Intelligent whipping control and monitoring system for eggbeater

Abstract

The invention provides an intelligent whipping control and monitoring system for an eggbeater, and the system comprises a rotating speed sensor, a torque sensor and a temperature sensor which are respectively used for detecting the rotating speed of the eggbeater, the torque change in the stirring process and the temperature of a stirred material in real time, and transmitting a detection signal to a control host. The control host comprises a processor and a memory, and standard torque curve databases corresponding to different whipping types are stored in the memory. And the processor calculates an actual torque curve of the current whipping process according to the sensor signal, and compares the actual torque curve with a standard torque curve in real time. When it is detected that the actual torque curve deviates from the standard torque curve and exceeds a preset threshold value, the system automatically adjusts the output power of the eggbeater motor so as to optimize the beating effect. According to the egg beater, accurate control over the beating process can be achieved, the stability of food material beating is improved, manual operation errors are reduced, and the intelligent level of the egg beater is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of egg beater control, and particularly to an intelligent whipping control and monitoring system for an egg beater. Background Art

[0002] In the field of food processing, egg beaters are widely used in scenarios such as egg white whipping, cream stirring, and batter mixing. Traditional egg beaters mainly rely on manual control, and users adjust the stirring speed and time based on experience to achieve the whipping effect of different textures of ingredients. Some high-end egg beaters integrate electronic speed regulation functions, enabling users to select fixed rotation speed modes to meet the needs of different ingredients.

[0003] However, there are still many problems in the actual use of existing egg beaters. First, the whipping processes of different ingredients have different requirements for rotation speed, stirring force, and temperature changes, and precise control cannot be achieved only through preset rotation speeds. Second, the physical properties of the stirred materials change dynamically during the whipping process, and traditional egg beaters lack a real-time monitoring mechanism, resulting in unstable stirring results. Finally, users usually need to continuously observe the whipping state and rely on personal experience for adjustment, which is complex to operate and easily affected by human errors.

[0004] Therefore, it is necessary to develop an intelligent whipping control and monitoring system for an egg beater. Summary of the Invention

[0005] The present application provides an intelligent whipping control and monitoring system for an egg beater to improve the control accuracy of the whipping process.

[0006] The present application provides an intelligent whipping control and monitoring system for an egg beater, including:

[0007] A rotation speed sensor, disposed on the motor shaft of the egg beater, for real-time detection of the rotation speed of the egg beater and transmission of the rotation speed signal to the control host;

[0008] A torque sensor, disposed on the stirring shaft of the egg beater, for detecting the torque change during stirring and transmission of the torque signal to the control host;

[0009] A temperature sensor, disposed near the stirring head of the egg beater, for detecting the temperature of the stirred material and transmission of the temperature signal to the control host;

[0010] A control host, in which a processor and a memory are provided; wherein, a standard torque curve database corresponding to different whipping types is stored in the memory; the processor is configured to: calculate the actual torque curve of the current whipping process in real time according to the rotation speed signal, torque signal and temperature signal; compare the actual torque curve with the standard torque curve in real time; when it is detected that the deviation between the actual torque curve and the standard torque curve exceeds a preset threshold, automatically adjust the output power of the egg beater motor so that the whipping process is maintained in an optimal state.

[0011] The present application has the following beneficial technical effects:

[0012] (1) Based on real-time rotation speed, torque and temperature signals, compare with the standard torque curve to achieve automatic power adjustment and ensure stable and efficient whipping process. (2) The system automatically monitors and adjusts the motor output, avoiding the need for users to manually judge the whipping state and improving the convenience of use. (3) By dynamically adjusting the stirring parameters, ensure that the ingredients are always in the best whipping state, improving the stability and consistency of the final product. (4) Preset the standard torque curve database for different whipping types, which is applicable to various ingredients such as protein, cream, batter, etc., to achieve wide adaptability. Description of the Drawings

[0013] Figure 1 It is a schematic diagram of an intelligent whipping control and monitoring system for an egg beater provided by the first embodiment of the present application. Detailed Embodiments

[0014] Many specific details are set forth in the following description in order to provide a thorough understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application. Therefore, the present application is not limited by the specific embodiments disclosed below.

[0015] The first embodiment of the present application provides an intelligent whipping control and monitoring system for an egg beater. Please refer to Figure 1 , which is a schematic diagram of the first embodiment of the present application. The following will be described in detail with reference to Figure 1 the intelligent whipping control and monitoring system for an egg beater provided by the first embodiment of the present application.

[0016] The intelligent whipping control and monitoring system for an egg beater includes a rotation speed sensor 101, a torque sensor 102, a temperature sensor 103 and a control host 104.

[0017] The rotation speed sensor 101 is disposed on the egg beater motor shaft and is configured to detect the rotation speed of the egg beater in real time and transmit the rotation speed signal to the control host.

[0018] The rotational speed sensor 101 is used to detect the rotational speed of the egg beater in real time, so as to provide accurate operation data to the control host 104, thereby realizing the intelligent control of the whipping process. The rotational speed sensor 101 is arranged on the motor shaft of the egg beater and is fixedly connected to the motor shaft, enabling it to directly measure the rotational speed of the motor shaft and generate corresponding rotational speed signals.

[0019] In an embodiment of the present invention, the rotational speed sensor 101 can adopt a Hall effect sensor, and its working principle is based on the induction of signals by magnetic field changes. When the motor shaft rotates, the magnet installed on the shaft will periodically pass by the Hall sensor, causing the sensor to detect the change in the magnetic field and output a pulse signal. The control host 104 can determine the current rotational speed by calculating the number of pulse signals within a unit time and perform subsequent analysis and control based on this rotational speed signal.

[0020] In another embodiment, the rotational speed sensor 101 can adopt an optical encoder. The optical encoder includes a fixed optical detection unit and a grating disk installed on the motor shaft. The grating disk rotates with the motor shaft and forms an alternating light and dark signal in the optical detection unit, thereby outputting a pulse signal. The control host 104 can calculate the real-time rotational speed based on the frequency of the pulses to ensure accurate monitoring of the operating state of the egg beater.

[0021] In addition, the rotational speed sensor 101 can transmit signals to the control host 104 in a wired or wireless manner. In the wired mode, communication protocols such as I 2 C, SPI or UART can be used to transmit data to ensure the stability and anti-interference ability of the signals. In the wireless mode, the rotational speed data can be transmitted to the control host via Bluetooth or Wi-Fi, which is suitable for intelligent home appliance integration systems. Regardless of the transmission mode adopted, the real-time and accuracy of the data need to be ensured to support the computing requirements of the control host 104.

[0022] To ensure the measurement accuracy, the installation position of the rotational speed sensor 101 should be as close as possible to the center of the motor shaft to avoid errors caused by shaft end vibration or mechanical structure gaps. At the same time, the fixing method between the sensor and the motor shaft can adopt bonding, screw fixing or embedded installation to ensure stable measurement during high-speed rotation. In addition, to prevent the external environment from affecting the detection accuracy of the sensor, a dust-proof cover or a sealing structure can be added to the surface of the sensor to reduce the interference of impurities such as dust and oil stains on the detection results.

[0023] In the specific application of the present invention, the control host 104 can adjust the motor output power of the egg beater in real time based on the signal of the rotational speed sensor 101. For example, in the initial stage of whipping egg whites, since the resistance of the liquid egg whites is relatively small, the control host can maintain a relatively high motor power output according to the rotational speed signal. When the egg whites gradually form foam and their resistance increases, the rotational speed may decrease. At this time, the control host can analyze the data of the torque sensor 102 and appropriately increase the motor power to compensate for the torque loss and maintain a stable stirring state. On the other hand, if it is detected that the rotational speed is too fast, it may lead to over-whipping and affect the quality of the final food. Therefore, the control host can automatically reduce the motor power to maintain the optimal whipping conditions.

[0024] In summary, as an important part of the present invention, the rotational speed sensor 101 provides accurate data support for the control host by real-time monitoring the rotational speed of the motor shaft of the egg beater, ensuring the stability and intelligent control of the whipping process. Its detection method can adopt a Hall effect sensor or an optical encoder, and the installation method can select a suitable fixing method according to the equipment structure and communicate with the control host in a wired or wireless manner to ensure the stable transmission and processing of data.

[0025] Furthermore, the rotational speed sensor adopts an adaptive multi-mode detection structure to improve the detection accuracy and enhance the adaptability to complex whipping working conditions. The rotational speed sensor includes:

[0026] A dual-channel rotational speed acquisition module, which combines optical sensing and Hall effect sensing technologies. Among them, optical sensing is used for high-precision detection of the rotational speed of the motor shaft, while Hall effect sensing is used to detect magnetic field changes to provide redundant signals in high-speed or low-speed states, ensuring that even when the sensor is covered with dust or interfered by ambient light, the rotational speed can still be accurately measured;

[0027] A dynamic signal calibration unit, connected to the control host, adaptively adjusts the filtering parameters of the rotational speed signal based on the torque sensor data and the motor load conditions, and uses an adaptive Kalman filtering algorithm to remove high-frequency noise and mechanical resonance interference, improving the real-time stability of the rotational speed signal and preventing misjudgment caused by the shaking of the stirring shaft or equipment aging;

[0028] An intelligent inertia compensation system, which combines the historical rotational speed curve with the current detection data, calculates the transient rotational speed fluctuation through the control host, and provides inertia prediction compensation during sudden changes in the motor load in a short time (such as adding auxiliary materials or changes in the density of ingredients), so as to avoid too fast or too slow instantaneous adjustment of the motor and improve the stability of the entire whipping process;

[0029] The energy feedback regulation module provides real-time signals to the control host when the rotational speed sensor detects slight vibrations or uneven loads in the motor operating state, enabling the system to finely adjust the power output, thereby reducing secondary vibrations caused by power changes, optimizing energy consumption, and improving the overall efficiency and service life of the egg beater.

