A method, device and system for controlling the motor of a hair clipper

Abstract

This invention relates to the field of communications, and particularly to a method, apparatus, and system for controlling the motor of a hair clipper. The method first identifies the distribution of hair characteristics of the person being cut, then predicts the movement path of the hair clipper based on the user's actions, determines the characteristic changes of the hair that the hair clipper passes through during movement, and predicts the load changes of the hair clipper's motor during movement based on these characteristic changes. This allows for the pre-planning of motor parameters for each segment of the movement path, and automatic control of the hair clipper to operate with the planned parameters for that segment when it reaches the corresponding segment. This eliminates the need for real-time manual parameter adjustments by the hairdresser, ensuring the accuracy of motor parameter adjustment, reducing manual operation, and improving the efficiency of parameter adjustment.

Description

Technical Field

[0001] This invention relates to the field of communications, and in particular to a method, apparatus, and system for controlling the motor of a hair clipper. Background Technology

[0002] When a barber operates a hair clipper to cut hair, he or she needs to adjust the motor parameters of the clipper to adapt to the cutting of hair in different positions.

[0003] However, the current method for adjusting the motor parameters of hair clippers is mainly a speed switching method. But hair clippers usually only have 2-3 speeds, and the motor parameters of each speed are fixed, which makes the adjustment space of the motor parameters very limited. Moreover, this adjustment needs to be done manually by the hairdresser, which is highly dependent on the hairdresser's experience, is prone to large adjustment errors, and has low adjustment efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide a motor control method, device, and system for a hair clipper to address the above-mentioned problems.

[0005] The present invention is implemented as follows: a motor control method for a hair clipper is provided, the method comprising:

[0006] S1: Acquire an image of the target area to be trimmed and identify the hair features at each location in the target area of ​​the image;

[0007] S2: Map the target region to a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0008] S3: Recognize the user's actions in operating the hair clipper to predict the movement path of the hair clipper in a two-dimensional plane;

[0009] S4: Determine the characteristic changes of the hair that the barber passes through during its movement on a two-dimensional plane based on the movement path and the marked hair features;

[0010] S5: Retrieve the prediction model of the torque load of the hair clipper to predict the load change of the hair clipper motor when it is moving, based on the characteristic changes of the hair.

[0011] S6: Motor parameters corresponding to each segment of the planned movement path based on load changes;

[0012] S7: When the hair clipper passes through any section of the moving path, the control motor runs according to the corresponding motor parameters.

[0013] In one embodiment, the present invention provides a motor control device for a hair clipper, the device comprising:

[0014] The acquisition module is used to acquire images of the target area to be trimmed and to identify hair features at various locations within the target area in the image.

[0015] The first processing module is used to map the target region into a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0016] The second processing module is used to identify the user's actions in operating the hair clipper in order to predict the movement path of the hair clipper on a two-dimensional plane.

[0017] The third processing module is used to determine the feature changes of the hair that the barber passes through during the movement on a two-dimensional plane based on the movement path and the marked hair features.

[0018] The fourth processing module is used to retrieve the prediction model of the torque load of the hair clipper in order to predict the load change of the hair clipper motor when it moves based on the characteristic changes of the hair.

[0019] The fifth processing module is used to plan the motor parameters corresponding to each segment of the movement path based on load changes.

[0020] The control module is used to control the motor to operate according to the corresponding motor parameters when the hair clipper passes through any segment of the moving path.

[0021] In one embodiment, the present invention provides a motor control system for a hair clipper, the system comprising:

[0022] Hair clipper with a built-in motor;

[0023] Hair feature acquisition device, used to acquire hair features;

[0024] Vision devices are used to recognize the user's actions in operating the hair clippers;

[0025] A computer device that communicates with a hair feature acquisition device, a vision device, and a motor in a hair clipper to execute a motor control method for the hair clipper.

