Hair curler curling degree adjusting method and system

Abstract

The invention relates to a hair curler curling degree adjusting method and system, and relates to the technical field of hairdressing equipment, and the method comprises the steps: detecting the hair quality of a user in response to a triggering instruction, and determining the hair quality information; matching according to the hair quality information and a preset hair quality classification standard to obtain a hair quality type; determining corresponding heating temperature, retention time and torsion parameters according to the hair quality type and a preset hair quality parameter model; obtaining a hair curling mode set by a user; determining the curling degree based on the curling mode and the hair quality type; determining a torsion direction and a torsion angle according to the crimpness and the torsion parameter; a preset clamping plate hair curler is controlled to conduct heating at the heating temperature, then hair curling is conducted in the twisting direction and the twisting angle, and after the standing time is up, hair curling is completed. The method has the effect of optimizing user experience and hair quality health.

Description

Technical Field

[0001] This invention relates to the field of hair styling equipment technology, and in particular to a method and system for adjusting the curl of a hair curler. Background Technology

[0002] As a mainstream hair styling tool, the core function of the flat iron curling iron is to shape hair strands through heat and mechanical curling. The degree of curl is a key indicator that determines the hairstyle effect.

[0003] In home use, flat iron curlers are more commonly used. Flat iron curlers have two plates with built-in heating wires. When curling hair, the temperature is adjusted by the button, and the hair is clamped between the two heated plates. At the same time, the plates are twisted to one side. By clamping, heating and twisting, and controlling the twisting force and the time the plates are held, the curl is changed, and the hair is made into a spiral curl. After heating, the plates are slowly released and cooled to set the style, thus completing the curl.

[0004] Currently, the curling effect is influenced by the difference in heat, which is controlled by the button settings and dwell time. However, users lack awareness of their hair quality and rely on their experience to make judgments, which can easily lead to curls that are too loose or too tight, resulting in a mismatch between the curl and the desired curl. Summary of the Invention

[0005] To optimize user experience and hair health, this invention provides a method and system for adjusting the curl of a hair curler.

[0006] In a first aspect, the present invention provides a method for adjusting the curl of a hair curler, employing the following technical solution: A method for adjusting the curl of a hair curler includes: In response to a trigger command, detect the user's hair quality and determine hair quality information; The hair type is determined by matching hair quality information with preset hair quality classification standards; The corresponding heating temperature, dwell time, and twisting parameters are determined based on the hair type and the preset hair parameter model. Get the curling mode set by the user; The degree of curl is determined based on the curling pattern and hair type; The direction and angle of twist are determined based on the degree of curl and the twist parameters; The preset hair curling iron is heated to a specific temperature, and then the hair is curled in different directions and angles. The curling is complete after the set time is reached.

[0007] By adopting the above technical solution, the hair quality is detected and matched in response to the trigger command, and then the heating temperature, dwell time and twisting parameters are determined. Combined with the user's set curling mode, the twisting direction and angle are calculated, and the flat iron curler is controlled to complete the heating and curling. The temperature is controlled according to the hair quality and the twisting parameters are determined according to the hairstyle. This allows the curl to be adjusted according to the hair quality, thereby effectively reducing heat damage and improving the curl's durability. The styling result takes into account both personalization and health, optimizing user experience and hair health.

[0008] Optional methods for determining hair quality information include: Collect the capacitance value and raw spectral data between the preset hair straightener and curling iron; Determine the overall parameters for curling based on the capacitance value and the preset hair material; Hair density is determined based on the original spectral data and a pre-set optical hair texture model; After extracting the spectrum from the original spectral data, the degree of hair damage is determined by combining it with preset keratin integrity parameters; Hair health parameters are determined based on comprehensive curly hair parameters and the degree of hair damage. Hair quality information is determined based on hair health parameters and hair density.

[0009] By adopting the above technical solution, capacitance values ​​and original spectral data between the clamps are collected, and capacitance-humidity correlation models and optical hair quality models are constructed respectively. Humidity, oil, transmittance and keratin integrity are extracted, and hair health parameters are calculated comprehensively to achieve multi-physical quantity fusion evaluation. This ensures that hair quality information is objective and accurate, provides a reliable basis for subsequent temperature and time settings, and improves the safety and scientific nature of hair curling.

[0010] Optional methods for determining the overall parameters of curly hair include: A capacitance-humidity correlation model is determined based on the capacitance value and the preset hair material, and the initial humidity value is calculated by multiplying the capacitance value and the preset dielectric constant. Hair humidity value is determined based on initial humidity value and a capacitance-humidity correlation model; Extract the capacitance signal of the capacitance value at the preset detection frequency; The oil content is calculated based on the initial humidity value using a preset reuse algorithm; The capacitance-oil model is determined based on the capacitance value and the calculated oil content; Hair oil content is determined based on capacitance signals and a capacitance-based oil model. Hair moisture level and hair oil content are used as comprehensive parameters for perming.

[0011] By adopting the above technical solution, the capacitive signal at the detection frequency is combined with a multiplexing algorithm to determine the hair humidity value and oil content through single parameter acquisition, forming comprehensive parameters for curling, improving detection efficiency and simplifying sensor hardware, so that the curling iron can complete hair quality determination in a single clamping, shortening the preparation cycle and enhancing the integration of the equipment.

[0012] Optional methods for determining hair density include: The sampling area and sampling brightness are determined based on the original spectral data and the preset sampling range, and the hair transmittance is determined from the original spectral data. The thickness and diameter of a single hair are determined based on the hair's transmittance. The cross-sectional area of ​​a single hair is obtained by calculating the diameter and adjusting the sampled brightness. The number of hairs is determined based on the cross-sectional area and hair translucency. The hair density is obtained by substituting the sampling area and the number of hairs into a preset optical hair texture model.

[0013] By adopting the above technical solution, hair density is calculated based on the sampling area, hair transmittance and single hair cross-sectional area. The number of hairs is inverted through spectral transmission characteristics, realizing non-contact density assessment, eliminating the need for microscopic counting or weighing steps, ensuring real-time accuracy of density results, and providing quantitative reference for setting twisting force and clamping gap, so as to improve the fullness and uniformity of curly hairstyles.

[0014] Optional methods for determining the diameter include: The transmitted light intensity, the detection reference light intensity, and the optical path length are extracted from the original spectral data. The difference between the transmitted light intensity and the detection reference light intensity is calculated to obtain the light intensity difference value, and the light intensity attenuation amount is obtained by matching. The light attenuation coefficient is determined based on the hair transmittance. The attenuation model is determined based on the light intensity attenuation and the light attenuation coefficient. The diameter is determined based on the attenuation model and optical path length.

