing device includes a plurality of trigger circuits for detecting the state of the door switch, the trigger circuit is disposed on the door body and/or the box body, and when the door body is closed, the trigger circuit is turned on and started.
  • the control device, the collecting device, the related sensor, the heating component and/or the fan realize that the intelligent device automatically recognizes and automatically heats the food to be heated by closing the door.
  • the heating member of this example may be a magnetron, a quartz tube/graphite tube, a resistance wire or the like, depending on the specific type of the smart device.
  • the smart device By combining the relevant sensors, the collecting device and the control device to identify some attributes of the food to be heated, the smart device automatically heats the food according to the identified temperature and type, and the user does not need to manually select the heating mode to improve the use experience.

Abstract

一种智能微波炉和具有食材识别的智能设备，智能微波炉包括测量待加热食材的温度传感器2；采集待加热食材的食物图像/或食物视频的采集装置3；对采集的食物图像进行特征点提取并进行特征点匹配的模型识别装置；以识别出待加热食材的类型；控制装置根据获取的待加热食材的温度和类型主动选择加热模式，根据加热模式控制磁控管对待加热食材进行加热，且在加热过程中，控制装置根据反馈的当前温度动态调整磁控管的输出功率或工作时间，以实现待加热食材的加热过程的闭环控制。使智能微波炉根据鉴别的温度及类型对待加热食材自动加热，无需用户手动操作选择加热模式，降低消费者使用微波炉加热食材的技巧及经验。

Description

一种智能微波炉和具有食材识别的智能设备 技术领域
本实用新型涉及微波炉技术领域，具体涉及一种智能微波炉和和具有食材识别的智能设备。
背景技术
随着生活节奏的加快，微波炉的使用越来越广泛，用户可以通过选择加热时间和加热模式来对食材进行加热，例如用户使用微波炉对某食材进行高火加热一分钟的操作。由于加热模式是通过用户手动选择，而非微波炉根据食材的重量、温度及类型主动选择相适应的加热模式，如果用户选择的加热时间过长或过短，或者加热模式不合适，都会导致食材焦糊或没有热透等情况的发生，因此，如果要对待加热食材进行恰好的加热，这对新手来说手动控制微波炉的加热参数具有一定的难度。
发明内容
根据第一方面，本申请提供一种智能微波炉，包括壳体，壳体的腔室内设有食物加热放置区；还包括：
温度传感器，设置于壳体的内壁上，用于测量待加热食材的温度；
采集装置，用于采集待加热食材的食物图像/或食物视频；
模型识别装置，与所述采集装置信号连接，直接接收食物图像/或将接收的食物视频转化为食物图像，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型；
控制装置，所述控制装置的输入端与所述温度传感器和匹配装置信号连接，以根据获取的待加热食材的温度和类型主动选择加热模式，所述控制装置的输出端与磁控管连接，根据主动选择的加热模式或被动选择的加热模式控制磁控管对待加热食材进行加热，且，加热过程中，控制装置根据所述温度传感器反馈的待加热食材的当前温度动态调整磁控管的输出功率或者工作时间，以实现待加热食材的加热过程的闭环控制。
