Food whipping equipment control method and device and food whipping equipment

Abstract

The invention relates to a food whipping equipment control method and device and food whipping equipment. When the food whipping equipment enters a whipping stage to operate, noise signals generated by whipping are obtained; determining acoustic characteristic parameters corresponding to the noise signals; and determining a current noise scene according to the acoustic characteristic parameters, and adjusting operation parameters of a whipping motor of the food whipping equipment by adopting a motor regulation and control mode corresponding to the current noise scene. In the early stage or the middle stage of the whipping stage, the current noise scene is determined through the acoustic characteristic parameters of the actual noise signals generated by whipping, and the noise components generated by different food material characteristics in the whipping process are distinguished, so that the operation parameters of the whipping motor are dynamically adjusted, and the noise interference is reduced while the whipping effect is ensured. And at the ending stage of the whipping stage, the food material crushing degree is increased or the whipping amount is less, and if the whipping completion condition is judged to be met, the whipping motor is controlled to stop running, so that the whipping process is optimized, and excessive whipping caused by a fixed time mode is avoided.

Description

Technical Field

[0001] This application relates to the field of electrical equipment technology, and in particular to a control method, apparatus, food mixing equipment, computer-readable storage medium, and computer program product for food mixing equipment. Background Technology

[0002] With the improvement of living standards, high-efficiency food blending equipment such as blenders, soy milk makers and food processors are used more frequently in daily life. Their application scope has expanded from traditional juice making to fields such as nut grinding, smoothie making and processing of high-hardness ingredients.

[0003] Traditional food blending equipment typically uses fixed speed and time control during blending operations, and the noise level during the regular blending phase usually exceeds 70 dB. When processing hard ingredients or adding large quantities, the motor load increases, leading to a significant enhancement of high-frequency noise components and producing a more piercing sound. Although some manufacturers have attempted to improve the design through sound insulation materials or noise reduction structures, these passive noise reduction methods cannot fundamentally solve the problem of noise fluctuations caused by load variations and may increase equipment cost and size. Summary of the Invention

[0004] Therefore, it is necessary to address the technical problem of noise fluctuations in food mixing equipment caused by changes in ingredients by providing a food mixing equipment control method, device, food mixing equipment, computer-readable storage medium, and computer program product.

[0005] In a first aspect, this application provides a method for controlling a food mixing device, the method comprising:

[0006] When the food mixing equipment enters the mixing stage, acquire the noise signal generated by the mixing;

[0007] Determine the acoustic characteristic parameters corresponding to the noise signal;

[0008] The current noise scene is determined based on the acoustic characteristic parameters, and the operating parameters of the mixing motor of the food mixing equipment are adjusted using the motor control method corresponding to the current noise scene.

[0009] In the final stage of the mixing phase, if the mixing completion condition is met, the mixing motor is controlled to stop running.

[0010] In one embodiment, the operating parameters include motor speed, and the acoustic characteristic parameters include the decibel value of the noise signal; determining the current noise scene based on the acoustic characteristic parameters includes:

[0011] If the decibel value of the noise signal is greater than or equal to the first decibel threshold, the current noise scene is determined to be a high sound pressure level scene. The motor control method corresponding to the high sound pressure level scene is the first control method, which includes reducing the motor speed.

[0012] In one embodiment, the acoustic feature parameters further include the dominant frequency value of the noise signal; determining the current noise scene based on the acoustic feature parameters further includes:

[0013] If the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is greater than or equal to the first preset frequency value, the current noise scene is determined to be a high-frequency noise scene, and the motor control method corresponding to the high-frequency noise scene is the first control method.

[0014] When the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is less than the second preset frequency value, the current noise scenario is determined to be a low-frequency noise scenario. The motor control method corresponding to the low-frequency noise scenario is the second control method, which includes increasing the motor speed.

[0015] In one embodiment, the first control method further includes: reducing the motor speed based on a first preset adjustment ratio corresponding to the dominant frequency value;

[0016] The second control method further includes: increasing the motor speed based on a second preset adjustment ratio corresponding to the dominant frequency value.

[0017] In one embodiment, the operating parameters of the agitator motor also include total running time;

[0018] The first control method further includes increasing the total running time based on a first preset adjustment ratio corresponding to the dominant frequency value;

[0019] The second control method also includes reducing the total running time based on a second preset adjustment ratio corresponding to the dominant frequency value.

[0020] In one embodiment, the method further includes: when there are multiple dominant frequency values ​​of the noise signal, fusing the preset adjustment ratios corresponding to the frequency intervals to which each dominant frequency value belongs to obtain the first preset adjustment ratio and the second preset adjustment ratio.

[0021] In one embodiment, the method further includes: at the end of the mixing stage, when the decibel value of the noise signal is less than or equal to a second decibel threshold, determining that the current noise scene is a low sound pressure scene, and adjusting the operating parameters of the mixing motor of the food mixing equipment using a third control method corresponding to the low sound pressure scene, wherein the third control method includes reducing the motor speed.

[0022] In one embodiment, the third control method further includes: reducing the motor speed based on a third preset adjustment ratio corresponding to the dominant frequency value.

[0023] In one embodiment, the operating parameters of the agitator motor also include the total running time; the third control method further includes reducing the total running time based on a third preset adjustment ratio corresponding to the dominant frequency value.

[0024] In one embodiment, the method further includes: at the end of the mixing stage, determining whether the mixing completion condition is met based on the acoustic characteristic parameters.

[0025] In one embodiment, the noise signal includes noise signals collected from multiple measurement points, and the acoustic characteristic parameters include the dominant frequency value and amplitude of the noise signal;

[0026] The step of determining whether the stirring completion condition is met based on the acoustic characteristic parameters includes: calculating the absolute amplitude error of the noise signal based on the amplitude of the dominant frequency values ​​of multiple noise signals; and determining that the stirring completion condition is met if the absolute amplitude error of the noise signal is less than a preset error threshold.

[0027] Secondly, this application also provides a control device for a food mixing apparatus, the device comprising:

[0028] The noise signal acquisition module is used to acquire the noise signal generated during the mixing process when the food mixing equipment enters the mixing stage.

[0029] An acoustic feature parameter determination module is used to determine the acoustic feature parameters corresponding to the noise signal;

[0030] A noise scene determination module is used to determine the current noise scene based on the acoustic feature parameters;

[0031] The motor control module is used to adjust the operating parameters of the mixing motor of the food mixing equipment using the motor control method corresponding to the current noise scenario. The operating parameters include the motor speed.

[0032] The motor control module is also used to control the agitator motor to stop running if the agitation completion conditions are met during the final stage of the agitation stage.

[0033] Thirdly, this application also provides a food mixing device, which includes a controller, a noise monitoring device and a mixing motor connected to the controller. The noise monitoring device is used to monitor the noise signal generated by the food mixing device during the mixing stage. The controller is used to control the operating parameters of the mixing motor according to the steps of any of the above embodiments.

