Device for controlling the particle size of a food preparation and method for using the food preparation device

Abstract

The present invention relates to a food preparation device (1) comprising: - at least one mechanical wave sensor (4), such as an accelerometer or a microphone; and - means for identifying the initial nature and / or physical properties before transformation of the one or more ingredients (A, AB) introduced into a container (3), wherein the signal delivered by the at least one mechanical wave sensor (4), and data relating to the initial nature and / or physical properties before transformation of the one or more ingredients (A, AB) introduced into the container (2), are sent to signal processing means (5), wherein the signal processing means (5) is intended to determine a result relating to a particle size level of the one or more ingredients (A, AB) after transformation by at least one tool (3), and wherein this result influences the operation of the food preparation device (1).

Description

Title of the invention: APPARATUS FOR CONTROLLING THE GRANULOMETRY OF A CULINARY PREPARATION AND METHOD FOR USING SAID CULINARY PREPARATION APPARATUS Technical field

[0001] The present invention relates to the general technical field of culinary preparation.

[0002] More particularly, the present invention relates to a food preparation appliance capable of delivering information on a level of granulometry of the ingredients introduced into the container of the food preparation appliance after their transformation, as well as to a method of using such an appliance. State of the art

[0003] It is known to have a kitchen appliance to mix ingredients.

[0004] Such a cooking appliance is for example a blender or a food processor and comprises, in a known manner, a container in the form of a bowl or a tank arranged to receive the ingredients of said preparation, a tool arranged to rotate inside said container in order to mix said ingredients, a motor arranged to drive the tool in rotation in the container, and a motor control interface.

[0005] Such a device is satisfactory in that it allows the function of mixing the ingredients of a preparation to be easily carried out.

[0006] However, such a kitchen appliance does not allow targeting a particular level of granulometry of the culinary preparation resulting from the processing of the ingredients.

[0007] However, a user can more or less appreciate the culinary preparation depending on this granulometry.

[0008] It is known from document EP3854277 to use an optical or ultrasonic sensor taking a measurement directly on the preparation to monitor its particle size.

[0009] However, such a system necessarily requires orienting the sensor directly towards the inside of the bowl.

[0010] It is also known from document US7591438 to carry out measurements electrical directly on the motor's power supply to determine, during operation, information on the particle size of the preparation placed inside the bowl.

[0011] Such a solution may be appropriate for devices used to repeatedly process ingredients of the same nature and with the same physical properties, for example ice cubes.

[0012] However, this solution can be inaccurate because the signal variation can be influenced by several factors other than the particle size of the preparation inside the bowl. The signal can also be affected by electrical interference or noise, which can make accurate analysis difficult without proper filtering or processing of the data.

[0013] Also, the present invention aims to resolve all or part of the drawbacks mentioned above, in particular by proposing a culinary preparation appliance capable of providing information on the particle size of the ingredients introduced into the container of the culinary preparation appliance after their transformation. Summary of the invention

[0014] To this end, the invention has as its first object a culinary preparation appliance comprising: - a container, for example a bowl or a tub, designed to receive one or more ingredients of a culinary preparation, - at least one tool for transforming the ingredient(s) introduced into the container from an initial state to a transformed state beyond a force threshold determined by the action of the tool on the ingredient(s), - an electric motor (M) arranged to drive the tool in rotation inside the container, - a control module (8) arranged to control the speed of the motor (M) and therefore of the tool, characterized in that the food preparation appliance further comprises: - at least one mechanical wave sensor, such as an accelerometer or a microphone, and - means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container, and in that the signal delivered by the at least one mechanical wave sensor, and data on the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container are sent to signal processing means, the signal processing means being intended to determine a result relating to a level of granulometry of the ingredient(s) after transformation by the at least one tool, this result having an influence on the operation of the culinary preparation appliance.

[0015] This arrangement allows a user to target a particular grain size level of the culinary preparation resulting from the processing of the ingredient(s). The mechanical wave sensor is a reliable alternative to other more conventional types of sensors such as those based on electrical measurements on the power supply of the electric motor.