[0026] This invention provides a motor control method for a hair clipper, including: acquiring an image of a target area to be trimmed; identifying hair features at various locations within the target area in the image; mapping the target area to a two-dimensional plane and marking the hair features on the two-dimensional plane; recognizing the user's actions while operating the hair clipper to predict the clipper's movement path on the two-dimensional plane; determining the feature changes of the hair the clipper passes through during movement on the two-dimensional plane based on the movement path and the marked hair features; retrieving a torque load prediction model for the hair clipper to predict the load changes of the clipper's motor during movement based on the hair feature changes; planning the motor parameters corresponding to each segment of the movement path based on the load changes; and controlling the clipper as it passes through any segment of the movement path. During a certain period, the control motor operates according to the corresponding motor parameters. In this application, the distribution of hair characteristics of the hairdresser can be identified first, and then the movement path of the hairdresser can be predicted based on the user's operation of the hairdresser. The characteristic changes of the hair that the hairdresser passes through during movement can be determined, so as to predict the load change of the hairdresser's motor during the movement of the hairdresser based on the characteristic changes. Thus, the motor parameters corresponding to each segment of the movement path can be planned in advance, and when the hairdresser reaches the corresponding segment, the hairdresser is automatically controlled to operate with the planned operating parameters of the hairdresser in that segment. There is no need for the hairdresser to manually adjust the parameters in real time, which not only ensures the accuracy of motor parameter adjustment, but also reduces manual operation and improves the efficiency of parameter adjustment. Attached Figure Description

[0027] Figure 1 A flowchart of a motor control method for a hair clipper provided in one embodiment;

[0028] Figure 2 This is an application environment diagram of a motor control method for a hair clipper provided in one embodiment;

[0029] Figure 3 This is a schematic diagram of the blade center point of a motor control method for a hair clipper provided in one embodiment;

[0030] Figure 4 A rectangular area schematic diagram of a motor control method for a hair clipper provided in one embodiment;

[0031] Figure 5 This is a schematic flowchart of a motor control device for a hair clipper provided in one embodiment;

[0032] Figure 6 This is a block diagram of the internal structure of a computer device in one embodiment. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0034] It is understood that the terms "first," "second," etc., used in this invention may be used to describe various elements herein, but unless specifically stated otherwise, these elements are not limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of this invention, a first script may be referred to as a second script, and similarly, a second script may be referred to as a first script.

[0035] like Figure 1 As shown, in one embodiment, a motor control method for a hair clipper is proposed, the method comprising:

[0036] S1: Acquire an image of the target area to be trimmed and identify the hair features at each location in the target area of ​​the image;

[0037] S2: Map the target region to a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0038] S3: Recognize the user's actions in operating the hair clipper to predict the movement path of the hair clipper in a two-dimensional plane;

[0039] S4: Determine the characteristic changes of the hair that the barber passes through during its movement on a two-dimensional plane based on the movement path and the marked hair features;

[0040] S5: Retrieve the prediction model of the torque load of the hair clipper to predict the load change of the hair clipper motor when it is moving, based on the characteristic changes of the hair.

[0041] S6: Motor parameters corresponding to each segment of the planned movement path based on load changes;

[0042] S7: When the hair clipper passes through any section of the moving path, the control motor runs according to the corresponding motor parameters.

[0043] In this embodiment, as Figure 2As shown, this method is executed in a computer device, which can be an independent physical server or terminal, or a server cluster consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud servers, cloud databases, cloud storage, and CDN. The computer device is connected to a hair feature acquisition device and a vision device. The hair feature acquisition device can send the acquired hair features to the computer device, and the computer device can recognize the user's actions of operating the hair clipper through the vision device. The hair clipper can be an electric clipper, and the motor in the hair clipper is controlled by the computer device, which can control the parameters of the hair clipper's motor rotation.

[0044] In this embodiment, the user is the barber; the visual device can be a high-definition camera, and the number of visual devices can be one or more, which is not limited here; the target area is the area where the hair is distributed; the hair feature acquisition device can be a scalp detector, and the barber can use the probe of the scalp detector to scan the target area where the hair of the hairdresser is located to obtain a scanned image; the scanning method includes close-range scanning (1~2cm from the scalp) and long-range scanning (20~40cm from the scalp). The image acquired by long-range scanning can present the entire head of the hairdresser, thereby determining the overall range of the target area and identifying the length of each position in the target area (if some positions cannot be identified due to obstruction, the barber can move the hair before identification); the image acquired by close-range scanning can present the scalp and hair roots, thereby identifying the hair density and hair diameter of the scalp at that location; in this embodiment, the target area can be divided into several unit areas (such as a square area with a side length of 1cm), one unit area corresponds to one position, and identifying the hair features of each position in the target area in the image is to identify the hair features of each unit area.

