A food processor appliance

Abstract

A food processor appliance, comprising: a food processing assembly comprising a motor operably coupled to a food processing accessory; one or more sensors; and one or more processors in communication with one or more memories, wherein the one or more processors are configured to: receive, during actuation of the food processing assembly, one or more signals from the one or more sensors; determine, based on the one or more signals and a classification engine stored in the one or more memories, a processing stage of the food; and control the food processor appliance in response to determining the processing stage of the food.

Description

RELATED APPLICATIONS

[0001] The current application claims priority from Australian Provisional Application No. 2023904019, filed 12 December 2023, the contents of which are incorporated by reference in entirety. TECHNICAL FIELD

[0002] The present invention relates to food processor appliances. BACKGROUND

[0003] Users of food processor appliances can find it difficult to determine when a processed food has transitioned to a particular stage.

[0004] In some instances, users are expected to use their senses to detect when the food may have transitioned to another stage. Until a user has trained their senses for the specific food being processed, this experience can frustrate the user.

[0005] Even once a user has trained their senses, in some instances the slightest distraction on behalf of the user may result in the processed food transitioning to a less desirable processing stage, potentially ruining the food.

[0006] In some instances, a user failing to determine when a processed food has transitioned to a particular stage can result in damage occurring to the food processor. For example, if a user fails to identify that the ingredients being processed has formed a dough, the food processor may knead the dough in a manner which causes the motor of the food processor to burn out. SUMMARY

[0007] There is therefore a need to at least ameliorate or alleviate one or more of the above-mentioned disadvantages or provide a useful alternative.

[0008] In one aspect there is provided a food processor appliance, comprising: a food processing assembly comprising a motor operably coupled to a food processing accessory; one or more sensors; and one or more processors in communication with one or more memories, wherein the one or more processors are configured to: receive, during actuation of the food processing assembly, one or more signals from the one or more sensors; determine, based on the one or more signals and a classification engine stored in the one or more memories, a processing stage of the food; and control the food processor appliance in response to determining the processing stage of the food.

[0009] In certain embodiments, the one or more sensors includes one or more vibration sensors.

[0010] In certain embodiments, the one or more vibration sensors includes one or more transducers.

[0011] In certain embodiments, the one or more sensors include one or more electrical current sensors.

[0012] In certain embodiments, the one or more sensors include one or more power sensors.

[0013] In certain embodiments, the one or more sensors include one or more torque sensors.

[0014] In certain embodiments, the one or more speed sensors.

[0015] In certain embodiments, the one or more sensors include one or more load sensors.

[0016] In certain embodiments, the one or more load sensors generate the one or more signals indicative of a load of the food.

[0017] In certain embodiments, the one or more sensors include one or more temperature sensors.

[0018] In certain embodiments, the one or more processors are configured to generate, using the one or more signals received from the one or more sensors, power spectral density data, and provide the power spectral density data as input to the classification engine to determine the processing stage of the food.

[0019] In certain embodiments, the food processing accessory is releasably coupled with the motor, wherein the one or more processors are configured to provide an accessory identifier, indicative of the food processing accessory releasably coupled with the motor, as input to the classification engine to determine the processing stage of the food.

[0020] In certain embodiments, the food processing accessory further includes an accessory identification sensor for identifying the food processing accessory releasably coupled with the motor, wherein the one or more processors are configured to receive one or more signals from the accessory identification sensor indicative of the food processing accessory releasably coupled with the motor.

[0021] In certain embodiments, the food processor appliance includes a user input device in communication with the one or more processors, wherein the one or more processors receive one or more signals from the user input device indicative of the food processing accessory indicated by a user via user interaction with the user input device.

[0022] In certain embodiments, the food processor appliance includes a user output device, wherein one or more processors are configured to control the user output device of the food processor appliance, in response to determining the processing stage of the food, to provide output indicative of the processing stage of the food.

[0023] In certain embodiments, the one or more processors are configured to control actuation of the food processing assembly in response to a change of the processing stage of the food.

[0024] In certain embodiments, the one or more processors are configured to stop actuation of the food processing assembly in response to the change of the processing stage of the food.