[0034] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0035] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0036] The aforementioned food mixing equipment control method, device, equipment, computer-readable storage medium, and computer program product, when the food mixing equipment enters the mixing stage, acquires the noise signal generated by mixing; determines the acoustic characteristic parameters corresponding to the noise signal; determines the current noise scenario based on the acoustic characteristic parameters, and adjusts the operating parameters of the mixing motor of the food mixing equipment using the motor control method corresponding to the current noise scenario. In the early or middle stages of the mixing stage, the current noise scenario is determined by the acoustic characteristic parameters of the actual noise signal generated by mixing, distinguishing the noise components generated during the mixing process by different food characteristics, so as to dynamically adjust the operating parameters of the mixing motor, ensuring the mixing effect while reducing noise interference. In the final stage of the mixing stage, if the food's pulverization degree increases or the mixing volume decreases, and the mixing completion condition is met, the mixing motor is controlled to stop running to optimize the mixing process and avoid over-mixing caused by a fixed-time mode. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of a system block diagram of a food mixing device in one embodiment;

[0039] Figure 2 This is a flowchart illustrating the control method for a food mixing device in one embodiment;

[0040] Figure 3 This is a flowchart illustrating the steps for determining the current noise scene in one embodiment;

[0041] Figure 4 This is a flowchart illustrating the control method for a food mixing device in another embodiment;

[0042] Figure 5 This is a schematic diagram of the spectrum of the dominant frequency value of the noise signal in one embodiment;

[0043] Figure 6 This is a flowchart illustrating the step of determining whether the mixing is complete in one embodiment;

[0044] Figure 7 This is a structural block diagram of the control device for a food mixing equipment in one embodiment;

[0045] Figure 8 This is a flowchart illustrating the control method for a food mixing device in another embodiment;

[0046] Figure 9 This is a flowchart illustrating the control method for a food mixing device in another embodiment;

[0047] Figure 10 This is a diagram of the internal structure of an electronic device in one embodiment. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0049] The food mixing equipment control method provided in this application embodiment can be applied to, for example, Figure 1 The food mixing equipment shown includes a controller 110, a noise monitoring device 120, and a mixing motor 130 connected to the controller 110. The noise monitoring device 120 monitors the noise signals generated by the food mixing equipment during the mixing stage. The controller 110 receives the noise signals collected by the noise monitoring device 120 and controls the operating parameters of the mixing motor 130 according to the food mixing equipment control method provided in this application embodiment. A data storage system can store the data that the controller 110 needs to process. The data storage system can be integrated into the controller 110 or placed in the cloud or on other network servers.

[0050] Specifically, when the controller 110 controls the start of the mixing motor 130, the food mixing equipment enters the mixing stage. The controller 110 can acquire the noise signal generated by the mixing collected by the noise monitoring device 120, determine the acoustic characteristic parameters corresponding to the noise signal, determine the current noise scene based on the acoustic characteristic parameters, and adjust the operating parameters of the mixing motor 130 using the motor control method corresponding to the current noise scene. The operating parameters include the motor speed. At the end of the mixing stage, if it is determined that the mixing completion conditions are met, the controller 110 can also control the mixing motor 130 to stop running.

[0051] The controller 110 can be a control chip or control circuit board installed on the food mixing equipment, or it can be an external control system based on wireless communication. The external control system can be implemented through devices such as terminals or servers. Terminals can be, but are not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle equipment, projection equipment, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0052] It is understood that the food mixing equipment targeted in this application refers to equipment that uses mechanical force to mix, crush, stir, whip, or emulsify various ingredients. It can be applied in home, commercial, or industrial settings. For example, the food mixing equipment can specifically be a food processor, blender, mixer, soy milk maker, food processor, or bread maker. By simply installing the noise monitoring device 120 described in this application embodiment on the aforementioned food mixing equipment to collect the noise signals generated during mixing, the food mixing equipment control method provided in this application embodiment can be achieved.

[0053] In one exemplary embodiment, such as Figure 2 As shown, a control method for a food mixing device is provided, which is applied to... Figure 1 Taking controller 110 as an example, the explanation includes the following steps S202 to S208. Wherein:

[0054] Step S202: When the food mixing equipment enters the mixing stage, the noise signal generated by the mixing is acquired.

[0055] It is understandable that food blending equipment can have multiple working stages depending on the processing method of different ingredients. Taking the making of rice paste with a high-speed blender as an example, it can include a heating stage, a blending stage, and a heat preservation stage. The embodiments of this application mainly focus on the blending stage. During the process of the blending motor of the food blending equipment working, driving the blades or stirring rod to blend the ingredients, noise monitoring and blending motor control are performed.

[0056] Specifically, the controller can start the mixing motor to mix the ingredients according to the preset program corresponding to the user-selected working mode when it determines that the mixing stage needs to be entered. Furthermore, a noise monitoring device can be installed on the food mixing equipment to monitor the noise signals generated during the mixing process.

[0057] In some examples, noise monitoring devices can be strategically placed on food blending equipment based on factors such as noise sources and propagation paths to accurately capture noise signals generated during blending. For instance, noise sources may include noise signals generated by high-speed motor operation (especially brushless motors) and mechanical transmission friction, noise signals generated by food colliding with blades or by idling eddies, noise signals caused by bearing wear or insufficient lubrication, or even noise signals generated by mechanical vibrations transmitted from the equipment base to the worktable. Noise signals generated by propagation paths may be airflow noise (especially in high-speed blenders) leaking through ventilation holes, or noise transmitted through gaps in the equipment casing, sound insulation layers, etc.

[0058] Correspondingly, different types of noise monitoring devices can be installed at different locations to monitor the noise signals generated by stirring, depending on the different noise signal generating factors. For example, the noise monitoring device can be a microphone sensor installed on the equipment housing or base, or a vibration sensor installed near the stirring motor or blade bearing. Furthermore, noise monitoring devices used to monitor different noise signals need to be isolated to avoid interference between them. For example, for microphone sensors installed on the equipment housing or base, the installation location can be away from the rotating shaft of the stirring motor, or a silicone gasket can be added for isolation during installation. In one example, the noise monitoring device includes multiple microphone sensors symmetrically installed on the base of the food mixing equipment to monitor noise signals at different spatial locations (front, back, left, right, etc.).

[0059] Step S204: Determine the acoustic characteristic parameters corresponding to the noise signal.

[0060] Specifically, the acoustic characteristic parameters corresponding to the noise signal are indicators that quantify the physical properties, spectral characteristics, and perceived effects of the noise. The specific types included are not unique and can be selected according to control requirements.