[0016] According to one aspect of the invention, the food preparation appliance comprises a user interface in communication with the signal processing means and arranged to provide, before processing, a level of granulometry desired by the user, of the ingredient(s) introduced into the container, and / or to provide, during the processing of the ingredient(s), at least one piece of information intended for the user correlated with the result determined by the signal processing means, including at least one piece of information relating to the achievement of a level of granulometry desired by the user.

[0017] This arrangement allows the user to easily enter a desired granulometry level and therefore automate the processing of the ingredient(s) and / or monitor the processing of the ingredient(s) and stop the processing of the ingredient(s) when the user wishes.

[0018] According to one aspect of the invention, the user interface comprises means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container, these being declared by the user.

[0019] This provision simplifies the declaration of identification of the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0020] According to one aspect of the invention, the user interface comprises visual and / or audio means for informing the user about the achievement of at least two different levels of granulometry.

[0021] This arrangement allows the user to easily monitor the achievement of at least two different levels of granulometry.

[0022] According to one aspect of the invention, the user interface comprises means for selecting by the user a desired granulometry level determined from a list of granulometry levels.

[0023] This arrangement allows the user to be guided in their choice of desired particle size for the ingredient(s) introduced into the container.

[0024] According to one aspect of the invention, the electronic module is arranged to interrupt the electrical supply to the motor when the granulometry level has reached the granulometry level desired by the user.

[0025] This arrangement makes it possible to automate the transformation of the ingredient(s) into a particle size desired by the user.

[0026] According to one aspect of the invention, the initial physical properties before processing of the ingredient(s) comprise at least the initial particle size level before processing of the ingredients.

[0027] This provision defines the minimum initial conditions necessary to enable the signal processing means to determine the different levels of granulometry during transformation.

[0028] According to one aspect of the invention, the means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container comprise a camera arranged to film or take images of the ingredient(s) introduced into the container, dedicated processing means using an artificial intelligence model being used to identify the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0029] This arrangement makes it possible to automate the identification of the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0030] According to one aspect of the invention, the at least one mechanical wave sensor is arranged to measure, during the transformation of the ingredient(s), the vibration emitted by the appliance in its environment and / or the vibrations inside the food preparation appliance.

[0031] This arrangement allows the acquisition of a signal in an optimal manner for processing by the signal processing means. It is the vibration of all or part of the food preparation appliance which can thus be measured by the mechanical wave sensor.

[0032] According to one aspect of the invention, the culinary preparation appliance comprises the means for processing the signal delivered by the at least one mechanical wave sensor, and data on the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0033] This arrangement simplifies the food preparation appliance and eliminates any issues related to the connectivity of the food preparation appliance with remote signal processing means. Information on the result of the transformation is also provided in real time.

[0034] According to one aspect of the invention, the signal processing means use an artificial intelligence model, in particular by machine learning.

[0035] This arrangement allows signal processing means to cover a wide variety of situations involving a large number of different ingredients.

[0036] According to one aspect of the invention, the artificial intelligence model is deployed: - during the design of the device and loaded into the signal processing means during the production phase of the food preparation device, and / or - by updating the firmware of the signal processing means of the food preparation appliance during use.

[0037] This arrangement makes it possible to integrate a model directly during production and / or to develop this model during use by the user.

[0038] According to one aspect of the invention, the artificial intelligence model is trained during the transformation of the ingredient(s) introduced into the container of the food preparation appliance.

[0039] This arrangement allows taking advantage of the use of the food preparation device to enrich the model used by artificial intelligence.

[0040] According to one aspect of the invention, the signal processing means use the frequency spectrum measured during the transformation by the at least one mechanical wave sensor to determine the result relating to the particle size of the ingredient(s) after transformation by the at least one tool.

[0041] This arrangement allows the use of data that can be easily acquired.

[0042] The present invention also has as a second object a culinary preparation system comprising: - a food preparation appliance as described above, connected to a communications network, and - means for processing the signal delivered by the at least one mechanical wave sensor, and data on the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container, arranged on another device connected to the same communication network as the food preparation device or on a remote server connected to the same communication network as the food preparation device.

[0043] This arrangement allows for the development of a system in which the signal processing means are not integrated into the food preparation appliance. The signal processing means can thus be constantly updated by a service provider.

