Potato slicer control method based on multi-blade rotary cutting

Abstract

The invention discloses a potato slicer control method based on multi-blade rotary cutting, and relates to the technical field of cutting. The method comprises the steps that the potato slicing machine is provided with a multi-blade rotary cutting head, a cutting fixing piece and a driving motor set; a to-be-cut potato is taken and placed on the cutting fixing piece, and sensing data of the to-be-cut potato is recognized; self-adaptive analysis is conducted on the gap-adjustable blade set, and a first adjustment parameter is output; carrying out collaborative analysis on the cutting fixed part according to the first adjustment parameter, and outputting a second adjustment parameter; and according to the first adjustment parameter and the second adjustment parameter, the multi-blade rotary cutting head and the cutting fixing piece are controlled to slice the potatoes. The technical problems that in the prior art, a potato slicer cannot adjust cutting parameters in a self-adaptive mode according to the sizes and the shapes of potatoes, so that cutting efficiency is low, and slicing thickness is uneven are solved, cutting operation is adjusted in a self-adaptive mode according to the actual conditions of the potatoes, and the technical effects of improving cutting efficiency and ensuring that the slicing thickness is even are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of cutting, and in particular to a control method for a potato slicer based on multi-blade rotary cutting. Background Art

[0002] In the food processing industry, potato slicing is a key process for many foods (such as potato chips, potato stew, etc.). Traditional potato slicers mostly use fixed blades and mechanical drive for cutting. Although they can complete basic slicing tasks, they still have many shortcomings in actual production. Due to the natural differences in size, shape and hardness of potatoes, traditional slicers cannot adjust the cutting parameters according to the specific situation, resulting in uneven slice thickness, affecting the quality of food processing. For example, slices that are too thick may lead to uneven subsequent processing (such as frying or baking), while slices that are too thin are easy to break. In addition, the fixed blade cutting method is difficult to adapt to different varieties of potatoes, resulting in some food waste and increased production costs. Secondly, on large-scale food processing production lines, the cutting efficiency of the slicer directly affects the overall production efficiency. The blade gap and speed of traditional equipment are fixed, and cannot be intelligently adjusted according to the characteristics of potatoes, which can easily cause problems such as blockage and poor cutting, affecting production continuity. Summary of the invention

[0003] The present application provides a control method for a potato slicer based on multi-blade rotary cutting, which solves the technical problem in the prior art that the potato slicer cannot adaptively adjust the cutting parameters according to the size and shape of the potato, resulting in low cutting efficiency and uneven slice thickness.

[0004] The present application provides a potato slicer control method based on multi-blade rotary cutting, the method comprising: The potato slicer is provided with a multi-blade rotary cutting head, a cutting fixture and a driving motor group, wherein the multi-blade rotary cutting head includes a gap-adjustable blade group, and the driving motor group includes a first driving motor connected to the multi-blade rotary cutting head and a second driving motor connected to the cutting fixture; potatoes to be cut are taken, placed on the cutting fixture and the sensor data of the potatoes to be cut are identified; the gap-adjustable blade group is adaptively analyzed according to the sensor data, and a first adjustment parameter is output, wherein the first adjustment parameter includes an adjustment gap and an adjustment speed; the cutting fixture is collaboratively analyzed according to the first adjustment parameter, and a second adjustment parameter is output, wherein the second adjustment parameter includes an adjustment displacement and an adjustment speed; the driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter respectively.