[0030] The rotational speed sensor adopts an adaptive multi-mode detection structure to improve detection accuracy and enhance adaptability to complex whipping conditions, enabling the egg beater to provide accurate rotational speed monitoring data under different ingredients, different environments, and different load conditions, ensuring the stability and uniformity of the whipping process. This rotational speed sensor combines two detection technologies, photoelectric sensing and Hall effect sensing, and through a series of signal optimization and compensation mechanisms, improves the stability and anti-interference ability of the data, enabling the device to still maintain high-precision operation control under various extreme working conditions.

[0031] The dual-channel rotational speed acquisition module is the core part of this sensor. Through the dual detection of photoelectric sensing and Hall effect sensing, it realizes high-precision monitoring of the rotational speed of the motor shaft. The photoelectric sensor is based on the principle of beam occlusion or reflection detection. There are high-contrast marking points or encoding disks on the motor shaft. When the shaft rotates, the photoelectric detector can continuously capture the change frequency of the marks, thereby calculating the rotational speed. This method has the characteristics of high precision and is suitable for accurate measurement under high-speed operation. However, in some working conditions, such as when the optical window is covered by dust or food residue after long-term use of the device, it may affect the detection accuracy. Therefore, a Hall effect sensor is added as a redundant signal source. The Hall effect sensor calculates the rotational speed by detecting the change of the magnetic field on the motor shaft and is not affected by optical interference, and can provide stable detection results under low-speed operation or harsh environments. When the system is running, the control host can integrate the data of the photoelectric signal and the Hall signal and automatically select the optimal signal source, switching to the Hall signal when the photoelectric signal is contaminated, ensuring the continuity and reliability of the measurement.

[0032] The dynamic signal calibration unit is connected to the control host and is mainly used for signal filtering and optimization to improve the accuracy of data. Since the motor rotating at high speed may be affected by bearing vibration, external noise, or the structural resonance of the equipment itself during operation, the sensor signal may be interfered by high-frequency noise, resulting in misreading. This calibration unit adopts the adaptive Kalman filtering algorithm to filter the rotational speed signal in real time, which can effectively remove the errors caused by high-frequency noise and mechanical resonance, while maintaining the response speed of the signal, making the data both stable and having good dynamics. In addition, this unit can dynamically adjust the filtering parameters based on the torque sensor data and the motor load conditions. For example, when a torque mutation is detected, the system may temporarily relax the filtering range to quickly adapt to the load change and avoid the situation of lagging misjudgment. This dynamic adjustment mechanism makes the rotational speed data more accurate and can adapt to different working states, improving the measurement reliability of the egg beater under various complex working conditions.

[0033] The intelligent inertia compensation system analyzes and predicts the transient rotational speed fluctuation of the motor by combining the historical rotational speed curve with the current detection data, thereby improving the stability of the system. During the whipping process, the user may temporarily add auxiliary materials or adjust the amount of ingredients, which may cause an instantaneous mutation in the motor load, affecting the stability of the rotational speed and thus the final whipping quality. This system can identify these sudden load changes and calculate a reasonable power adjustment strategy through the inertia prediction algorithm, enabling the motor to make a smooth transition and avoiding problems such as overshoot or overcompensation caused by mutations. For example, when a load increase is detected, the system does not immediately increase the motor power but calculates and anticipates an appropriate speed increase amplitude to make the adjustment process smoother, thereby reducing the impact on the stirring process. This compensation mechanism not only helps to improve the consistency of ingredient whipping but also reduces the mechanical shock of the motor and extends the service life of the equipment.

[0034] The energy feedback regulation module is an important part of this system, aiming to optimize the motor power output and improve the overall energy efficiency of the equipment. When the rotational speed sensor detects slight vibration or uneven load in the motor operation state, this module will provide a real-time feedback signal to the control host, enabling the system to finely adjust the motor power, thereby reducing the secondary vibration caused by power changes. The core principle of this mechanism is to calculate the optimal power output method by detecting the motor operation state, so that the motor always operates at the most energy-efficient working point. For example, during low-load operation, the system can appropriately reduce the motor power to reduce unnecessary energy consumption, while during high-load operation, it can adjust the power output according to the real-time load demand, enabling the motor to meet the stirring requirements without consuming excessive energy. In addition, this module can combine the energy consumption pattern during the entire whipping process to optimize the power curve, enabling the egg beater to operate in a more efficient manner at different working stages, improving the overall energy efficiency ratio, and reducing the motor heating problem during long-term operation.

[0035] The rotational speed sensor of the present invention adopts dual-channel detection, multi-level signal optimization, and an intelligent compensation mechanism, enabling the egg beater to operate stably under various complex working conditions, ensuring high precision and stability of data. Through innovative technologies such as adaptive signal calibration, inertial prediction compensation, and energy feedback regulation, the system can not only adapt to different load changes, but also optimize the motor power output, improve the overall operation efficiency, and extend the service life of the equipment.

[0036] The torque sensor 102 is arranged on the stirring shaft of the egg beater and is used to detect the torque change during the stirring process and transmit the torque signal to the control host.

[0037] The torque sensor 102 is used to detect the torque change suffered by the stirring shaft of the egg beater during the stirring process and transmit this signal to the control host 104 to achieve precise monitoring and automatic adjustment of the whipping state. This sensor is installed on the stirring shaft of the egg beater, and its installation position can be selected in the middle of the shaft or at one end close to the stirring head to ensure that the real-time change of torque during the stirring process can be accurately measured. Since the rheological properties of the ingredients change continuously during the stirring process, the real-time monitoring of the torque sensor can effectively reflect the whipping degree and provide key data for the control host to achieve intelligent control.

[0038] In an embodiment of the present invention, the torque sensor 102 can adopt a strain gauge type torque sensor, which uses the change of strain resistance to detect torque. When the stirring shaft is subjected to rotational resistance, a small deformation will occur on the surface of the shaft, and the strain gauge attached to the shaft will change its resistance accordingly and convert this change into an electrical signal. This electrical signal can be accurately read and processed by the control host after being amplified by the signal conditioning circuit. To improve the detection accuracy, the strain gauges of the sensor should be evenly adhered to the surface of the stirring shaft, and the signal line shielding treatment should be ensured to reduce the error caused by electromagnetic interference.

[0039] In another embodiment, the torque sensor 102 can adopt a magnetoelectric or optoelectronic measurement method. The magnetoelectric torque sensor uses the magnetostrictive effect to calculate the torque by measuring the change of the magnetic flux of the shaft. This method is suitable for non-contact measurement, which can effectively reduce mechanical wear and improve the long-term stability of the equipment. The optoelectronic torque sensor sets a grating structure on the stirring shaft and uses a light source and a photodetector to measure the change of the torsional angle of the shaft, thereby calculating the torque value. This method has a high resolution and is suitable for application scenarios that require precise measurement of small torque changes.

[0040] The signal of the torque sensor 102 can be transmitted to the control host 104 in a wired or wireless manner. In the wired mode, voltage signals or digital signals can be used for transmission. For example, using I 2C, SPI or CAN bus protocols to ensure the stability of data transmission. In the wireless mode, low-power wireless communication protocols such as Bluetooth or ZigBee can be adopted, enabling the sensor to adapt to more flexible installation requirements, especially in situations where mechanical wiring needs to be reduced. Regardless of the method used, signal acquisition and transmission must have high anti-interference capabilities to avoid the influence of environmental factors on data accuracy.

[0041] To ensure the stability and accuracy of detection, the installation of the torque sensor 102 needs to consider the reliability of the mechanical structure. When using a strain gauge sensor, the sensor needs to be firmly fixed to the stirring shaft with an adhesive and a protective layer is covered on the surface to prevent the influence of external moisture, dust or grease on the sensor performance. When using a magnetoelectric or optoelectronic sensor, it is necessary to ensure the stable relative position between the sensor and the stirring shaft to guarantee the measurement accuracy. In addition, the working environment of the sensor should avoid strong vibrations to reduce the possibility of misdetection.

[0042] In practical applications, the detection data of the torque sensor 102 can help the control host 104 analyze the current state of the food ingredients. For example, during the process of whipping egg whites, the egg whites gradually change from a liquid state to a foam. As the number of bubbles increases, its viscosity and resistance will gradually increase, and correspondingly, the torque of the stirring shaft will also increase. The control host can judge the whipping degree of the egg whites by analyzing the change trend of the torque signal and adjust the motor power in a timely manner to keep the whipping process in the best state. If the torque changes too quickly or exceeds the set threshold, the system can automatically reduce the motor speed to prevent over-whipping and ensure the stable quality of the final food. In addition, during the whipping process of cream or batter, the change in torque can also reflect the mixing uniformity and consistency, and the control host can adjust the stirring speed based on the torque curve to optimize the whipping effect.

[0043] In summary, the torque sensor 102 plays a key monitoring role in the present invention. It can detect the torque change of the stirring shaft in real time and provide accurate data support so that the control host can make intelligent adjustments according to the actual state of the whipped material. By implementing measurements with different types of torque sensors, suitable solutions can be selected according to different application requirements, and appropriate signal transmission methods can be adopted to ensure measurement accuracy, stability and the overall reliability of the system.