一种实施例中，所述模型识别装置内置有已训练的用于离线识别的神经网络模型，所述神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
一种实施例中，所述模型识别装置还根据识别的食材体积或面积估算食材重量，所述控制装置根据待加热食材的温度、类别属性、体积大小和重量主动选择加热模式、及根据类别属性和体积大小控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率。
一种实施例中，所述采集装置为若干个摄像头，所述摄像头设置于腔室的内部，且所述腔室的内部还分别设有隔热、隔湿、透明的玻璃板，所述玻璃板将所述摄像头隐藏于玻璃板与腔室内顶角形成的密封腔内，以使待加热食材或磁控管所产生的温度/湿度与所述摄像头隔离。
一种实施例中，所述腔室内还安装有配合所述摄像头使用的照明灯，所述照明灯和摄像头的安装孔径小于3mm，当所述摄像头对待加热食材进行图像拍摄时，所述照明灯向所述待加热食材补充拍摄图像所需光源。
一种实施例中，还包括对待加热食材进行称重的称重传感器，所述称重传感器设置于所述壳体底部并位于所述加热放置区下方；
所述称重传感器与所述控制装置的输入端信号连接，所述控制装置还根据待加热食材的重量、温度和食材类型主动选择加热模式。
一种实施例中，还包括若干个温/湿度传感器，所述温/湿度传感器设置于壳体内壁，以检测待加热食材表面的温/湿度，和/或以检测腔室内部的温/湿度，所述腔室内还设有加湿部，所述电路板还根据当前检测的所述温/湿度控制所述加湿部工作，以使所述腔室或/和待加热食材保持一设定的湿度。
一种实施例中，所述腔室内安装有向所述待加热食材的放置区发射出标记点的指示灯，所述指示灯的安装孔径小于3mm，所述指示灯用以指示需要加热和进行温度测试的食材放置参考位置，或者，所述放置区上设有用以提示需要加热和进行温度测试的食材放置参考位置的标识符。
一种实施例中，所述壳体的外表面设有人机交互组件，所述人机交互组件包括但不限于触控显示屏和语音组件，所述控制装置包括主控制板和人机交互显控板；
所述人机交互显控板根据获取的待加热食材的温度和食材类型主动选择加热模式，或者通过所述人机交互组件获取被动选择的加热模式，并将所述加热模式发送至所述主控制板，所述主控制板根据加热模式控制磁控管对待加热食材进行加热；
所述人机交互显控板与所述主控制板为一体式集成结构或分体式通过线路连接，且，所述人机交互显控板还将待加热食材的温度实时反馈至所述主控制板，使得加热过程中，所述主控制板根据反馈的温度动态调整磁控管的输出功 率，以实现待加热食材的加热过程的闭环控制。
一种实施例中，还包括智能感应装置，
所述智能感应装置包括若干用于检测门体开关状态的触发电路，所述触发电路设置在所述门体和/或箱体上，待所述门体闭合时，所述触发电路接通并启动所述控制装置、采集装置、相关温度传感器、磁控管和/或风扇，实现所述智能微波炉通过关门操作对待加热食材自动识别、自动加热。
根据第二方面，提供另外一种智能微波炉，包括壳体，所述壳体的腔室内设有食物加热放置区；其特征在于，还包括但不限于：
称重传感器，设置于壳体底部并位于所述放置区下方，用于对待加热食材进行称重；
温/湿度传感器，设置于壳体的内壁上，用于检测待加热食材的温度；
食材识别装置，设置于壳体的内壁上或者外壁上，用于识别待加热食材的类型；
电路板，封装于壳体的内壁和外壁之间，与称重传感器、温/湿度传感器和食材识别装置信号连接，用于根据待加热食材的重量、温度、湿度或/和类型选择加热模式，并用于根据加热模式控制微波炉对待加热食材进行加热。
一种实施例中，智能微波炉为微烤箱(集成微波炉与烤箱功能的设备)和蒸烤箱(集成蒸箱与烤箱功能的设备)中的任一种或者为微蒸烤(集成微波炉、蒸箱与烤箱功能的设备)一体机。
根据第三方面，提供一种具有食材识别的智能设备，包括壳体，所述壳体的腔室内设有食物加热放置区，还包括：
温度传感器，设置于所述壳体的内壁上，用于检测待加热食材/腔室的温度；
采集装置，用于采集待加热食材的食物图像/或食物视频；
模型识别装置，与所述采集装置信号连接，直接接收食物图像/或将接收的食物视频转化为食物图像，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型；
控制装置，所述控制装置的输入端与所述温度传感器和模型识别装置信号连接，以根据获取的待加热食材/腔室的温/湿度和类型主动选择加热模式，所述控制装置的输出端与加热部件连接，根据主动选择的加热模式或被动选择的加热模式控制智能设备对待加热食材进行加热，且，加热过程中，控制装置根据所述温度传感器反馈的待加热食材/腔室的当前温度动态调整智能设备的输出功率或者工作时间，以实现待加热食材的加热过程的闭环控制。