[0025] In certain embodiments, the one or more processors are configured to determine a processing stage of the food based on one or more processing events being detected, wherein the one or more processors are configured to provide the one or more signals received from the one or more sensors as input to the classification engine to detect the one or more processing events, wherein the processing stage of the food is determined by the one or more processors based on whether the one or more detected processing events satisfy a processing stage criterion.

[0026] In certain embodiments, the food processing accessory is a slicing accessory, wherein each processing event is a slice performed by the slicing accessory to the food, wherein the processing stage of the food is a sliced processing stage, and wherein the processing stage criterion is based on a predefined number of slices being detected.

[0027] In certain embodiments, the one or more processors are configured to control a brake associated with the food processing assembly to stop actuation of the slicing accessory in response to the food transitioning to the sliced processing stage.

[0028] In certain embodiments, the one or more processors store in the one or more memories the processing stage criterion, wherein the processing stage criterion is set based on user input.

[0029] In certain embodiments, the one or more processors are configured to: determine, based on the one or more signals and a further classification engine stored in the one or more memories, whether the food processor appliance is malfunctioning; and stop actuation of the food processor appliance in response to the further classification engine determining that the food processor appliance is malfunctioning.

[0030] Other aspects and embodiments will be appreciated throughout the detailed description of example embodiments. Brief Description of the Figures

[0031] Preferred embodiments of the present invention will now be described by way of example, with reference to the accompanying drawings.

[0032] Figure 1 is a block diagram representing a food processor appliance.

[0033] Figure 2 is a flowchart representing a method performed by one or more processors of the food processor appliance.

[0034] Figure 3 is a flowchart representing a method of training a classification engine for use by the one or more processors of the food processor appliance.

[0035] Figure 4 is a flowchart representing a further method performed by one or more processors of the food processor appliance.

[0036] Figure 5A is a graph showing vibration sensed from a tri-axis vibration sensor of a food processor appliance without any food in the food processor appliance.

[0037] Figure 5B is a graph showing filtered vibration overtime based on the vibration data of Figure 5A.

[0038] Figure 5C is a graph showing power spectral density for filtered signals received from a tri-axis vibration sensor without any food in the food processor appliance.

[0039] Figure 6A is a graph showing a magnitude of vibration sensed overtime from a triaxis vibration sensor of a food processor appliance operating to combine ingredients together.

[0040] Figure 6B is a graph showing a magnitude of filtered vibration overtime based on the vibration data of Figure 6A.

[0041] Figure 6C is a graph showing power spectral density for filtered signals of Figure 6B.

[0042] Figure 7A is a graph showing a magnitude of vibration sensed overtime from a triaxis vibration sensor of a food processor appliance operating after the ingredients have combined.

[0043] Figure 7B is a graph showing a magnitude of filtered vibration overtime based on the vibration data of Figure 7A.

[0044] Figure 7C is a graph showing power spectral density for filtered signals of Figure 7B.

[0045] Figure 8 is a schematic perspective view of a food processor appliance.

[0046] Figures 9A, 9B and 9C show cross-sectional views of a food processor assembly of a food processor appliance including an attachable food processing accessory with an associated reader or sensor.

[0047] Figure 10 shows a functional block diagram representing a processing system for generating and training a classification engine.

[0048] Figure 11 shows an example graphical user interface of software for generating and training a classification engine. DETAILED DESCRIPTION

[0049] The following modes, given by way of example only, are described to provide a more precise understanding of the subject matter of a preferred embodiment or embodiments. In the figures, incorporated to illustrate features of an example embodiment, like reference numerals are used to identify like parts throughout the figures.

[0050] Referring to Figure 1 there is shown a block diagram representing a food processor appliance 100. In particular, the food processor appliance 100 includes a food processor assembly 110, one or more processors 140 in communication with one or more memories 130, and one or more sensors 190.

[0051] The food processor assembly 100 includes a motor 120 which is operably coupled with a food processing accessory 130.

[0052] The one or more processors 140 and the one or more memories 150 are generally part of one or more controllers 145 which are electrically coupled with the food processing assembly 110. The one or more processors 140 and the one or more memories 150 are in communication via a data bus 165. An input / output interface 160 is also in communication with the one or more processors 140 and the one or more memories 150, wherein one or more peripheral devices are in communication with the controller 145 via the i / o interface 160. The one or more controllers 145 can be electrically coupled to an electrical interface of the motor 120 or potentially a dedicated motor controller of the motor 120.