[0061] In some examples, the acoustic characteristic parameters corresponding to noise signals include intensity parameters, used to describe the magnitude of noise energy. For example, the decibel value of the noise signal reflects the quantitative index of sound pressure level; the peak sound pressure level reflects the maximum instantaneous absolute value of the noise signal; and the equivalent continuous sound level reflects the average energy of the sound pressure level over a period of time. In some examples, the acoustic characteristic parameters corresponding to noise signals may also include spectral parameters, used to describe frequency distribution characteristics. For example, the dominant frequency value of the noise signal refers to the highest energy frequency component in the spectrum, reflecting the main tone of the noise; and the spectral steepness of the noise signal refers to the slope of spectral energy decay, reflecting the proportion of high-frequency components. In some examples, the acoustic characteristic parameters corresponding to noise signals may also include perceptual parameters, used to simulate subjective human hearing. For example, the loudness of the noise signal can convert sound pressure level into subjective loudness perception; and the sharpness of the noise signal refers to the perceptual quantification of the proportion of high-frequency components in the noise signal, with a larger value indicating more piercing noise.

[0062] Specifically, this application can determine the various acoustic feature parameters corresponding to the noise signal through calculation methods corresponding to various feature parameters, so as to serve as the data basis for determining the current noise scene. It can be understood that the various types of acoustic feature parameters mentioned above together constitute the complete acoustic fingerprint of the noise signal, providing a quantitative basis for the noise-optimized device control provided in the embodiments of this application.

[0063] Step S206: Determine the current noise scene based on the acoustic characteristic parameters, and adjust the operating parameters of the mixing motor of the food mixing equipment by adopting the motor control method corresponding to the current noise scene.

[0064] Specifically, based on the meanings represented by different acoustic characteristic parameters, different noise scenarios can be identified. For example, intensity-type acoustic characteristic parameters and loudness-type acoustic characteristic parameters such as perception-type acoustic characteristic parameters can be used to identify high sound pressure levels, normal sound pressure levels, and low sound pressure levels, thus describing the impact of noise signal energy on the environment in which the equipment is located. Similarly, spectral-type acoustic characteristic parameters and sharpness-type acoustic characteristic parameters such as perception-type acoustic characteristic parameters can be used to identify high-frequency noise scenarios, normal-frequency noise scenarios, and low-frequency noise scenarios, thus describing the impact of the frequency distribution characteristics of noise signals on the environment in which the equipment is located.

[0065] Furthermore, for the different noise scenarios mentioned above, corresponding motor control methods can be set to dynamically adjust operating parameters according to specific usage scenarios and optimize the mixing process. Since the core component of the mixing stage is the mixing motor of the food mixing equipment, the control method provided in this application is mainly used to adjust the operating parameters of the mixing motor.

[0066] The operating parameters of the agitator motor are the core variables controlling its working state, performance output, and energy efficiency. These parameters can include various types, such as motor speed, motor torque, motor power, motor current, and total motor operating time. This application primarily uses motor speed and total operating time as examples to explain the motor control method. Of course, other operating parameters can also be adjusted to achieve the desired technical effect of the corresponding motor control method.

[0067] In some examples, for high sound pressure level (SPL) and high-frequency noise scenarios, a lower motor speed can be set to avoid significant noise interference, while a longer total runtime can be set to ensure optimal blending results. For low-frequency noise and low SPL scenarios, due to less noise interference, a higher motor speed and a shorter total runtime can be set to improve blending efficiency. Furthermore, in the final stages of blending, for low-frequency noise and low SPL scenarios, a lower motor speed and a shorter total runtime can also be set to prevent over-blending of the ingredients.

[0068] It is understandable that when the ingredients being blended are hard or in large quantities, the high-frequency noise components generated during blending are significantly amplified, potentially resulting in louder and harsher sounds. However, as blending progresses, the ingredients are gradually broken down into smaller pieces, and the energy and pitch of the noise signal gradually decrease. Therefore, the process of adjusting the motor operating parameters based on the current noise level in this step can be performed intermittently at preset time intervals to adjust the blending process in real time and precisely match the actual situation.

[0069] In this step, the acoustic characteristic parameters of different noise signals are used to accurately describe the current noise scenario, characterize the noise impact corresponding to different food characteristics and addition amounts, and characterize the actual progress of the mixing stage. This allows the food mixing equipment to dynamically adjust its operating parameters according to the specific scenario and optimize the mixing process.

[0070] Step 208: In the final stage of the mixing phase, if it is determined that the mixing completion conditions are met, control the mixing motor to stop running.

[0071] Specifically, the final stage of the mixing phase can be understood as the period nearing the end of the motor's total running time. During this final stage, most of the ingredients should be thoroughly broken down, with only a small amount remaining that is not completely broken down. The ingredients need to be mixed more evenly. Therefore, to prevent over-mixing, the mixing phase can be prematurely terminated by determining if the mixing completion conditions have been met, thus stopping the mixing motor.

[0072] In some examples, the conditions for completing the stirring can also be set based on the acoustic characteristic parameters of the noise signal. For example, it can be set based on the equivalent continuous sound level of the noise signal, i.e., the average energy of the sound pressure level is less than a certain threshold over a period of time. Another example is that it can be set based on the amplitude of the dominant frequency values ​​of the noise signal from multiple directions, to reflect whether the noise amplitude in multiple directions tends to stabilize.

[0073] In some examples, the completion condition for blending can be set based on the operating parameters of the blending motor. For example, it can be set based on the motor torque, which is the rotational torque output by the motor and reflects the blades' ability to overcome the resistance of the food. This can be understood as follows: the finer the food particles are blended, the lower the fluid resistance, and the lower the motor's torque load.

[0074] The specific duration of the final stage is not limited and can be set based on the total runtime and different working modes. For example, for the working mode selected for hard ingredients, a longer time is required to fully break them down. In one example, the final stage could be set as the last 30% of the total runtime. For instance, with a total runtime of 15 minutes, the final stage could be set as the last 5 minutes.

[0075] Of course, the above-mentioned conditions for completing the agitation can also be that the running time of the agitator motor reaches the total running time.

[0076] The aforementioned food mixing equipment control method involves acquiring noise signals generated during the mixing stage, determining the corresponding acoustic characteristic parameters, identifying the current noise scenario based on these parameters, and adjusting the operating parameters of the mixing motor using the corresponding motor control method. In the early or middle stages of mixing, the current noise scenario is determined by the acoustic characteristic parameters of the actual noise signals generated during mixing. This allows for the differentiation of noise components generated by different food ingredients during mixing, enabling dynamic adjustment of the mixing motor's operating parameters to ensure effective mixing while reducing noise interference. In the final stage of mixing, if the food ingredient fineness increases or the mixing volume decreases, and the mixing completion condition is met, the mixing motor is stopped to optimize the mixing process and avoid over-mixing caused by a fixed-time mode.

[0077] In one exemplary embodiment, the operating parameters of the agitator motor include motor speed, and the acoustic characteristic parameters include the decibel value of the noise signal. Correspondingly, as... Figure 3As shown, step S206, which determines the current noise scene based on acoustic feature parameters, includes step S302: when the decibel value of the noise signal is greater than or equal to the first decibel threshold, the current noise scene is determined to be a high sound pressure scene, and the motor control method corresponding to the high sound pressure scene is the first control method, which includes reducing the motor speed.