[0015] By adopting the above technical solution, the difference between transmitted light intensity and reference light intensity is extracted, and an attenuation model is established in combination with the light attenuation coefficient. This accurately inverts the diameter of a single hair, laying a high-resolution data foundation for subsequent calculations of fiber strength and damage, and enhancing the robustness and generalization ability of the hair quality assessment model.

[0016] Optional methods for determining the degree of hair damage include: Effective spectral data is obtained from the original spectral data through a correction algorithm; Peak intensity of keratin in hair was extracted from effective spectral data; Hair integrity is determined based on peak intensity and preset keratin integrity parameters; Based on the original spectral data, the characteristic spectral values ​​corresponding to the fiber strength are extracted, and then the hair fiber strength is determined. The degree of hair damage is calculated by weighting the hair's integrity and hair fiber strength.

[0017] By adopting the above technical solution, an effective spectrum is obtained using a correction algorithm. The peak intensity of keratin and the characteristic spectral values ​​of fibers are extracted, and the degree of hair damage is obtained through weighted fusion. This achieves simultaneous quantification of chemical and mechanical damage, avoids misjudgment based on a single indicator, and ensures that the damage classification is precise and accurate. This allows for dynamic compensation of negative ions and clamping force, reducing the risk of breakage.

[0018] Optional methods for determining hair fiber strength include: The raw spectral data is preprocessed to obtain the net spectrum; Identify characteristic peaks and valleys in the net spectrum that reflect fiber integrity; Spectral absorbance for protein structure extraction based on net spectrum; Calculate the peak-valley intensity difference based on characteristic peaks and valleys; A fiber strength model based on spectral absorbance and peak-valley intensity difference; The hair fiber strength is obtained by substituting the characteristic spectral values ​​into the fiber strength model.

[0019] By adopting the above technical solution, the characteristic peaks and valleys of the net spectrum are identified and the peak-valley intensity difference is calculated. The fiber strength model is constructed by combining the absorbance of the protein structure, which directly links the microscopic features of the spectrum with the macroscopic mechanical properties. This eliminates the need for tensile testing in fiber strength assessment, improves detection speed and non-destructive testing, provides a safe threshold for setting the upper limit of the clamping force, and ensures the integrity of the hair strands during the curling process.

[0020] Optional methods for determining the torsional parameters include: The negative ion output reference range and clamping force reference range are obtained by matching the preset hair quality parameter model according to the hair type. Preliminary negative ion parameters are determined based on hair quality information and the negative ion output baseline range; Determine the initial clamping force based on hair quality information and the baseline range of clamping force; Verify whether the initial negative ion parameters and initial clamping force are within the safe range of the preset equipment safe operating threshold; If the safe range is exceeded, the initial negative ion parameters and initial clamping force are adjusted proportionally based on the preset equipment safe operation threshold, initial negative ion parameters, and initial clamping force, and used as torsional parameters. If it is within the safe range, the final negative ion parameters and the final clamping force will be used as the torsion parameters of the hair straightener.

[0021] By adopting the above technical solution, the negative ions and clamping force are matched according to the hair type and adjusted proportionally after being verified within a safe range. The final parameters are used as the basis for torsion, thereby achieving synergistic optimization of negative ions and mechanical force, avoiding excessive clamping or excessive negative ions, and balancing style maintenance and hair protection.

[0022] Optional methods for determining the curl degree include: The corresponding baseline curl range is determined based on the curling pattern and the preset curl baseline model; Based on the hair type and the preset hair characteristic correction coefficient table, determine the hair correction coefficient for the corresponding hair type; Extract the morphological parameters corresponding to the curling mode to determine the additional correction value for the mode; Based on the baseline curl range, hair quality correction coefficient, and pattern-added correction value, a preliminary curl value is obtained through weighted calculation. The initial curl value is checked to see if it is within a reasonable range based on the preset effective curl range. If the initial curl value is within a reasonable range, then the initial curl value is taken as the degree of curl. If the initial curl value is outside the range, the final curl degree is determined by proportional calculation based on the initial curl value and the preset effective curl range.

[0023] By adopting the above technical solution, the curl degree is determined by weighted calculation of the benchmark curl degree range, hair quality correction coefficient and pattern additional correction value, and after effective range verification. This ensures that the curl degree setting meets both user aesthetics and hair quality limits, avoids ineffective heating and repeated styling, improves the success rate of one-time styling, saves energy and enhances user satisfaction.

[0024] Secondly, this application provides a curl adjustment system for a hair curler, which adopts the following technical solution: A curling iron curl adjustment system includes: The acquisition module is used to acquire capacitance values, raw spectral data, and curling patterns.

[0025] The memory is used to store programs that implement any method for adjusting the curl of a hair curler.

[0026] The processor loads and executes programs from memory.

[0027] In summary, this application includes at least one of the following beneficial technical effects: 1. Responding to the trigger command, the hair texture is detected and matched with the hair type, and then the heating temperature, dwell time and twisting parameters are determined. Combined with the user's set curling mode, the twisting direction and angle are calculated, and the flat iron curler is controlled to complete the heating and curling. The temperature is controlled according to the hair texture and the twisting parameters are determined according to the hairstyle. This allows the curl to be adjusted according to the hair texture, thereby effectively reducing heat damage and improving the curl's durability. The styling result takes into account both personalization and health, optimizing user experience and hair health. 2. Based on the sampling area, hair transmittance and single hair cross-sectional area, hair density is calculated. The number of hairs is inverted through spectral transmittance characteristics to achieve non-contact density assessment, eliminating the need for microscopic counting or weighing steps, ensuring real-time and accurate density results, and providing quantitative reference for setting twisting force and clamping gap, so as to improve the fullness and uniformity of curly hairstyles. 3. A calibration algorithm is used to obtain an effective spectrum, extract the peak intensity of keratin and the characteristic spectral values ​​of fibers, and obtain the degree of hair damage through weighted fusion. This achieves simultaneous quantification of chemical and mechanical damage, avoids misjudgment by a single indicator, and ensures that the damage classification is precise and accurate. This allows for dynamic compensation of negative ions and clamping force, reducing the risk of breakage. Attached Figure Description

[0028] Figure 1 This is a flowchart of a method for adjusting the curl of a hair curler according to an embodiment of the present invention; Figure 2 This is a flowchart of the method for determining the overall parameters of hair curling according to an embodiment of the present invention. Detailed Implementation

[0029] 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.