[0044] According to one aspect of the invention, the system further comprises dedicated processing means using an artificial intelligence model to identify the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0045] This arrangement makes it possible to develop a system in which the dedicated processing means using an artificial intelligence model to identify the nature and / or initial physical properties before transformation of the ingredients introduced into the container would not be integrated into the food preparation appliance. The dedicated processing means can thus be constantly updated by a service provider.

[0046] According to one aspect of the invention, the signal processing means use an artificial intelligence model by machine learning.

[0047] According to one aspect of the invention, the artificial intelligence model is trained during the transformation of the ingredient(s) introduced into the container of the food preparation appliance.

[0048] This arrangement makes it possible to take advantage of the use of the food preparation appliance to enrich the model used by artificial intelligence, this model being able to be used by all users of different food preparation appliances in communication with the signal processing means.

[0049] According to one aspect of the invention, the means for processing the signal delivered by the at least one mechanical wave sensor, and data on the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container use the frequency spectrum measured during the transformation by the at least one mechanical wave sensor to determine the result relating to the particle size of the ingredient(s) after transformation by the at least one tool.

[0050] This arrangement allows the use of data that can be easily acquired.

[0051] The present invention also has as a third object a method of using a culinary preparation appliance as described previously, comprising the following steps: - start the food preparation appliance; - use a manual mode or select a program to prepare a meal; - identify the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container; - transform the ingredient(s) in manual mode or when the program reaches a stage requiring the transformation of the ingredient(s), - determine a result relating to a level of granulometry of the ingredient(s) after transformation by the at least one tool as a function of the signal delivered by the at least one mechanical wave sensor, and data on the nature and / or initial physical properties before transformation of the ingredient(s) introduced into the container.

[0052] This implementation makes it possible to easily determine a result relating to a level of granulometry of the ingredient(s) after transformation by at least one tool.

[0053] According to one implementation of the method, before transformation the user enters on a user interface a desired level of granulometry of the ingredient(s) introduced into the container and the electrical power supply to the motor is interrupted by the control module when the level of granulometry of the ingredient(s) introduced into the container has reached the level of granulometry desired by the user, and / or a user interface delivers in real time during the transformation information intended for the user correlated with the result determined by the signal processing means including information relating to the achievement of a level of granulometry desired by the user.

[0054] This arrangement allows the user to easily enter a desired granulometry level and therefore automate the processing of the ingredient(s) and / or monitor the processing of the ingredient(s) and stop the processing of the ingredient(s) when the user wishes.

[0055] According to one implementation of the method, during the transformation the signal processing means acquire data provided by the at least one mechanical wave sensor, to train the model of an artificial intelligence used by the signal processing means in order to deliver on the user interface the information intended for the user correlated with the result determined by the signal processing means including information relating to the achievement of a level of granulometry desired by the user.

[0056] This implementation allows taking advantage of the use of the food preparation device to enrich the model used by artificial intelligence. Brief description of the figures

[0057] The aims, aspects and advantages of the present invention will be better understood from the description given below of a particular embodiment of the invention presented by way of non-limiting example, with reference to the appended drawings in which:

[0058] Figure 1 is an overview of an example of a food preparation appliance according to the invention, in particular a blender;

[0059] Figure 2 is an illustration of a first result of transformation of fines according to a first level of granulometry obtained from a culinary preparation apparatus or system according to the invention;

[0060] Figure 3 illustrates the shape of a frequency spectrum obtained from a fast Fourier transformation of the signal from a vibration sensor measured along a first representative axis and corresponding to the first level of granulometry obtained from a culinary preparation device or system according to the invention;

[0061] Figure 4 is an illustration of a first result of transformation of fines according to a second level of granulometry obtained from a culinary preparation apparatus or system according to the invention;

[0062] Figure 5 illustrates the shape of a frequency spectrum obtained from a fast Fourier transformation of the signal from a vibration sensor measured along a first representative axis and corresponding to the second level of granulometry obtained from a culinary preparation appliance or system according to the invention;

[0063] Figure 6 is an illustration of a first result of transformation of fines according to a third level of granulometry obtained from a culinary preparation apparatus or system according to the invention;

[0064] Figure 7 illustrates the shape of a frequency spectrum obtained from a fast Fourier transformation of the signal from a vibration sensor measured along a first representative axis and corresponding to the third level of granulometry obtained from a preparation device or system culinary according to the invention;