[0078] Specifically, this embodiment takes the decibel value of the noise signal as an example of acoustic characteristic parameters. When the decibel value of the noise signal is greater than or equal to the first decibel threshold, it can be determined that the current noise scene is a high sound pressure scene, which indicates that the energy of the noise signal is very high and belongs to a scene that will cause great noise interference to the equipment environment.

[0079] Furthermore, in high sound pressure level scenarios, the motor control mode should be set as the primary control mode to reduce noise interference to the equipment environment. Taking adjusting the motor speed as an example, the primary control mode could include reducing the motor speed.

[0080] In one example, the decibel value of a noise signal acquired by a microphone sensor can be obtained using the following formula:

[0081]

[0082] Among them, V rms V is the root mean square voltage value of the microphone sensor output signal. ref The reference voltage is used. The specific value of the first decibel threshold G1 is not limited and can be obtained based on test results of the decibel values ​​of noise signals generated by stirring different ingredients. For example, for hard ingredients, the noise signal generated in the early stages of stirring is approximately 70-90 decibels; for soft ingredients, the noise signal generated in the early stages of stirring is approximately 60-80 decibels. As the stirring process progresses, entering the middle stage, the noise signal generated by hard ingredients is approximately 65-85 decibels; the noise signal generated by soft ingredients is approximately 55-75 decibels. Through analysis, in this embodiment, the first decibel threshold G1 can be set to 65 decibels.

[0083] In an exemplary embodiment, the operating parameters of the agitator motor also include the total running time. Correspondingly, the first control method further includes increasing the total running time. It is understood that in high sound pressure level scenarios, the motor control method needs to be set to the first control method, such as reducing the motor speed, to reduce noise interference to the equipment environment. However, reducing the motor speed will also reduce the agitation effect. Therefore, the first control method may also include increasing the total running time to agitate for a longer period, ensuring that the overall agitation effect remains unchanged.

[0084] It is understandable that adjusting the motor speed and total running time can be achieved in various ways. For example, the motor speed and total running time can be adjusted based on a fixed adjustment ratio each time, or the corresponding adjustment ratio can be dynamically determined based on the difference between the current decibel value and the first decibel threshold.

[0085] In one example, an adjustment ratio can be set based on the dominant frequency value of the noise signal, dynamically determining the adjustment ratio to adjust the motor speed and total running time. The dominant frequency value refers to the frequency component with the highest energy in the frequency distribution characteristics of the noise signal. This application can preset the adjustment ratio corresponding to the dominant frequency value based on the positive correlation between the dominant frequency value and the adjustment ratio, to be applied to dynamically adjust the operating parameters of the stirring motor. This can be understood as setting a larger adjustment ratio when the dominant frequency value and energy of the noise signal are higher, and a smaller adjustment ratio when the dominant frequency value and energy of the noise signal are lower. This design allows for the adjustment of the stirring motor's operating parameters according to the specific energy distribution of the noise signal, ensuring that the frequency distribution characteristics of the noise signal are accurately changed after adjustment, reducing the highest energy frequency component.

[0086] In one example, to simplify the process of setting the adjustment ratio, multiple frequency ranges can be defined, and then the adjustment ratio corresponding to each frequency range can be preset. During actual adjustment, the corresponding adjustment ratio can be obtained based on the frequency range to which the dominant frequency value belongs, and can be applied to dynamically adjust the operating parameters of the stirring motor.

[0087] In one exemplary embodiment, the first control method further includes: reducing the motor speed based on a first preset adjustment ratio corresponding to the dominant frequency value. And in another exemplary embodiment, the first control method further includes: increasing the total running time based on a first preset adjustment ratio corresponding to the dominant frequency value.

[0088] Specifically, the dominant frequency value of the noise signal can be obtained by signal processing the noise signal through a time-domain to frequency-domain transformation method. The specific type of time-domain to frequency-domain transformation method is not unique; for example, it can be Fourier transform, short-time Fourier transform, etc. In this embodiment, Fourier transform can be used to process the noise signal, converting the time-domain signal f(t) into a frequency-domain expression F(ω) to obtain the dominant frequency value of the noise signal. The processing formula for Fourier transform can be expressed as follows:

[0089]

[0090] Here, the frequency domain expression F(ω) represents the amplitude of the noise signal at each frequency value in the frequency domain. Then, based on the amplitude corresponding to each frequency value, a polling comparison can be performed to obtain the frequency value that satisfies the peak detection condition (e.g., using local maximum search) as the dominant frequency value.

[0091] Furthermore, after obtaining the dominant frequency value of the noise signal, a first preset adjustment ratio can be obtained based on the preset correspondence between the dominant frequency value and the adjustment ratio, and the motor speed and total running time can be adjusted accordingly based on the first preset adjustment ratio. Specifically, in the first control method, the adjustment method involves reducing the motor speed and increasing the total running time according to the first preset adjustment ratio.

[0092] It is understandable that reducing the motor speed according to the first preset adjustment ratio can be achieved by first obtaining the motor speed adjustment range by multiplying the first preset adjustment ratio by the current motor speed, and then reducing the motor speed adjustment range based on the current motor speed to obtain the adjusted motor speed for controlling the agitator motor.

[0093] Similarly, increasing the total running time according to the first preset adjustment ratio can also be achieved by first multiplying the first preset adjustment ratio by the current total running time to obtain the total running time adjustment range, and then increasing the total running time adjustment range on the basis of the current total running time to obtain the adjusted total running time to control the stirring motor to stop running.

[0094] In one exemplary embodiment, the acoustic characteristic parameters also include the dominant frequency value of the noise signal. Correspondingly, continuing to refer to... Figure 3 Step S206, which involves determining the current noise scene based on acoustic characteristic parameters, further includes steps S304 and S306. Wherein:

[0095] Step S304: If the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is greater than or equal to the first preset frequency value, the current noise scenario is determined to be a high-frequency noise scenario, and the motor control method corresponding to the high-frequency noise scenario is the first control method.

[0096] It is understandable that when the decibel value of a noise signal is less than the first decibel threshold, although it indicates that the noise signal energy is not high, it is still necessary to further determine the frequency distribution of the noise signal based on the dominant frequency value to avoid noise interference that is not strong but has a high pitch, such as sharp and piercing noise interference. For example, in the initial stage of blending hard ingredients such as almonds, nuts, or ice cubes, high-frequency noise may occur.

[0097] Specifically, in this embodiment, taking the dominant frequency value of the noise signal as an example, when the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is greater than or equal to the first preset frequency value, it can be determined that the current noise scene is a high-frequency noise scene, characterized by the frequency distribution of the noise signal being high-frequency noise, which belongs to a scene of noise interference with low intensity but high pitch.

[0098] Furthermore, in high-frequency noise scenarios, the motor control method should be set as the primary control method to reduce noise interference to the equipment environment. The primary control method can include reducing motor speed and increasing total runtime. It can be understood that in high-frequency noise scenarios, reducing motor speed can effectively suppress the impact of high-frequency noise sources, while increasing the total runtime can compensate for the overall agitation effect. The specific limitations of the primary control method can be found in the relevant description above regarding high sound pressure level scenarios, and will not be repeated here.