[0030] This application discloses a method for adjusting the curl of a hair curler.

[0031] Reference Figure 1 A method for adjusting the curl of a hair curler includes the following steps: Step S100: In response to the trigger command, detect the user's hair quality and determine hair quality information.

[0032] The trigger command is an electronic signal that starts the entire curling process, which can be issued by a button on the curling iron.

[0033] Hair quality information refers to parameters related to the overall condition of a user's hair. The physical and chemical state data of the user's hair includes humidity, oil, density, and degree of damage, which are further determined by parameters detected by various sensors on the curling iron.

[0034] The specific methods are described in steps S200 to S205, and will not be repeated here.

[0035] Step S101: Obtain the hair type by matching the hair quality information with the preset hair quality classification standard.

[0036] Hair quality classification standards refer to the preset standard range that divides hair into major categories such as fine and soft, normal, and coarse and hard. These standards are set in advance by technicians based on actual conditions and will not be elaborated on here.

[0037] Hair type refers to the specific hair type that is used to define the type of hair for curling.

[0038] The hair quality information, including humidity, oil content, density, and degree of damage, is compared with the parameter threshold ranges corresponding to various hair types in the preset standards for hair quality. When the hair quality information meets the threshold range of a certain type of hair, the hair type can be matched and determined.

[0039] Step S102: Determine the corresponding heating temperature, dwell time, and twisting parameters based on the hair type and the preset hair parameter model.

[0040] The hair quality parameter model refers to a parameter data model that stores information suitable for users' hair types when curling. It includes a database of relationships between different hair types and heating temperature and dwell time. This model is pre-set by technicians according to actual conditions and will not be elaborated on here.

[0041] Heating temperature refers to the working temperature of the heating element of the hair straightener, usually expressed in °C. The heating temperature varies depending on the hair type.

[0042] The dwell time refers to the length of time the hair is clamped and heated by the hair straightener; the longer the time, the more pronounced the curl.

[0043] The twist parameter refers to the combined value of the twist direction and angle of the clamp, which determines the spiral direction and number of turns of the curling iron.

[0044] By inputting hair type into a relational database, the relationship between heating temperature and dwell time is obtained. The actual correspondence is pre-built and set by technicians through a large amount of experimental data, which will not be elaborated here.

[0045] The specific method for twisting parameters is described in steps S800 to S805, and will not be repeated here.

[0046] Step S103: Obtain the curling mode set by the user.

[0047] The curling mode refers to the curling style selected by the user, which can be provided through the external device's APP and preset by technicians according to the actual situation. It will not be elaborated here.

[0048] Once the user confirms, the data is transmitted to the curling iron via the app. The specific method is common knowledge known to those skilled in the art and will not be elaborated here.

[0049] Step S104: Determine the degree of curl based on the curling pattern and hair type.

[0050] Curl refers to the degree of curl in hair. It is a comprehensive quantitative indicator used to represent the final degree of curl. The higher the value, the more obvious the curl.

[0051] The specific method for determining the degree of curl is described in steps S900 to S906, and will not be repeated here.

[0052] Step S105: Determine the direction and angle of twist based on the curvature and twist parameters.

[0053] The direction of rotation refers to whether the clamp rotates clockwise or counterclockwise, which affects the direction of the curl.

[0054] The twist angle refers to the absolute angle of rotation of the hair straightener, measured in degrees, and determines the number of curls required.

[0055] First, the degree of curl directly determines the direction and basic range of the twist. The higher the degree of curl, the larger the required twist angle, and the lower the degree of curl, the smaller the twist angle. Then, the angle is adjusted in detail according to the twist parameters to ensure the suitability for hair type, and finally the twist angle is determined.

[0056] Step S106: Control the preset hair curling iron to heat at the heating temperature, and then curl the hair in the twisting direction and twisting angle. When the dwell time is reached, the curling is completed.

[0057] A hair straightener is a device used for heating and curling hair. It has a built-in heating element and a twistable clamping mechanism for clamping, heating and twisting hair strands.

[0058] The curling iron uses a built-in temperature sensor and heating module to heat the plates to a target temperature determined according to the hair type, and monitors and maintains the temperature in real time to avoid damage from overheating or failure to set the style due to insufficient temperature. Once the temperature is reached, the built-in motor drives the plates to complete a precise twist according to the twisting direction and angle, while maintaining a clamping force that matches the hair type. Then, the built-in timer starts, and when the dwell time determined according to the hair type is reached, the motor resets and releases the hair, completing one curling and setting cycle. The entire process is coordinated by a microcontroller to achieve an automated curling effect that is adapted to the hair type.

[0059] The method for determining hair quality information includes the following steps: Step S200: Collect the preset capacitance value and raw spectral data between the hair straightener and the curling iron.

[0060] The capacitance value refers to the capacitance measured between the two poles of the hair clip. It varies with the dielectric properties of hair and can reflect humidity and oil.

[0061] Raw spectral data refers to the hair reflectance spectral information collected by a spectral sensor, which is used to analyze the physicochemical state of hair.

[0062] The capacitance value is obtained by collecting the capacitance value between the clamp and the hair through the capacitive sensor built into the clamp-type hair curler.

[0063] The raw spectral data was obtained by collecting near-infrared reflectance spectra using a miniature spectral sensor built into the hair curler.

[0064] Step S201: Determine the overall parameters for curling based on the capacitance value and the preset hair material.

[0065] Hair material refers to the inherent physical and chemical properties of hair, such as capacitance values ​​under different humidity levels. These parameters are preset by technicians based on actual conditions and will not be elaborated upon here.

[0066] The comprehensive parameters of curly hair refer to a two-dimensional comprehensive index of hair moisture and oiliness derived from the capacitance value, which is used for subsequent model calculations.

[0067] The specific methods for calculating the overall parameters of the curling hair are described in steps S300 to S306, and will not be repeated here.

[0068] Step S202: Determine hair density based on the original spectral data and the preset optical hair texture model.

[0069] An optical hair quality model is a computational model used to analyze hair density based on the principle of spectral detection. The optical hair quality model is pre-established based on a large amount of experimental data and user needs analysis. It internally stores the correlation between hair density determined from the original spectral data and is pre-set by technicians according to the actual situation, which will not be elaborated here.