[0044] The torque sensor plays a core monitoring and regulation role in the present invention. Its multi-dimensional composite detection structure aims to improve the measurement accuracy and ensure the stability and intelligence of the whipping process. Since the viscosity of the ingredients varies during the stirring process, the traditional torque detection method is easily affected by short-term fluctuations, resulting in the system being unable to make timely adjustments. Therefore, this torque sensor adopts a flexible strain gauge array, a dynamic compensation unit, a transient impact detection module, and a self-learning feedback system to more accurately monitor and adapt to various complex stirring conditions, improving the consistency and reliability of whipping.

[0045] The flexible strain gauge array is arranged on the surface of the stirring shaft to form a high-precision torque detection grid. This structure can sense the axial and radial torque changes in real time under different load states. The change in torque will cause a small deformation on the surface of the shaft, and the strain gauge can capture these deformations and calculate the torque value through the small change in resistance. Since the rheological properties of the ingredients change continuously during the stirring process, such as the gradual transformation of protein from a liquid state to a foam state, or the formation of different viscous layers in the batter during stirring, this grid detection method can ensure a stable monitoring signal under various ingredient viscosity conditions. Compared with the traditional single-point torque sensor, this array can be evenly distributed in the key areas of the stirring shaft and automatically adjust the detection sensitivity according to the force change, so as to obtain more accurate real-time information on the ingredient state.

[0046] To further optimize the accuracy of the data, the dynamic compensation unit is connected to the control host. Based on the rotational speed, temperature, and load historical data, it adaptively corrects the torque measurement error. Since the torque signal may shift under high and low load states, especially when the ingredients have strong fluidity at the initial stage of whipping, the measurement data may be interfered by factors such as centrifugal force and shear force. Therefore, this unit adopts a real-time compensation mechanism. By analyzing the load mode of the motor and combining historical data, it corrects the torque signal output by the sensor. In addition, this unit uses a neural network model to analyze the torque change trend during the whipping process to predict the upcoming viscosity mutation situation, enabling the system to adjust the motor power output in advance. For example, during the protein whipping process, the formation of foam will cause the torque to gradually increase. This system can predict the development of the torque curve based on the data of the previous few seconds and reduce the motor power at the appropriate time to prevent over-whipping, thus reducing the risk of foam collapse. In addition, when stirring high-viscosity ingredients (such as butter or batter), this unit can adapt to the non-linear change of the load, prevent the stirring speed from fluctuating too much, and improve the stability of the overall stirring rhythm.

[0047] The transient impact detection module is built with a high-sensitivity inertial sensor, which is specifically used to identify instantaneous torque fluctuations caused by uneven distribution of ingredients or sudden external forces. During the stirring process, if some ingredients suddenly enter the stirring area or fail to be evenly distributed after the addition of auxiliary materials, the torque of the stirring shaft will fluctuate violently in a short period of time, which may cause the equipment to vibrate or the load of the stirring head to rise sharply. To prevent these sudden changes from impacting the stirring system, this module can, while detecting abnormal torque fluctuations, adjust the stirring path or motor power through the control host to make the torque curve return to a stable state. For example, when the system detects that the local viscosity of the ingredients is too high, resulting in a sudden increase in torque, the control host can briefly reduce the stirring speed, allow the ingredients to flow fully, and then restore the original speed, reducing the uneven stirring caused by the impact. In addition, this module can also protect the structure of the stirring shaft during high-load operation, avoiding damage to bearings or mechanical structures caused by long-term vibration and improving the overall durability of the equipment.

[0048] The self-learning feedback system, based on historical whipping data and real-time torque curves, continuously optimizes the operation strategy of the equipment, enabling it to adapt to the subtle differences of different batches of ingredients and providing personalized adjustment solutions after multiple uses by the user. Since the viscosity and characteristics of the same type of ingredient may vary due to factors such as brand, storage conditions, or room temperature, traditional preset torque curves may not fully match all situations. Therefore, this system can store whipping curves of different batches and find the best stirring strategy for similar ingredients through data analysis, gradually adjusting the standard torque curve database. For example, during continuous multiple uses, if the system detects that the user often manually adjusts the motor power at a certain time point, the system will record this behavior and automatically optimize the stirring power curve in the future, enabling the equipment to actively adapt to the user's usage habits. In addition, in situations where the environment changes significantly, such as in a lower temperature or higher humidity environment, this system can combine the data from temperature sensors for torque correction, making the stirring process more stable and reducing the quality fluctuations of whipping caused by environmental factors.

[0049] The multi-dimensional composite detection structure of this torque sensor, through the collaborative work of the flexible strain gauge array, dynamic compensation unit, transient impact detection module, and self-learning feedback system, enables the equipment to maintain high-precision monitoring capabilities under various stirring conditions and provide intelligent feedback regulation. Whether it is during the process of whipping egg whites, stirring cream, or mixing high-viscosity batter, this system can accurately identify the state of the ingredients, optimize the stirring rhythm, and ensure the stability and consistency of the final product by intelligently adjusting the motor power. Through this innovative design, the egg beater can be made more intelligent and precise, while improving the user experience, reducing the need for human intervention, and always maintaining the best whipping effect under different ingredient conditions.

[0050] The temperature sensor 103 is set near the stirring head of the egg beater and is used to detect the temperature of the stirred material and transmit the temperature signal to the control host.

[0051] The temperature sensor 103 is used to detect the temperature of the stirred material and transmit the temperature signal to the control host 104 to ensure temperature monitoring and regulation during the whipping process. Since temperature has a significant impact on the whipping effect, for example, the whipping efficiency of egg whites is optimal within an appropriate temperature range, and too high or too low a temperature may lead to whipping failure. Therefore, real-time temperature monitoring helps to optimize the overall stirring process and enables the final product to achieve an ideal quality.

[0052] In the embodiment of the present invention, the temperature sensor 103 is set near the stirring head so as to be as close as possible to the stirred material while avoiding measurement errors caused by direct contact with the stirring head. The sensor can be installed on the outer surface of the stirring head by mechanical fixation or adhesion, or embedded in the internal structure of the stirring head to reduce the influence of the ambient temperature on the measurement. For the scheme of directly measuring the material temperature, the temperature sensor can be in contact with the metal part of the stirring head through a heat-conducting material, enabling the sensor to quickly sense the temperature change of the material and provide accurate data in real time.

[0053] The temperature sensor 103 can adopt different types of sensors such as a thermistor, a thermocouple, or an infrared temperature sensor. The specific selection depends on the detection accuracy, response speed, and whether contact measurement is required. When using a thermistor, the temperature change will cause a change in the resistance value, and the control host can calculate the temperature value by measuring the change in resistance. This method has a simple structure and low cost and is suitable for most application scenarios, but it may be affected by the heat dissipation of the egg beater itself. When using a thermocouple, the temperature sensor can measure the potential change generated by the temperature difference between the contact points of two different metals and then calculate the temperature. This method has a wide measurement range and is suitable for egg beaters with higher power or applications that require precise control of temperature changes. When using an infrared temperature sensor, the sensor can measure the temperature based on the infrared wavelength radiated by the surface of the material to achieve non-contact measurement. This method will not affect the stirring process and can avoid sensor contamination caused by adhering materials, improving the long-term stability of the measurement.

[0054] To improve the measurement accuracy, the signal of the temperature sensor 103 needs to be filtered and corrected by a signal processing circuit to reduce noise interference and improve data stability. The measurement signal can be transmitted to the control host 104 in analog or digital mode. In the analog mode, the temperature signal is usually transmitted in the form of voltage or current, while in the digital mode, data can be transmitted through communication protocols such as I 2 C, SPI, or UART. To ensure the stability of signal transmission, shielded wires or differential signal transmission can be used for long-distance transmission to reduce the influence of electromagnetic interference.

[0055] In practical applications, the data of the temperature sensor 103 can be used for various control logics. For example, during the process of whipping egg whites, the control host 104 can adjust the working state of the egg beater based on the temperature data. When it detects that the temperature is too low, the control host can appropriately increase the motor power or suggest that the user take external heating measures to accelerate the whipping speed of the egg whites. When the temperature is too high, the system can reduce the rotation speed of the egg beater to reduce the frictional heat generated during the stirring process, or prompt the user to take cooling measures to prevent the protein structure from being damaged. In addition, during the process of whipping cream, too high a temperature may cause poor emulsification of the cream. The control host can use the data of the temperature sensor to adjust the stirring strategy in advance to keep the temperature within the optimal range at all times.

[0056] In summary, the temperature sensor 103 plays an important role in this invention by monitoring the temperature of the stirred material in real time and providing key data support for the control host. Its detection method can adopt contact or non-contact measurement. Select the appropriate sensor type according to different application requirements, and ensure the accuracy and stability of the data through appropriate signal processing and transmission methods. Through the real-time monitoring of this temperature sensor, the egg beater can adjust the stirring process more intelligently, improve the whipping quality, and ensure the consistency and reliability of food processing.

[0057] The temperature sensor plays a key role in this invention. Its multi-point temperature detection structure and intelligent thermal compensation algorithm ensure that the stirred material is always within the optimal temperature range throughout the whipping process, improve the measurement accuracy, and optimize the temperature control in different whipping stages, enabling the system to adapt to different types of ingredients and intelligently adjust the stirring strategy to ensure the stability and consistency of the final whipping quality.