[0065] Figure 8 illustrates a first embodiment of a culinary preparation system according to the invention;

[0066] Figure 9 illustrates a second embodiment of a culinary preparation system according to the invention;

[0067] Figure 10 illustrates a third embodiment of a culinary preparation system according to the invention;

[0068] As illustrated in Figure 1, a food preparation appliance 1 according to the invention may be a blender comprising a container 2, in particular a bowl in the case of a blender, arranged to receive the ingredient(s) A, AB of a food preparation. Of course, the present invention is not limited to a blender but finds an application with all food preparation appliances 1 capable of transforming the ingredient(s) A, AB, in particular their level of granulometry. Thus, a food preparation appliance 1 according to the invention could also be a food processor.

[0069] Such a culinary preparation appliance 1 further comprises at least one tool 3 for transforming one or more ingredients A, AB introduced into the container 2 from an initial state to a transformed state AND beyond a force threshold determined by the action of the tool 3 on the ingredient(s) A, AB. In other words, there is a force threshold specific to each ingredient A or combination of ingredients AB beyond which the tool transforms the ingredient A or the combination of ingredients AB from an initial state before introduction into the container 2 to another transformed state AND following the action of the tool 3 on said ingredient A or on said combination of ingredients AB.

[0070] In a known manner, such a food preparation appliance 1 also comprises an electric motor M arranged to drive the tool 3 in rotation inside the container 2, and a control module 8 arranged to control the speed of the motor and therefore of the tool 3.

[0071] The engine can be of several types, including the M engine type universal or a brushless synchronous motor commonly referred to as a brushless motor.

[0072] The control module 8 corresponds to the type of motor M used. It may in particular include a rotor position sensor for motor M.

[0073] The food preparation appliance 1 further comprises at least one mechanical wave sensor 4.

[0074] A mechanical wave is a disturbance that propagates in a material medium, with energy transport but without matter transport. Such mechanical waves can be detected, for example, by an accelerometer when the disturbance propagates on an element of the food preparation appliance 1 or a microphone if the disturbance moves in the air.

[0075] In the example illustrated in Figure 1, the food preparation appliance 1 is equipped with a microphone 4a arranged on the skirt of the food preparation appliance 1 near the bowl. This microphone 4a picks up the sound vibrations emitted in the environment close to the bowl.

[0076] As previously stated, other types of mechanical wave sensors 4 may be used without departing from the scope of the invention, in particular an accelerometer arranged on the inner surface of the skirt of the blender. Such an arrangement of the mechanical wave sensor 4 also makes it invisible to the user's eyes.

[0077] The food preparation appliance 1 also comprises means for identifying the nature and / or physical properties in their initial state AND before transformation into a transformed state AND of the ingredient(s) A, AB introduced into the container 2. The nature of the ingredient(s) A, AB generally defines their name. In the example proposed, the nature of ingredient A is “almond”. All kinds of ingredients A, AB that can undergo transformation by the tool 3 of the food preparation appliance 1 can be defined by their nature. A combination of ingredients AB could also be defined by their nature, for example a combination with almonds A and walnuts B where the proportions of each ingredient in the combination would be known, for example 60% almonds by weight and 40% walnuts by weight.

[0078] The initial physical properties before processing of the ingredient(s) A, AB introduced into the container 2 are also identified. Such physical properties may relate to the quantity of ingredients, their size, their shape or specific surface area, their mass, etc. In the case of a combination of ingredients AB, these physical properties also include the relative proportions of each of the ingredients within this combination of ingredients AB, for example 150 grams of whole almonds and 100 grams of whole walnuts. These initial properties include at least the initial particle size level before processing of the ingredient(s) A, AB.

[0079] The identification of the nature and / or physical properties of the ingredient(s) A, AB in their initial state can be declared by a user or determined automatically.

[0080] In the case of an automatic determination, the means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) A, AB introduced into the container 2 comprise a camera arranged to film or take images of the ingredient(s) A, AB introduced into the container 2. Dedicated processing means 9 using an artificial intelligence model are used to identify the nature and / or initial physical properties before transformation of the ingredient(s) A, AB introduced into the container 2.

[0081] These processing means 9 dedicated to the identification of the nature and / or the physical properties of the ingredient(s) A, AB in their initial state may be integrated into the culinary preparation appliance 1 or not be integrated into the culinary preparation appliance 1 as illustrated in figures 9 and 10.