[0099] The first preset frequency value represents the frequency threshold of high-frequency noise, which can be set according to the frequency distribution of the actual noise signal. This application embodiment does not limit this setting.

[0100] Step S306: When the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is less than the second preset frequency value, the current noise scenario is determined to be a low-frequency noise scenario. The motor control method corresponding to the low-frequency noise scenario is the second control method, which includes increasing the motor speed.

[0101] Specifically, this embodiment takes the dominant frequency value of the noise signal as an example, which is an acoustic characteristic parameter. When the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is less than the second preset frequency value, the current noise scene can be determined to be a low-frequency noise scene. This is characterized by the frequency distribution of the noise signal being low-frequency noise, which is a noise scene with low intensity and low pitch. For example, low-frequency noise is more likely to occur in the middle and later stages of stirring soft ingredients such as soy milk or rice paste.

[0102] Furthermore, in low-frequency noise scenarios, where noise interference is minimal, the motor control mode can be set to a second control mode to improve overall mixing efficiency. Taking adjusting the motor speed as an example, the second control mode could include increasing the motor speed. It can be understood that increasing the motor speed effectively accelerates the crushing speed of the ingredients, thereby improving overall mixing efficiency and speeding up the mixing process.

[0103] In one exemplary embodiment, the operating parameters of the agitator motor also include the total running time. Correspondingly, the second control method further includes reducing the total running time. It can be understood that in low-frequency noise scenarios, setting the motor control method to the second control method, such as increasing the motor speed, effectively improves the overall agitation efficiency. At the same time, the second control method may also include reducing the total running time to shorten the agitation duration and compensate for the over-processing caused by increasing the motor speed.

[0104] In one example, increasing the motor speed in the second control method can be achieved by increasing the motor speed based on a second preset adjustment ratio corresponding to the dominant frequency value. Similarly, reducing the total running time in the second control method can be achieved by reducing the total running time based on a second preset adjustment ratio corresponding to the dominant frequency value.

[0105] Consistent with the above, this embodiment can also preset the adjustment ratio corresponding to the dominant frequency value based on the positive correlation between the dominant frequency value and the adjustment ratio, so as to dynamically adjust the operating parameters of the stirring motor. This can be understood as setting a larger adjustment ratio when the dominant frequency value and energy of the noise signal are higher, and a smaller adjustment ratio when the dominant frequency value and energy of the noise signal are lower. The method for obtaining the dominant frequency value of the noise signal can also be referred to the description above, and will not be repeated here.

[0106] Furthermore, after obtaining the dominant frequency value of the noise signal, a second preset adjustment ratio can be obtained based on the preset correspondence between the dominant frequency value and the adjustment ratio. The motor speed and total running time are then adjusted accordingly based on this second preset adjustment ratio. Specifically, in the second control method, the adjustment method involves increasing the motor speed and decreasing the total running time based on the second preset adjustment ratio.

[0107] It is understandable that increasing the motor speed according to the second preset adjustment ratio can be achieved by first multiplying the second preset adjustment ratio by the current motor speed to obtain the motor speed adjustment range, and then increasing the motor speed adjustment range based on the current motor speed to obtain the adjusted motor speed for controlling the agitator motor.

[0108] Similarly, reducing the total running time according to the second preset adjustment ratio can also be achieved by first multiplying the second preset adjustment ratio by the current total running time to obtain the total running time adjustment range, and then reducing the total running time adjustment range based on the current total running time to obtain the adjusted total running time to control the agitator motor to stop running.

[0109] In one exemplary embodiment, such as Figure 4As shown, the above-mentioned food mixing equipment control method further includes step S207: in the final stage of the mixing stage, and when the decibel value of the noise signal is less than or equal to the second decibel threshold, the current noise scene is determined to be a low sound pressure scene, and the operating parameters of the mixing motor of the food mixing equipment are adjusted by the third control method corresponding to the low sound pressure scene. The third control method includes reducing the motor speed.

[0110] Specifically, this embodiment takes the decibel value of the noise signal as an example of acoustic characteristic parameters. When the decibel value of the noise signal is less than or equal to the second decibel threshold, the current noise scene can be determined to be a low sound pressure scene, which is characterized by a low energy of the noise signal. If the current noise scene is determined to be a low sound pressure scene at the end of the mixing stage, it can be judged that the ingredients have been mixed into relatively fine pieces.

[0111] The method for obtaining the decibel value of the noise signal is described above and will not be repeated here. The specific value of the second decibel threshold G2 is not limited and can be obtained based on the test results of the decibel values ​​of the noise signals generated by stirring different ingredients. For example, at the end of the stirring stage, the noise signal generated by hard ingredients is approximately 45-60 decibels; the noise signal generated by soft ingredients is approximately 40-55 decibels. Through analysis, in this embodiment of the application, the second decibel threshold G2 can be set to 50 decibels.

[0112] Furthermore, in the final stage of the mixing process, and assuming the current noise level is low, the motor control mode can be set to a third control mode to reduce ineffective mixing during the final stage. Taking adjusting the motor speed as an example, the third control mode could include reducing the motor speed. This can be understood as effectively reducing the mixing force on the ingredients.

[0113] In one exemplary embodiment, the operating parameters of the agitator motor also include the total running time. Correspondingly, the third control method may also include reducing the total running time. It can be understood that in low sound pressure scenarios, reducing the total running time can shorten the agitation duration and reduce the ineffective agitation process in the final stage.

[0114] In one example, reducing motor speed in the third control method can be achieved by reducing motor speed based on a third preset adjustment ratio corresponding to the dominant frequency value. Similarly, reducing total running time in the third control method can also be achieved by reducing total running time based on a third preset adjustment ratio corresponding to the dominant frequency value.

[0115] Consistent with the above, this embodiment can also preset the adjustment ratio corresponding to the dominant frequency value based on the positive correlation between the dominant frequency value and the adjustment ratio, so as to dynamically adjust the operating parameters of the stirring motor. This can be understood as setting a larger adjustment ratio when the dominant frequency value and energy of the noise signal are higher, and a smaller adjustment ratio when the dominant frequency value and energy of the noise signal are lower. The method for obtaining the dominant frequency value of the noise signal can also be referred to the description above, and will not be repeated here.

[0116] Furthermore, after obtaining the dominant frequency value of the noise signal, a third preset adjustment ratio can be obtained based on the preset correspondence between the dominant frequency value and the adjustment ratio. The motor speed and total running time are then adjusted accordingly based on this third preset adjustment ratio. Specifically, in the third control method, the adjustment method involves reducing the motor speed and the total running time based on the third preset adjustment ratio.