[0045] In this embodiment, since the head of the person getting a haircut is three-dimensional, the target area in the scanned image is also three-dimensional (i.e., the scanned target area is a curved surface). In order to facilitate image and data analysis, this embodiment maps the target area in the image to a two-dimensional plane. Specifically, the point cloud coordinates of each position point in the target area can be identified in the scanned image, and three-dimensional modeling software (such as Blender) can be called to generate a three-dimensional curved surface corresponding to the target area based on the point cloud coordinates. The three-dimensional curved surface can then be unfolded into a two-dimensional plane using the UV unfolding function of the three-dimensional modeling software.

[0046] In this embodiment, as the barber pushes the clipper along the movement path, the computer device can monitor the position of the clipper (focusing on the blade) in real time through the sensing device (specifically, which segment in the movement path), and then automatically control the clipper to operate with the planned operating parameters for that segment.

[0047] In this application, the distribution of hair features of the hairdresser can be identified first, and then the movement path of the hairdresser can be predicted based on the user's operation of the hairdresser. The feature changes of the hair that the hairdresser passes through during movement can be determined, and the load changes of the hairdresser's motor during movement can be predicted based on the feature changes. Thus, the motor parameters corresponding to each segment of the movement path can be planned in advance, and when the hairdresser reaches the corresponding segment, the hairdresser is automatically controlled to run with the planned operating parameters for that segment. There is no need for the hairdresser to manually adjust the parameters in real time, which not only ensures the accuracy of motor parameter adjustment, but also reduces manual operation and improves the efficiency of parameter adjustment.

[0048] In a preferred embodiment, hair features include length, density, and diameter; identifying hair features at various locations within a target region of an image includes, for each hair feature, identifying the range of feature values ​​for that hair feature at each location.

[0049] Marking hair features on a two-dimensional plane includes:

[0050] For each hair feature, a feature layer is generated that overlaps with the target region, wherein the shape and size of the feature layer are the same as those of the two-dimensional plane;

[0051] For each feature layer, the feature layer is divided into several feature blocks according to the distribution of the feature value range of the corresponding hair feature, wherein the feature value range in each feature block is the same.

[0052] The feature value range of each feature block is marked on that feature block.

[0053] In this embodiment, since the influence of hair characteristics on load is phased—that is, the changes in load caused by hair characteristics within a certain range of characteristic values ​​are roughly the same, and only when the range is crossed will there be a significant change in load—several characteristic value ranges are preset for each hair characteristic. For example, for hair density, a range of 60-70 hairs / cm is preset. 2 70~80 roots / cm 2 ... 140~150 strands / cm 2 When more than 70% of the hair density in a unit area of ​​the target region falls within the same density range, such as 70-80 hairs / cm², 2 Therefore, the hair density range of this unit area can be considered to be 70~80 hairs / cm. 2Following this method, the feature value ranges of all unit regions in the target area can be obtained, that is, the distribution of feature value ranges can be obtained. For each feature value range, unit regions with the same feature value range are identified, and the regions corresponding to these unit regions are identified on the corresponding feature layer, that is, the feature blocks corresponding to the feature value range on the feature layer are obtained (which may be a continuous region or multiple discrete regions, depending on the actual distribution of feature value ranges). Following this method, multiple feature blocks of the feature layer can be determined.

[0054] like Figure 3 As shown, in a preferred embodiment, recognizing the user's actions in operating the hair clipper to predict the movement path of the hair clipper on a two-dimensional plane includes:

[0055] S31: Identify whether the user places the clippers on the hair of the person being cut;

[0056] S32: If so, identify the orientation of the hair clipper's blade and the position of the blade's center point on the hair;

[0057] S33: Mark the position point corresponding to the center point of the cutter head on the two-dimensional plane, and generate a straight line extending to the boundary of the target area along the direction of the cutter head with the starting point of the position point.

[0058] The predicted movement path is the movement path of a user pushing the hair clipper in a single push;

[0059] S8: After step S7, the user completes a single push of the hair clipper. Continue to identify the user's actions in operating the hair clipper to predict the new movement path of the hair clipper. Repeat steps S4 to S8 until the user completes the haircut.