[0082] In particular, these dedicated processing means 9 can be arranged on a remote server accessible directly by the food preparation appliance 1 or via a communication gateway, in particular a smartphone.

[0083] The signal delivered by the at least one mechanical wave sensor 4 as well that data on the nature and / or physical properties in their initial state before transformation to a transformed state AND of ingredient A or of the combination of ingredients AB introduced into the container 2 are sent to signal processing means 5.

[0084] These signal processing means 5 are intended to determine a result relating to a level of granulometry NI, N2, N3 of the ingredient(s) A, AB after transformation by the at least one tool 3, this result having an influence on the operation of the culinary preparation appliance 1.

[0085] As illustrated in Figures 8 or 9, these signal processing means 5 can also be integrated into the food preparation appliance 1 or not be integrated into the food preparation appliance 1 as illustrated in Figure 10.

[0086] In particular, these signal processing means 5 can be arranged on a remote server accessible directly by the food preparation appliance 1 or via a communication gateway, in particular a smartphone. In the case of remote processing, the signal delivered by the at least one mechanical wave sensor 4 is transmitted in real time so as to avoid a lag between the information given in real time by the at least one mechanical wave sensor 4 and the result determined by the signal processing means 5.

[0087] In order to avoid such a shift, the signal processing means 5 are preferably integrated into the food preparation appliance 1 as illustrated in Figures 8 and 9.

[0088] In the case where the signal processing means 5 are not integrated into the culinary preparation appliance 1 then the combination of the culinary preparation appliance 1 and the signal processing means 5 would form a culinary preparation system 10. This culinary preparation system 10 could also furthermore integrate the dedicated processing means 9 for identifying the nature and / or the physical properties of the ingredient(s) in their initial state.

[0089] Signal processing means 5 use an artificial intelligence model, notably through machine learning.

[0090] This artificial intelligence model is deployed: - during the design of the device and loaded into the signal processing means 5 during the production phase of the food preparation device 1, and / or - by updating the firmware of the signal processing means 5 of the food preparation appliance 1 during the use phase.

[0091] A food preparation appliance 1 connected directly or indirectly to a remote server will thus have the possibility of being able to evolve by increasing the precision and variety of the results determined by the signal processing means 5.

[0092] It is also possible to train the artificial intelligence model during the transformation of the ingredient(s) A, AB introduced into the container 2 of the food preparation appliance 1. For this, it will be important that the user correctly declares the nature and / or the initial physical properties before transformation of the ingredient(s) A, AB introduced into the container 2 but that he also declares that the result determined by the processing means 5 is indeed in correspondence with the desired result. In any event, the user will have the possibility of refining this result as he trains the artificial intelligence model.

[0093] As mentioned above, the result determined by the signal processing means 5 has an influence on the operation of the food preparation appliance 1 as will be explained below.

[0094] As illustrated in Figure 1, a food preparation appliance 1 may further comprise a user interface HMI in communication with the signal processing means 5.

[0095] The HMI user interface may include means of identifying the nature and / or initial physical properties before processing of the ingredient(s) A, AB introduced into the container 2, so that the user can declare this nature and / or these initial physical properties.

[0096] For this purpose, the HMI user interface may comprise a control interface 6 allowing a user to control the food preparation appliance 1, in particular to select or create preparation programs, and a display device 7 to allow the user to view information on the operation of the food preparation appliance 1.

[0097] This control interface 6 comprises, for example, control buttons allowing interaction with menus displayed on the display device 7.

[0098] Furthermore, the display device 7 may be touch-sensitive in order to simplify the control interface of one or more control buttons and could even fully integrate the control interface 6.

[0099] The control interface 6 and the display device 7 are in communication with the signal processing means 5.

[0100] The control interface 6 can be used to enter, before processing, a granulometry level desired by the user determined from a list of granulometry levels N1, N2, N3 of the ingredient(s) A, AB introduced into the container 2.

[0101] In this case, the electronic module 8 is arranged to interrupt the electrical supply to the motor when the granulometry level N1, N2, N3 has reached the granulometry level desired by the user.