[0058] To obtain more accurate temperature data, the temperature sensor adopts a multi-point distributed temperature measurement unit, which is respectively arranged inside the stirring head, at the connection of the stirring shaft, and on the outer wall of the stirring chamber. Since the stirring process involves high-speed rotation, material flow, and continuous contact between the stirring head and the container wall, single-point temperature detection may lead to misjudgment, especially when the ingredients are not evenly distributed. Therefore, this multi-point temperature measurement structure can ensure that the temperature measurement is not limited to one area, but covers multiple key points in the entire stirring area. For example, the sensor inside the stirring head can detect the core temperature of the material, the sensor at the connection of the stirring shaft can identify the temperature change caused by stirring friction, and the sensor on the outer wall of the stirring chamber can monitor the influence of the external environment temperature. This distributed temperature measurement scheme can effectively reduce the overall temperature misjudgment caused by local measurement deviation, enable the control host to obtain more comprehensive temperature data, and ensure the precise control of the heating or cooling state of the entire ingredient.

[0059] During long-term operation, the continuous operation of the motor may cause the local temperature to rise, and the change in ambient temperature may also affect the whipping state of the ingredients. To solve these problems, the temperature sensor integrates a dynamic thermal compensation module, which is connected to the control host and dynamically corrects the temperature measurement value based on the motor operating state, ambient temperature, and the heat capacity parameters of the material. After the motor operates for a long time, the internal temperature of the device may rise due to insufficient heat dissipation. Without compensation, it may lead to errors in the measurement data. For example, during low-speed stirring, the motor generates less heat, and the measurement data can more accurately reflect the true temperature of the material. However, during high-speed operation, the additional heat generated by the motor may cause the temperature sensor value near the stirring shaft to be on the high side. Therefore, the compensation module will automatically calculate and adjust the measurement data by combining the motor speed, running time, and external ambient temperature to ensure that the temperature signal accurately reflects the true state of the ingredients. In addition, the compensation module can also optimize the power adjustment strategy of the control host, enabling the egg beater to adjust the stirring rhythm while maintaining the appropriate temperature of the ingredients to prevent the rapid temperature change from affecting the final whipping effect.

[0060] To further improve the intelligent level of temperature control, the temperature sensor also integrates an intelligent temperature control system. This system combines historical temperature data with the current ingredient state to predict the temperature change trend and actively adjusts the stirring power and rhythm when it may affect the whipping quality. For example, during the protein whipping process, too high a temperature may cause the protein foam to collapse, affecting the final texture. Therefore, when the system detects that the temperature is approaching the critical value, the control host can automatically reduce the stirring speed or the motor power output to control the heat generated by friction, thereby maintaining the optimal whipping conditions. Similarly, during the cream whipping process, if the temperature is too low, the milk fat may not be fully emulsified, resulting in uneven final whipping. The system can adjust the stirring strategy at the appropriate time to gradually bring the ingredients to the ideal temperature. In addition, the system can also provide user prompts. When it detects that the ingredient temperature deviates from the optimal range, it will notify the user through the interface or voice, such as suggesting that the user refrigerate the cream to the appropriate temperature in advance, or preheat the ingredients in advance in a winter environment to optimize the overall whipping effect.

[0061] Since traditional contact temperature sensors may be affected by the fluidity of the food ingredients, contamination of the sensor surface, or mechanical structure limitations, resulting in a decrease in measurement accuracy, this temperature sensor also integrates a non-contact infrared temperature measurement auxiliary unit. This unit is installed in the outer edge area of the mixing head and provides additional temperature monitoring data by detecting the infrared radiation on the surface of the food ingredients, compensating for the limitations of contact temperature measurement. Compared with traditional temperature measurement methods, infrared temperature measurement technology can quickly respond to temperature changes and avoid problems such as decreased sensitivity caused by the sensor surface being covered by food ingredients or long-term use. This infrared temperature measurement auxiliary unit can combine with contact temperature measurement data, enabling the system to adapt to different types of food ingredients and adjust the temperature measurement method respectively in liquid, semi-solid, or solid mixtures, improving the accuracy and stability of overall temperature detection. In high-temperature environments, such as when mixing mayonnaise or syrup, the system can preferentially use non-contact temperature measurement to avoid the influence of viscous food ingredients on the sensor. In low-temperature application scenarios, such as when mixing cream or smoothies, the system can combine contact sensors to provide more stable temperature data.

[0062] Through this design, this temperature sensor can provide accurate temperature monitoring and control in different food ingredients, different environments, and different mixing stages, enabling the egg beater to more intelligently adapt to various complex working conditions, improving the stability of the whipping process, and reducing the need for human intervention. Combining distributed temperature measurement, multi-level thermal compensation, intelligent temperature control adjustment, and non-contact temperature measurement technology, the entire mixing system can dynamically adapt to different temperature changes, providing more powerful guarantee for the quality of the final food.

[0063] The control host 104, in which a processor and a memory are provided; wherein, a standard torque curve database corresponding to different whipping types is stored in the memory; the processor is configured to: calculate the actual torque curve of the current whipping process in real time according to the rotation speed signal, torque signal, and temperature signal; compare the actual torque curve with the standard torque curve in real time; when it is detected that the deviation between the actual torque curve and the standard torque curve exceeds a preset threshold, automatically adjust the output power of the egg beater motor to keep the whipping process in the best state.

[0064] The control host 104, as the core component of the present invention, is responsible for receiving and processing the real-time signals obtained from the rotation speed sensor 101, torque sensor 102, and temperature sensor 103, and calculating the state of the current whipping process based on the standard torque curve database corresponding to different whipping types preset in the memory, thereby dynamically adjusting the motor output power to achieve intelligent control. The control host 104 mainly includes a processor and a memory inside, which respectively undertake the tasks of data calculation and storage management, enabling the entire system to efficiently and accurately execute whipping control.

[0065] As the computing core of the control host, the processor can be a high-performance microcontroller (MCU), a digital signal processor (DSP), or an embedded processor. Its main function is to collect data from various sensors and perform real-time analysis. The processor reads analog signals from the torque sensor and temperature sensor through the analog-to-digital conversion module (ADC), and receives pulse signals provided by the rotational speed sensor through the counter module. The timer integrated inside the processor is used to ensure the synchronization of data acquisition and avoid calculation errors caused by inconsistent data updates. In addition, to improve the computing efficiency, the processor can adopt multi-threading or interrupt mechanisms to ensure that while processing sensor data, it can perform tasks such as torque curve comparison, anomaly detection, and motor control.

[0066] The memory is used to store the standard torque curve database, system parameters, and historical data. The standard torque curve database contains the torque change characteristics for different types of ingredients, such as the gradually increasing trend of torque during egg white whipping, the stable range during cream stirring, and the torque fluctuation pattern during batter mixing. These data can be based on empirically measured values from experiments or generated through machine learning algorithms to ensure the best adaptability. In addition, the memory is also used to record the historical data of the whipping process for subsequent analysis and optimization. The memory can use non-volatile memory (such as EEPROM, Flash memory) to ensure that data will not be lost after a power outage, and at the same time, RAM can be used as a temporary cache to accelerate data processing.

[0067] One of the core functions of the control host 104 is to calculate the actual torque curve of the current whipping process in real time and compare it with the standard torque curve. Based on the rotational speed signal, torque signal, and temperature signal, the processor uses algorithms such as curve fitting and smoothing filtering to calculate the current whipping curve and establish a torque curve that changes over time in the memory. Then, the processor extracts the standard torque curve of the corresponding ingredient from the database and performs a real-time comparison. When it is detected that the deviation of the actual torque curve from the standard torque curve exceeds the preset threshold, the processor will trigger a command to adjust the motor power to bring the whipping process back to the optimal state.

[0068] The regulation of the motor output power is an important function for controlling the main machine. When the torque curve deviates from the standard range, the processor can adjust the motor drive circuit through PWM (Pulse Width Modulation) signals to change the input voltage of the motor, thereby controlling its speed and torque. For example, during the process of whipping egg whites, when the torque rises too fast, it indicates that the foam has formed and may enter the over-whipped state. At this time, the processor will reduce the motor power to appropriately decrease the stirring speed to prevent the collapse of the egg white structure; when the torque rises slowly, it indicates that the egg whites have not been fully foamed, and the processor can appropriately increase the motor power to accelerate the whipping process. In addition, in the case of high torque, the processor can dynamically adjust the stirring strategy, such as increasing the motor power for a short period of time and then gradually decreasing it to make the whipping process more stable.

[0069] In terms of temperature control, the control main machine can perform temperature compensation according to the data of the temperature sensor. If the temperature is too low, it may cause difficulty in foaming the egg whites, and the control main machine can appropriately increase the motor speed to increase the heat generated by stirring friction; if the temperature is too high, it may affect the emulsification effect of the cream, and the control main machine can reduce the stirring intensity, or in some advanced applications, actively reduce the material temperature by communicating with an external refrigeration device. In addition, the stored temperature data can be used for subsequent analysis, such as optimizing the whipping curve under different seasons or ambient temperatures.

[0070] Signal transmission and system interaction are important parts of the control main machine. The control main machine exchanges data with each sensor through communication protocols such as I 2 C, SPI or UART, and controls the motor driver through PWM or other signals. In addition, the control main machine can integrate a wireless communication module, such as Wi-Fi or Bluetooth, enabling users to remotely monitor the whipping status through a mobile application (APP) or a smart home system and adjust the device parameters as needed. Through the display screen or LED indicator lights, users can understand the whipping progress in real time, and the control main machine can also provide alarm prompts in case of abnormalities, such as overload protection, too high temperature or abnormal torque fluctuations.

[0071] In summary, the control main machine 104 undertakes the tasks of core data processing, real-time monitoring, intelligent regulation and system interaction in the present invention. Through an efficient processor and memory architecture, combined with a variety of signal processing and calculation algorithms, the whipping process is made more stable and accurate, and can adapt to the needs of different types of food ingredients. The automatic adjustment mechanism based on torque curve comparison ensures consistent whipping effects under different environmental conditions. At the same time, combined with the temperature control strategy, it improves the quality of food processing and provides users with a more intelligent usage experience.