一种实施例中，所述模型识别装置内置有已训练的用于离线识别的神经网 络模型，所述神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
一种实施例中，所述模型识别装置还根据识别的食材体积或面积估算食材重量，所述控制装置根据待加热食材/腔室的温/湿度、类别属性、体积大小和重量主动选择加热模式、及根据类别属性和体积大小控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率。
一种实施例中，还包括智能感应装置，所述智能感应装置包括若干用于检测门体开关状态的触发电路，所述触发电路设置在所述门体和/或箱体上，所述门体闭合时，所述触发电路接通并启动所述控制装置、采集装置、相关传感器、加热部件和/或风扇，实现所述智能设备通过关门操作对待加热食材自动识别、自动加热。
依据上述实施例的智能微波炉，由于通过对食材先进行识别，根据识别的类型主动选择加热模式，使智能微波炉无需用户手动选择加热模式就能实现自动加热，且，不论是主动选择加热还是用户选择加热，在加热过程中均通过实时反馈的食材温度，动态调整磁控管的输出功率或工作时间，以实现待加热食材的加热过程的闭环控制，通过闭环控制提高食材的口味，提高微波炉的使用体验，降低新手使用微波炉加热食材的技巧及经验。
附图说明
图1为智能微波炉结构示意图；
图2为实施例一的智能微波炉电路原理图；
图3为实施例二的智能微波炉电路原理图。
具体实施方式
下面通过具体实施方式结合附图对本实用新型作进一步详细说明。
实施例一：
本例提供一种智能微波炉，结构图如图1所示，包括壳体1、温度传感器2、采集装置3、模型识别装置和控制装置(图中未显示)，各个部件的结构及实现的功能具体描述如下。
壳体1的腔室内设有食物加热放置区11，使待加热食材放置在加热放置区11即可，另外，为了给出加热食材放置的参考位置，可以在该加热放置区11内 设置参考位置标识线，如，圆形的参考位置标识线，以提示待加热食材放置在参考位置标识线内即可；在另外一种实施例中，还可以在腔室内安装向加热放置区11发射出标记点的指示灯，该指示灯用以指示出需要加热和进行温度测试的食材放置参考位置，为了防止微波泄漏，该指示灯的安装孔径小于3mm。
温度传感器2设置于壳体1的内壁上，该内壁指的是壳体1内部的壁，可以是内侧壁、内顶壁、内顶角等，具体根据温度传感器2的类型及所要检测的温度而将温度传感器2设置于壳体1内部的相应位置，该温度传感器2可以为红外温度传感器，以测量待加热食材表面的温度；在其他实施例中，该温度传感器也可以是热敏电阻、热电偶、MEMS温度传感器等，可以采集腔体内部温度及测量待加热食材内部的温度。
采集装置3可以设置于腔室11内，也可以设置于腔室11外，采集装置3用于采集待加热食材的食物图像或食物视频，本例提供两种采集待加热食材图像的方式，一种是直接采集待加热食材的食物图像，该采集的食物图像是一个固定角度的静态图像；另一种方式是直接采集待加热食材的食物视频，然后再对该视频进行切割、整合，以获得多角度的食材图像，由于后一种方式获取的是多角度的食物图像，通过对多角度的食材图像进行识别能获得更精准的食物类型。
本例的采集装置3为若干个摄像头，若干个摄像头设置于壳体1腔室内部，本例的摄像头优选为广角摄像头。
作为一优选实施例，摄像头的位置设置在微波炉内顶部的顶角处，在顶角时摄像头能够获得较大的拍摄视角，因而数量可以至少为一个，当然根据需要也可在两个或三个顶点位置处均设置一摄像头，以实现多方位获取食材图像的目的，从而能提高参数的准确度。
以防止摄像头长时间在高温下工作发生故障，腔室的内部还分别设有隔热、隔湿、透明的玻璃板，玻璃板将摄像头隐藏于玻璃板与腔室形成的密封腔内，以使待加热食材吸收微波所产生的温度/湿度或磁控管产生的温/湿度与摄像头隔离，也即是，摄像头通过隔热的透明的玻璃板将摄像头与腔室内部隔开；另外，还可以在密封腔内加装风扇部件，以实现对摄像头工作时产生的热量进行散热。
在腔室内还设置有照明灯，优选设置在摄像头的同一侧或箱体内的顶部，该照明灯与摄像头一同启动，用于为摄像头提取清晰的食材图片，当摄像头对待加热食材进行图像拍摄时，照明灯向待加热食材补充拍摄图像所需光源。
为保证食材照片的准确性，照明灯优选白光灯，其他颜色的等虽然也能起 到照明的目的，但会影响对食材的判断。当然，摄像头的位置不局限于上述中的内部顶点处，还可以设置在顶部或侧壁，具体位置不做具体限定。照明灯的位置设置在摄像头侧或微波炉的顶部目的是防止摄像头拍照时发生逆光或食材出现阴影的问题，因此在不影响拍照效果的情况下可适当调整灯与摄像头的位置。摄像头采用MIPI或者USB等接口与控制单元相连接。