[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages: The potato slicer is provided with a multi-blade rotary cutting head, a cutting fixture and a driving motor group, wherein the multi-blade rotary cutting head includes a gap-adjustable blade group, and the driving motor group includes a first driving motor connected to the multi-blade rotary cutting head and a second driving motor connected to the cutting fixture. First, potatoes to be cut are taken, placed on the cutting fixture and the sensor data of the potatoes to be cut are identified. Then, the gap-adjustable blade group is adaptively analyzed according to the sensor data, and a first adjustment parameter is output, wherein the first adjustment parameter includes an adjustment gap and an adjustment speed. Then, the cutting fixture is collaboratively analyzed according to the first adjustment parameter, and a second adjustment parameter is output, wherein the second adjustment parameter includes an adjustment displacement and an adjustment speed. Finally, the driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter. The technical problem that the potato slicer in the prior art cannot adaptively adjust the cutting parameters according to the size and shape of the potato, resulting in low cutting efficiency and uneven slice thickness is solved, and the cutting operation is adaptively adjusted according to the actual situation of the potato, thereby achieving the technical effect of improving cutting efficiency and ensuring uniform slice thickness. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0007] Figure 1 A schematic flow chart of a potato slicer control method based on multi-blade rotary cutting provided in an embodiment of the present application; Figure 2 A schematic diagram of a flow chart for iterative optimization in a control method for a potato slicer based on multi-blade rotary cutting provided in an embodiment of the present application. DETAILED DESCRIPTION

[0008] The present application solves the technical problem in the prior art that potato slicers cannot adaptively adjust cutting parameters according to potato size and shape, resulting in low cutting efficiency and uneven slice thickness by providing a potato slicer control method based on multi-blade rotary cutting.

[0009] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0010] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0011] Examples, such as Figure 1 As shown, the embodiment of the present application provides a potato slicer control method based on multi-blade rotary cutting, wherein the method includes: The potato slicer is provided with a multi-blade rotary cutting head, a cutting fixture and a driving motor group, wherein the multi-blade rotary cutting head comprises a gap-adjustable blade group, and the driving motor group comprises a first driving motor connected to the multi-blade rotary cutting head and a second driving motor connected to the cutting fixture.

[0012] In an embodiment of the present application, a potato slicer based on multi-blade rotary cutting is provided. The potato slicer includes a multi-blade rotary cutting head, a cutting fixture, and a drive motor group to achieve efficient and accurate slicing of potatoes.

[0013] The multi-blade rotary cutting head is provided with a gap-adjustable blade set, which is composed of a plurality of adjacently arranged blades, and the gaps between the blades are adjustable to accommodate potatoes of different sizes and slice thickness requirements. The blades are gap-adjusted by an adjustable mounting structure (such as a slide rail mechanism, a spiral lifting mechanism or an electric adjustment mechanism), and the first drive motor provides rotational power, thereby achieving a stable and efficient cutting operation.

[0014] The cutting fixture is used to carry the potatoes to be cut, and dynamically adjusts its displacement or rotation during the cutting process to optimize the cutting angle and improve the cutting accuracy. The cutting fixture can adopt a deformable bracket, a clamping mechanism or a flexible fixing component to adapt to potatoes of different shapes and sizes, and is driven by a second drive motor so that it can move or rotate according to the calculated adjustment parameters to ensure that the potatoes are in the best cutting position.

[0015] The driving motor group includes a first driving motor and a second driving motor, which are respectively used to drive a multi-blade rotating cutting head and a cutting fixture, wherein the first driving motor is connected to the multi-blade rotating cutting head, drives the blades to rotate at a set speed, and dynamically adjusts the blade gap according to the calculated adjustment parameters to ensure uniform slice thickness, and the second driving motor is connected to the cutting fixture, controls the displacement or rotation of the cutting fixture according to the adjustment parameters, so that the potatoes and the blades maintain the best cutting coordination, reduce cutting errors, and improve slicing uniformity.

[0016] Furthermore, the multi-blade rotary cutting head includes a plurality of adjacently arranged blades, and a phase difference threshold constraint is included between adjacent blades; and the sensing data is adaptively constrained to analyze the gap-adjustable blade set according to the phase difference threshold constraint.

[0017] The multi-blade rotary cutting head consists of multiple adjacently arranged blades, each of which is arranged according to a set phase difference threshold constraint to ensure stability and slice quality during the cutting process. The phase difference threshold constraint is used to ensure that adjacent blades maintain an appropriate relative position relationship during rotation to avoid problems such as uneven slice thickness or reduced cutting efficiency due to blade phase asynchrony. Specifically, the phase difference threshold can be set according to the number of blades, the rotation speed, and the geometric characteristics of the potato to be cut, so that adjacent blades form a continuous and uniform slicing path during the cutting process.