[0053] The one or more memories 150 may be part of the one or more controllers 145. The one or more memories 150 can include volatile memory and non-volatile memory. The non-volatile memory 150 has stored therein a classification engine 155.

[0054] The one or more sensors 190 are in communication with the one or more processors 140 via the i / o interface 160. It will be appreciated that the sensors 190 may be in wired or wireless communication with the one or more processors 140. The one or more sensors 190 can include one or more vibration sensors. In one form, the one or more vibration sensors can include one or more transducers. Additionally or alternatively, the one or more sensors 190 can include one or more electrical current sensors. Additionally or alternatively, the one or more sensors 190 can include one or more electrical power sensors. Additionally or alternatively, the one or more sensors 190 can include one or more torque sensors. Additionally or alternatively, the one or more sensors 190 can include one or more speed sensors. Additionally or alternatively, the one or more sensors 190 can include one or more load sensors. In one form, the one or more load sensors generate the one or more signals indicative of a load of the food. Additionally or alternatively, the one or more sensors 190 can include one or more temperature sensors.

[0055] Referring to Figure 2 there is shown a flowchart representing a method 200 performed by the one or more processors 140 of the food processor appliance 100.

[0056] In particular, at step 210, the method 200 includes the one or more processors 140 receiving, during actuation of the food processor assembly 110, one or more signals from the one or more sensors 190.

[0057] At step 220, the method 200 includes the one or more processors 140 determining, based on the one or more signals and the classification engine 155 stored in the one or more memories 150, a processing stage of the food. The classification engine is configured to classify feedback from the one or more signals into a plurality of classes. Each class represents a different processing stage of the food, for example combining ingredients, ingredients combined, etc.

[0058] At step 230, the method 200 includes the one or more processors 140 controlling the food processor appliance 100 in response to determining the processing stage of the food.

[0059] Referring to Figure 3 there is shown a flowchart representing a method 300 of generating and training the classification engine 155 for use with the food processor appliance 100. This process is generally performed by a processing system 1000 as illustrated in Figure 10 that is a separate device to the food processor appliance 100. The processing system 1000 includes one or more processors 1010 coupled to a memory 1020 and an input / output interface 1030 coupled together via a data bus 1040. In one form, the processing system could be a cloud computing resource.

[0060] In particular, at step 310 the method 300 includes the one or more processors 1010 acquiring sensor data indicative of one or more signals from the one or more sensors 190 of one or more food processor appliances 100. Generally, the sensor data may be received via the i / o interface. In one example, the sensor data may be received during operation of the one or more food processor appliances 100. Alternatively, a data logger may receive and store the sensor data, wherein the sensor data is subsequently transferred to the processing system 1000 via the i / o interface 1030.

[0061] At step 320, the method 300 includes the one or more processors 1010 portioning the sensor data into testing sensor data and training sensor data.

[0062] At step 330, the method 300 includes the one or more processors 1010 analysing the training sensor data to generate sensor analysis data. Other pre-processing of the training sensor data may be performed at step 330 in relation to the training sensor data.

[0063] At step 340, the method 300 includes the one or more processors 1010 generating a feature vector based on the training sensor data and / or the sensor analysis data generated using the training sensor data.

[0064] At step 350, the method 300 includes the one or more processors 1010 training the classification engine 155 using the training sensor data and sensor analysis data,

[0065] At step 360, the method 300 includes the one or more processors 1010 evaluating the classification of the one or more food processing stage(s) of the food based on the testing sensor data and / or sensor analysis data generated using the testing sensor data.

[0066] At step 370, the method 300 includes the one or more processors 1010 determining whether the classification is acceptable. If the classification is unacceptable, the method 300 proceeds back to step 350 to continue training the classification engine 155. If the classification is acceptable, the method 300 concludes as the classification engine 155 has been trained.

[0067] The classification engine may be a neural network classifier. One example of software which can be used to generate and train the classification engine is Edge Impulse (available at https: / / gdgeimpyjse.gom / ). An example software interface 1100 presented by the processing system 1000 which defines various parameters of the neural network classifier is shown in Figure 11. In this example, the software interface 1100 visually presents the classification of the windows of sensor data into three processing stages 1110, 1120, 1130 based on the parameters of the neural network.