[0070] Hair density refers to the number of hairs per unit area.

[0071] The specific methods for determining hair density are described in steps S400 to S405, and will not be repeated here.

[0072] Step S203: After extracting the spectrum based on the original spectral data, determine the degree of hair damage by combining it with the preset keratin integrity parameters.

[0073] Keratin integrity parameters refer to standard parameters used to assess keratin integrity. These parameters are preset by technicians according to the actual situation and will not be elaborated here.

[0074] Hair damage level refers to a numerical value that quantifies the degree of damage to the hair cuticle.

[0075] The specific methods are described in steps S600 to S604, and will not be repeated here.

[0076] Step S204: Determine hair health parameters based on overall curly hair parameters and hair damage level.

[0077] Hair health parameters refer to numerical indicators that comprehensively assess the health status of hair.

[0078] The overall parameters of the curl and the degree of hair damage are weighted and calculated to obtain the hair health parameters by combining the quantitative indicators of the two. The specific weights are preset by the technicians according to the actual situation, which will not be elaborated here.

[0079] Step S205: Determine hair quality information based on hair health parameters and hair density.

[0080] First, hair density is used to classify hair into three core categories: fine and soft, normal, and coarse and hard, thus clarifying the basic thickness attributes of hair. Then, hair health parameters are combined to further distinguish between healthy, slightly damaged, and severely damaged levels. The dry and wet state of hair (dry / slightly wet / wet) and oil content are marked to classify low, medium, and high oil levels. These health dimensions are combined with density categories to form complete hair quality information that combines basic attributes and health status, providing a basis for matching curly hair parameters in the future.

[0081] Reference Figure 2 The method for determining the overall parameters of curly hair includes the following steps: Step S300: Determine the capacitance-humidity correlation model based on the capacitance value and the preset hair material, and calculate the initial humidity value by multiplying the capacitance value and the preset dielectric constant.

[0082] The capacitance-humidity correlation model refers to a mathematical model used to convert capacitance values ​​into humidity values. It is a function that describes the relationship between capacitance and humidity conversion and is preset by technicians according to the actual situation. It will not be elaborated here.

[0083] The dielectric constant refers to the dielectric coefficient of a hair fiber in an electric field. It is preset by technicians according to the actual situation and will not be elaborated here.

[0084] The initial humidity value refers to the amount of humidity used to initially determine the humidity level of the hair.

[0085] Based on the capacitance and humidity data of hair materials under various humidity levels, the characteristic that the capacitance value increases with the increase of hair moisture content is determined. Regression analysis is used to fit the mapping relationship between the capacitance value and humidity of different materials. The resulting functional relationship is the capacitance-humidity correlation model.

[0086] The initial humidity value is obtained by multiplying the capacitance value and the dielectric constant.

[0087] Step S301: Determine the hair humidity value based on the initial humidity value and the capacitance humidity correlation model.

[0088] Hair moisture value refers to the current moisture content of the hair.

[0089] The initial humidity value is fed into the function of the capacitance-humidity correlation model, and the initial humidity value is calibrated using the functional relationship to finally obtain a hair humidity value that accurately reflects the actual condition of the hair. For example, if high hair oil content is detected (which would lead to an inflated capacitance value), the model will reduce the initial humidity value using an oil compensation coefficient; if the hair is severely damaged (loose fiber structure leading to a deviation in dielectric constant), the value is adjusted using a structure correction coefficient, and finally, the actual hair humidity value after removing interference is output.

[0090] Step S302: Extract the capacitance signal of the capacitance value at the preset detection frequency.

[0091] The detection frequency refers to the specific operating frequency at which the capacitive sensor measures hair quality. This frequency is preset by technicians based on actual conditions and will not be elaborated upon here.

[0092] A capacitance signal refers to a capacitance change signal measured at a specific frequency.

[0093] By setting a specific frequency suitable for reflecting the characteristics of hair oil, capacitance values ​​are collected at that frequency and electrical signals corresponding to the characteristics of hair oil are extracted, providing basic data for subsequent calculation of hair oil content using a capacitance-based oil model.

[0094] Step S303: Calculate the oil content based on the initial humidity value using a preset reuse algorithm.

[0095] The reuse algorithm refers to the algorithm used to derive the oil content from the humidity value. It is preset by technicians according to the actual situation and will not be described in detail here.

[0096] Calculating oil content refers to using an algorithm to calculate and output the amount of oil in the hair based on the capacitance value.

[0097] In hair detection, both humidity and oil affect the dielectric properties of hair (such as changes in capacitance value). The two are related. Therefore, the preset multiplexing algorithm first extracts the oil feature information from the capacitance signal corresponding to the initial humidity value, and finally calculates the oil content. The specific method is common knowledge known to those skilled in the art and will not be elaborated here.

[0098] Step S304: Determine the capacitor grease model based on the capacitance value and the calculated grease content.

[0099] The capacitive sebum model is a model used to assess the sebum content of hair, and can use the conversion curve between capacitance and sebum.

[0100] First, the capacitance value and the calculated oil content are processed to determine the data distribution and select the appropriate method. If the capacitance value and the calculated oil content show a significant linear correlation, linear regression can be used to fit the basic function relationship. If there are nonlinear characteristics (such as significant differences in the rate of change of capacitance value when the oil content is too high or too low), multinomial regression or machine learning algorithms such as random forests and neural networks can be used to explore the deep mapping pattern between the two and generate a more accurate nonlinear model. The specific methods are common knowledge to those skilled in the art and will not be elaborated here.

[0101] Step S305: Determine hair oil content based on capacitance signal and capacitance oil model.

[0102] Hair oil content refers to the percentage of actual oil in the hair by mass.

[0103] The hair oil content is calculated by substituting the capacitance signal into the capacitance oil model.

[0104] Step S306: Use hair moisture value and hair oil content as comprehensive parameters for curling.

[0105] Hair moisture content and oil content are core indicators reflecting the immediate physical state of hair. Therefore, they are used as comprehensive parameters for curling, providing a precise basis for matching key parameters such as heating temperature and twisting force, thus balancing the curling effect and hair health.

[0106] The method for determining hair density includes the following steps: Step S400: Determine the sampling area and sampling brightness based on the original spectral data and the preset sampling range.

[0107] The sampling range refers to the size of the area corresponding to the field of view of the spectral sensor. It is used for spectral analysis and is preset by technicians according to the actual situation. It will not be elaborated here.