[0018] Based on the sensor data, the gap-adjustable blade group is subjected to adaptive constraint analysis. Specifically, first, the shape, size and material data of the potato are obtained by using the sensor, and the data are input into the control system; second, the control system calculates the optimal adjustment parameters of the current blade group, including blade gap adjustment, rotation angle correction and blade synchronization optimization, in combination with the preset phase difference threshold constraint; then, the control system drives the first drive motor according to the calculated adjustment parameters to ensure that the multi-blade rotary cutting head maintains the best relative motion state during the cutting process, thereby ensuring the consistency of slice thickness and cutting efficiency. During the cutting process, the system can also monitor the phase changes between the blades in real time. If it is detected that the blade phase offset exceeds the preset threshold range, the blade rotation angle or gap is automatically adjusted to compensate for the error and ensure the stability of the cutting process.

[0019] Take the potatoes to be cut, place them on the cutting fixture and identify the sensor data of the potatoes to be cut.

[0020] First, place the potatoes to be cut on a cutting fixture, which may include a clamping mechanism, a support tray or a flexible limiter to accommodate potatoes of different sizes and shapes, and provide the necessary restraint force to prevent the potatoes from shifting or rotating during the cutting process. Subsequently, start the sensor to collect relevant data of the potatoes to be cut, and the sensing data includes but is not limited to geometric shape data (such as length, width, diameter, surface curvature), material data (such as density, hardness, moisture content) and temperature state (such as room temperature or frozen state). The geometric shape data can be obtained through a laser ranging sensor, a 3D imaging device or a visual recognition system, the material data can be measured by an ultrasonic sensor, a pressure sensor or an infrared detection device, and the temperature state can be detected by a thermocouple or an infrared temperature sensor.

[0021] Further, after taking the potatoes to be cut, the method further comprises: The state of the potatoes to be cut is detected according to the thermocouple in the cutting fixture, including a frozen state and a non-frozen state; if the state of the potatoes to be cut is a non-frozen state, the gap-adjustable blade group is adaptively analyzed according to the sensing data to output a first adjustment parameter.

[0022] After taking the potatoes to be cut and placing them on the cutting fixture, the temperature state of the potatoes needs to be detected to determine whether they are in a frozen state or a non-frozen state. Specifically, a thermocouple sensor is integrated inside the cutting fixture, which can detect the temperature data of the surface and inside of the potatoes in real time and transmit the temperature signal to the control system. The control system determines the state of the potatoes based on a preset temperature threshold. For example, when the temperature is detected to be lower than the preset freezing temperature threshold (such as -5°C or lower), the system determines that the potatoes are in a frozen state; if the temperature is higher than the threshold, it is determined to be in a non-frozen state. If the detection result shows that the potatoes are in a non-frozen state, the system further performs an adaptive analysis of the gap-adjustable blade group based on the sensing data (including the shape, size, hardness, density, etc. of the potatoes), calculates and outputs the first adjustment parameter. The first adjustment parameter includes the blade gap adjustment value and the blade rotation speed to adapt to potatoes of different sizes and hardnesses, ensuring uniform slice thickness and optimal cutting efficiency. The control system adjusts the relative spacing of the blades by analyzing the geometric shape and material properties of the potatoes, so that the cutting process can adapt to the individual differences of the potatoes, thereby optimizing the cutting quality, improving production efficiency, and reducing waste and blade loss caused by improper cutting.

[0023] Furthermore, if the state of the potatoes to be cut is a frozen state, a protection control mode is started, and the protection control mode includes a protection rotation speed and a protection gap; under the protection control mode, an adaptive protection analysis is performed on the gap-adjustable blade group according to the sensor data, and a first protection adjustment parameter is output.

[0024] If the state of the potato to be cut is determined to be frozen by thermocouple detection, that is, its temperature is lower than the preset freezing temperature threshold (e.g. -5°C or lower), the system automatically starts the protection control mode to prevent damage to the blade, excessive cutting resistance or reduced cutting effect due to increased potato hardness. The protection control mode includes adjustment strategies for protection speed and protection gap to adapt to the special physical characteristics of frozen potatoes.