当然，本方案中摄像头的位置不局限于上述实施例中的顶点位置，其位置也可设置在微波炉内壁或顶部。
摄像头设置于外壁时主要是使得消费者可以通过识别食材方便的调用相关菜谱以及相关知识及云端的交互。
进一步的，配合摄像头使用的灯最好选用色温5000K～6500K左右的LED灯源，使得光线能够均匀的照射在食材表面，灯需要用1～3层的防高温玻璃进行隔热处理，最外层玻璃还需要进行散射处理。
如果照明灯采用卤素灯等其他光源，需要系统用软件对色温进行修正，也可以外加滤光片进行修正，如果修正的不好会降低食材识别准确率，具体解决方案视具体产品进行设置。
照明灯可放置在摄像头附近或者顶板上，灯也可以采用1～3个，视具体产品需求和配置决定。
本例采用色温为6500K的LED光源，并进行了隔热处理。
本例的模型识别装置与采集装置3信号连接，直接接收采集装置3采集的食物图像或直接接收采集装置3采集的食物视频，再将该食物视频转化为相应的食物图像(如将视频中的每N帧转化为一张图像，即可获得多张不同角度的食物图像)，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型。
模型识别装置内置有已训练的用于离线识别的神经网络模型，神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
由于本申请所采用的神经网络模型是线下通过大数据训练得到的，训练包括对大数据的采集、清洗及使用，还包括使用环境及设备的影响，如各种盛器的不同情况对食材的影响，通过相关的数据进行训练以保证最后的神经网络模型能够进行食材识别及不同盛器下的食材识别，因此，即使所采集的食物视频或食物图像除了包括食物本身还进一步包括用于存放食物的器具，如存放食物的盘子，本申请的模型识别装置也能根据采集的食物图像或器具图像识别出相 应的食材类型，如，模型识别装置通过对杯子的识别，进而实现对液体的识别。
本例的模型识别装置为离线的图像识别，这样使得智能微波炉本地化使用时识别速度更快，将无线网络传输对图像识别的影响降到最低。且，神经网络模型可以根据食材种类的变化、精度的提升等进行在线的实时更新。
控制装置的输入端与温度传感器2和匹配装置信号连接，以根据获取的待加热食材的温度和类型主动选择加热模式，控制装置的输出端与磁控管连接，根据主动选择的加热模式或被动选择的加热模式控制磁控管对待加热食材进行加热，且，加热过程中，控制装置根据温度传感器反馈的待加热食材的当前温度动态调整磁控管的输出功率或工作时间，以实现待加热食材的加热过程的闭环控制。即使是同一种食材，因体积大小不同、温度不同，所需加热模式及加热时间也不同，因此，模型识别装置还根据识别的食材体积或面积估算食材重量，控制装置根据待加热食材的温度、类别属性、体积大小和重量主动选择加热模式、及根据类别属性和体积大小控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率或加热时间。
需要说明的是，在具体应用中，模型识别装置可以与采集装置3集成在一起，也可以与控制装置集成在一起，还可以独立使用，具体采用何种方式，根据产品的具体要求而设定，本例不作特殊要求。
进一步，针对特定的应用场合，为了能直接对食物进行称重，如，对标准器具内的食物直接称重，本例还包括称重传感器，称重传感器对待加热食材进行直接称重，设置于壳体1底部并位于加热放置区11下方，称重传感器与控制装置的输入端信号连接，控制装置还根据待加热食材的重量、温度和食材类型主动选择加热模式。
进一步，为了使智能微波炉不仅具有加热食材的功能，同时还具有烹饪的功能，由于在烹饪的过程中需要控制食材的温/湿度，进一步，本例还包括若干个温/湿度传感器，温/湿度传感器可以采用几种方式，可以同时使用也可以根据不同产品需求组合进行使用，一种用于测量智能微波炉腔体内部的温度(采用热电偶、热敏电阻以及MEMS温度传感器等各种方式)；一种用于测量食材表面的温度(采用非接触式红外传感器等方式，同时给出放置食材位置的参考标记)；一种用于测量食材内部的温度(采用热电偶、热敏电阻以及MEMS温度传感器等各种方式，这里温度敏感元件需要插入待测试的食材内部)，温/度传感器可以设置在腔体内部的任何位置，以检测待加热食材表面的温/湿度，和/或以检测腔室内部的温/湿度；优选方案中，温/湿度传感器设置于壳体内侧壁的中部及中部以下位置，以检测待加热食材表面的温/湿度，和/或以检测腔室内 部的温/湿度，腔室内还设有加湿部，控制装置还根据当前检测的温/湿度控制加湿部工作，以使腔室或/和待加热食材保持一设定的湿度。