[0108] The sampling area refers to the numerical value of the area within the sampling range.

[0109] Sampling brightness refers to the integrated brightness of the infrared spectrum within the region, which is used to correct for hair transmittance.

[0110] The sampling range typically corresponds to the fixed field of view of the optical probe in the hair curler detection module (such as the size of the physical area covered by the probe), which directly determines the actual area of ​​the sampling region. The original spectral data contains the light signal information reflected or transmitted by the hair in that region. By extracting the light intensity parameters from the spectral data and converting them, the sampling brightness reflecting the light reflection intensity of the hair in that region can be obtained. This provides basic parameters for subsequent calculations of hair quantity, thickness, etc., to determine hair density. The specific method for extracting the sampling brightness is common knowledge to those skilled in the art and will not be elaborated here.

[0111] Step S401: Determine the hair transmittance from the raw spectral data.

[0112] Hair transmittance refers to the proportion of light that passes through the hair.

[0113] Based on Beer-Lambert law, the transmittance of hair at the corresponding wavelength is calculated. The specific method is common knowledge to those skilled in the art and will not be elaborated here.

[0114] Step S402: Determine the thickness and diameter of a single hair based on the hair's transmittance.

[0115] The thickness diameter refers to the diameter of a single hair.

[0116] The specific methods for determining the diameter are described in steps S500 to S504, and will not be repeated here.

[0117] Step S403: Calculate the cross-sectional area of ​​a single hair based on the diameter and adjust it in conjunction with the sampled brightness.

[0118] Cross-sectional area refers to the area of ​​the hair's cross-section when the hair is approximated as a cylinder.

[0119] The initial cross-sectional area of ​​a single hair is calculated based on its diameter. The diameter is then fine-tuned based on the uniformity of the sampled brightness. If the brightness of the hair area is uneven (e.g., the brightness changes gradually due to blurred edges), it indicates a slight deviation in the contour extraction. The diameter value is then corrected according to the brightness gradient (the larger the brightness deviation, the smaller the correction range, to ensure it does not exceed a reasonable range). Finally, the corrected effective diameter is substituted into the circle area formula to calculate the final cross-sectional area of ​​a single hair.

[0120] Step S404: Determine the number of hairs based on the cross-sectional area and hair transmittance.

[0121] Hair count refers to the number of hairs counted within the sampling area.

[0122] The number of hairs is obtained by inputting the cross-sectional area and hair transmittance into a preset hair quantity database. The hair quantity database is a database that is preset by technicians according to the actual situation. The hair quantity database contains the correspondence between cross-sectional area, hair transmittance and hair quantity. The correspondence is preset by technicians according to the actual situation and will not be elaborated here.

[0123] Step S405: Substitute the sampling area and the number of hairs into the preset optical hair texture model to obtain hair texture density.

[0124] The optical hair quality model is a functional relationship for calculating hair density based on the area of ​​the sampling region and the number of hairs. Through experimental setup by technicians, the area of ​​the sampling region and the number of hairs are substituted into the optical hair quality model to obtain the hair density.

[0125] The method for determining the diameter includes the following steps: Step S500: Extract the transmitted light intensity, the detection reference light intensity, and the optical path length based on the original spectral data.

[0126] Transmitted light intensity refers to the light intensity value after passing through the hair.

[0127] The reference light intensity refers to the standard light intensity value used for comparison after removing ambient light intensity.

[0128] Optical path length refers to the geometric path length of light rays as they travel through the inside of a hair.

[0129] Transmitted light intensity is obtained by directly capturing the light signal after passing through the hair from the original spectral data, and then filtering and denoising to obtain a specific value; the detection reference light intensity is determined by collecting the light signal directly from the light source when there is no hair obstruction from the original spectral data, and subtracting ambient light interference (such as dark current calibration and background light sampling cancellation), and serves as a comparison benchmark; the emitted light intensity is the emitted light from the optical sensor, and the received light intensity is the average value of the light intensity in the original spectral data; the optical path length is calculated by substituting the emitted light intensity and the received light intensity into the light attenuation formula, and the specific method is common knowledge to those skilled in the art and will not be elaborated here.

[0130] Step S501: Calculate the difference between the transmitted light intensity and the detection reference light intensity to obtain the light intensity difference value, and match it to obtain the light intensity attenuation amount.

[0131] The light intensity difference refers to the difference between the transmitted light intensity used to determine the light intensity attenuation and the detection reference light intensity.

[0132] Light intensity attenuation refers to the degree to which light intensity decreases during propagation.

[0133] The difference between the transmitted light intensity and the detection reference light intensity is the light intensity difference. The light intensity attenuation is obtained by inputting the light intensity difference into a preset light intensity attenuation database. The light intensity attenuation database is a database that is preset by technicians according to the actual situation. The light intensity attenuation database contains the correspondence between the light intensity difference and the light intensity attenuation. The actual correspondence is preset by technicians according to the actual situation, which will not be elaborated here.

[0134] Step S502: Determine the light attenuation coefficient based on the hair transmittance.

[0135] The light attenuation coefficient refers to the ratio of light attenuation in hair.

[0136] The light attenuation coefficient is obtained by inputting the hair transmittance into a preset light attenuation coefficient database. The light attenuation coefficient database is a lookup table that is preset by technicians according to the actual situation. The light attenuation coefficient lookup table contains the correspondence between hair transmittance and light intensity attenuation. The actual correspondence is preset by technicians according to the actual situation, which will not be elaborated here.

[0137] Step S503: Determine the attenuation model based on the light intensity attenuation and the light attenuation coefficient.

[0138] The attenuation model refers to a mathematical model used to describe the attenuation law of light intensity.

[0139] By mathematically fitting the quantitative relationship between light intensity attenuation and light attenuation coefficient (such as establishing a functional relationship), a mathematical model that can accurately describe the intensity attenuation law of light passing through hair is constructed, namely the attenuation model. The specific method is common knowledge to those skilled in the art and will not be elaborated here.

[0140] Step S504: Determine the diameter based on the attenuation model and optical path length.

[0141] Substituting the optical path length into the attenuation model, which clearly establishes a quantitative correlation between light intensity attenuation and hair characteristics, the thickness and diameter of a single hair can be derived through reverse calculation by utilizing the correspondence between the degree of light intensity attenuation and hair diameter in the model.