[0060] In this embodiment, the hair clipper can be an electric clipper with a blade of a certain width. The edge of the blade can be considered as a straight line, and the center point of the blade is the center point of this straight line. Furthermore, since the two-dimensional plane is obtained by unfolding the three-dimensional curved surface corresponding to the target area in the image, a corresponding position point can be found on the two-dimensional plane for each point in the target area, thereby determining the position point of the blade center point on the two-dimensional plane. In addition, the blade direction is perpendicular to the straight line where the center point is located, and a vector corresponding to the blade direction can be generated at the center point. The relative position of this vector with the target area can be identified, and a corresponding vector can be generated on the two-dimensional plane based on this relative position. The direction of this vector is the direction corresponding to the blade direction. In addition, the hairdresser usually pushes the hair clipper along a straight line, so the predicted movement path is also a straight line.

[0061] In this embodiment, during the haircutting process, the hairdresser often needs to push the clipper multiple times to complete the haircut. The movement path identified in this embodiment is the movement path of one push. After the push is completed, a new movement path is identified again to adjust the motor parameters. This cycle is repeated until the hairdresser is identified to turn off the clipper and complete the haircut.

[0062] like Figure 4 As shown, in a preferred embodiment, predicting the load change of the hair clipper's motor during movement based on changes in hair characteristics includes:

[0063] Generate n points between the starting point and the ending point of the movement path to obtain n+2 trajectory points. The trajectory points include the starting point and the ending point, and the distance between any two adjacent trajectory points is a set length.

[0064] At each trajectory point, a line segment is generated centered at that trajectory point and perpendicular to the movement trajectory, wherein the length of the line segment is longer than the width of the hair clipper head;

[0065] For every two adjacent line segments, connect the two ends of the two line segments respectively to obtain n+1 rectangular regions;

[0066] For each rectangular region, the weighted average length, weighted average density, and weighted average diameter of the hair in that rectangular region are determined based on the feature value range of each feature layer corresponding to that rectangular region.

[0067] The torque load of the rectangular region is calculated based on the weighted average length, weighted average density, weighted average diameter, and the torque load prediction model.

[0068] In this embodiment, the rectangular area is the area enclosed by two adjacent line segments and the line connecting the two ends of the line segments; the set length can be 1cm, 2cm or other values; each rectangular area is the area that the blade will fall into during the movement, that is, the area where the blade can cut the hair within the rectangular area; the length of the line segment can be 1cm longer than the width of the hair clipper blade, so that the area formed by the rectangular area is slightly larger than the area that the blade passes through during the movement of the electric clipper, so as to ensure that the blade can fall into the rectangular area even when it deviates slightly during the movement. Since the load change and the motor parameters are determined by the hair characteristics in the rectangular area, it can be ensured that the planned motor parameters are also applicable to the area that the blade actually passes through when the blade deviates slightly.

[0069] As a preferred embodiment, determining the weighted average length, weighted average density, and weighted average diameter of the hair in the rectangular region based on the feature value range corresponding to each feature layer includes:

[0070] Identify the rectangular region within the feature layer corresponding to its length, and identify the first sub-block within the selected region that belongs to each feature block. Calculate the weighted average length of the hair within this rectangular region using the following formula:

[0071]

[0072] in, For weighted average length, Let i be the area of ​​the first sub-block of the i-th sub-block. Let l be the median of the feature value range of the i-th first sub-block, and l be the number of first sub-blocks;

[0073] Identify the rectangular region within the feature layer corresponding to the density, and identify the second sub-blocks within the selected region that belong to each feature block. Calculate the weighted average density of the hair in this rectangular region using the following formula:

[0074]

[0075] in, For weighted average density, Let j be the area of ​​the second sub-block. Let m be the median of the feature value range of the j-th second sub-block, and m be the number of second sub-blocks;

[0076] Identify the rectangular region within the feature layer corresponding to the density, and identify the third sub-block within the selected region that belongs to each feature block. Calculate the weighted average diameter of the hairs within this rectangular region using the following formula:

[0077]

[0078] in, For the weighted average diameter, Let the area of ​​the k-th third sub-block be . Let be the median of the feature value range of the j-th third sub-block, and n be the number of third sub-blocks.

[0079] The prediction model for torque load is as follows:

[0080]

[0081] in, For torque load, and represents the fitting coefficient.

[0082] In this embodiment, the unit of length is cm, and the unit of density is roots / cm. 2The diameter is in cm. Since the selected area may cover multiple feature blocks, and only one local block (i.e., sub-block) is covered in each feature block, the selected area includes several sub-blocks with different corresponding feature values. Therefore, it is necessary to determine the weighted average feature value of the selected area by weighted averaging.