为了实现智能微波炉的人机交互功能，壳体1的外表面设有人机交互组件，该人机交互组件包括但不限于触控显示屏4和语音组件5，其中，触控显示屏4可直观显示微波炉当前的工作模式和工作时间，另外，用户通过触控显示屏4还可以直接修改微波炉当前的工作模式，如，由高火模式切换至低火模式，用户还可以通过触控显示屏4获得当前食材的相关烹饪食普或相关烹饪教程；本例的语音组件5包括麦克风和喇叭，通过语音组件5对微波炉内部及外部进行声音鉴别以实现某类食材自动加热过程和外部的语音控制，如，当某种食材加热完成后，微波炉可通过语音组件5发出相应的语音提示，或者，用户可以通过语音组件5语音选择微波炉的加热模式。
本例的微波炉的加热模式可以是控制装置根据获取的温度、食材类型、食材体积大小自主选择相应的加热模式，从微波炉的角度看，这种加热模式是微波炉主动选择的，而不是人为选择的；另外，通过设置人机交互组件，使得用户可以通过触控显示屏4或通过语音组件5选择加热模式，从微波炉的角度看，这种加热模式是微波炉被动选择的。
另外，为了实现微波炉全自动化控制，本例还包括智能感应装置，智能感应装置包括若干用于检测门体开关状态的触发电路，触发电路设置在门体和/或箱体上，待门体闭合时，触发电路接通并启动控制装置、采集装置、相关传感器、磁控管和/或风扇，实现智能微波炉通过关门操作对待加热食材自动识别、自动加热。
其中，该触发电路为一门控开关，具体可以采用机械开关、电子开关和光学开关等各种形式，安装位置可以在门上、门框上等适合的位置，保证关门信号可以及时、可靠和安全的传输。当门关闭后，门控开关处于闭合状态，并将闭合信号传递至智能感应装置中，并启动后续操作。
本实用新型中包括多种用于检测腔室内部参数的多种传感器，多种传感器与控制装置连接，且在门体处设置有一开关，当门体关闭后自动触发开关，控制装置得到开关闭合的指令后自动启动微波炉和多种传感器，根据传感器检测到的数据以及食材种类等参数自动设定加热时间和加热温度，实现全自动加热功能，避免了人为设定导致的因设定不准确导致的烹饪过度或者烹饪不到位的问题。
进一步，控制装置包括主控制板和人机交互显控板，人机交互显控板根据获取的待加热食材的温度和食材类型主动选择加热模式，或者通过人机交互组 件获取被动选择的加热模式，并将加热模式发送至主控制板，主控制板根据加热模式控制磁控管对待加热食材进行加热；人机交互显控板与主控制板为一体式集成结构或分体式通过线路连接，且，人机交互显控板还将待加热食材的温度实时反馈至主控制板，使得加热过程中，主控制板根据反馈的温度动态调整磁控管的输出功率，以实现待加热食材的加热过程的闭环控制。智能微波炉的基本原理框图如图2和图3所示。
进一步，为了实现本例的智能微波炉与云端或者其他外部终端连接，以扩展智能微波炉的应用，本例还包括无线通讯模块，无线通讯模块与人机交互显控板信号连接，该无线通讯模块可以是wifi模块，也可以是蓝牙模块、2G/3G/4G/5G模块，还可以是几个模块的组合使用，如，可以通过wifi模块连接云端，将智能微波炉的加热过程和结果上传至云端或外部终端，另外，也可以通过外部终端无线控制微波炉的加热模式，还可以通过无线通讯模块在云端下载菜谱到触控显示屏5，然后，再通过人机交互显控板根据下载的菜谱控制微波炉的加热模式。
本例中选用的各种摄像头、红外传感器、灯器件需要但不限于选用直径小于3mm的元器件，以防止发生微波泄露的问题。
实施例二：
基于实施例一，本例提一种具体应用的智能微波炉，其结构图可参考图1，包括壳体1，还包括但不限于：称重传感器、温/湿度传感器、食材识别装置、从控电路板、主控电路板；其中，壳体1的腔室内设有食物加热放置区11，称重传感器设置于壳体1底部并位于食物加热放置区下方，称重传感器用于对食物加热放置区11上承载的待加热食材进行称重；温/湿度传感器设置于壳体1的内壁上，温/湿度传感器用于检测待加热食材的温度；食材识别装置设置于壳体1的腔室内部，食材识别装置用于识别待加热食材的类型；从控电路板和主控电路板分别封装于壳体1的内壁和外壁之间，从控电路板与主控电路板两者之间通讯连接，从控电路板与称重传感器、温/湿度传感器和食材识别装置信号连接，用于根据待加热食材的重量、温度、湿度或/和类型选择加热模式，并将该加热模式传输至主控电路板，主控电路板根据加热模式主动控制微波炉对待加热食材进行加热；本例的智能微波炉能实现对待加热食材进行全自动控制加热，无需用户手动操作加热，从而提高微波炉的使用体验。本例的从控电路板其实质是实施例一的人机交互显控板，本例的主控电路板其实质是实施例一的主控制板，仅是名称的文字上的描述不同，其工作原理相同，也可以将人控制电路板称为人机交互显控板，将主控电路板称为主控制板。