[0072] Furthermore, the processor of the control host adopts an adaptive non-linear regulation algorithm to optimize the power regulation of the motor during the whipping process. The adaptive non-linear regulation algorithm includes the following steps:

[0073] The processor receives real-time data from the rotational speed sensor, torque sensor, and temperature sensor, and constructs the state variable matrix S(t) provided by Equation 1 below:

[0074]

[0075] where ω(t) is the current rotational speed of the stirring shaft, in rad / s, and this data is detected in real time by the rotational speed sensor;

[0076] T τ (t) is the torque of the current stirring shaft, in N·m, and this data is measured by the torque sensor, representing the resistance force on the stirring shaft and being directly related to the viscosity of the ingredients;

[0077] T θ (t) is the temperature of the ingredients, in °C, and this data is measured by the temperature sensor, affecting the rheological properties and whipping stability of the ingredients;

[0078] P(t) is the current motor power, in W, representing the energy consumption of the egg beater at time t, and this value can be calculated from the current and voltage of the motor;

[0079] represents the instantaneous change rate of torque, in rad / s 2 , and this value is calculated by the processor through numerical differentiation of the data from the rotational speed sensor, reflecting the acceleration or deceleration state of the current motor;

[0080] represents the instantaneous change rate of torque, in N·m / s, and this value is calculated by the processor through numerical differentiation of the data from the torque sensor, reflecting the change in the viscosity of the ingredients in a short period of time.

[0081] Based on the state variable matrix, the processor calculates the target motor power adjustment amount ΔP according to Equation 2 below:

[0082]

[0083] where T τ (t) is the torque of the current stirring shaft;

[0084] is the standard torque curve corresponding to the current ingredients, in N·m, and this curve is stored in the database of the control host, and its optimal stirring torque range is set according to different types of ingredients (such as egg white, cream, batter);

[0085] represents the instantaneous change rate of torque; ω(t) is the current rotational speed of the stirring shaft;

[0086] ω std (t) is the target rotational speed curve, with the unit of rad / s. This value is also stored in the database and is dynamically adjusted according to different whipping stages. For example, during the formation process of protein from liquid to foam structure, the rotational speed usually needs to be gradually reduced to prevent over-stirring;

[0087] T θ (t) is the temperature of the food ingredients;

[0088] is the optimal temperature curve, with the unit of °C, representing the optimal temperature that the food ingredients should maintain at different whipping stages. For example, a lower temperature is beneficial for the stability of protein foam during whipping, while cream is easier to whip at an appropriate temperature.

[0089] K1, K2, K3, K4 are adaptive gain coefficients; their recommended values are 50 rad / s, 0.5 rad / s 2 , 0.2 N·m, and 5 W / K respectively.

[0090] The processor adjusts the motor power according to the following formula 3:

[0091] P(t + 1) = P(t) + ΔP(3)

[0092] where P(t + 1) is the motor power at time t + 1, with the unit of W, representing the power output adjusted by the system according to the current state; P(t) is the current motor power; ΔP is the motor power adjustment amount ΔP, which is obtained according to formula 2.

[0093] In the present invention, the processor of the control host further adopts a non-linear time-varying compensation algorithm to dynamically optimize the adjustment of the motor power during the whipping process, enabling the stirring process to adapt to the characteristics of different food ingredients, reducing power fluctuations caused by sudden viscosity changes or uneven stirring, and thus improving the consistency and stability of the whipping quality. This compensation mechanism is based on the transient characteristics of torque changes and adjusts the motor power by calculating the compensation correction term C(t) to keep the stirring shaft running smoothly in a complex food ingredient environment.

[0094] Calculate the compensation correction term C(t) according to the following formula 4:

[0095]

[0096] where, is the second derivative of torque, representing the acceleration change of torque with time, with the unit of N·m / s 2, which is used to characterize the acceleration of the viscosity change of the food ingredients, that is, the non-linear change rate of the torque during the stirring process. When the state of the food ingredients undergoes a sudden change, such as when the protein is whipped into a stable foam stage, or when the torque suddenly drops due to the adjustment of the fluidity of the high-viscosity batter, the second derivative can effectively capture this phenomenon, ensuring that the control system can make adjustments in advance to avoid energy waste or uneven stirring caused by inertia. In order to make this compensation term adaptable to different types of food ingredients, its gain coefficient λ1 should be adjusted according to the characteristics of different food ingredients, and the recommended value range is 0.1–0.5. The unit of λ1 is s.

[0097] The non-linear amplification term representing the torque change rate, where represents the first derivative of the torque, with the unit of N·m / s, which is used to describe the trend and rate of torque change. Due to the different physical properties of the food ingredients, their viscosities may show non-linear changes. Especially during high-speed stirring, the change of shear stress inside the food ingredients may cause the torque to rise or fall instantaneously. In order to enhance the adaptability of the system to torque changes at different rates, this term adopts an exponential amplification method, where the exponent α ranges from 0.5–2. When α is 0.5, the system is more sensitive to slowly changing torque changes, while when α is 2, the system has a stronger response ability to violently changing torque changes. The gain coefficient λ2 is mainly used to adjust the influence weight of this term, and the recommended value range is 0.05–0.2 to ensure that the compensation intensity will not cause the system to over-adjust. The unit of λ2 is:

[0098]

[0099] Calculate the product of the rotational speed change rate and the torque change rate, with the unit of (rad / s 2 )·(N·m / s) = W / s, which is used to evaluate the dynamic response of the stirring shaft caused by the change of food ingredient resistance. When the rotational speed of the motor changes, its load may change instantaneously. This term can capture the synchronous change trend of torque and rotational speed, ensuring that the system can maintain a stable stirring effect when adjusting the power. For example, when the rotational speed suddenly rises but the torque change is small, it indicates that the fluidity of the food ingredients increases, and at this time, there is no need to significantly adjust the power; while when the rotational speed drops but the torque increases violently, it indicates that the viscosity of the food ingredients has increased significantly, and it is necessary to increase the power output to maintain the stirring intensity. The gain coefficient λ3 is responsible for the influence of this term on the total power adjustment, and its recommended value range is 0.5–2. The unit of λ3 is s 2 .

[0100] After calculating the compensation correction term C(t), according to the following formula 5, update the motor power adjustment amount:

[0101] P′(t + 1) = P(t) + ΔP + C(t) (5)

[0102] Among them, P′(t + 1) is the motor power at time t + 1; P(t) is the current motor power; ΔP is the motor power adjustment amount ΔP, which is obtained according to Formula 2.

[0103] The introduction of this compensation algorithm enables the system to achieve more precise power control under complex ingredient conditions, improve the mixing quality, optimize the energy consumption management at the same time, and reduce the situations of overmixing or power waste. By reasonably setting the gain coefficients λ1, λ2, and λ3, the system can dynamically adjust the power output strategy according to the characteristics of different ingredients, making the quality of the final product more stable and enhancing the overall intelligence level of the equipment.

[0104] As an important part of the present invention, the control interface realizes the interaction between the user and the intelligent whipping control and monitoring system of the egg beater, enabling the user to intuitively monitor the whipping state and adjust the operating parameters of the equipment according to actual needs. The control interface consists of a display module, a touch input module, an intelligent recommendation module, and a voice prompt module, and establishes stable data interaction with the control host to ensure the intelligence, precision, and personalization of the whipping process.

[0105] The main function of the display module is to provide visual data feedback, enabling the user to grasp the operating state of the egg beater in real time. This module uses a high-definition LCD or OLED screen, which can intuitively display key parameters such as rotational speed, torque, and temperature, and uses a dynamic graph to show the comparison between the current actual torque curve and the standard torque curve. To improve readability, the display interface uses color coding, and the curves and data changes in different states are represented by different colors or dynamic animations, enabling the user to quickly judge whether the whipping is in the best state. For example, when the torque change curve deviates greatly from the standard curve, the system can warn the user through color and provide corresponding adjustment suggestions. In addition, the display module can provide a time-axis progress bar, intuitively reflecting the phased changes in the whipping process, and combining historical data analysis to enable the user to obtain more precise preset parameters in subsequent use.

[0106] The touch input module provides users with convenient parameter setting and mode selection, enabling the operating mode of the egg beater to be adjusted according to the characteristics of different ingredients. Users can select the whipping mode through the touch screen. For example, for different ingredients such as egg whites, cream, and batter, the corresponding whipping mode can be selected, and the system automatically matches the standard torque curve and optimizes the whipping strategy. In addition, users can also manually adjust the torque sensitivity to adapt to the individual differences of different batches of ingredients. For example, in a low-humidity environment, egg whites may require a longer whipping time, and users can make fine adjustments through this module to ensure the final whipping effect. The temperature adjustment strategy setting function enables users to optimize the temperature requirements of different ingredients. For example, for cream-based foods, a low-temperature mode can be set to avoid emulsion failure, while for egg yolk batter, an appropriate temperature compensation strategy can be set to ensure that the viscosity reaches the ideal state. In addition, the personalized whipping curve setting function allows users to adjust parameters during actual use and store them as custom modes. The system can directly call these parameters during subsequent use, improving the convenience and consistency of use.