[0068] The trained classification engine 155 can be copied to the memory 150 of one or more food processor appliances for matching with real time data. This can be performed during the manufacture and configuration of each food processor appliance 100.

[0069] Referring to Figure 4, there is shown a flowchart representing a method 400 performed by the one or more processors 140 to determine the processing stage of food for processing by a food processor appliance 100.

[0070] In particular, at step 410, the method 400 includes the one or more processors 140 receiving, during actuation of the food processing assembly 110, one or more signals from the one or more sensors 190.

[0071] At step 420, the method 400 includes the one or more processors 140 filtering the one or more signals received from the one or more sensors 190. In one example, a low pass filter can be used by the one or more processors 140 to filter the one or more signals received from the one or more sensors 190.

[0072] At step 430, the method 400 includes the one or more processors 140 analysing the one or more filtered signals to generate power spectral density (PSD) data for the one or more filtered signals.

[0073] At step 440, the method 400 includes the one or more processors 140 providing input data, based on the PSD data, as input to the classification engine 155 to determine the processing stage of the food being processed by the food processor appliance 100. In an additional or alternate form, other features which are not generated from step 430 can be provided as input data to the classification engine 155. For example, other sensor data, or filtered sensor data, may be provided as input data to the classification engine 155. For example, the discrete temperature data of the motor 110 captured overtime may be provided as input data to the classification engine 155.

[0074] In one example, the one or more processors 120 are configured to analyse a shifting temporal window of signals received from the one or more sensors 190. In one example, the shifting window may have a length of 2 seconds and the shifting temporal window is sampled every 100 milliseconds. In this arrangement, a new 100 milliseconds of signals received from one or more sensors 190 are obtained and the oldest 100 milliseconds of signals from the previous window are dropped from analysis. In this arrangement, processing efficiency can be obtained by performing power spectrum analysis over the newest 100 milliseconds of signals which is then combined with PSD data determined for the previous 1.9 seconds of signals for the previous window. It will be appreciated that at the start of operation for the food processor device, the entire window of signals may need to initially undergo PSD analysis. Preferably, for each window of each signal, the average that is calculated of the PSD values in each window, is stored in the memory 150 and is assigned a food processing stage classification. As will be explained further below, the most recent (e.g., 10) window stage classifications are counted to determine the general classification of the signal. If the windows stage classifications are programmed to be within 80% accuracy (and as will be explained below, they can be programmed to have a lower accuracy, such as 70% accuracy), then the microcontroller determines whether at least 8 classifications in the array of 10 match a specific force transfer member classification (e.g., dough is complete) and upon such classification, the one or more processors are configured to stop operating the machine.

[0075] Once PSD analysis has been performed for the respective window of signals (some of which may have been previously performed in relation to one or more preceding windows), the classification engine 155 can compare at least some of the PSD data for the respective window against one or a plurality of criteria or thresholds stored in memory 150 to classify the window of signals into one of the processing stage classes. In some instances, only a portion of the PSD data (i.e., specific frequency ranges) may need to be compared against the one or more criteria to classify the window of signals into one of a plurality processing stage classes for the food.

[0076] In one form, the one or more processors 120 store in memory 150 a current processing stage, wherein the one or more processors 120 can be configured to determine a change of a processing stage for the food being processed based on a threshold number of windows being detected as having a changed processing stage compared to the current processing stage recorded in memory 150. For example, the one or more processors 120 may be configured to detect a change in the processing stage of the food in response to a majority of recent windows (e.g., seven or eight out often) having a different processing stage to that of the current stage recorded in memory 150. Upon determining this criterion having been satisfied, the one or more processors 120 are configured to record in memory 150 the different processing stage as the current processing stage. This configuration removes a false detection of a transition to a different food processing stage based on noise obtained from the one or more sensor signals. It will be appreciated that other configurations could also be implemented, such as detecting a specified number (e.g., equal to 2 to 10 depending on the configuration for desired accuracy) of consecutive windows having a different processing stage classification to the currently processing stage recorded in memory 150.

[0077] At step 450, the method 400 includes the one or more processors 140 controlling the food processor appliance 100 in response to determining the processing stage of the food.