[0102] The display device 7 can also provide, during the transformation of the ingredient(s) A, AB, at least one piece of information intended for the user, correlated with the result determined by the signal processing means, including at least one piece of information relating to the achievement of a level of granulometry N1, N2, N3 desired by the user.

[0103] This information can for example be displayed on visual means of the display device 7 of the type of light meter or bargraph indicating the evolution of the level of granulometry N1, N2, N3 of the ingredient(s) A, AB transformed inside the container 2 and the level of granulometry N1, N2, N3 desired by the user so that the user can know when the level of granulometry N1, N2, N3 of the ingredient(s) A, AB has reached the desired level of granulometry N1, N2, N3.

[0104] Alternatively or in a complementary manner, the information can also be delivered in sound form by emitting a sound when the granulometry level N1, N2, N3 has reached the desired granulometry level N1, N2, N3.

[0105] As illustrated in figures 3, 5 and 7, the signal processing means 5 use the frequency spectrum SF measured during the transformation by the at least one mechanical wave sensor 4 to determine the result relating to the particle size N1, N2, N3 of the ingredient(s) A, AB after transformation by the at least one tool 3.

[0106] Typically this frequency spectrum is obtained from a fast Fourier transform of the signal measured by at least one mechanical wave sensor, typically a vibration sensor. This signal is measured along a representative axis, preferably the axis on which the vibrations have the greatest amplitude. The Fourier transform is also averaged in order to reduce the weighting that would be due to the presence of harmonics.

[0107] In the example shown, the user wants to process A almonds and can choose from three different granulometry levels: chopped N1, crushed N2 and fine grains N3.

[0108] The user begins by entering, via the control interface 6, the nature and / or initial physical properties before transformation of the ingredient(s) A, AB introduced into the container 2.

[0109] Thus, the user declares to introduce into the container for example a quantity of 300 grams of whole almonds. As mentioned above, it is also possible that the nature and / or initial physical properties before processing of the ingredient(s) A, AB introduced into the container 2 could be determined automatically using a camera arranged to film or take images of the ingredient(s) A, AB introduced into the container 2, dedicated processing means 9 using an artificial intelligence model being used to identify the nature and / or initial physical properties before processing of the ingredient(s) A, AB introduced into the container 2.

[0110] The user then has at least one of the following two operating modes of the food preparation appliance 1: either he indicates a desired transformation state ET directly on the control interface 6, or he decides to observe the evolution of the granulometry of the almonds A on the display device 7 and to interrupt the action of the tool 3 on the almonds A once the desired granulometry is reached.

[0111] In the example presented, the user indicates directly on the command interface 6 that he wants almonds with fine grains corresponding to a granulometry N3.

[0112] As illustrated in Figure 2, the action of tool 3 on the whole almonds A introduced into container 2 transforms the almonds A, in particular their granulometry.

[0113] As illustrated in Figure 3, during the progress of the transformation of the almonds A, the mechanical wave sensor 4, in particular the microphone 4a, acquires a signal characteristic of a transformation state for the quantity of whole almonds A introduced into the container 2.

[0114] The signal processing means 5 interpret this signal from its frequency spectrum SF to determine that the almonds A are then in a state of transformation corresponding to a chopped particle size N1. The display device 7 can then indicate to the user that this first state of N1 granulometry has been reached.

[0115] However, this transformation state with this chopped granulometry N1 does not correspond to the fine grain granulometry N3 desired by the user.

[0116] Therefore, the motor control module 8 instructs the motor M to continue driving the tool 3 so as to further process the almonds A.

[0117] As illustrated in Figure 4, the action of tool 3 on the whole almonds A introduced into container 2 transforms the almonds A into another state of granulometry.

[0118] As illustrated in Figure 5, during the progress of the transformation of the almonds A, the mechanical wave sensor 4, in particular the microphone 4a, acquires a signal characteristic of a transformation state for the quantity of whole almonds A introduced into the container 2.

[0119] The signal processing means 5 interpret this signal from its frequency spectrum SF to determine that the almonds A are then in a transformation state corresponding to a crushed particle size N2. The display device 7 can then indicate to the user that this second particle size state N2 has been reached.

[0120] However, this transformation state with this crushed granulometry N2 still does not correspond to the fine grain granulometry N3 desired by the user.