[0117] It is understandable that reducing the motor speed according to the third preset adjustment ratio can be achieved by first multiplying the third preset adjustment ratio by the current motor speed to obtain the motor speed adjustment range, and then reducing the motor speed adjustment range based on the current motor speed to obtain the adjusted motor speed for controlling the agitator motor.

[0118] Similarly, reducing the total running time according to the third preset adjustment ratio can also be achieved by first multiplying the third preset adjustment ratio by the current total running time to obtain the total running time adjustment range, and then reducing the total running time adjustment range based on the current total running time to obtain the adjusted total running time to control the agitator motor to stop running.

[0119] In one example, to simplify the process of setting the adjustment ratio, multiple frequency ranges can be defined, and then the adjustment ratio corresponding to each frequency range can be preset. During actual adjustment, the corresponding adjustment ratio can be obtained based on the frequency range to which the dominant frequency value belongs, and can be applied to dynamically adjust the operating parameters of the stirring motor.

[0120] It should be noted that in the embodiments of this application, the dominant frequency value of the acquired noise signal may be one or multiple, and needs to be determined based on the actual analysis results. For example Figure 5 In one example shown, the dominant frequency values ​​of the acquired noise signal include two dominant frequency values: 100Hz and 230Hz.

[0121] In an exemplary embodiment, the above-mentioned food mixing equipment control method further includes: when there are multiple dominant frequency values ​​of the noise signal, fusing the preset adjustment ratios corresponding to the frequency intervals to which each dominant frequency value belongs to obtain a first preset adjustment ratio, a second preset adjustment ratio, and a third preset adjustment ratio.

[0122] Specifically, in the first control method, it is possible to first determine the frequency range to which multiple dominant frequency values ​​belong, then match the first preset adjustment ratio corresponding to the multiple dominant frequency values ​​based on the preset correspondence between frequency range and adjustment ratio, and then merge the above multiple first preset adjustment ratios to obtain the final first preset adjustment ratio, which can be applied to dynamically adjust the operating parameters of the stirring motor.

[0123] In the second control method, it is possible to first determine the frequency range to which multiple dominant frequency values ​​belong, then match the second preset adjustment ratio corresponding to the multiple dominant frequency values ​​based on the preset frequency range-adjustment ratio correspondence, and then merge the above multiple second preset adjustment ratios to obtain the final second preset adjustment ratio, which can be applied to dynamically adjust the operating parameters of the stirring motor.

[0124] In the third control method, the frequency range to which multiple dominant frequency values ​​belong can be determined first. Then, based on the correspondence between the preset frequency range and the adjustment ratio, the third preset adjustment ratio corresponding to the multiple dominant frequency values ​​can be matched and obtained. The above multiple third preset adjustment ratios can then be merged to obtain the final third preset adjustment ratio, which can be applied to dynamically adjust the operating parameters of the stirring motor.

[0125] There is no single way to merge multiple preset adjustment ratios; it can be done by using the average value as the fusion result or by merging based on different weight coefficients.

[0126] It's understandable that the adjustment ratio of the operating parameters of a blending motor in a single operation needs to be set based on certain technical constraints and performance balance considerations. For example, a sudden increase in motor speed may cause impact on the bearings and transmission mechanism, significantly affecting the motor's lifespan and posing certain safety hazards. Furthermore, the motor rotor has an inherent resonant frequency; excessive adjustment may trigger resonance. In the application scenario of food blending equipment, a sudden change in motor speed can also significantly affect the uniformity of food blending.

[0127] Correspondingly, in one example, the first, second, and third preset adjustment ratios are set to values ​​less than the preset ratio values. These preset ratio values ​​can be set according to the actual operating parameter range of the agitator motor to avoid excessive adjustments to the operating parameters.

[0128] Taking a stirring motor starting at a speed of 15000 RPM and a total running time of 20 minutes as an example, the preset ratio can be set to 1%, that is, the preset adjustment ratio is set to a value less than 1%. Correspondingly, if the first preset adjustment ratio is 0.45%, the motor speed adjustment range can be calculated as: 15000 * 0.45% = 112.5 RPM, and the total running time adjustment range can be calculated as: 20 minutes * 0.45% = 0.15 minutes.

[0129] In an exemplary embodiment, the above-described food mixing equipment control method further includes: at the end of the mixing stage, determining whether the mixing completion conditions are met based on acoustic characteristic parameters. Specifically, this can be set based on the equivalent continuous sound level of the noise signal, i.e., the average energy of the sound pressure level is less than a certain threshold over a period of time. Alternatively, it can be set based on the amplitude of the dominant frequency values ​​of noise signals from multiple directions to reflect whether the noise amplitudes in multiple directions tend to stabilize.

[0130] In one exemplary embodiment, the noise signal includes noise signals collected from multiple measurement points, and the acoustic characteristic parameters include the dominant frequency value and amplitude of the noise signal. Figure 6 As shown, determining whether the mixing completion conditions are met based on acoustic characteristic parameters includes the following steps S402 and S404. Wherein:

[0131] Step S402: Calculate the absolute amplitude error of the noise signal based on the amplitude of the dominant frequency values ​​of multiple noise signals.

[0132] Specifically, when the noise signal includes noise signals collected from multiple measurement points, the dominant frequency value can be calculated for each noise signal, and then the dominant frequency values ​​of all noise signals can be summed to obtain the final dominant frequency value. When there is overlap between the dominant frequency values ​​of multiple noise signals, the higher amplitude can be retained as the amplitude of the overlapping dominant frequency value.

[0133] Furthermore, taking the final result of obtaining three dominant frequency values, with amplitudes corresponding to Q1, Q2, and Q3 respectively, as an example, the absolute amplitude error X2 can be calculated according to the following formula:

[0134] X2=|(Q1-q)|+|(Q2-q)|+|(Q3-q)|

[0135] Where q is the average of the amplitudes of the three dominant frequency values, i.e., q = (Q1 + Q2 + Q3) / 3.

[0136] Step S404: If the absolute amplitude error of the noise signal is less than a preset error threshold, it is determined that the stirring completion condition is met.

[0137] Specifically, if the absolute amplitude error X2 of the noise signal is less than the preset error threshold X1, it indicates that the amplitude of the noise signal in multiple directions tends to a certain uniform value, and the overall noise signal tends to be stable. Correspondingly, it can be determined that the ingredients have been sufficiently mixed and the mixing process can be ended. Thus, it can be determined that the mixing completion condition has been met, and the mixing motor is controlled to stop running accordingly.

[0138] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0139] Based on the same inventive concept, this application also provides a food mixing equipment control device for implementing the aforementioned food mixing equipment control method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the food mixing equipment control device provided below can be found in the limitations of the food mixing equipment control method described above, and will not be repeated here.

[0140] In one exemplary embodiment, such as Figure 7 As shown, a food mixing equipment control device is provided, including: a noise signal acquisition module 710, an acoustic characteristic parameter determination module 720, a noise scene determination module 730, and a motor control module 740, wherein:

[0141] The noise signal acquisition module 710 is used to acquire the noise signal generated by the mixing when the food mixing equipment enters the mixing stage.