[0078] In one form, the food processor appliance 100 can also include a user output device 180, wherein one or more processors 140 are configured to control the user output device 180 of the food processor appliance 100, in response to determining the processing stage of the food, to provide output to the user indicative of the processing stage of the food. For example, a graphical user interface may be presented via an electronic display, wherein the one or more processors 140 are configured to control presentation of the graphical user interface indicative of the determined processing stage of the food via the electronic display 180. In other forms, the output device may be a simple electronic component, such as a light emitting diode, to indicate a particular food processing stage has been detected by the classification engine 155. In another form, numerical data or graphical data could be presented to the user via the user output device 180.

[0079] In an additional or alternate form, the one or more processors 140 are configured to control actuation of the food processing assembly 110 in response to a change of the processing stage of the food. For example, the one or more processors 140 are configured to stop actuation of the food processing assembly 110 in response to the change of the processing stage of the food. More specifically, in the event that food processor appliance 100 is being used for making dough, the detected transition of the food from an ingredient combining stage to a dough ball stage may result in the one or more processors 140 changing the speed of actuation of the motor 120, such as increasing or decreasing the speed of the motor 120, or potentially stopping the actuation of the motor 120 entirely as the food processing has been completed.

[0080] Referring to Figures 5Ato 5C, 6Ato 6C, and 7Ato 7C there is shown various graphs of sensor data, filtered sensor data, PSD data respectively. Figures 6Ato 6C, and 7A to 7C relate specifically to processing ingredients for making dough.

[0081] In Figure 5A there is shown the raw vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor 190 of a food processor appliance 100 operating without any food being processed. In Figure 6A there is shown the raw vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor of a food processor appliance 100 operating to combine ingredients. In Figure 7A there is shown the raw vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor 190 of a food processor appliance 100 which has combined the ingredients.

[0082] In Figure 5B there is shown filtered vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor 190 of a food processor appliance 100 operating without any food being processed. In Figure 6B there is shown filtered vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor 190 of a food processor appliance 100 operating to combine ingredients. In Figure 7B there is shown filtered vibration sensor data captured in x, y, and z axes by a tri-axis vibration sensor 190 of a food processor appliance 100 which has combined the ingredients.

[0083] In Figures 5C, 6C and 7C, the graphs show PSD data using the filtered sensor data as discussed in relation to Figures 5B, 6B and 7B respectively. The graph of Figure 5C represents the power spectral density in the x, y and z axes whilst the food processor appliance 100 is empty with no food being processed. The graph of Figure 6C represents the power spectral density in the x, y and z axes whilst the food processor appliance 100 is combining ingredients. The graph of Figure 7C represents the power spectral density in the x, y and z axes after the ingredients have been combined by the food processor appliance 100.

[0084] In relation to Figures 5A, 5B and 5C which relates to operating the food processor appliance 100 without any food being processed, it is apparent that the magnitudes of the vibration in the x, y, and z axes are low with a peak magnitude occurring between a frequency range of 5-15 Hz.

[0085] In relation to Figures 6A, 6B and 6C, when the food processor appliance 100 is combining ingredients, it is apparent that the peak magnitude of the power spectral density data captured in the x, y, and z axes is slightly higher comparative to Figure 5C. Furthermore, it is apparent that the magnitude of the power spectral density data in the x axis is greater than the y and z axes. Additionally, the peak magnitude of the power spectral density data for the x-axis occurs at a higher frequency range than the y and z axes.

[0086] In relation to Figures 7A, 7B and 7C, when the ingredients combine into a single dough ball, the magnitude of the power spectral density data for the x axis elevates from approximately 30Hz to 60 Hz compared to 0 to 29 Hz. Additionally, the magnitude of the power spectral density data for the x axis is significantly greater than the magnitude of the power spectral density data for the y and z axes.

[0087] As will be appreciated, these features or markers are indicative of different processing stages for food being processed by the food processor appliance 100 and can be used by the classification engine 155 to classify the processing stage of the food. For the examples shown in Figures 5Ato 7C, it is possible to monitor different stages of the food processing by monitoring vibration and provide real time feedback to the user regarding the detected stage of the food processing. In additional or alternate forms, the one or more processors 140 can monitor one or more motor 110 characteristics (e.g., current (Amps), power (Watts), torque (Nm)) of the food processor appliance 100 to determine a processing stage for the food being processed by the food processor appliance 100.