本例的食材识别装置集成了实施例一中的采集装置和匹配装置的功能，即，食材识别装置具有采集图像和识别图像的功能，进一步，食材识别装置包括若干个摄像头，若干个摄像头设置于壳体1腔室内部的任何位置，只要能采集到食物即可，本例的摄像头优选为广角摄像头，该广角摄像头集成了图像识别算法的电路板(该电路板与实施例一的模型识别装置相对应)，通过该图像识别算法对广角摄像头采集的待加热食材的图像进行离线的智能识别，可以识别出所需要加热的食材类别，比如包子、馒头、液体、鸡腿、鱼等家庭常用的食材；图像识别算法可以利用无线网络从云端进行在线的模型更新(比如增加了食材种类或者提高了识别精度的模型)。
该图像识别算法采用了人工智能技术，利用神经网络和大数据进行模型的训练，然后在本地进行离线的模型使用，即离线的图像识别，这样使得智能设备本地化使用时识别速度更快，同时将无线网络传输对图像识别的影响降到最低。模型可以根据食材种类的变化、精度的提升等进行在线的实时更新。
识别出食材类别后再根据获得的食材温度、重量等参数对食材进行自动加热(控制加热的功率和时间)，待加工食材在放入智能设备并关门后可进入全自动控制过程，使得烹饪体验显著提升；同时也可以利用语音、触控显示屏等交互方式对智能设备进行控制。
另外，针对具有包装的食材，摄像头还可以识别该包装上的二维码或条形码以识别食材的类型，进而对待加热食材根据对应的程序进行自动的控制；摄像头的具体安装请参考实施例一，在此不作赘述。
进一步，为了降低对待加热食材的温/湿度检测的误差，本例的温/湿度传感器的数量为若干个，优先的，本例的温/湿度传感器的数量为两个，分别设置于壳体1腔室的相对侧壁上，在其他实施例中，也可以设置大于两个的温/湿度传感器，以及以其他排布方式安装温/湿度传感器，只要能达到精确检测待加热食材与腔体的温/湿度即可。
其中温/湿度传感器可以采用几种方式，可以同时使用也可以根据不同产品需求组合进行使用，一种用于测量智能微波炉腔体内部的温度(采用热电偶、热敏电阻以及MEMS温度传感器等各种方式)；一种用于测量食材表面的温度(采用非接触式红外传感器等方式，同时给出放置食材位置的参考标记)；一种用于测量食材内部的温度(采用热电偶、热敏电阻以及MEMS温度传感器等各种方式，这里温度敏感元件需要插入待测试的食材内部)。
从控电路板根据待加热食材的重量、温度、湿度及类型选择加热模式，然后，将该加热模式传输至主控电路板，主控电路板根据该加热模式控制磁控管 组件工作，对待加热食材进行主动加热。
需要说明的是，在其他实施例中，还可以在壳体1内增加其他传感器，如气味传感器，通过多种类型传感器对待加热食材进行全方位感知和测量，从控电路板根据全方位感知和测量的结果综合选择最佳的加热模式，达到微波炉对食材进行最优的加热。
本例中选用的各种摄像头、红外传感器、灯器件需要但不限于选用直径小于3mm的元器件，以防止发生微波泄露的问题。
为了使智能微波炉具有多样化设计，本例的从控电路板和主控电路板为两个独立的电路板，并通过线路通讯连接，可以根据实际需要对从控电路板进行其他功能设计的扩展，使智能微波炉能实现相应功能的智能控制。在其他实施例中，主控电路板和从控电路板也是一体式集成设计，具体情况，主控电路板和从控电路板是集成设计还是分离设计根据微波炉的研发设计及用户实际需求而具体设定，不作具体限定。
需要说明的是，在本例的构思下，本领域技术人员通过变换也可以实现微波炉的智能控制，如，在其他实施例中，智能微波炉可以不设置称重传感器和温/湿度传感器，如，智能微波炉可以仅包括食材识别装置，即从控电路板通过类型选择加热模式；或者，在其他实施例中，智能微波炉可以设置称重传感器或温/湿度传感器，这样，从控电路板通过重量和类型或者温湿度和类型选择加热模式。
本领域技术人员在本例的构思下，通过变换，可以将智能微波炉制成微烤箱和微蒸箱中的任一种或者制成微蒸烤一体机。
实施例三
本实用新型提供了一种具有食材识别的智能设备，智能设备包括但不局限于微烤箱和微蒸箱中的任一种或者为微蒸烤一体机，关于智能设备全自动识别食材、加热食材的具体详细细节请参考实施例一，本例不作赘述，本例仅介绍智能设备的基本组成及基本工作方式。
智能设备的壳体的腔室内设有食物加热放置区，其还包括：
温度传感器，设置于壳体的内壁上，用于检测待加热食材/腔室的温度，与实施例一相对应，本例的内壁也是指壳体内腔的壁，并不限定为内侧壁或内顶壁，也即是，温度传感器设置于壳体的内部达到检测温度即可，本例的温度传感器的类型及测温方式请参考实施例一，此处不作赘述，关于是检测加热食材的温度还是腔室内的温度是根据智能设备的具体类型而定的，如，若智能设备是烤箱类，则只需要检测烤箱腔室内的温度即可，若智能设备是微蒸箱类，则 可以检测待加热食材的温度；
采集装置，用于采集待加热食材的食物图像/或食物视频；本例的采集装置为若干个摄像头，当摄像头设置于腔室的内部时，腔室的内部还分别设有隔热、隔湿、透明的玻璃板，玻璃板将摄像头隐藏于玻璃板与腔室形成的密封腔内，以使待加热食材或加热部件所产生的温度/湿度与摄像头隔离；本例的采集装置的具体工作方式、安装方式请参考实施例一，此处不作赘述。