[0025] Under the protection control mode, the control system first analyzes the sensor data, including the shape and size of the potatoes, the surface hardness, and the possible distribution of ice crystals, and based on these data, performs adaptive protection analysis on the gap-adjustable blade set. By analyzing the hardness and density distribution of the potatoes, the system calculates the first protection adjustment parameters suitable for the frozen state, among which the protection speed adjustment is used to reduce the rotation speed of the blade to reduce the possible damage or breakage of the blade during high-speed cutting; the protection gap adjustment is used to appropriately increase the blade gap to reduce the resistance during cutting, improve the cutting stability, and prevent the blade from getting stuck or uneven cutting due to the hard potatoes. In addition, the system can dynamically optimize the protection adjustment parameters in combination with the real-time detection of the cutting resistance data, so that the blade is always in a safe and efficient operating state when cutting frozen potatoes.

[0026] The gap-adjustable blade set is adaptively analyzed according to the sensing data to output a first adjustment parameter, wherein the first adjustment parameter includes an adjustment gap and an adjustment rotation speed.

[0027] After receiving the sensor data, the control system analyzes the specific characteristics of the potatoes (such as size, shape, material hardness, etc.) to calculate a first adjustment parameter suitable for the current potatoes. The first adjustment parameter includes an adjustment gap and an adjustment rotation speed.

[0028] Depending on the size and hardness of the potatoes, the system can adaptively adjust the gap between the blades. When the potatoes are soft or small, the system may reduce the gap to improve cutting accuracy; for harder or larger potatoes, the system may increase the gap between the blades to reduce resistance during cutting and avoid blade damage. Based on the hardness and density information in the sensor data, the appropriate rotation speed is determined to ensure uniform cutting without excessive cutting resistance. For example, if the potatoes are hard, the rotation speed may be reduced to avoid excessive friction and blade wear; if the potatoes are soft, the rotation speed can be appropriately increased to improve cutting efficiency.

[0029] Furthermore, the method of adaptively analyzing the gap-adjustable blade set according to the sensing data and outputting a first adjustment parameter includes: Wherein, the sensor data includes geometric sensor data and material sensor data; the geometric sensor data and the material sensor data are used as input data and input into a blade group adaptive analysis model, and a first adjustment parameter is output according to the blade group adaptive analysis model. The blade group adaptive analysis model is trained through sensor data training samples and labels representing slice uniformity until convergence.

[0030] The sensing data includes geometric sensing data and material sensing data. The geometric sensing data mainly includes the shape, size, surface characteristics (such as diameter, aspect ratio, surface convexity, etc.) of the potato, while the material sensing data includes the hardness, density, water content, and other physical properties of the potato. The geometric sensing data is obtained through laser rangefinders, 3D vision sensors, or other precision measuring equipment; while the material sensing data is usually obtained through ultrasonic waves, pressure sensors, or other non-contact sensing technologies to accurately identify the physical characteristics of potatoes.

[0031] The geometric sensing data and material sensing data are used as input data and input into the blade group adaptive analysis model. The blade group adaptive analysis model is a trained machine learning that can automatically evaluate and analyze the cutting characteristics of different potatoes based on the input data. The blade group adaptive analysis model gradually adjusts the parameters by learning the sensor data training samples and the label data of slice uniformity until the model converges. The training process uses a large amount of data of different types of potatoes. The model is continuously optimized so that it can accurately adjust the cutting of potatoes of various shapes and materials in practical applications. Finally, the blade group adaptive analysis model outputs the first adjustment parameter, which includes the optimal value of adjusting the blade gap and blade speed. The adjustment parameter ensures that the blade group can be dynamically adjusted according to the actual characteristics of the potato (such as hardness, size, etc.) during the cutting process, thereby optimizing the cutting quality, improving the uniformity of the slices, and ensuring that the cutting effect of each potato slice is optimal.