[0088] Whilst Figures 6Ato 7C relate to a dough making process, it will be appreciated that different classification engines 155 can be generated for different types of food (e.g., dough, salad, cake mix) and / or food processing process (e.g., mince, slice, whisk, etc.). For example, a mincing classification engine ora peanut butter classification engine could be generated, trained and stored in the one or more memories 150 associated with the one or more processors 140. In one form, the user may provide input via the input device 170 to indicate that the food that is intended to be processed by the food processor appliance 100 so that the one or more processors 140 use the appropriate classification engine 155 to determine the processing stage of the food whilst being processed by the appliance 100.

[0089] In one form, the one or more processors 140 are configured to additionally determine a processing stage of the food based on one or more processing events being detected by the classification engine 155. More specifically, the one or more processors 140 are configured to provide the one or more signals received from the one or more sensors 190 as input to the classification engine 155 to detect the one or more processing events. In this configuration, the processing stage of the food is determined by the one or more processors 140 based on whether the one or more detected processing events satisfy a processing stage criterion. For example, the food processing accessory 130 can be a slicing accessory. In this example, each processing event to be detected is a slicing event performed by the slicing accessory on the food. Furthermore, in this example, the processing stages of the food may be a non-sliced processing stage and a sliced processing stage. Additionally, in this example, the processing stage criterion is based on a predefined number of slices being detected by the classification engine 155 for the one or more processors to determine that the food has transitioned from a non-sliced processing stage to a slice processing stage. The one or more processors 120 can be configured to control a brake associated with the food processing assembly 110 to stop actuation of the slicing accessory 130 in response to the food transitioning to the sliced processing stage. Alternatively, the user may be prompted to stop actuation. In one form, the one or more processors 140 store in the one or more memories 150 the processing stage criterion, wherein the processing stage criterion is set based on user input via the user input device 170. For example, the user may set that a particular food is considered sliced once one hundred slicing events have been detected.

[0090] In certain embodiments, the one or more processors 140 are configured to determine, based on the one or more signals received from the sensors and a further classification engine 155 stored in the one or more memories 150, whether the food processor appliance 100 is malfunctioning or approaching a malfunction event. In this embodiment, the further classification engine 155 is trained to classify feedback from the one or more signals into a plurality of further classes (e.g., normal operation class and malfunctioning class). The one or more processors 140 can be configured to stop actuation of the food processor appliance 100 in response to the further classification engine 155 determining that the food processor appliance 100 is malfunctioning.

[0091] Referring to Figures 8 and 9 there is shown an example of a food processor appliance 100. The food processor 100 comprises a base 811 with internal motor 110, user operated controls 170, an electronic display 180 and a vessel 814 provided in the form of a processing container. The vessel 814 further comprises a bowl 815 with a handle 816 and a lid 817 with an integral and wide feed tube 818. The feed tube 818 is configured to receive a pusher 819. In this example, the pusher 819 accommodates a smaller second pusher 820.

[0092] An upper surface of the base 811 further comprises a display 180 such as an LCD display. Adjacent to the display 180 there are user controls 170 for operating a timer that associates the display 180 with the operation of the motor 110 and feed tube 818. More details regarding features of the food processor appliance 100 are described in Australian Patent Application No. AU2011340788, the contents of which is incorporated by reference in its entirety.

[0093] Referring to Figures 9A, 9B and 9C, there is shown various cross-sectional views of a food processor assembly 110 of a food processor appliance 100 including an attachable food processing accessory 130. In particular, the food processing accessory includes an identifier 912, wherein the food processing assembly 110 includes a sensor for identifying the food processing accessory releasably coupled with the motor 110 based on the identifier, as described in PCT Publication No. WO 2014 / 201509 A2, the contents of which are incorporated by reference in its entirety. In this embodiment, the one or more processors 120 are configured to receive one or more signals from the accessory identification sensor indicative of the food processing accessory releasably coupled with the motor 110.