[0083] In this embodiment, It is 0.02. The value is 0.005. The prediction model for torque load is obtained by conducting multiple experiments in advance and fitting the experimental data. For example, select multiple hair samples with different feature combinations (which can be wigs), use electric clippers to cut the samples to obtain the output torque that just cuts them, and then derive the torque load based on the output torque and transmission efficiency. This yields the correspondence between multiple hair sample features and torque loads, and then linear fitting is performed to obtain the prediction model for torque load.

[0084] In a preferred embodiment, the motor parameters include output torque and speed; each rectangular area corresponds to a segment of the movement path;

[0085] The motor parameters corresponding to each segment of the planned movement path based on load changes include:

[0086] For each rectangular region, the output torque corresponding to that region is determined by the following formula:

[0087]

[0088] in, For output torque, This is the transmission efficiency coefficient;

[0089] The rotational speed corresponding to this rectangular region can be calculated using the following formula:

[0090]

[0091] in, For rotational speed, This represents the output power of the motor.

[0092] In this embodiment, the transmission efficiency will be reduced due to transmission losses. Therefore, the transmission efficiency coefficient needs to be considered when calculating the output torque. This coefficient can be 0.8 or other values, depending on the type of motor of the hair clipper. Since the hairdresser does not need to adjust the gear, the output power of the motor remains constant. Given the output power and output torque, the speed can be directly determined.

[0093] like Figure 5 As shown, in one embodiment, a motor control device for a hair clipper is provided, the device comprising:

[0094] The acquisition module is used to acquire images of the target area to be trimmed and to identify hair features at various locations within the target area in the image.

[0095] The first processing module is used to map the target region into a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0096] The second processing module is used to identify the user's actions in operating the hair clipper in order to predict the movement path of the hair clipper on a two-dimensional plane.

[0097] The third processing module is used to determine the feature changes of the hair that the barber passes through during the movement on a two-dimensional plane based on the movement path and the marked hair features.

[0098] The fourth processing module is used to retrieve the prediction model of the torque load of the hair clipper in order to predict the load change of the hair clipper motor when it moves based on the characteristic changes of the hair.

[0099] The fifth processing module is used to plan the motor parameters corresponding to each segment of the movement path based on load changes.

[0100] The control module is used to control the motor to operate according to the corresponding motor parameters when the hair clipper passes through any segment of the moving path.

[0101] The process by which each module in the motor control device of the hair clipper provided in this application implements its respective function can be specifically referred to the foregoing. Figure 1 The description of the illustrated embodiment will not be repeated here.

[0102] like Figure 2 As shown, in one embodiment, a motor control system for a hair clipper is provided, the system comprising:

[0103] Hair clipper with a built-in motor;

[0104] Hair feature acquisition device, used to acquire hair features;

[0105] Vision devices are used to recognize the user's actions in operating the hair clippers;

[0106] A computer device that communicates with a hair feature acquisition device, a vision device, and a motor in a hair clipper to execute a motor control method for the hair clipper.

[0107] In this embodiment, the computer equipment works in conjunction with the hair clipper, hair feature acquisition device, and vision device to first identify the distribution of hair features of the hairdresser, then predict the movement path of the hair clipper based on the user's operation of the hair clipper, and determine the feature changes of the hair that the hair clipper passes through during movement. Based on the feature changes, the load changes of the hair clipper's motor during the movement of the hair clipper can be predicted. This allows for the pre-planning of motor parameters for each segment of the movement path, and when the hair clipper reaches the corresponding segment, it is automatically controlled to operate with the planned operating parameters for that segment. This eliminates the need for the hairdresser to manually adjust parameters in real time, ensuring the accuracy of motor parameter adjustment, reducing manual operation, and improving the efficiency of parameter adjustment.

[0108] Figure 6 An internal structural diagram of a computer device in one embodiment is shown. Figure 6 As shown, the computer device includes a processor, memory, network interface, input device, and display screen connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement the motor control method for the hair clipper provided in this embodiment of the invention. The internal memory may also store a computer program, which, when executed by the processor, enables the processor to execute the motor control method for the hair clipper provided in this embodiment of the invention. The display screen of the computer device can be a liquid crystal display screen or an e-ink display screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad mounted on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0109] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0110] In one embodiment, the motor control device for the hair clipper provided by this invention can be implemented as a computer program, and the computer program can be implemented as follows: Figure 6 The computer device shown runs on this device. The computer device's memory can store the various program modules that make up the motor control unit of the hair clipper, for example, Figure 5The diagram shows a data acquisition module, a first processing module, a second processing module, a third processing module, a fourth processing module, a fifth processing module, and a sixth processing module. The computer program comprised of these modules causes the processor to execute the steps of the motor control method for the hair clipper described in the various embodiments of the present invention.