[0032] The cutting fixture is collaboratively analyzed according to the first adjustment parameter to output a second adjustment parameter, wherein the second adjustment parameter includes an adjustment displacement and an adjustment rotation speed.

[0033] The first adjustment parameters include the blade gap and the blade speed. Based on these parameters, the position and movement of the cutting fixture are further optimized so that the blade can maintain the best contact state with the potato to be cut during the cutting process, thereby improving the stability and efficiency of the cutting. The second adjustment parameter is determined through collaborative analysis. The second adjustment parameter includes adjusting the displacement and adjusting the speed. According to the geometric shape of the potato and the position of the blade during the cutting process, the displacement of the cutting fixture is calculated and adjusted to ensure that the potato to be cut is always in the correct position to avoid uneven cutting or blade jamming due to improper position. According to the first adjustment parameters (such as blade speed and gap) and the hardness, density and other characteristics of the potato, the speed of the cutting fixture is adjusted so that the mechanical action during the cutting process is evenly distributed, the cutting resistance is reduced, and the stability of the slicing effect is ensured.

[0034] Further, the method of performing collaborative analysis on the cutting fixture according to the first adjustment parameter includes: A motion coupling relationship between the multi-blade rotary cutting head and the cutting fixture is established; the first adjustment parameter is used as an input variable, a collaborative analysis is performed on the cutting fixture based on the motion coupling relationship, and a second adjustment parameter is output.

[0035] Specifically, a kinematic coupling relationship between the multi-blade rotary cutting head and the cutting fixture is established. The coupling relationship describes the mutual influence between the cutting head and the cutting fixture, which is mainly reflected in the coordination between the displacement, rotation speed and rotational motion of the cutting fixture and the blades. For example, when the blade speed or gap changes, the displacement and speed of the cutting fixture need to be adjusted accordingly to ensure the stability and accuracy of the cutting process.

[0036] On the basis of establishing the kinematic coupling relationship, the control system uses the first adjustment parameter (including blade gap and blade speed) as the input variable for collaborative analysis. Through the kinematic coupling relationship, the system can comprehensively consider the rotation characteristics of the cutting head and the motion requirements of the cutting fixture to calculate the optimal motion state of the cutting fixture. Based on this kinematic coupling relationship, the system performs a collaborative analysis of the cutting fixture and outputs the second adjustment parameter, including adjusting the displacement and speed of the cutting fixture.

[0037] Furthermore, the kinematic coupling relationship is expressed as Wherein, x is the real-time displacement of the cutting fixture, d is the diameter of the potato to be cut, is a fixed phase offset, used for the periodic error of the cutting process, K S is the weight coefficient representing the complexity of potato shape, and S is the shape parameter of the sensing data.

[0038] The kinematic coupling relationship between the multi-blade rotary cutting head and the cutting fixture is expressed as follows: Where x is the real-time displacement of the cutting fixture, which indicates the distance the cutting fixture needs to move during the cutting process to ensure that the cutting head can cut accurately; d is the diameter of the potato to be cut, which reflects the size of the potato; is a fixed phase offset, which is used to represent the periodic error in the cutting process. This error reflects the uneven cutting phenomenon that may be caused by the periodic change of the rotation position between the blades. S is the weight coefficient of the potato shape complexity, reflecting the influence of the potato shape on the cutting process; S is the shape parameter of the sensor data, representing the geometric shape feature data of the potato. The motion coupling relationship takes into account the size and shape of the potato and the rotation period error between the blades during the cutting process. By adjusting the displacement and motion trajectory of the cutting fixture, it can ensure that the contact between the cutting head and the potato is more uniform and accurate, and effectively compensate for the error in the cutting process.

[0039] The driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter.

[0040] The drive motor group controls the multi-blade rotary cutting head according to the first adjustment parameters (including blade gap and speed). By adjusting the blade speed, the relative movement between the blade and the potato during the cutting process can be optimized, and the jamming or unevenness that may occur during the cutting process can be reduced, thereby improving the cutting efficiency. At the same time, the drive motor group controls the movement of the cutting fixture according to the second adjustment parameters (including displacement and speed). The speed and displacement adjustment of the cutting fixture ensure that the potato always maintains proper positioning and stability during the cutting process to avoid uneven cutting or blade failure due to improper displacement. By accurately adjusting the speed and displacement of the cutting fixture, the system can ensure that the contact between the potato and the blade is more stable, so that the cutting effect of each potato can meet the predetermined requirements.