[0094] Referring more specifically to Figures 9A, the food processing accessory 130 can include a near field communication (NFC) or radio frequency identification (RFID) element 912, which can cooperate with a reader / sensor 914 located within the food processing apparatus. The reader / sender 914 can be coupled to the one or more processors 140 for enabling identification of the food processing accessory 130. It will be appreciated that the vessel 814 of the food processor assembly 110 could also include a hall-effect sensor or interlock switch for confirming coupling of the food processing accessory 130 to an attachment coupling. This is beneficial in limiting operation of the motor 110 or limiting motor 110 speed when the food processing accessory 130 is located proximal to the sensor element 914.

[0095] By way of example only, Figure 9B and Figure 9C show use of a further wireless communication element (for example: NFC, RFID or hall effect) 922 in the food processing accessory 130, such that a second reader / sensor device 924 can appropriately detect and identify the food processing accessory 922, and convey identification data to the one or more processors 140. The one or more processors 140 may use the identification data select the appropriate classification engine for use in monitoring the sensor data to determine a processing stage of the food. In addition, the identification data can be used by the one or more processors 140 to apply appropriate operational parameters for processing the food using the food processing accessory 130, such as blade 930 or accessory speed, or maximum speed, cooking times or temperatures or other modifiable functions of the appliance.

[0096] Figure 9B shows the identification element or sensor or detector 922 and corresponding sensor / reader 924 being located about a periphery of the vessel of the food processor appliance 100. FIG. 10C shows the identification element 922 and corresponding detection / reader element 924 being located more centrally about a vessel lid 817.

[0097] It will also be appreciated that the food processing accessory 130 can include a chopping blade 930 located below a food chute 818, wherein the food chute 818 has a cooperating pusher 819 that slidably engages within the chute 818.

[0098] In an alternate form to Figures 9A, 9B and 9C, the one or more processors 140 receive one or more signals from the user input device 170 indicative of the food processing accessory 130 as indicated by a user via user interaction with the user input device 170. Based on the received user input data indicative of the attached food processing accessory 130, the one or more processors 140 can select a classification engine 155 from a plurality of classification engines 155 stored in the one or more memories 150 for use during food processing.

[0099] In one form, when a transition to a different food processing stage is detected by the one or more processors 140, the one or more processors 140 can query the one or more memories 150 to determine if a change in food processing accessary 130 is required. For example, if ingredients are being combined and the transition to a dough is detected, the one or more processors 140 can query the one or more memories 150 to detect that the motor is required to stop and a prompt is to be presented by the output device to request the user change the food processing accessory 130 to a plastic dough blade. Once the change of the food processing accessory 130 has been completed, the user may provide an indication to recommence food processing via one or more input devices of the food processor appliance. It will be appreciated that the above technique of determining the identity of the food processing accessory 130 can be used to check the user can coupled the correct food processing accessory 130 for the type of food being processed and the food processing stage that has been identified. It will also be appreciated that the mode of operation of the motor operation as instructed by the one or more processors 140 can alter in response to a detected transition in the food processing stage. For example, once the ingredients have been combined to form a dough which can be detected using the above techniques, the motor can be controlled by the one or more processors 140 to operate in a pulse action. It will be appreciated that various modes of motor operation can be defined and associated with the food processing stage as stored in the one or more memories 150.

[00100] Throughout this specification and the claims which follow, unless the context requires otherwise, the word "comprise", and variations such as "comprises" and “comprising", will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

[00101] The reference in this specification to any known matter or any prior publication is not, and should not be taken to be, an acknowledgment or admission or suggestion that the known matter or prior art publication forms part of the common general knowledge in the field to which this specification relates.

[00102] While specific examples of the invention have been described, it will be understood that the invention extends to alternative combinations of the features disclosed or evident from the disclosure provided herein.

[00103] Many and various modifications will be apparent to those skilled in the art without departing from the scope of the invention disclosed or evident from the disclosure provided herein. Reference number list 100   food processor appliance 110   food processor assembly 120 motor 130 food processing accessory 140 processor 145 controller 150 memory 155 classification engine 160    input / output (i / o) interface 165 bus 170 input device(s) 180 output device(s) 190 sensor(s) 811 base 814 vessel 815 bowl 816 handle 817 lid 818 feed tube 819 pusher 820 further pusher 912 food processor accessory identifier 914 sensor / reader 916 blending / mixing arm 922    further identifier 924   further sensor / reader 930 blade 1000 processing system 1010 processor 1020 memory 1030 i / o interface 19 1040 bus

Claims

1. A food processor appliance, comprising:a food processing assembly comprising a motor operably coupled to a food processing accessory;one or more sensors; andone or more processors in communication with one or more memories, wherein the one or more processors are configured to:receive, during actuation of the food processing assembly, one or moresignals from the one or more sensors;determine, based on the one or more signals and a classification enginestored in the one or more memories, a processing stage of the food; andcontrol the food processor appliance in response to determining theprocessing stage of the food.