[0111] For example, Figure 6 The computer equipment shown can be used as follows Figure 5 The acquisition module in the motor control device of the hair clipper shown executes step S1; the computer device can execute step S2 through the first processing module; the computer device can execute step S3 through the second processing module; the computer device can execute step S4 through the third processing module; the computer device can execute step S5 through the fourth processing module; the computer device can execute step S6 through the fifth processing module; and the computer device can execute step S7 through the control module.

[0112] In one embodiment, a computer device is provided, the computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps:

[0113] S1: Acquire an image of the target area to be trimmed and identify the hair features at each location in the target area of ​​the image;

[0114] S2: Map the target region to a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0115] S3: Recognize the user's actions in operating the hair clipper to predict the movement path of the hair clipper in a two-dimensional plane;

[0116] S4: Determine the characteristic changes of the hair that the barber passes through during its movement on a two-dimensional plane based on the movement path and the marked hair features;

[0117] S5: Retrieve the prediction model of the torque load of the hair clipper to predict the load change of the hair clipper motor when it is moving, based on the characteristic changes of the hair.

[0118] S6: Motor parameters corresponding to each segment of the planned movement path based on load changes;

[0119] S7: When the hair clipper passes through any section of the moving path, the control motor runs according to the corresponding motor parameters.

[0120] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, causes the processor to perform the following steps:

[0121] S1: Acquire an image of the target area to be trimmed and identify the hair features at each location in the target area of ​​the image;

[0122] S2: Map the target region to a two-dimensional plane and annotate hair features on the two-dimensional plane;

[0123] S3: Recognize the user's actions in operating the hair clipper to predict the movement path of the hair clipper in a two-dimensional plane;

[0124] S4: Determine the characteristic changes of the hair that the barber passes through during its movement on a two-dimensional plane based on the movement path and the marked hair features;

[0125] S5: Retrieve the prediction model of the torque load of the hair clipper to predict the load change of the hair clipper motor when it is moving, based on the characteristic changes of the hair.

[0126] S6: Motor parameters corresponding to each segment of the planned movement path based on load changes;

[0127] S7: When the hair clipper passes through any section of the moving path, the control motor runs according to the corresponding motor parameters.

[0128] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0129] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0130] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0131] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A motor control method for a hair clipper, characterized in that, The method includes: S1: Acquire an image of the target area to be trimmed and identify the hair features at each location in the target area of ​​the image; S2: Map the target region to a two-dimensional plane and annotate hair features on the two-dimensional plane; S3: Recognize the user's actions in operating the hair clipper to predict the movement path of the hair clipper in a two-dimensional plane; S4: Determine the characteristic changes of the hair that the barber passes through during its movement on a two-dimensional plane based on the movement path and the marked hair features; S5: Retrieve the prediction model of the torque load of the hair clipper to predict the load change of the hair clipper motor when it is moving, based on the characteristic changes of the hair. S6: Motor parameters corresponding to each segment of the planned movement path based on load changes; S7: When the hair clipper passes through any section of the moving path, the control motor runs according to the corresponding motor parameters.

2. The method according to claim 1, characterized in that, Hair features include length, density, and diameter; identifying hair features at various locations within a target region of an image includes, for each hair feature, identifying the range of feature values ​​for that hair feature at each location. Marking hair features on a two-dimensional plane includes: For each hair feature, a feature layer is generated that overlaps with the target region, wherein the shape and size of the feature layer are the same as those of the two-dimensional plane; For each feature layer, the feature layer is divided into several feature blocks according to the distribution of the feature value range of the corresponding hair feature, wherein the feature value range in each feature block is the same. The feature value range of each feature block is marked on that feature block.

3. The method according to claim 2, characterized in that, Recognizing user actions while operating the hair clipper to predict its movement path in a two-dimensional plane includes: S31: Identify whether the user places the clippers on the hair of the person being cut; S32: If so, identify the orientation of the hair clipper's blade and the position of the blade's center point on the hair; S33: Mark the position point corresponding to the center point of the cutter head on the two-dimensional plane, and generate a straight line extending to the boundary of the target area along the direction of the cutter head with the starting point of the position point.