[0107] The intelligent recommendation module provides users with optimized whipping parameter suggestions based on the historical data stored in the control host and the current ingredient status. This module analyzes past usage data and combines current sensor feedback to intelligently predict the best whipping strategy. For example, during the egg white whipping process, this module can judge the formation of egg white foam based on the changing trends of the real-time temperature and torque curve, and recommend to users to adjust the whipping speed or extend the stirring time at the appropriate time. When abnormal changes during the stirring process are detected, such as a sudden increase or decrease in torque, this module can provide an early warning and recommend that users take corresponding measures, such as reducing the stirring intensity or adjusting the stirring time. The intelligent recommendation module can also be personalized and optimized based on the usage habits of different users. For example, for the texture or consistency preferred by certain users, the system can generate a personalized curve based on multiple usage data to make each whipping process more in line with user needs.

[0108] The voice prompt module provides users with instant audio feedback, enabling users to grasp the whipping status without looking at the display screen. This module uses intelligent voice synthesis technology and can announce the current whipping progress, such as "The egg whites have reached the seven-point whipped state. You can continue to stir to form a more stable foam" or "The torque has risen abnormally. It is recommended to reduce the stirring speed to prevent over-whipping". When an abnormal state is detected, the voice prompt module can actively warn users. For example, when the system detects that the motor is overloaded or the temperature is too high, it issues prompts such as "The device temperature is abnormal. Please check the stirring ingredients" or "The stirring resistance is too large. It is recommended to reduce the amount of ingredients" to ensure that users can make adjustments in a timely manner. In addition, this module also supports the user voice control function. Users can perform simple operations through voice commands, such as "Start whipping", "Switch to high-speed mode", "Reduce the rotation speed", etc., improving the operation convenience and reducing cumbersome manual settings.

[0109] The control interface of the present invention not only provides intuitive data display and convenient operation methods, but also has intelligent parameter recommendation and real-time voice feedback functions, enabling the egg beater to more precisely adapt to the whipping requirements of different ingredients and be optimized in combination with the user's personalized preferences. Through efficient data interaction and intelligent control, the whipping process has been comprehensively optimized to ensure that each whipping can achieve the best effect, while reducing the user's dependence on whipping techniques and making the egg beater more intelligent and user-friendly.

[0110] The intelligent stirring head assembly, as an important part of the present invention, aims to optimize the stirring flow path of the ingredients, improve the uniformity of whipping, and reduce adhesion problems through a series of innovative structures and control methods, thereby significantly enhancing the working efficiency and whipping quality of the egg beater. This assembly can adaptively adjust the angle of the stirring paddle, optimize the ingredient distribution, and combine vibration and centrifugal effects to ensure a more stable whipping effect, adapt to the characteristics of different ingredients, and reduce the need for manual intervention.

[0111] The adaptive stirring paddle structure adopts adjustable angles and deformation characteristics, enabling the stirring paddle to dynamically adjust according to torque data and resistance changes during the stirring process. Based on the real-time calculation of the torque signal, the control host analyzes the viscosity of the ingredients and the mixing resistance, and adjusts the tilt angle or rotation direction of the stirring paddle through the actuator to adapt to the current stirring requirements of the ingredients. For example, at the initial stage of whipping egg whites, the torque is small, and the stirring paddle can maintain a steeper angle to enhance the shearing effect and accelerate foam formation; when the egg whites are approaching the stiff peak stage, the torque increases, and the system can automatically adjust the angle of the stirring paddle to make the stirring more gentle to prevent the foam structure from being damaged. This dynamic adjustment mechanism effectively avoids problems such as local over-stirring or uneven mixing, making the entire whipping process more efficient and stable. In addition, the shape of the stirring paddle can adaptively change according to the whipping mode selected by the user. For example, through the adjustment of flexible materials or mechanical structures, a geometric shape more suitable for whipping egg whites or stirring cream is formed to adapt to the characteristics of different ingredients.

[0112] In order to reduce the problem of uneven stirring or reduced efficiency caused by the adhesion of ingredients to the surface of the stirring paddle, the surface of the stirring paddle adopts a food-grade low-adhesion coating or microstructure design, making it difficult for high-viscosity ingredients such as egg whites and cream to adhere to the stirring paddle, thereby improving the smoothness of stirring. This coating can be a nano-coating with hydrophobic and oleophobic properties, which can reduce the accumulation of ingredients on the surface of the stirring paddle, allowing the stirring head to move more freely without interference from attachments, while reducing the difficulty of cleaning and enhancing the ease of use of the equipment. In addition, in the microstructure surface design, a micron-level raised texture is formed on the surface of the stirring paddle, which reduces the adhesion by reducing the contact area of ​​the ingredients, and uses the shear force generated during the stirring process to automatically peel off the attached ingredients, further reducing residues and improving the full mixing effect of the ingredients.

[0113] In order to optimize the mixing distribution of ingredients, the outer edge of the mixing head is designed with a centrifugal force-assisted discharge structure. This structure uses the centrifugal effect during high-speed rotation to make the ingredients evenly diffuse outward during the mixing process, avoiding some materials from being trapped near the mixing paddle, thereby improving the overall mixing efficiency. The centrifugal discharge channel is designed on the outer edge of the mixing head. Through the fluid dynamics-optimized guide groove structure, the materials can be distributed according to the set flow path during the mixing process to ensure that the ingredients in the entire mixing chamber are fully mixed. For example, during the egg white whipping process, the centrifugal force of the stirring head can promote the uniform distribution of bubbles and avoid excessive accumulation of egg white foam in a certain area. During the batter mixing process, this structure can ensure that the powder ingredients are evenly dispersed, making the final stirring effect more stable and controllable. This design reduces the problem of food retention in dead corners, avoids uneven whipping due to local material accumulation, and improves the overall whipping quality of the ingredients.

[0114] During the whipping process, due to the low fluidity of some ingredients, it is easy to form local adhesion or uneven mixing in the stirring chamber. The intelligent stirring head assembly specially introduces a vibration fine-tuning module, which is integrated inside the stirring shaft. When the adhesion or uneven stirring of ingredients is detected, the ingredients are redistributed through short-term micro-vibration, reducing the blind area of ​​stirring and improving the overall stirring effect. The intensity and frequency of the vibration can be dynamically adjusted by the control host according to the torque data and temperature data. For example, when the torque of a certain area is detected to increase suddenly, it may indicate that the ingredients in the area are over-aggregated. The vibration module can start a short-term high-frequency vibration to make the ingredients flow again and break the stagnation area near the stirring paddle. In addition, the module can be combined with intelligent control strategies, such as strong vibration in the early stage of egg white whipping to promote foam formation, and gradually reduce the vibration amplitude in the later stage to avoid affecting the stability of the foam structure. This intelligent vibration mechanism can effectively improve the problem of uneven whipping, make the stirring effect more stable and consistent, and reduce the user's manual intervention in the whipping process, improving the level of automation.

[0115] The design of the intelligent stirring head assembly not only optimizes the shape of the stirring paddle, enabling it to adapt to different states of the ingredients, but also reduces adhesion problems through a low-adhesion surface, combines a centrifugal force-assisted discharging structure to improve the uniform distribution of the ingredients, and dynamically adjusts the stirring state through a vibration fine-tuning module to achieve more intelligent and precise whipping control. This structure can effectively improve the intelligence level of the egg beater, enabling it to maintain consistent whipping quality under different ingredients and environmental conditions, significantly reducing the need for manual intervention, and enhancing the overall performance and user experience of the device.

[0116] The intelligent ingredient dosing system is an important part of the present invention, aiming to optimize the blending effect of the ingredients during stirring by precisely controlling the dosing time, dosing speed, and dosing amount of the auxiliary materials, ensuring the uniformity and stability of the final product. Based on the real-time monitoring data of the control host, this system is linked with key parameters such as rotational speed, torque, and temperature, making the dosing process more accurate, thus improving the whipping efficiency and reducing errors caused by manual intervention.

[0117] The controllable dosing device is ingeniously integrated at the top or side of the egg beater, designed with multiple independent dosing bins to meet the storage and dosing requirements of different auxiliary materials. Each dosing bin works independently and can store powdered sugar, vanilla extract, lemon juice, tartaric acid, or other stabilizers respectively, and uses an electric switch or a controllable valve for quantitative release, thus avoiding problems such as uneven stirring or excessive local concentration caused by one-time dosing. The structure of the dosing bin adopts a sealed design, which can effectively prevent the powdered or liquid auxiliary materials from caking or volatilizing due to changes in environmental humidity, thus ensuring the accuracy and stability of dosing. During the dosing process of powdered auxiliary materials, a vibration mechanism is set at the bottom of the dosing bin to make the auxiliary materials fall evenly, preventing caking problems caused by moisture or static electricity and improving the fluidity of dosing. For liquid auxiliary materials, the dosing bin is equipped with a micro-pump mechanism to enable the liquid to be stably released in the form of drops or atomization, thus preventing the local concentration from being too high due to direct pouring of the liquid and affecting the whipping effect.

[0118] The dosing control module is connected to the control host. By analyzing the rotational speed, torque, and temperature data, it accurately calculates the current stirring state and, in combination with the standard whipping curve, determines the optimal dosing timing for the auxiliary materials. For example, during the whipping of egg whites, the protein structure gradually forms stable foam, and its ability to accept powdered sugar depends on the foaming degree of the foam. Therefore, this module can determine whether the egg white foam has reached the appropriate six-whipped state and slowly dose the powdered sugar within an appropriate time period to improve the stability of the foam. If the powdered sugar is dosed too early, an insufficiently stable protein network is formed, which may cause the foam to collapse; if dosed too late, the sugar is difficult to fully dissolve, thus affecting the final taste and texture. Therefore, this dosing control module can accurately calculate the optimal dosing window for each auxiliary material to ensure a high degree of matching between the dosing timing and the state of the ingredients. In addition, in the application scenario of complex formulas, this module can also perform optimized control according to the interaction relationship between different auxiliary materials. For example, when whipping cream, the system can dose vanilla essence at an appropriate time and dose the powdered sugar after detecting that the emulsification state has reached stability to enhance the overall flavor and stability.