[0142] Acoustic characteristic parameter determination module 720 is used to determine the acoustic characteristic parameters corresponding to the noise signal;

[0143] The noise scene determination module 730 is used to determine the current noise scene based on acoustic characteristic parameters;

[0144] The motor control module 740 is used to adjust the operating parameters of the food mixing motor of the food mixing equipment using the motor control method corresponding to the current noise scenario. The operating parameters include the motor speed. It is also used to control the mixing motor to stop running at the end of the mixing stage if the mixing completion condition is met.

[0145] In an exemplary embodiment, the operating parameters include motor speed, and the acoustic characteristic parameters include the decibel value of the noise signal; the noise scene determination module 730 is further configured to determine that the current noise scene is a high sound pressure scene when the decibel value of the noise signal is greater than or equal to a first decibel threshold, and the motor control method corresponding to the high sound pressure scene is a first control method, the first control method including reducing the motor speed.

[0146] In one exemplary embodiment, the acoustic characteristic parameters also include the dominant frequency value of the noise signal;

[0147] The noise scene determination module 730 is further configured to determine that the current noise scene is a high-frequency noise scene when the decibel value of the noise signal is less than a first decibel threshold and the dominant frequency value is greater than or equal to a first preset frequency value, and the motor control method corresponding to the high-frequency noise scene is a first control method; and to determine that the current noise scene is a low-frequency noise scene when the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is less than a second preset frequency value, and the motor control method corresponding to the low-frequency noise scene is a second control method, the second control method including increasing the motor speed.

[0148] In an exemplary embodiment, the motor control module 740 is further configured to reduce the motor speed based on a first preset adjustment ratio corresponding to the dominant frequency value under a first control mode; and to increase the motor speed based on a second preset adjustment ratio corresponding to the dominant frequency value under a second control mode.

[0149] In an exemplary embodiment, the operating parameters of the agitator motor also include the total running time; the motor control module 740 is further configured to increase the total running time based on a first preset adjustment ratio corresponding to the dominant frequency value under the first control mode; and to decrease the total running time based on a second preset adjustment ratio corresponding to the dominant frequency value under the second control mode.

[0150] In an exemplary embodiment, the motor control module 740 is further configured to, when there are multiple dominant frequency values ​​of the noise signal, fuse the preset adjustment ratios corresponding to the frequency ranges to which each dominant frequency value belongs to obtain a first preset adjustment ratio and a second preset adjustment ratio.

[0151] In an exemplary embodiment, the noise scene determination module 730 is further configured to determine that the current noise scene is a low sound pressure scene when the noise signal decibel value is less than or equal to a second decibel threshold at the end of the mixing stage, and is further configured to adjust the operating parameters of the mixing motor of the food mixing equipment using a third control method corresponding to the low sound pressure scene, the third control method including reducing the motor speed.

[0152] In an exemplary embodiment, the motor control module 740 is further configured to reduce the motor speed based on a third preset adjustment ratio corresponding to the dominant frequency value under the third control mode.

[0153] In an exemplary embodiment, the operating parameters of the agitator motor also include the total running time; the motor control module 740 is further configured to reduce the total running time based on a third preset adjustment ratio corresponding to the dominant frequency value under the third control mode.

[0154] In an exemplary embodiment, the motor control module 740 is further configured to determine, based on acoustic characteristic parameters, whether the mixing completion conditions are met during the final stage of the mixing phase.

[0155] In an exemplary embodiment, the noise signal includes noise signals collected from multiple measurement points, and the acoustic characteristic parameters include the dominant frequency value and amplitude of the noise signal; the motor control module 740 is further configured to calculate the absolute amplitude error of the noise signal based on the amplitude of the dominant frequency values ​​of the multiple noise signals; if the absolute amplitude error of the noise signal is less than a preset error threshold, it is determined that the stirring completion condition is met.

[0156] Each module in the aforementioned food mixing equipment control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the electronic device in hardware form or independent of it, or stored in the memory of the electronic device in software form, so that the processor can call and execute the operations corresponding to each module.

[0157] In one exemplary embodiment, such as Figure 1 As shown, a food mixing device is provided, including a controller 110, a noise monitoring device 120 and a mixing motor 130 connected to the controller 110. The noise monitoring device 120 is used to monitor the noise signal generated by the food mixing device during the mixing stage. The controller 110 is used to receive the noise signal collected by the noise monitoring device 120 and control the operating parameters of the mixing motor 130 according to the food mixing device control method provided in the embodiments of this application.

[0158] The following is Figure 8 and Figure 9Using the flowchart shown as an example, the operation process of the food blending equipment provided in this embodiment will be explained. In this embodiment, the food blending equipment can be a high-speed blender. Specifically, it includes the following steps:

[0159] S101, the blender is starting up and is in the early to middle stage of the blending process. Then proceed to S102.

[0160] S102 uses multiple microphone sensors evenly distributed on the base of the blender to acquire noise signals from multiple directions, which are then sent to S103.

[0161] S103, through time-domain to frequency-domain conversion, performs signal processing on the noise signals collected from multiple directions to obtain the acoustic characteristic parameters of the noise signals, mainly including the decibel value, dominant frequency value, and amplitude corresponding to the dominant frequency value of the noise signals, and then proceeds to S104.

[0162] S104, determine whether the decibel value of the noise signal during the current stirring is greater than or equal to the set maximum decibel value G1, and proceed to S105, S106, or S107.

[0163] S105, when the judgment condition of S104 is met, the motor speed of the agitator motor is reduced proportionally and the total running time of the agitator motor is increased based on the first preset adjustment ratio corresponding to the dominant frequency value, and then proceeds to S102.

[0164] S106. If the judgment condition of S104 is not met, and the dominant frequency of the noise signal is greater than or equal to the set frequency value F1, proceed to S108.

[0165] S107. If the judgment condition of S104 is not met and the dominant frequency of the noise signal is less than the set frequency value F2, proceed to S109.

[0166] S108, based on the first preset adjustment ratio corresponding to the dominant frequency value, proportionally reduce the motor speed of the agitator motor and proportionally increase the total running time of the agitator motor, then proceed to S102.

[0167] S109, based on the second preset adjustment ratio corresponding to the dominant frequency value, proportionally increase the motor speed of the agitator motor and proportionally decrease the total running time of the agitator motor, and proceed to S102.

[0168] S110, the blender has reached the later stage of the blending process (final stage), then enters S111.

[0169] S111, determine whether the running time of the agitator motor has reached the total running time, then proceed to S115 or S112.

[0170] S112, through multiple microphone sensors evenly distributed on the base of the blender, acquires noise signals from multiple directions and enters S113.

[0171] S113, through time-domain to frequency-domain conversion, the noise signals collected from multiple directions are processed to obtain the acoustic characteristic parameters of the noise signals, mainly including the decibel value, dominant frequency value and the amplitude corresponding to the dominant frequency value of the noise signals, and then proceed to S114.