模型识别装置，与采集装置信号连接，直接接收食物图像/或将接收的食物视频转化为食物图像，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型；
控制装置，控制装置的输入端与温度传感器和模型识别装置信号连接，以根据获取的待加热食材/腔室的温/湿度和类型主动选择加热模式，控制装置的输出端与加热部件连接，根据主动选择的加热模式或被动选择的加热模式控制智能设备对待加热食材进行加热，且，加热过程中，控制装置根据温度传感器反馈的待加热食材/腔室的当前温度动态调整智能设备的输出功率或者工作时间，以实现待加热食材的加热过程的闭环控制。
其中，模型识别装置内置有已训练的用于离线识别的神经网络模型，神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
模型识别装置还根据识别的食材体积或面积估算食材重量，控制装置根据待加热食材/腔室的温度、类别属性、体积大小和重量主动选择加热模式、及根据类别属性和体积大小控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率或加热时间。
本例还包括智能感应装置，智能感应装置包括若干用于检测门体开关状态的触发电路，触发电路设置在所述门体和/或箱体上，门体闭合时，触发电路接通并启动控制装置、采集装置、相关传感器、加热部件和/或风扇，实现智能设备通过关门操作对待加热食材自动识别、自动加热。本例的加热部件可以是磁控管、石英管/石墨管、电阻丝等，具体根据智能设备的具体类型而定。
由于结合相关传感器、采集装置、控制装置对待加热食材的部分属性进行鉴别，使智能设备根据鉴别的温度和类型对待加热食材自动加热，无需用户手动操作选择加热模式，提高其使用体验。
以上应用了具体个例对本实用新型进行阐述，只是用于帮助理解本实用新型，并不用以限制本实用新型。对于本实用新型所属技术领域的技术人员，依 据本实用新型的思想，还可以做出若干简单推演、变形或替换。

Claims (15)

  1. 一种智能微波炉，包括壳体，所述壳体的腔室内设有食物加热放置区，其特征在于，还包括：
    温度传感器，设置于壳体的内壁上，用于测量待加热食材的温度；
    采集装置，用于采集待加热食材的食物图像/或食物视频；
    模型识别装置，与所述采集装置信号连接，直接接收食物图像/或将接收的食物视频转化为食物图像，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型；
    控制装置，所述控制装置的输入端与所述温度传感器和匹配装置信号连接，以根据获取的待加热食材的温度和类型主动选择加热模式，所述控制装置的输出端与磁控管连接，根据主动选择的加热模式或被动选择的加热模式控制磁控管对待加热食材进行加热，且，加热过程中，控制装置根据所述温度传感器反馈的待加热食材的当前温度动态调整磁控管的输出功率或者工作时间，以实现待加热食材的加热过程的闭环控制。
  2. 如权利要求1所述的智能微波炉，其特征在于，所述模型识别装置内置有已训练的用于离线识别的神经网络模型，所述神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
  3. 如权利要求2所述的智能微波炉，其特征在于，所述模型识别装置还根据识别的食材体积或面积估算食材重量，所述控制装置根据待加热食材的温度、类别属性、体积大小和重量主动选择加热模式、及根据类别属性、体积大小和重量控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率或加热时间。
  4. 如权利要求1所述的智能微波炉，其特征在于，所述采集装置为若干个摄像头，所述摄像头设置于腔室的内部，且所述腔室的内部还分别设有隔热、隔湿、透明的玻璃板，所述玻璃板将所述摄像头隐藏于玻璃板与腔室形成的密封腔内，以使待加热食材或磁控管所产生的温度/湿度与所述摄像头隔离。
  5. 如权利要求4所述的智能微波炉，其特征在于，所述腔室内还安装有配合所述摄像头使用的照明灯，所述照明灯和摄像头的安装孔径小于3mm，当所述摄像头对待加热食材进行图像拍摄时，所述照明灯向所述待加热食材补充拍摄图像所需光源。
  6. 如权利要求1所述的智能微波炉，其特征在于，还包括对待加热食材进行称重的称重传感器，所述称重传感器设置于所述壳体底部并位于所述加热放 置区下方；
    所述称重传感器与所述控制装置的输入端信号连接，所述控制装置还根据待加热食材的重量、温度和食材类型主动选择加热模式。