[0119] The adjustable-speed dosing mechanism further enhances the accuracy of dosing, enabling the dosing rate of the auxiliary materials to be dynamically adjusted according to the real-time rotational speed of the stirring head and the stirring resistance to ensure that the auxiliary materials can be fully integrated with the base ingredients. For example, during the whipping of egg whites, as the egg white foam gradually forms, its fluidity continuously decreases, and the torque during the stirring process gradually increases. At this time, the system can reduce the dosing speed of the powdered sugar to match the absorption capacity of the foam and prevent the powder from forming particle deposition due to too fast dosing. In addition, during the whipping of cream, the change in the dosing speed can avoid the oil-water separation caused by the too fast mixing of the oil, improving the fineness and stability of the final product. This mechanism dynamically controls the release rate of the dosing bin by real-time sensing of the stirring state, enabling the auxiliary materials to be evenly distributed throughout the stirring area, thus achieving a more uniform integration of the ingredients.

[0120] The intelligent compensation mechanism enables the intelligent ingredient dosing system to have an adaptive adjustment ability. When the viscosity, temperature or torque data during the whipping process deviates from the ideal range, this mechanism can automatically adjust the dosing amount of specific auxiliary materials. For example, during the whipping of egg whites, if the control host detects that the foam structure is unstable, which means that the protein network has not been fully formed, the system can automatically dispense acidic stabilizers such as lemon juice or tartaric acid to enhance the persistence of the foam and improve the cross-linking effect of proteins, preventing the foam from breaking during subsequent stirring. In addition, when whipping in a high-temperature environment, this mechanism can appropriately increase the dosing amount of liquid auxiliary materials according to the data of the temperature sensor to compensate for the decrease in humidity caused by water evaporation, preventing the ingredients from drying out excessively and affecting the texture of the final product. For application scenarios such as batter mixing, this intelligent compensation mechanism can also dynamically adjust the ratio of liquid and powdered auxiliary materials to ensure that the viscosity of the batter always remains within the ideal range, thereby improving the consistency and success rate of baked products.

[0121] The design of the intelligent ingredient dosing system not only optimizes the way of adding auxiliary materials during the whipping process, making it more accurate and controllable, but also improves the consistency, stability and overall quality of whipping through real-time monitoring and dynamic adjustment. By deeply integrating with the control host, this system can adapt to the characteristics of different ingredients and perform intelligent adjustment according to the real-time data during the whipping process, enabling the entire egg beater system to achieve more efficient and intelligent automated operation, reducing the operation difficulty of users, and improving the quality of the final food.

[0122] Furthermore, the intelligent whipping control and monitoring system of the egg beater further includes an intelligent shock absorption and stable support system. The intelligent shock absorption and stable support system is used to reduce the vibration of the egg beater during high-speed operation, improve the stability of the equipment, optimize the movement accuracy of the stirring head during the whipping process, and reduce the energy loss caused by vibration, thereby improving the whipping quality and user experience. The intelligent shock absorption and stable support system includes:

[0123] An adaptive shock absorption base is provided at the bottom of the egg beater, which includes a plurality of independent shock absorption units. Each shock absorption unit is internally provided with a pressure sensor and an adjustable damping structure to sense the vibration amplitude of the egg beater during operation in real time, and automatically adjust the damping size according to the motor speed, torque load and external environment to reduce the vibration caused by high-speed stirring or uneven load, ensuring that the equipment can still operate stably under high-load conditions;

[0124] An intelligent balance adjustment mechanism is located inside the egg beater and is linked with the stirring shaft. Based on the real-time torque data and the rotational inertia of the stirring shaft, it automatically adjusts the built-in weight structure to keep the stirring system in the best balance state all the time, reducing the vibration and noise caused by eccentric rotation, and improving the operation accuracy of the stirring head, thereby optimizing the consistency of ingredient whipping;

[0125] An active shock absorption control module, connected to the control host. When it detects that the vibration exceeds the safe range or may affect the whipping effect, the control host automatically adjusts the operating state of the motor, including changing the rotation speed gradient, optimizing the stirring path, or adjusting the power output, to make the stirring process smoother, and at the same time reduce the impact of long-term high-frequency vibration on the equipment life.

[0126] An asymmetric dynamic support mechanism, with deformable support foot pads set at the bottom around the egg beater, which can be dynamically adjusted according to the vibration direction and amplitude, enabling the egg beater to remain stable even on an uneven workbench, and reducing the fluctuation of the whipping quality caused by the influence of the external environment by absorbing part of the vibration energy, ensuring that the egg beater can provide consistent stirring performance in various environments.

[0127] The intelligent shock absorption and stable support system is an important part of the present invention, aiming to reduce the vibration problems caused by uneven load, unstable workbench or high-speed rotation inertia during the high-speed operation of the egg beater, thereby improving the operation stability of the equipment and ensuring that the ingredients always maintain a uniform and consistent whipped state during the stirring process. The core of this system lies in the cooperation of a series of sensors and actuators to achieve real-time monitoring and dynamic adjustment of the vibration state, enabling the equipment to adapt to different load conditions, while optimizing the stability of the stirring process, reducing noise, and enhancing the overall user experience.

[0128] The adaptive shock absorption base is installed at the bottom of the egg beater and contains multiple independent shock absorption units. Each unit is internally equipped with a pressure sensor and an adjustable damping structure to sense the vibration amplitude during the operation of the equipment and adjust the damping size in real time according to the motor speed, torque load, and external environmental factors, thereby effectively reducing the vibration caused by high-speed rotation or uneven load. The pressure sensor can monitor the bottom force of the egg beater under different load states and calculate the optimal damping adjustment parameters, enabling the shock absorption unit to make active adjustments according to the operating state of the equipment. When it detects that one side of the equipment vibrates greatly due to uneven load, the system can automatically adjust the shock absorption unit in the corresponding area to increase the damping coefficient of this part to offset the vibration and ensure that the equipment can still operate stably under high load conditions. In addition, this base adopts a combination of high-elastic materials and a shock absorption support mechanism, enabling the egg beater to effectively absorb vibration energy at high rotation speeds, thereby reducing the impact of vibration on the stirring quality.

[0129] The intelligent balance adjustment mechanism is located inside the egg beater and is linked to the stirring shaft. Relying on the real-time data provided by the torque sensor and the rotational speed sensor, it automatically adjusts the counterweight structure inside the device to optimize the balance state and reduce the vibration and noise caused by the eccentric rotation of the stirring shaft. This mechanism can dynamically identify changes in the load during the stirring process. For example, when stirring thinner liquids, the system can reduce the counterweight compensation, while when stirring thicker ingredients or high-viscosity batters, the system can appropriately increase the counterweight to make the rotation of the stirring shaft more stable. In addition, this balance adjustment mechanism uses an inertial compensation algorithm to calculate in real time the centrifugal force received during the rotation of the stirring head, and micro-adjusts the position of the counterweight structure through an electric adjustment mechanism to reduce the additional vibration caused by eccentric rotation, enabling the device to maintain a high stirring accuracy under different ingredient states, thus ensuring the consistency and stability of the final product.

[0130] The active shock absorption control module is connected to the control host and optimizes the operating state of the motor by analyzing the vibration data of the device in real time. When it detects that the vibration amplitude exceeds the set safety range or may interfere with the whipping process, the system can automatically adjust the output strategy of the motor. For example, by changing the rotational speed gradient to smooth the start or deceleration of the motor, it reduces the mechanical impact caused by instantaneous torque fluctuations, or optimizes the stirring path according to the vibration data to make the rotation of the stirring paddle more smooth. In addition, in the case of long-term continuous operation, this module can detect the cumulative vibration of the device and adjust the motor power output when necessary to prevent the high-frequency vibration from affecting the device life and improve the durability and operating stability of the whole machine.

[0131] The asymmetric dynamic support mechanism is set at the bottom of the egg beater and uses a deformable support footpad structure that can be dynamically adjusted according to the real-time monitored vibration direction and amplitude, enabling the egg beater to remain stable even when placed on an uneven workbench. The support footpads are made of high-elasticity materials and combined with piezoelectric sensors to detect the force condition of the egg beater on different workbenches. When it detects that the device tilts or the vibration increases due to external factors, the system can automatically adjust the height or deformation of the support footpads to keep the device in a horizontal state and reduce the impact on the stirring quality by absorbing part of the vibration energy. In addition, this support mechanism can adapt to different material workbenches. For example, on a smooth marble workbench, the system can increase the friction to reduce sliding, while on a wooden or plastic workbench, it can adjust the flexibility of the support structure to optimize the overall stability.

[0132] The intelligent shock absorption and stable support system enables the egg beater to maintain extremely high stability during high-speed operation through the linkage of a series of sensors, control algorithms, and actuators, effectively reducing the impact of vibration on the whipping quality and improving the accuracy of the stirring process. Through real-time balance adjustment, vibration suppression, and adaptive support, the device can adapt to different ingredient states and usage environments, while ensuring the final whipping effect, extending the service life of the device, and providing a better user experience.

[0133] Although this application is disclosed above with preferred embodiments, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the protection scope of this application shall be subject to the scope defined by the claims of this application.