2. The food processor appliance of claim 1, wherein the one or more sensors includes one or more vibration sensors.

3. The food processor appliance of claim 2, wherein the one or more vibration sensors includes one or more transducers.

4. The food processor appliance of any one of claims 1 to 3, wherein the one or more sensors include one or more electrical current sensors.

5. The food processor appliance of any one of claims 1 to 4, wherein the one or more sensors include one or more power sensors.

6. The food processor appliance of any one of claims 1 to 5, wherein the one or more sensors include one or more torque sensors.

7. The food processor appliance of any one of claims 1 to 6, wherein the one or more speed sensors.

8. The food processor appliance of any one of claims 1 to 7, wherein the one or more sensors include one or more load sensors.

9. The food processor appliance of claim 8, wherein the one or more load sensors generate the one or more signals indicative of a load of the food.

10. The food processor appliance of any one of claims 1 to 9, wherein the one or more sensors include one or more temperature sensors.

11. The food processor appliance of any one of claims 1 to 9, wherein the one or more processors are configured to generate, using the one or more signals received from the one or more sensors, power spectral density data, and provide at least some of the power spectral density data as input to the classification engine to determine the processing stage of the food.

12. The food processor appliance of any one of claims 1 to 11, wherein the food processing accessory is releasably coupled with the motor, wherein the one or more processors are configured to provide an accessory identifier, indicative of the food processing accessory releasably coupled with the motor, as input to the classification engine to determine the processing stage of the food.

13. The food processor appliance of claim 12, wherein the food processing accessory further includes an accessory identification sensor for identifying the food processing accessory releasably coupled with the motor, wherein the one or more processors are configured to receive one or more signals from the accessory identification sensor indicative of the food processing accessory releasably coupled with the motor.

14. The food processor appliance of claim 12, wherein the food processor appliance includes a user input device in communication with the one or more processors, wherein the one or more processors receive one or more signals from the user input device indicative of the food processing accessory indicated by a user via user interaction with the user input device.

15. The food processor appliance of any one of claims 1 to 14, wherein the food processor appliance includes a user output device, wherein one or more processors are configured to control the user output device of the food processor appliance, in response to determining the processing stage of the food, to provide output indicative of the processing stage of the food.

16. The food processor appliance of claim 15, wherein the one or more processors are configured to control actuation of the food processing assembly in response to a change of the processing stage of the food.

17. The food processor appliance of claim 16, wherein the one or more processors are configured to stop actuation of the food processing assembly in response to the change of the processing stage of the food.

18. The food processor appliance of any one of claims 1 to 17, wherein the one or more processors are configured to determine a processing stage of the food based on one or more processing events being detected, wherein the one or more processors are configured to provide the one or more signals received from the one or more sensors as input to the classification engine to detect the one or more processing events, wherein the processing stage of the food is determined by the one or more processors based on whether the one or more detected processing events satisfy a processing stage criterion.

19. The food processor appliance of claim 18, wherein the food processing accessory is a slicing accessory, wherein each processing event is a slice performed by the slicing accessory to the food, wherein the processing stage of the food is a sliced processing stage, and wherein the processing stage criterion is based on a predefined number of slices being detected.

20. The food processor appliance of claim 19, wherein the one or more processors are configured to control a brake associated with the food processing assembly to stop actuation of the slicing accessory in response to the food transitioning to the sliced processing stage.

21. The food processor appliance of any one of claims 18 to 20, wherein the one or more processors store in the one or more memories the processing stage criterion, wherein the processing stage criterion is set based on user input.

22. The food processor appliance of any one of claims 1 to 21, wherein the one or more processors are configured to:determine, based on the one or more signals and a further classification engine stored in the one or more memories, whether the food processor appliance is malfunctioning; andstopping actuation of the food processor appliance in response to the further classification engine determining that the food processor appliance is malfunctioning.

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