4. The method according to claim 3, characterized in that, The predicted movement path is the movement path of a user pushing the hair clipper in a single push; S8: After step S7, the user completes a single push of the hair clipper. Continue to identify the user's actions in operating the hair clipper to predict the new movement path of the hair clipper. Repeat steps S4 to S8 until the user completes the haircut.

5. The method according to claim 3, characterized in that, Predicting load changes on the clipper motor during movement based on changes in hair characteristics includes: Generate n points between the starting point and the ending point of the movement path to obtain n+2 trajectory points. The trajectory points include the starting point and the ending point, and the distance between any two adjacent trajectory points is a set length. At each trajectory point, a line segment is generated centered at that trajectory point and perpendicular to the movement trajectory, wherein the length of the line segment is longer than the width of the hair clipper head; For every two adjacent line segments, connect the two ends of the two line segments respectively to obtain n+1 rectangular regions; For each rectangular region, the weighted average length, weighted average density, and weighted average diameter of the hair in that rectangular region are determined based on the feature value range of each feature layer corresponding to that rectangular region. The torque load of the rectangular region is calculated based on the weighted average length, weighted average density, weighted average diameter, and the torque load prediction model.

6. The method according to claim 5, characterized in that, Based on the feature value range of each feature layer corresponding to the rectangular region, the weighted average length, weighted average density, and weighted average diameter of the hair in the rectangular region are determined, including: Identify the rectangular region within the feature layer corresponding to its length, and identify the first sub-block within the selected region that belongs to each feature block. Calculate the weighted average length of the hair within this rectangular region using the following formula: in, For weighted average length, Let i be the area of ​​the first sub-block of the i-th sub-block. Let l be the median of the feature value range of the i-th first sub-block, and l be the number of first sub-blocks; Identify the rectangular region within the feature layer corresponding to the density, and identify the second sub-blocks within the selected region that belong to each feature block. Calculate the weighted average density of the hair in this rectangular region using the following formula: in, For weighted average density, Let j be the area of ​​the second sub-block. Let m be the median of the feature value range of the j-th second sub-block, and m be the number of second sub-blocks; Identify the rectangular region within the feature layer corresponding to the density, and identify the third sub-block within the selected region that belongs to each feature block. Calculate the weighted average diameter of the hairs within this rectangular region using the following formula: in, For the weighted average diameter, Let the area of ​​the k-th third sub-block be . Let be the median of the feature value range of the j-th third sub-block, and n be the number of third sub-blocks.

7. The method according to claim 6, characterized in that, The prediction model for torque load is as follows: in, For torque load, and represents the fitting coefficient.

8. The method according to claim 7, characterized in that, Motor parameters include output torque and speed; each rectangular area corresponds to a segment of the movement path; The motor parameters corresponding to each segment of the planned movement path based on load changes include: For each rectangular region, the output torque corresponding to that region is determined by the following formula: in, For output torque, This is the transmission efficiency coefficient; The rotational speed corresponding to this rectangular region can be calculated using the following formula: in, For rotational speed, This represents the output power of the motor.

9. A motor control device for a hair clipper, characterized in that, The device includes: The acquisition module is used to acquire images of the target area to be trimmed and to identify hair features at various locations within the target area in the image. The first processing module is used to map the target region into a two-dimensional plane and annotate hair features on the two-dimensional plane; The second processing module is used to identify the user's actions in operating the hair clipper in order to predict the movement path of the hair clipper on a two-dimensional plane. The third processing module is used to determine the feature changes of the hair that the barber passes through during the movement on a two-dimensional plane based on the movement path and the marked hair features. The fourth processing module is used to retrieve the prediction model of the torque load of the hair clipper in order to predict the load change of the hair clipper motor when it moves based on the characteristic changes of the hair. The fifth processing module is used to plan the motor parameters corresponding to each segment of the movement path based on load changes. The control module is used to control the motor to operate according to the corresponding motor parameters when the hair clipper passes through any segment of the moving path.

10. A motor control system for a hair clipper, characterized in that, The system includes: Hair clipper with a built-in motor; Hair feature acquisition device, used to acquire hair features; Vision devices are used to recognize the user's actions in operating the hair clippers; A computer device, communicating with a hair feature acquisition device, a vision device, and a motor in a hair clipper, for performing a motor control method for a hair clipper as described in any one of claims 1-8.

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