  7. 如权利要求1所述的智能微波炉，其特征在于，还包括若干个温/湿度传感器，所述温/湿度传感器设置于壳体内壁，以检测待加热食材表面的温/湿度，和/或以检测腔室内部的温/湿度，所述腔室内还设有加湿部，所述控制装置还根据当前检测的所述温/湿度控制所述加湿部工作，以使所述腔室或/和待加热食材保持一设定的湿度。
  8. 如权利要求1所述的智能微波炉，其特征在于，所述腔室内安装有向所述待加热食材的放置区发射出标记点的指示灯，所述指示灯的安装孔径小于3mm，所述指示灯用以指示需要加热和进行温度测试的食材放置参考位置，或者，所述放置区上设有用以提示需要加热和进行温度测试的食材放置参考位置的标识符。
  9. 如权利要求1所述的智能微波炉，其特征在于，所述壳体的外表面设有人机交互组件，所述人机交互组件包括但不限于触控显示屏和语音组件，所述控制装置包括主控制板和人机交互显控板；
    所述人机交互显控板根据获取的待加热食材的温度和食材类型主动选择加热模式，或者通过所述人机交互组件获取被动选择的加热模式，并将所述加热模式发送至所述主控制板，所述主控制板根据加热模式控制磁控管对待加热食材进行加热；
    所述人机交互显控板与所述主控制板为一体式集成结构或分体式通过线路连接，且，所述人机交互显控板还将待加热食材的温度实时反馈至所述主控制板，使得加热过程中，所述主控制板根据反馈的温度动态调整磁控管的输出功率，以实现待加热食材的加热过程的闭环控制。
  10. 如权利要求1所述的智能微波炉，其特征在于，还包括智能感应装置，
    所述智能感应装置包括若干用于检测门体开关状态的触发电路，所述触发电路设置在所述门体和/或箱体上，待所述门体闭合时，所述触发电路接通并启动所述控制装置、采集装置、相关传感器、磁控管和/或风扇，实现所述智能微波炉通过关门操作对待加热食材自动识别、自动加热。
  11. 一种智能微波炉，包括壳体，所述壳体的腔室内设有食物加热放置区；其特征在于，还包括但不限于：
    称重传感器，设置于壳体底部并位于所述放置区下方，用于对待加热食材进行称重；
    温/湿度传感器，设置于壳体的内壁上，用于检测待加热食材的温度；
    食材识别装置，设置于壳体的内壁上，用于识别待加热食材的类型；
    电路板，封装于壳体的内壁和外壁之间，与称重传感器、温/湿度传感器和食材识别装置信号连接，用于根据待加热食材的重量、温度、湿度或/和类型选择加热模式，并用于根据加热模式控制微波炉对待加热食材进行加热。
  12. 一种具有食材识别的智能设备，包括壳体，所述壳体的腔室内设有食物加热放置区，其特征在于，还包括：
    温度传感器，设置于所述壳体的内壁上，用于检测待加热食材/腔室的温度；
    采集装置，用于采集待加热食材的食物图像/或食物视频；
    模型识别装置，与所述采集装置信号连接，直接接收食物图像/或将接收的食物视频转化为食物图像，通过算法模型提取食物图像的特征点并进行特征点匹配，以识别出待加热食材的类型；
    控制装置，所述控制装置的输入端与所述温度传感器和模型识别装置信号连接，以根据获取的待加热食材/腔室的温/湿度和类型主动选择加热模式，所述控制装置的输出端与加热部件连接，根据主动选择的加热模式或被动选择的加热模式控制智能设备对待加热食材进行加热，且，加热过程中，控制装置根据所述温度传感器反馈的待加热食材/腔室的当前温度动态调整智能设备的输出功率或者工作时间，以实现待加热食材的加热过程的闭环控制。
  13. 如权利要求12所述的智能设备，其特征在于，所述模型识别装置内置有已训练的用于离线识别的神经网络模型，所述神经网络模型的训练集包括大数据的食材和/或食材盛器图像集，使已训练的神经网络模型根据采集的食物图像的特征点和/或盛器图像的特征点识别出食材的类别属性和/或食材体积。
  14. 如权利要求13所述的智能微波炉，其特征在于，所述模型识别装置还根据识别的食材体积或面积估算食材重量，所述控制装置根据待加热食材/腔室的温/湿度、类别属性和体积大小主动选择加热模式、及根据类别属性、体积大小和重量控制主动选择或被动选择的加热模式所需的加热时间、及根据反馈的温度闭环控制加热模式所需的加热功率。
  15. 如权利要求12所述的智能设备，其特征在于，还包括智能感应装置，所述智能感应装置包括若干用于检测门体开关状态的触发电路，所述触发电路设置在所述门体和/或箱体上，所述门体闭合时，所述触发电路接通并启动所述控制装置、采集装置、相关传感器、加热部件和/或风扇，实现所述智能设备通过关门操作对待加热食材自动识别、自动加热。
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