[0142] The method for determining the degree of hair damage includes the following steps: Step S600: Obtain effective spectral data based on the original spectral data through a correction algorithm.

[0143] Valid spectral data refers to spectral data after baseline correction and smoothing.

[0144] The original spectral data may be affected by ambient light, equipment noise, etc. By using a correction algorithm to remove background drift, reduce scattering effects and random noise, and eliminate the influence of these non-target factors, we can finally obtain effective spectral data that can truly represent the structure of hair keratin, fiber integrity and other information. The correction algorithm refers to the algorithm used to correct the error of the spectral data, which is common knowledge in the art and will not be described in detail here.

[0145] Step S601: Extract the peak intensity of keratin in hair from the effective spectral data.

[0146] Peak intensity refers to the characteristic peak intensity of the absorption peak of keratin in the spectrum.

[0147] In valid spectral data, the characteristic absorption peaks unique to keratin are located by spectral analysis techniques and peak detection algorithms. The spectral signal intensity at the location of the characteristic peak is then extracted, which is the peak intensity of keratin. This is common knowledge to those skilled in the art and will not be elaborated here.

[0148] Step S602: Determine hair integrity based on peak intensity and preset keratin integrity parameters.

[0149] Hair integrity refers to the degree to which the keratin structure is intact.

[0150] Keratin is the core structural protein of hair, and its structural integrity is directly related to hair health. In healthy hair, keratin molecules are arranged in an orderly manner and exhibit characteristic peak intensities in specific spectral detection. In damaged hair, the keratin structure is disrupted, resulting in a decrease or shift in the corresponding peak intensity. By comparing the extracted keratin peak intensity with keratin integrity parameters and calculating the degree of deviation, the proportion of intact keratin in the hair can be determined, which is the hair integrity. The smaller the deviation, the higher the hair integrity; the larger the deviation, the more severe the keratin damage and the lower the hair integrity. The keratin integrity parameters are a standard range established based on keratin spectral data from a large number of healthy hair samples.

[0151] Step S603: Extract the characteristic spectral values ​​corresponding to the fiber strength based on the original spectral data, and then determine the hair fiber strength.

[0152] Characteristic spectral values ​​refer to the reflectance values ​​of specific bands of spectral data points that are related to fiber strength.

[0153] Hair fiber strength is a quantitative indicator of hair's resistance to breakage.

[0154] The specific methods for strengthening hair fibers are described in steps S700 to S705, and will not be repeated here.

[0155] Step S604: The degree of hair damage is calculated by weighting based on hair integrity and hair fiber strength.

[0156] The degree of hair damage is calculated by weighting the hair integrity and hair fiber strength. The specific weights are preset by technicians based on the actual situation and will not be elaborated here.

[0157] The method for determining hair fiber strength includes the following steps: Step S700: Preprocess the raw spectral data to obtain the net spectrum.

[0158] Net spectrum refers to the spectrum after removing background noise.

[0159] The raw spectral data is filtered and denoised to obtain the net spectrum. The specific methods are common knowledge to those skilled in the art and will not be described in detail here.

[0160] Step S701: Identify the characteristic peaks and valleys in the net spectrum that reflect fiber integrity.

[0161] Characteristic peaks refer to the peak values ​​of characteristic wavelengths in a spectrum.

[0162] Characteristic valleys refer to the peak and valley data of characteristic wavelengths in a spectrum.

[0163] The absorption peaks and valleys at these characteristic wavelengths are located by using a peak detection algorithm, thereby obtaining the characteristic valleys and characteristic peaks.

[0164] Step S702: Extract the spectral absorbance of the protein structure based on the net spectrum.

[0165] Spectral absorbance refers to the light absorption intensity of protein structures in a spectrum.

[0166] By utilizing the light absorption characteristics of protein structures at specific wavelengths, the absorbance value at that wavelength can be extracted by identifying the spectral signal corresponding to that characteristic wavelength, which is the spectral absorbance.

[0167] Step S703: Calculate the peak-valley intensity difference based on the characteristic peak and characteristic valley.

[0168] Peak-valley intensity difference refers to the intensity difference between a characteristic peak and a characteristic valley.

[0169] The peak-valley intensity difference is obtained by subtracting the valley value from the peak value of the characteristic peak.

[0170] Step S704: Fiber strength model established based on spectral absorbance and peak-valley intensity difference.

[0171] The fiber strength model refers to the regression mathematical model used to calculate fiber strength.

[0172] The spectral absorbance, peak-to-valley intensity difference, and corresponding actual fiber strength of different hair samples are pre-set. Then, the spectral absorbance and peak-to-valley intensity difference are used as input features, and the actual fiber strength is used as the output label. Linear regression or machine learning algorithms are used to fit the sample data to determine the mapping relationship between the two and the hair fiber strength, thereby obtaining the peak-to-valley intensity difference.

[0173] Step S705: Substitute the characteristic spectral values ​​into the fiber strength model to obtain the hair fiber strength.

[0174] By substituting the characteristic spectral values ​​into the mapping relationship of the fiber strength model, the hair fiber strength can be obtained.

[0175] The method for determining the torsional parameters includes the following steps: Step S800: Based on the hair type, the negative ion output reference range and clamping force reference range are matched from the preset hair quality parameter model.

[0176] The negative ion output reference range refers to the standard range of output from the negative ion generator, which is used for subsequent verification.

[0177] The clamping force reference range refers to the standard force range within which the clamp holds the hair, and is used for subsequent verification.

[0178] The hair quality parameter model pre-stores the negative ion output reference range and clamping force reference range corresponding to different hair types, so that the hair type is input into the negative ion output reference range and clamping force reference range matched in the hair quality parameter model.

[0179] Step S801: Determine the preliminary negative ion parameters based on hair quality information and the negative ion output reference range.

[0180] Preliminary negative ion parameters refer to the negative ion output value directly derived from hair quality.

[0181] Hair quality information includes specific conditions such as hair moisture, oil content, damage level, and density. The negative ion output benchmark range is a preset range of negative ion concentration or output for this hair type, used to adapt to the basic needs of this type of hair. Based on the specific indicators in the hair quality information, targeted weighted calculations are performed within the benchmark range to obtain preliminary negative ion parameters to match the actual needs of the hair. For example, when dry hair has a low moisture value, the negative ion output is increased within the benchmark range; when oily hair has a high oil content, the output is decreased within the benchmark range.

[0182] Step S802: Determine the initial clamping force based on hair quality information and the clamping force reference range.