[0041] Through the comprehensive application of the first adjustment parameter and the second adjustment parameter, the drive motor group can accurately control the movement of the multi-blade rotary cutting head and the cutting fixture, making the entire potato cutting process efficient and accurate, and can adaptively adjust according to the different shapes, sizes and materials of potatoes to ensure the consistency of slicing quality and maximize cutting efficiency.

[0042] Furthermore, when the driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter, the method further includes: By real-time detection of the resistance sensor data of the multi-blade rotary cutting head, it is determined whether the resistance sensor data is within an abnormal resistance threshold; if so, the spring mechanism of the multi-blade rotary cutting head is activated to stop the cutter shaft.

[0043] In the process of driving the motor group to control the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter, real-time monitoring of cutting resistance and a response mechanism for abnormal situations are also included. Specifically, the resistance sensor installed on the multi-blade rotary cutting head continuously detects the resistance data of the blade during the cutting process, and compares the data with the preset abnormal resistance threshold. If the resistance sensor data is detected to be beyond the normal working range and reaches or exceeds the abnormal resistance threshold, the system determines that there may be abnormal conditions in the cutting process, such as the hard part inside the potato (such as an area that is not completely thawed), blade jamming, foreign matter blocking or severe blade wear.

[0044] In the case of abnormal resistance, in order to avoid damaging the blade, reducing cutting accuracy or affecting the overall cutting efficiency, the system will immediately trigger the safety protection mechanism and start the spring mechanism of the multi-blade rotary cutting head to stop the knife shaft. The stop knife shaft mechanism provides a buffering effect through the spring mechanism, so that when the blade encounters a situation that exceeds the normal cutting load, it can quickly stop rotating or properly retract to reduce the risk of blade damage and equipment loss. At the same time, the activation of the stop knife shaft also provides the system with an abnormal alarm signal, allowing the control system to take further remedial measures, such as adjusting cutting parameters, recalibrating the blade gap, or prompting manual intervention to check the equipment status.

[0045] Furthermore, after outputting the second adjustment parameter, the first adjustment parameter and the second adjustment parameter are iteratively optimized to obtain the first optimized adjustment parameter and the second optimized adjustment parameter; the driving motor group controls the multi-blade rotating cutting head and the cutting fixture to slice potatoes according to the first optimized adjustment parameter and the second optimized adjustment parameter.

[0046] After outputting the second adjustment parameter, in order to further optimize the accuracy and efficiency of the cutting process, the system iteratively optimizes the first adjustment parameter and the second adjustment parameter to obtain the first optimized adjustment parameter and the second optimized adjustment parameter. Specifically, based on the initially calculated first adjustment parameter (including blade gap and rotation speed) and the second adjustment parameter (including displacement and rotation speed of the cutting fixture), combined with the feedback data obtained during the actual cutting process, the cutting control parameters are dynamically adjusted and optimized, so that the system can adapt to the shapes, sizes and material characteristics of different potatoes during the cutting process, and improve the uniformity and stability of the cutting.

[0047] Furthermore, if Figure 2 As shown, the first adjustment parameter and the second adjustment parameter are iteratively optimized, and the method includes: Taking the second adjustment parameter as an input variable, performing reverse collaborative analysis on the multi-blade rotary cutting head based on the motion coupling relationship, and outputting an updated first adjustment parameter; taking the updated first adjustment parameter as an input variable, performing collaborative analysis on the cutting fixture based on the motion coupling relationship, and outputting an updated second adjustment parameter; and so on, until the first update difference and the second update difference are both smaller than a preset threshold, obtaining a first optimized adjustment parameter and a second optimized adjustment parameter, wherein the first update difference is the difference between the updated first adjustment parameter and the unupdated first adjustment parameter, and the second update difference is the difference between the updated second adjustment parameter and the unupdated second adjustment parameter.