[0121] Therefore, the control module 8 of the motor M instructs the motor to continue driving the tool 3 so as to further process the almonds A.

[0122] As illustrated in Figure 6, the action of tool 3 on the whole almonds A introduced into container 2 transforms the almonds A into another state of granulometry.

[0123] As illustrated in Figure 7, during the progress of the transformation of the almonds A, the mechanical wave sensor 4, in particular the microphone 4a, acquires a signal characteristic of a transformation state for the quantity of whole almonds A introduced into the container 2.

[0124] The signal processing means 5 interpret this signal from its frequency spectrum SF to determine that the almonds A are then in a transformation state corresponding to a granulometry with fine grains N3. The display device 7 can then indicate to the user that this third granulometry state N3 has been reached.

[0125] This transformation state with this granulometry with fine grains N3 corresponds to the fine grain granulometry N3 desired by the user.

[0126] Therefore, the control module 8 of the motor M interrupts the power supply to the motor driving the tool 3 so as not to further process the almonds A.

[0127] The user then has the A almonds with the desired granulometry.

[0128] Of course, the invention is in no way limited to the embodiment described and illustrated, which has been given only as an example. Modifications remain possible, in particular from the point of view of the composition of the various elements or by substitution of technical equivalents, without departing from the scope of protection of the invention.

Claims

CLAIMS

1. Food preparation appliance (1) comprising: a container (2), for example a bowl or a vat, arranged to receive one or more ingredients (A, AB) of a food preparation, at least one tool (3) for transforming the ingredient(s) (A, AB) introduced into the container from an initial state to a transformed state (ET) beyond a force threshold determined by the action of the tool (A, AB) on the ingredient(s) (A, AB), an electric motor (M) arranged to drive the tool (3) in rotation inside the container (2), a control module (8) arranged to control the speed of the motor (M) and therefore of the tool (3), characterized in that the food preparation appliance (1) further comprises: at least one mechanical wave sensor (4), such as an accelerometer or a microphone, and means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB). AB) introduced into the container (3),and in that the signal delivered by the at least one mechanical wave sensor (4), and data on the nature and / or the initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2) are sent to signal processing means (5), the signal processing means (5) being intended to determine a result relating to a level of granulometry of the ingredient(s) (A, AB) after transformation by the at least one tool (3), this result having an influence on the operation of the culinary preparation appliance (1).,

2. Food preparation appliance (1) according to claim 1, comprising a user interface (HMI) in communication with the signal processing means (5) and arranged to provide information, before transformation, on a level of granulometry desired by the user, of the ingredients (A, AB) introduced into the container (2), and / or provide during the transformation of the ingredient(s) (A, AB) at least one piece of information intended for the user correlated with the result determined by the signal processing means (5) including at least one piece of information relating to the achievement of a level of granulometry (N1, N2, N3) desired by the user. [Claim s] Food preparation appliance (1) according to claim 2, in which the user interface (HMI) comprises the means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2), these being declared by the user.

4. Food preparation appliance (1) according to one of claims 2 to 3, in which the user interface (HMI) comprises visual and / or audible means for informing the user when at least two different levels of granulometry have been reached. [Claim s] Food preparation appliance (1) according to one of claims 2 to 4, in which the user interface (HMI) comprises means for selection by the user of a desired granulometry level (N1, N2, N3) determined from a list of granulometry levels (N1, N2, N3). [Claim s] Food preparation appliance (1) according to one of claims 2 to 5, in which the electronic module is arranged to interrupt the electrical supply to the motor when the granulometry level (N1, N2, N3) has reached the granulometry level (N1, N2, N3) desired by the user.

7. Food preparation appliance (1) according to one of claims 1 to 6, in which the initial physical properties before transformation of the ingredient(s) (A, AB) comprise at least the initial granulometry level (N1, N2, N3) before transformation of the ingredients (A, AB).

8. Food preparation appliance according to one of claims 1 to 7, in which the means for identifying the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2) comprise a camera arranged to film or take images of the ingredient(s) (A, AB) introduced into the container (2), dedicated processing means (9) using an artificial intelligence model being used to identify the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2).

9. Food preparation appliance (1) according to one of claims 1 to 8, in which the at least one mechanical wave sensor (4) is arranged to measure during the transformation of the ingredient(s) (A, AB) the vibration emitted by the food preparation appliance (1) in its environment and / or the vibrations inside the food preparation appliance (1).