[0183] Initial clamping force refers to the initial value of the force used to clamp the hair.

[0184] First, the hair quality information includes details such as hair moisture, oil content, degree of damage, and density. The clamping force baseline range is a preset reasonable force range for different hair types. It will be adjusted according to the specific hair quality information within the corresponding baseline range based on preset weights to obtain the initial clamping force. The preset weights are set by technicians in advance according to the actual situation and will not be elaborated here. For example, fine or damaged hair has weak tensile strength, so a lower force will be selected within the baseline range to reduce pulling damage; coarse and stiff hair will have a higher force selected within the baseline range to ensure the curl setting effect; if the hair moisture is high, the force may be appropriately reduced to avoid excessive squeezing of water and damage to the hair cuticle.

[0185] Step S803: Verify whether the initial negative ion parameters and initial clamping force are within the safe range of the preset equipment safe operation threshold.

[0186] The equipment safety operation threshold refers to the upper limit of the parameters for safe operation of the equipment. It is divided into two types: preliminary negative ion parameters and preliminary clamping force. These are preset by technicians according to the actual situation and will not be elaborated here.

[0187] The initial negative ion parameters and initial clamping force are compared with the equipment's safe operating threshold to determine whether they are within the corresponding range, and to judge whether the equipment can stably withstand them without posing a potential risk to the user, thus ensuring safety.

[0188] Step S804: If the safe range is exceeded, the initial negative ion parameters and initial clamping force are adjusted proportionally based on the preset equipment safe operation threshold, initial negative ion parameters, and initial clamping force, and used as torsion parameters.

[0189] If the limits are exceeded, it indicates a safety hazard, and adjustments must be made proportionally to meet safety requirements, ultimately ensuring reliable equipment operation and user safety.

[0190] Divide the equipment's safe operating threshold by the initial negative ion parameter and the initial clamping force, and multiply by 100% to obtain the initial ratio. Multiply the corresponding initial ratio by the initial negative ion parameter and the initial clamping force to obtain the torsion parameter.

[0191] Step S805: If it is within the safe range, use the final negative ion parameters and the final clamping force as the torsion parameters of the hair straightener.

[0192] Torsion parameters refer to the set of parameters used to control the torsion action of a hair curler.

[0193] If it is within the safe range, it means that it can withstand the pressure stably and will not pose a potential risk to the user, thus ensuring safety. The final negative ion parameters and the final clamping force will be used as the torsion parameters of the hair straightener.

[0194] The method for determining the degree of curl includes the following steps: Step S900: Determine the corresponding reference curl range based on the curling mode and the preset curl reference model.

[0195] The curling reference model refers to the standard model used to calculate curling. It is set up in advance by technicians according to the actual situation and will not be elaborated here.

[0196] The baseline curliness range refers to the reference range for describing the degree of curl in hair.

[0197] The curl benchmark model is pre-established based on a large amount of experimental data and user needs analysis. It stores the correlation between different curling modes and the corresponding basic curl range. When the user sets the curling mode, the corresponding benchmark curl range can be matched by querying the benchmark model, which serves as the basis for further precise adjustment of the curl in combination with factors such as hair quality.

[0198] Step S901: Determine the hair quality correction coefficient for the corresponding hair type based on the hair type and the preset hair quality characteristic correction coefficient table.

[0199] The hair quality characteristic correction coefficient table refers to a coefficient table used to correct the degree of curl. The coefficient table is based on the physical characteristics of different hair types (such as hair elasticity, toughness, and morphological stability after heat). It is pre-set through experimental data statistics. The table clearly associates each hair type with the corresponding correction coefficient (for example, due to the fragile structure of damaged hair, the correction coefficient may be smaller to avoid excessive curling and damage, while the correction coefficient of coarse and stiff hair may be larger to ensure the curl is formed). It is pre-set by technicians according to the actual situation, and will not be elaborated here.

[0200] Based on the aforementioned method, the specific hair type is obtained. Then, the hair type correction coefficient table is called. By matching the hair type with the coefficient table, the corresponding hair type correction coefficient can be determined. This is used for the accurate calculation of the curl degree in the subsequent process, so that the curl effect is more suitable for the hair type.

[0201] Step S902: Extract the morphological parameters corresponding to the curling mode and determine the additional correction value for the mode.

[0202] Morphological parameters refer to the geometric feature parameters corresponding to different curling patterns.

[0203] The pattern-additional correction value refers to the targeted adjustment value made to the baseline curl degree based on the differences in morphological parameters of different curling patterns.

[0204] The system extracts key morphological parameters corresponding to the mode from the preset mode parameter library, including the size of the curl, the number of curls, and the fullness of the arc. It combines the correlation model between different curling modes and curl correction (for example, the smaller the curl diameter and the more curls, the stronger the curl correction is usually required), substitutes the extracted morphological parameters into the model calculation, and obtains the additional correction value of the mode for fine-tuning the baseline curl, so that the final curling effect is more in line with the morphological characteristics of the selected mode.

[0205] Step S903: Based on the baseline curl range, hair quality correction coefficient, and pattern additional correction value, a preliminary curl value is obtained through weighted calculation.

[0206] The preliminary curl value refers to the preliminary curl result after weighted calculation.

[0207] Different weights are assigned to the baseline curl range, hair quality correction coefficient, and pattern-added correction value to calculate the initial curl value. The specific weights are preset by technicians according to the actual situation and will not be elaborated here.

[0208] Step S904: Verify whether the initial curl value is within a reasonable range based on the preset effective curl range.

[0209] The effective curling range refers to the allowable range of curling degree, which is preset by technicians according to the actual situation and will not be elaborated here.

[0210] Based on the initial curl value, determine whether it is within a reasonable range of the effective curl range parameters, and then make corrections.

[0211] Step S905: If the initial curl value is within a reasonable range, then the initial curl value is taken as the degree of curl.

[0212] If the initial curl value is within a reasonable range, it means that the curl degree is suitable for the user's hairstyle, and the initial curl value is taken as the curl degree.

[0213] Step S906: If the initial curl value is outside the range, the final curl degree is determined by proportional calculation based on the initial curl value and the preset effective curl range.

[0214] The final curl degree refers to the actual curl degree value determined after correction.

[0215] If the initial curl value is outside the range, it means that the curl is too large and not suitable for the user's hairstyle. Adjustment is required. Divide the corresponding threshold closest in the effective curl range by the initial curl value, multiply by 100% to obtain the initial ratio, and then multiply the corresponding initial ratio by the initial curl value to complete the ratio adjustment.