[0172] S114, determine whether the absolute error X2 of the amplitude of the dominant frequency value of the noise signal in multiple directions is less than the set error value X1, and proceed to S115 or S116.

[0173] S115. If the judgment condition in S111 or the judgment condition in S114 is met, the mixing phase is exited.

[0174] S116. If the judgment condition in S113 is not met, continue to judge whether the current noise signal decibel value is less than or equal to the set decibel value G2. If yes, proceed to S117; otherwise, proceed to S111.

[0175] S117, when the judgment condition of S116 is met, the motor speed of the agitator motor is reduced proportionally and the total running time of the agitator motor is reduced proportionally based on the third preset adjustment ratio corresponding to the dominant frequency value, and then proceeds to S111.

[0176] In this embodiment, noise signals are automatically detected during motor operation. In the early or middle stages of the mixing phase, the amount of food added is determined by the user. When a larger amount of food is added, the noise generated during motor mixing is louder, so the motor speed is reduced proportionally and the mixing time is increased. Conversely, when a smaller amount of food is added, the noise generated during motor mixing is quieter, so the motor speed is increased proportionally and the mixing time is reduced, optimizing the mixing process while ensuring the mixing effect. In the later stages of the mixing phase, the less food is ground or mixed, the quieter the motor mixing is, so the motor speed and mixing time are reduced proportionally, optimizing the mixing process. The motor speed and total running time can be intelligently adjusted according to the characteristics of the food (including hardness and amount added), dynamically adjusting the mixing parameters according to the specific usage scenario, thereby providing a more personalized and comfortable user experience.

[0177] The solution provided by this food mixing equipment is similar to the solution described in the above-mentioned food mixing equipment control method. Therefore, the specific limitations of the one or more food mixing equipment control embodiments can be found in the limitations of the food mixing equipment control method described above, and will not be repeated here.

[0178] In one exemplary embodiment, an electronic device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10 As shown, the electronic device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for controlling a food mixing device. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the electronic device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the electronic device, or external keyboards, touchpads, or mice, etc.

[0179] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0180] In one exemplary embodiment, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the above embodiments.

[0181] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0182] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0183] It should be noted that the user information (including but not limited to food mixing equipment information, user personal information, etc.) and data (including but not limited to data used to control the mixing motor, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with relevant regulations.

[0184] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0185] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0186] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling a food mixing device, characterized in that, The method includes: When the food mixing equipment enters the mixing stage, acquire the noise signal generated by the mixing; Determine the acoustic characteristic parameters corresponding to the noise signal; The current noise scene is determined based on the acoustic characteristic parameters, and the operating parameters of the mixing motor of the food mixing equipment are adjusted using the motor control method corresponding to the current noise scene. In the final stage of the mixing phase, if the mixing completion condition is met, the mixing motor is controlled to stop running.

2. The method according to claim 1, characterized in that, The operating parameters include the motor speed, and the acoustic characteristic parameters include the decibel value of the noise signal; Determining the current noise scene based on the acoustic feature parameters includes: If the decibel value of the noise signal is greater than or equal to the first decibel threshold, the current noise scene is determined to be a high sound pressure level scene. The motor control method corresponding to the high sound pressure level scene is the first control method, which includes reducing the motor speed.

3. The method according to claim 2, characterized in that, The acoustic characteristic parameters also include the dominant frequency value of the noise signal; The step of determining the current noise scene based on the acoustic feature parameters further includes: If the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is greater than or equal to the first preset frequency value, the current noise scene is determined to be a high-frequency noise scene, and the motor control method corresponding to the high-frequency noise scene is the first control method. When the decibel value of the noise signal is less than the first decibel threshold and the dominant frequency value is less than the second preset frequency value, the current noise scenario is determined to be a low-frequency noise scenario. The motor control method corresponding to the low-frequency noise scenario is the second control method, which includes increasing the motor speed.

4. The method according to claim 3, characterized in that, The first control method further includes: reducing the motor speed based on a first preset adjustment ratio corresponding to the dominant frequency value; The second control method further includes: increasing the motor speed based on a second preset adjustment ratio corresponding to the dominant frequency value.

5. The method according to claim 3 or 4, characterized in that, The operating parameters of the agitator motor also include the total running time; The first control method further includes increasing the total running time based on a first preset adjustment ratio corresponding to the dominant frequency value; The second control method also includes reducing the total running time based on a second preset adjustment ratio corresponding to the dominant frequency value.

6. The method according to claim 5, characterized in that, The method further includes: When there are multiple dominant frequency values ​​of the noise signal, the preset adjustment ratios corresponding to the frequency ranges to which each dominant frequency value belongs are fused to obtain the first preset adjustment ratio and the second preset adjustment ratio.

7. The method according to claim 3, characterized in that, The method further includes: In the final stage of the mixing phase, when the decibel value of the noise signal is less than or equal to the second decibel threshold, the current noise scenario is determined to be a low sound pressure scenario, and the operating parameters of the mixing motor of the food mixing equipment are adjusted using the third control method corresponding to the low sound pressure scenario. The third control method includes reducing the motor speed.

8. The method according to claim 7, characterized in that, The third control method further includes: reducing the motor speed based on a third preset adjustment ratio corresponding to the dominant frequency value.

9. The method according to claim 8, characterized in that, The operating parameters of the agitator motor also include the total running time; The third control method further includes reducing the total running time based on a third preset adjustment ratio corresponding to the dominant frequency value.

10. The method according to claim 1, characterized in that, The method further includes: At the end of the mixing stage, the acoustic characteristic parameters are used to determine whether the mixing completion conditions are met.

11. The method according to claim 10, characterized in that, The noise signal includes noise signals collected from multiple measurement points, and the acoustic characteristic parameters include the dominant frequency value and amplitude of the noise signal; The step of determining whether the mixing completion condition is met based on the acoustic characteristic parameters includes: The absolute amplitude error of the noise signal is obtained by calculating based on the amplitude of the dominant frequency values ​​of the multiple noise signals. If the absolute amplitude error of the noise signal is less than a preset error threshold, the stirring completion condition is determined to be met.

12. A control device for a food mixing equipment, characterized in that, The device includes: The noise signal acquisition module is used to acquire the noise signal generated during the mixing process when the food mixing equipment enters the mixing stage. An acoustic feature parameter determination module is used to determine the acoustic feature parameters corresponding to the noise signal; A noise scene determination module is used to determine the current noise scene based on the acoustic feature parameters; The motor control module is used to adjust the operating parameters of the mixing motor of the food mixing equipment using the motor control method corresponding to the current noise scenario; The motor control module is also used to control the agitator motor to stop running if the agitation completion conditions are met during the final stage of the agitation stage.

13. A food mixing device, characterized in that, The device includes a controller, a noise monitoring device and a mixing motor connected to the controller, the noise monitoring device being used to monitor the noise signal generated by the food mixing equipment during the mixing stage, and the controller being used to control the operating parameters of the mixing motor according to the steps of any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 11.

Images