[0048] First, the second adjustment parameter currently calculated is used as an input variable, and based on the pre-established motion coupling relationship, the multi-blade rotary cutting head is subjected to reverse collaborative analysis to calculate and output the updated first adjustment parameter. The goal of the reverse collaborative analysis is to adjust the cutting gap and rotation speed of the multi-blade rotary cutting head based on the motion state of the cutting fixture to achieve more accurate cutting control. Next, the updated first adjustment parameter is used as an input variable, and the cutting fixture is again subjected to collaborative analysis based on the motion coupling relationship to calculate and output the updated second adjustment parameter. The above optimization process is continued in an iterative manner, that is, the latest calculated adjustment parameter is continuously used for the next round of optimization calculation until the first update difference and the second update difference obtained in the optimization process are both less than the preset threshold. Specifically, the first update difference refers to the numerical difference between the latest calculated first adjustment parameter and the first adjustment parameter calculated in the previous round, and the second update difference refers to the numerical difference between the latest calculated second adjustment parameter and the second adjustment parameter calculated in the previous round. When the first update difference and the second update difference converge to within the preset threshold, that is, the change of the adjustment parameter tends to be stable, it means that the system has found the optimal first optimization adjustment parameter and the second optimization adjustment parameter, and the iterative optimization process is stopped at this time. Finally, the driving motor group controls the operation of the multi-blade rotary cutting head and the cutting fixture according to the optimized first optimization adjustment parameters and the second optimization adjustment parameters, respectively, to ensure the accuracy and uniformity of potato slices and the high efficiency of the cutting process.

[0049] In summary, the embodiments of the present application have at least the following technical effects: The potato slicer is provided with a multi-blade rotary cutting head, a cutting fixture and a driving motor group, wherein the multi-blade rotary cutting head includes a gap-adjustable blade group, and the driving motor group includes a first driving motor connected to the multi-blade rotary cutting head and a second driving motor connected to the cutting fixture. First, potatoes to be cut are taken, placed on the cutting fixture and the sensor data of the potatoes to be cut are identified. Then, the gap-adjustable blade group is adaptively analyzed according to the sensor data, and a first adjustment parameter is output, wherein the first adjustment parameter includes an adjustment gap and an adjustment speed. Then, the cutting fixture is collaboratively analyzed according to the first adjustment parameter, and a second adjustment parameter is output, wherein the second adjustment parameter includes an adjustment displacement and an adjustment speed. Finally, the driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter. The technical problem that the potato slicer in the prior art cannot adaptively adjust the cutting parameters according to the size and shape of the potato, resulting in low cutting efficiency and uneven slice thickness is solved, and the cutting operation is adaptively adjusted according to the actual situation of the potato, thereby achieving the technical effect of improving cutting efficiency and ensuring uniform slice thickness.

[0050] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0051] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0052] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A potato slicer control method based on multi-blade rotary cutting, characterized in that: The method comprises: The potato slicer is provided with a multi-blade rotary cutting head, a cutting fixture and a drive motor group, wherein the multi-blade rotary cutting head comprises a gap-adjustable blade group, and the drive motor group comprises a first drive motor connected to the multi-blade rotary cutting head and a second drive motor connected to the cutting fixture; Taking potatoes to be cut, placing them on the cutting fixture and identifying sensor data of the potatoes to be cut; Adaptively analyzing the gap-adjustable blade set according to the sensing data, and outputting a first adjustment parameter, wherein the first adjustment parameter includes an adjustment gap and an adjustment speed; Performing collaborative analysis on the cutting fixture according to the first adjustment parameter to output a second adjustment parameter, wherein the second adjustment parameter includes an adjustment displacement and an adjustment rotation speed; The driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter.