[0216] Based on the same inventive concept, embodiments of the present invention provide a curling iron curl adjustment system, comprising: The acquisition module is used to acquire capacitance values, raw spectral data, and curling patterns.

[0217] The memory is used to store programs that implement any method for adjusting the curl of a hair curler.

[0218] The processor loads and executes programs from memory.

[0219] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0220] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for adjusting the curl of a hair curler, characterized in that, include: In response to a trigger command, detect the user's hair quality and determine hair quality information; The hair type is determined by matching hair quality information with preset hair quality classification standards; The corresponding heating temperature, dwell time, and twisting parameters are determined based on the hair type and the preset hair parameter model. Get the curling mode set by the user; The degree of curl is determined based on the curling pattern and hair type; The direction and angle of twist are determined based on the degree of curl and the twist parameters; The preset hair curling iron is heated to a specific temperature, and then the hair is curled in different directions and angles. The curling is complete after the set time is reached.

2. The method for adjusting the curl of a hair curler according to claim 1, characterized in that, Methods for determining hair quality information include: Collect the capacitance value and raw spectral data between the preset hair straightener and curling iron; Determine the overall parameters for curling based on the capacitance value and the preset hair material; Hair density is determined based on the original spectral data and a pre-set optical hair texture model; After extracting the spectrum from the original spectral data, the degree of hair damage is determined by combining it with preset keratin integrity parameters; Hair health parameters are determined based on comprehensive curly hair parameters and the degree of hair damage. Hair quality information is determined based on hair health parameters and hair density.

3. The method for adjusting the curl of a hair curler according to claim 2, characterized in that, Methods for determining the overall parameters of curly hair include: A capacitance-humidity correlation model is determined based on the capacitance value and the preset hair material, and the initial humidity value is calculated by multiplying the capacitance value and the preset dielectric constant. Hair humidity value is determined based on initial humidity value and a capacitance-humidity correlation model; Extract the capacitance signal of the capacitance value at the preset detection frequency; The oil content is calculated based on the initial humidity value using a preset reuse algorithm; The capacitance-oil model is determined based on the capacitance value and the calculated oil content; Hair oil content is determined based on capacitance signals and a capacitance-based oil model. Hair moisture level and hair oil content are used as comprehensive parameters for perming.

4. The method for adjusting the curl of a hair curler according to claim 2, characterized in that, Methods for determining hair density include: The sampling area and sampling brightness are determined based on the original spectral data and the preset sampling range, and the hair transmittance is determined from the original spectral data. The thickness and diameter of a single hair are determined based on the hair's transmittance. The cross-sectional area of ​​a single hair is obtained by calculating the diameter and adjusting the sampled brightness. The number of hairs is determined based on the cross-sectional area and hair translucency. The hair density is obtained by substituting the sampling area and the number of hairs into a preset optical hair texture model.

5. The method for adjusting the curl of a hair curler according to claim 4, characterized in that, Methods for determining the diameter include: The transmitted light intensity, the detection reference light intensity, and the optical path length are extracted from the original spectral data. The difference between the transmitted light intensity and the detection reference light intensity is calculated to obtain the light intensity difference value, and the light intensity attenuation amount is obtained by matching. The light attenuation coefficient is determined based on the hair transmittance. The attenuation model is determined based on the light intensity attenuation and the light attenuation coefficient. The diameter is determined based on the attenuation model and optical path length.

6. The method for adjusting the curl of a hair curler according to claim 5, characterized in that, Methods for determining the degree of hair damage include: Effective spectral data is obtained from the original spectral data through a correction algorithm; Peak intensity of keratin in hair was extracted from effective spectral data; Hair integrity is determined based on peak intensity and preset keratin integrity parameters; Based on the original spectral data, the characteristic spectral values ​​corresponding to the fiber strength are extracted, and then the hair fiber strength is determined. The degree of hair damage is calculated by weighting the hair's integrity and hair fiber strength.

7. The method for adjusting the curl of a hair curler according to claim 6, characterized in that, Methods for determining hair fiber strength include: The raw spectral data is preprocessed to obtain the net spectrum; Identify characteristic peaks and valleys in the net spectrum that reflect fiber integrity; Spectral absorbance for protein structure extraction based on net spectrum; Calculate the peak-valley intensity difference based on characteristic peaks and valleys; A fiber strength model based on spectral absorbance and peak-valley intensity difference; The hair fiber strength is obtained by substituting the characteristic spectral values ​​into the fiber strength model.

8. The method for adjusting the curl of a hair curler according to claim 1, characterized in that, Methods for determining torsional parameters include: The negative ion output reference range and clamping force reference range are obtained by matching the preset hair quality parameter model according to the hair type. Preliminary negative ion parameters are determined based on hair quality information and the negative ion output baseline range; Determine the initial clamping force based on hair quality information and the baseline range of clamping force; Verify whether the initial negative ion parameters and initial clamping force are within the safe range of the preset equipment safe operating threshold; If the safe range is exceeded, the initial negative ion parameters and initial clamping force are adjusted proportionally based on the preset equipment safe operation threshold, initial negative ion parameters, and initial clamping force, and used as torsional parameters. If it is within the safe range, the final negative ion parameters and the final clamping force will be used as the torsion parameters of the hair straightener.

9. The method for adjusting the curl of a hair curler according to claim 1, characterized in that, Methods for determining curl include: The corresponding baseline curl range is determined based on the curling pattern and the preset curl baseline model; Based on the hair type and the preset hair characteristic correction coefficient table, determine the hair correction coefficient for the corresponding hair type; Extract the morphological parameters corresponding to the curling mode to determine the additional correction value for the mode; Based on the baseline curl range, hair quality correction coefficient, and pattern-added correction value, a preliminary curl value is obtained through weighted calculation. The initial curl value is checked to see if it is within a reasonable range based on the preset effective curl range. If the initial curl value is within a reasonable range, then the initial curl value is taken as the degree of curl. If the initial curl value is outside the range, the final curl degree is determined by proportional calculation based on the initial curl value and the preset effective curl range.

10. A curling iron curl adjustment system, characterized in that, include: The acquisition module is used to acquire capacitance values, raw spectral data, and curling modes; A memory for storing a program that implements any one of the curl adjustment methods for a hair curler according to claims 1 to 9; The processor loads and executes programs from memory.

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