Claims

1. An intelligent egg beater control and monitoring system, characterized in that: include: The speed sensor is arranged on the motor shaft of the egg beater and is used to detect the speed of the egg beater in real time and transmit the speed signal to the control host; The torque sensor is arranged on the stirring shaft of the egg beater and is used to detect the torque change during the stirring process and transmit the torque signal to the control host; The temperature sensor is arranged near the stirring head of the egg beater, and is used to detect the temperature of the stirring material and transmit the temperature signal to the control host; A control host is provided with a processor and a memory; wherein the memory stores a preset database of standard torque curves corresponding to different whipping types; the processor is used to: calculate the actual torque curve of the current whipping process in real time according to the speed signal, torque signal and temperature signal; compare the actual torque curve with the standard torque curve in real time; when it is detected that the deviation between the actual torque curve and the standard torque curve exceeds a preset threshold, automatically adjust the output power of the egg beater motor to maintain the whipping process in an optimal state.

2. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: Also included is a control interface, the control interface comprising: A display module, connected to the control host, for visually displaying the speed, torque and temperature parameters of the whipping process in real time, and showing the comparison between the current actual torque curve and the standard torque curve in a dynamic graphic form; A touch input module, connected to the control host, for receiving user input of whipping mode selection, torque sensitivity adjustment, temperature adjustment strategy setting and personalized whipping curve setting to meet the whipping requirements of different ingredients; The intelligent recommendation module provides users with optimized whipping parameter suggestions based on the historical data stored in the control host and the current food status, and automatically adjusts the operation strategy of the egg beater motor after the user confirms; The voice prompt module is used to provide voice feedback during the sending process, including real-time broadcast of the current sending progress, abnormal status warnings and operation suggestions.

3. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: It also includes an intelligent stirring head assembly, which is used to dynamically optimize the stirring process, make the whipping more uniform, and reduce the adhesion of ingredients. The intelligent stirring head assembly includes: Adaptive stirring paddle structure, which is used to automatically adjust the inclination angle or rotation direction of the stirring paddle based on the torque data and stirring resistance calculated by the control host to optimize the flow path of the ingredients during the stirring process; Low-adhesion surface coating: the stirring paddle surface adopts food-grade anti-stick coating or micro-structure surface to reduce the adhesion of high-viscosity ingredients such as egg whites and cream; Centrifugal force-assisted discharge structure: a tiny centrifugal discharge channel is provided on the outer edge of the mixing head, which uses the centrifugal force generated by rotation to guide the ingredients to be evenly distributed outwards, preventing some materials from being retained around the mixing paddle; The vibration fine-tuning module is integrated inside the stirring shaft and is used to apply small vibrations for a short time to optimize the distribution of ingredients when food adhesion or uneven mixing is detected.

4. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: It also includes an intelligent ingredient delivery system, which is used to automatically adjust the delivery time and delivery amount of additional ingredients according to real-time monitoring data during the whipping process to optimize the whipping effect. The intelligent ingredient delivery system includes: The controllable feeding device is arranged on the top or side of the egg beater body, and includes at least one independent feeding bin, each of which is used to store different types of auxiliary materials and is accurately fed through an electric switch or a controllable valve; The dosing control module is connected to the control host and is used to analyze the current stirring state based on the speed, torque and temperature data, and calculate the optimal dosing time point in combination with the standard whipping curve; The adjustable speed feeding mechanism is used to control the main machine to dynamically adjust the feeding speed according to the current stirring resistance and speed status to match the rotation rhythm of the stirring head; The intelligent compensation mechanism is used to adjust the dosage of specific auxiliary materials when it detects that the viscosity or temperature deviates from the ideal range during the whipping process, so as to enhance the persistence of protein foam and improve the quality and stability of the final product.

5. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: It also includes an intelligent shock absorption and stable support system, which is used to reduce the vibration of the egg beater during high-speed operation and improve the stability of the equipment. The intelligent shock absorption and stable support system includes: The adaptive damping base is arranged at the bottom of the egg beater and includes multiple independent damping units. Each damping unit is equipped with a pressure sensor and an adjustable damping structure to sense the vibration amplitude of the egg beater in real time during operation and automatically adjust the damping size according to the motor speed, torque load and external environment to reduce the vibration caused by high-speed stirring or uneven load. The intelligent balance adjustment mechanism is located inside the egg beater and is linked to the stirring shaft. Based on the real-time torque data and the rotational inertia of the stirring shaft, the built-in counterweight structure is adjusted to keep the stirring system in the best balance state at all times. The active vibration reduction control module is connected to the control host. When it detects that the vibration exceeds the safety range or may affect the whipping effect, the control host adjusts the running state of the motor, including changing the speed gradient, optimizing the stirring path or adjusting the power output to make the stirring process smoother. The asymmetric dynamic support mechanism includes deformable support pads arranged around the bottom of the egg beater for dynamic adjustment according to the vibration direction and amplitude, so that the egg beater can remain stable even on an uneven work surface.

6. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: The speed sensor adopts an adaptive multi-mode detection structure to improve detection accuracy and enhance adaptability to complex working conditions. The speed sensor includes: The dual-channel speed acquisition module is realized by combining photoelectric sensing and Hall effect sensing technology. The photoelectric sensor is used to detect the speed of the motor shaft with high precision, and the Hall effect sensor is used to detect the change of magnetic field. A dynamic signal calibration unit is connected to the control host, and based on the torque sensor data and the motor load condition, adaptively adjusts the filter parameters of the speed signal, and uses an adaptive Kalman filter algorithm to remove high-frequency noise and mechanical resonance interference; Intelligent inertia compensation system, which combines historical speed curves with current detection data, calculates transient speed fluctuations through the control host, and provides inertia prediction compensation when the motor load changes suddenly in a short period of time; The energy feedback regulation module is used to provide real-time signals to the control host when the speed sensor detects slight vibration or uneven load in the running state of the motor, so that the system can fine-tune the power output.

7. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: The torque sensor adopts a multi-dimensional composite detection structure to improve detection accuracy and enhance adaptability to different whipping stages. The torque sensor includes: A flexible strain gauge array is arranged on the surface of the stirring shaft to form a high-precision torque detection grid, which is used to sense the axial and radial torque changes in real time under different load conditions and calculate the precise torque value through the tiny deformation of the strain resistor; The dynamic compensation unit is connected to the control host. Based on the historical data of speed, temperature and load, it adaptively corrects the torque measurement error, and uses the neural network model to analyze the torque change trend during the whipping process, predict the upcoming viscosity mutation, and enable the system to adjust the motor power output in advance. Transient impact detection module, with built-in high-sensitivity inertial sensor, is used to identify instantaneous torque fluctuations caused by uneven distribution of ingredients or sudden external forces during mixing; The self-learning feedback system combines historical whipping data and real-time torque curves to adjust the standard torque curve database so that it can adapt to the subtle differences in different batches of ingredients, and provide personalized adjustment plans after users use it multiple times.

8. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: The temperature sensor comprises: Multi-point distributed temperature measurement units are arranged inside the stirring head, at the connection of the stirring shaft, and on the outer wall of the stirring chamber. By simultaneously monitoring the temperature data of multiple key positions, the uneven temperature judgment caused by single-point measurement errors can be avoided. A dynamic thermal compensation module is connected to the control host, and dynamically corrects the temperature measurement value based on the motor operation state, ambient temperature and material heat capacity parameters to eliminate the additional heat accumulation error caused by the long-term operation of the motor; Intelligent temperature control system, which combines historical temperature data with current food status to predict temperature change trends and proactively adjusts the stirring power and rhythm in situations that may lead to whipping failure; The non-contact infrared temperature measurement auxiliary unit is integrated into the outer edge area of ​​the mixing head to supplement the limitations of traditional contact temperature measurement and provide additional temperature monitoring data by detecting infrared radiation on the material surface.

9. The intelligent egg beater control and monitoring system according to claim 1, characterized in that: The processor of the control host uses an adaptive nonlinear control algorithm to optimize the power regulation of the motor during the whipping process, wherein the adaptive nonlinear control algorithm includes the following steps: The processor receives real-time data from the speed sensor, torque sensor and temperature sensor, and constructs the state variable matrix S(t) provided by the following formula 1: Where, ω(t) is the current stirring shaft speed; T τ (t) is the current torque of the stirring shaft; T θ (t) is the temperature of the food; P(t) is the current motor power; Indicates the instantaneous rate of change of torque; Indicates the instantaneous rate of change of torque; Based on the state variable matrix, the processor calculates the target motor power adjustment ΔP according to the following formula 2: Among them, T τ (t) is the current torque of the stirring shaft; It is the standard torque curve corresponding to the current food; represents the instantaneous rate of change of torque; ω(t) is the current stirring shaft speed; ω std (t) is the target speed curve; T θ (t) is the temperature of the food; is the optimal temperature curve; K1, K2, K3, K4 are adaptive gain coefficients; The processor adjusts the motor power according to the following formula 3: P(t+1)=P(t)+ΔP(3) Among them, P(t+1) is the motor power at time t+1; P(t) is the current motor power; ΔP is the motor power adjustment amount ΔP.

10. The intelligent egg beater control and monitoring system according to claim 9, characterized in that: The processor of the control host is also used for: The compensation correction term C(t) is calculated according to the following formula 4: in, is the second-order derivative of torque, which indicates the acceleration change of torque over time; Represents the nonlinear amplification term of the torque change rate; α is the adjustment coefficient; It is used to calculate the product of the speed change rate and the torque change rate, and is used to evaluate the dynamic response of the stirring shaft caused by the change of food resistance; λ1, λ2, and λ3 are time-varying compensation gain coefficients; Update the motor power adjustment according to the following formula 5: P′(t+1)=P(t)+ΔP+C(t)(5) Among them, P′(t+1) is the motor power at time t+1; P(t) is the current motor power; ΔP is the motor power adjustment amount ΔP.

Images