2. The potato slicer control method based on multi-blade rotary cutting as claimed in claim 1, characterized in that: After taking the potatoes to be cut, the method further comprises: Detecting the state of the potatoes to be cut according to the thermocouple in the cutting fixture, including a frozen state and a non-frozen state; If the state of the potatoes to be cut is a non-frozen state, the gap-adjustable blade set is adaptively analyzed according to the sensor data to output a first adjustment parameter.

3. The potato slicer control method based on multi-blade rotary cutting as claimed in claim 1, characterized in that: The multi-blade rotary cutting head includes a plurality of adjacently arranged blades, and a phase difference threshold constraint is included between adjacent blades; The sensing data is subjected to an adaptive constraint analysis on the gap-adjustable blade set according to the phase difference threshold constraint.

4. The potato slicer control method based on multi-blade rotary cutting as claimed in claim 1, characterized in that: According to the sensing data, the gap-adjustable blade set is adaptively analyzed to output a first adjustment parameter. include: Wherein, the sensing data includes geometric sensing data and material sensing data; The geometric sensing data and the material sensing data are used as input data and input into a blade group adaptive analysis model, and a first adjustment parameter is output according to the blade group adaptive analysis model. The blade group adaptive analysis model is trained until convergence through sensor data training samples and labels representing slice uniformity.

5. The potato slicer control method based on multi-blade rotary cutting as claimed in claim 4, characterized in that: The method of performing collaborative analysis on the cutting fixture according to the first adjustment parameter includes: Establishing a kinematic coupling relationship between the multi-blade rotary cutting head and the cutting fixture; The first adjustment parameter is used as an input variable, and a collaborative analysis is performed on the cutting fixture based on the motion coupling relationship to output a second adjustment parameter.

6. The control method of a potato slicer based on multi-blade rotary cutting as claimed in claim 5, characterized in that: The kinematic coupling relationship expression is: ; Wherein, x is the real-time displacement of the cutting fixture, d is the diameter of the potato to be cut, is a fixed phase offset, used for the periodic error of the cutting process, K S is the weight coefficient representing the complexity of potato shape, and S is the shape parameter of the sensing data.

7. The control method of a potato slicer based on multi-blade rotary cutting as claimed in claim 5, characterized in that: After outputting the second adjustment parameter, iteratively optimizing the first adjustment parameter and the second adjustment parameter to obtain a first optimized adjustment parameter and a second optimized adjustment parameter; The driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first optimized adjustment parameter and the second optimized adjustment parameter.

8. The control method of a potato slicer based on multi-blade rotary cutting as claimed in claim 7, characterized in that: Iteratively optimizing the first adjustment parameter and the second adjustment parameter, the method comprising: Using the second adjustment parameter as an input variable, performing a reverse collaborative analysis on the multi-blade rotary cutting head based on the kinematic coupling relationship, and outputting an updated first adjustment parameter; Using the updated first adjustment parameter as an input variable, performing a collaborative analysis on the cutting fixture based on the kinematic coupling relationship, and outputting an updated second adjustment parameter; And so on, until the first update difference and the second update difference are both smaller than the preset threshold, the first optimized adjustment parameter and the second optimized adjustment parameter are obtained, wherein the first update difference is the difference between the updated first adjustment parameter and the unupdated first adjustment parameter, and the second update difference is the difference between the updated second adjustment parameter and the unupdated second adjustment parameter.

9. The control method of a potato slicer based on multi-blade rotary cutting as claimed in claim 2, characterized in that: If the state of the potatoes to be cut is a frozen state, a protection control mode is started, wherein the protection control mode includes a protection speed and a protection gap; Under the protection control mode, an adaptive protection analysis is performed on the gap-adjustable blade set according to the sensor data, and a first protection adjustment parameter is output.

10. The potato slicer control method based on multi-blade rotary cutting as claimed in claim 1, characterized in that: When the driving motor group controls the multi-blade rotary cutting head and the cutting fixture to slice potatoes according to the first adjustment parameter and the second adjustment parameter, the method further includes: By real-time detection of the resistance sensor data of the multi-blade rotary cutting head, determining whether the resistance sensor data is within an abnormal resistance threshold; If it is, start the spring mechanism of the multi-blade rotary cutting head to stop the knife shaft.

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