10. Food preparation appliance (1) according to one of claims 1 to 9, comprising the means for processing the signal (5) delivered by the at least one mechanical wave sensor (4), and data on the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2).

11. Food preparation appliance (1) according to claim 10, in which the signal processing means (5) use an artificial intelligence model, in particular by machine learning.

12. A food preparation apparatus according to claim 11, wherein the artificial intelligence model is deployed: - during the design of the food preparation appliance (1) and loaded into the signal processing means (5) during the production phase of the food preparation appliance (1), and / or - by updating the firmware of the signal processing means (5) of the food preparation appliance (1) during use.

13. Food preparation appliance (1) according to one of claims 11 or 12, in which the artificial intelligence model is trained during the transformation of the ingredient(s) (A, AB) introduced into the container (é) of the food preparation appliance (1).

14. Food preparation apparatus (1) according to one of the Claims 10 to 13, wherein the signal processing means (5) use the frequency spectrum SF measured during the transformation by the at least one mechanical wave sensor (4) to determine the result relating to the granulometry (N1, N2, N3) of the ingredient(s) (A, AB) after transformation by the at least one tool (“).

15. Food preparation system (10) comprising: - a food preparation appliance (1) according to one of claims 1 to 9 connected to a communication network, and - means for processing the signal (5) delivered by the at least one mechanical wave sensor (4), and data on the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2), arranged on another device connected to the same communication network as the culinary preparation device (1) or on a remote server connected to the same communication network as the culinary preparation device (1).

16. Culinary preparation system (10) according to claim 15, further comprising dedicated processing means (9) using an artificial intelligence model to identify the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2).

17. Food preparation system (10) according to one of claims 15 or 16, in which the signal processing means (5) use an artificial intelligence model by machine learning.

18. Food preparation system (10) according to claim 17, wherein the artificial intelligence model is trained during the transformation of the ingredient(s) (A, AB) introduced into the container (2) of the food preparation appliance (1).

19. Culinary preparation system (10) according to one of claims 15 to 18, in which the signal processing means (5) delivered by the at least one mechanical wave sensor (4), and data on the nature and / or initial physical properties before transformation of the at least one mechanical wave sensor (4), ingredients (A, AB) introduced into the container (2) use the frequency spectrum (SF) measured during the transformation by the at least one mechanical wave sensor (4) to determine the result relating to the granulometry (N1, N2, N3) of the ingredient(s) (A, AB) after transformation by the at least one tool (3).

20. Method of using a food preparation appliance (1) according to one of claims 1 to 14, comprising the following steps: - start the food preparation appliance (1); - use a manual mode or select a program to prepare a meal; - identify the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2); - transform the ingredient(s) (A, AB) in manual mode or when the program reaches a stage requiring the transformation of the ingredient(s) (A, AB), - determine a result relating to a granulometry level (N1, N2, N3) of the ingredient(s) (A, AB) after transformation by the at least one tool (3) as a function of the signal delivered by the at least one mechanical wave sensor (4), and data on the nature and / or initial physical properties before transformation of the ingredient(s) (A, AB) introduced into the container (2).

21. Method of use according to claim 20 in which before transformation the user enters on a user interface (HMI) a desired level of granulometry (N1, N2, N3) of the ingredient(s) (A, AB) introduced into the container (2) and the electrical supply of the motor (M) is interrupted by the control module (8) when the level of granulometry (N1, N2, N3) of the ingredient(s) (A, AB) introduced into the container (2) has reached the level of granulometry (N1, N2, N3) desired by the user, and / or a user interface (HMI) delivers in real time during the transformation information intended for the user correlated with the result determined by the signal processing means (5) including a information relating to the achievement of a granulometry level (N1, N2, N3) desired by the user.

22. Method according to claim 21, in which during the transformation the signal processing means (5) proceed to the acquisition of data provided by the at least one mechanical wave sensor (4), to train the model of an artificial intelligence used by the signal processing means (5) in order to deliver on the user interface (HMI) the information intended for the user correlated with the result determined by the signal processing means (5) including information relating to the achievement of a level of granulometry (N1, N2, N3) desired by the user.

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