A dynamic control method based on intelligent hair dryer

Abstract

The present application belongs to the technical field of hair dryer control, and in particular relates to a dynamic control method based on an intelligent hair dryer, which comprises: collecting temperature and wind speed gear timing data of different users using the hair dryer to construct a historical user library, calculating dehydration efficiency and energy consumption values of all gear combinations, and screening out optimal energy-saving gear combinations in each dehydration efficiency grade, updating to obtain an energy-saving user library, after a user turns on the hair dryer, recording the gear combination switching sequence and time nodes in real time, calculating the similarity of the current user and the historical user and the switching time node deviation value, identifying whether it is a historical user according to the similarity and the switching time node deviation value, and calling the optimal energy-saving gear combination adapted to the current user. The present application controls the gear combination from two aspects of user usage habits and energy-saving needs, can realize dynamic control of high energy efficiency without manual intervention, and has strong adaptability.

Description

Technical Field

[0001] This invention belongs to the technical field of hair dryer control, and more specifically, relates to a dynamic control method based on an intelligent hair dryer. Background Technology

[0002] Hair dryers are household appliances used for drying and styling hair in daily life. They typically use fixed speed and temperature settings, which users manually switch between. To improve the user experience and energy efficiency of hair dryers, dynamic control is needed.

[0003] Existing technologies, such as the intelligent hair dryer temperature and wind speed adaptive control method and system disclosed in Chinese invention patent application number 202511328342.0, relate to the field of intelligent control. This invention's method constructs a local feature map by collecting temperature, humidity, and wind speed data, establishes a dynamic evaporation thermodynamic model to calculate the regional evaporation rate and corresponding energy demand, and then generates a wind cavity control signal based on a competitive sensing wind energy mapping model to achieve spatial regional adaptive adjustment of wind temperature and wind speed. Simultaneously, a feedback difference mechanism is constructed to iteratively correct the dynamic evaporation thermodynamic model and energy demand, ultimately sensing changes in the physical state of hair drying in real time and achieving a dynamic balance by integrating user habits and comfort perception.

[0004] Based on the aforementioned existing technology, it is known that the current hair dryer control method collects the temperature and humidity of different areas of the user's hair and the wind speed of the hair dryer, calculates the evaporation rate and corresponding energy requirements of each area, and then generates a wind chamber control signal to control the adjustment of the hair dryer's wind speed and temperature. However, it does not take into account the user's actual usage habits, nor does it consider the energy loss of the hair dryer at different wind temperatures and wind speeds. It also has the following problems: 1. Currently, the evaporation rate is calculated only by measuring the temperature and humidity of different areas of the user's hair and the wind speed of the hair dryer, and then the wind temperature and wind speed of the hair dryer are adjusted in real time. This ignores the user's actual usage habits, resulting in the hair dryer's self-adjusted wind temperature and wind speed failing to meet the user's usage needs.

[0005] 2. Currently, the blower temperature and speed are adjusted only based on the evaporation rate, without taking into account the energy loss after adjustment, which may result in significant energy loss during the entire adjustment process. Summary of the Invention

[0006] In view of this, in order to solve the above problems, a dynamic control method based on a smart hair dryer is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: This invention provides a dynamic control method based on a smart hair dryer. The method includes: collecting time-series data of temperature and wind speed settings of hair dryers used by different users, constructing a historical user database, extracting all temperature and wind speed settings from the database, and calculating the dehydration efficiency and energy consumption of each settings combination.

[0008] The efficiency levels of each gear combination are divided according to the dehydration efficiency. Gear combinations belonging to the same efficiency level are merged to obtain the complete gear combination corresponding to each efficiency level. Based on the energy consumption value, the optimal energy-saving gear combination is determined from the complete gear combinations corresponding to each efficiency level and updated to the historical user database to form an energy-saving user database.

[0009] After a user turns on the hair dryer, the sequence and time points of their switching gear combinations are recorded in real time. The similarity between this sequence and the sequences of each historical user are calculated, and the deviation between the current user and each historical user at the switching time points is calculated.

[0010] The similarity and deviation values ​​are used to determine whether the current user is a user in the historical user database.

[0011] If so, the optimal energy-saving gear combination corresponding to that user will be retrieved directly from the energy-saving user database.

[0012] If not, the dehydration efficiency of the current gear combination is calculated in real time, its efficiency level is determined, and the optimal energy-saving gear combination of that level is called from the energy-saving user database.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention constructs a historical user database by collecting time-series data of user temperature and wind speed settings, and then analyzes the optimal energy-saving gear combination with the minimum energy consumption value in each dehydration efficiency level from the two aspects of dehydration efficiency and energy consumption value. The historical user database is then updated to obtain an energy-saving user database, ensuring that each optimal energy-saving gear combination can meet the dehydration efficiency requirements of the corresponding scenario while conforming to the actual use scenario of the user.

[0014] (2) This invention identifies historical users by using the user's gear switching sequence, number of switching and time nodes, i.e. actual usage habits, through similarity and deviation values, and directly matches the corresponding optimal energy-saving gear combination to the historical user, so that the optimal energy-saving gear combination matched by the hair dryer fits the user's actual usage habits, achieving the purpose of adaptation without manual intervention, and reducing energy loss.

[0015] (3) For users who cannot be matched in the historical user database, the present invention calculates the dehydration efficiency of the current gear combination and calls the optimal energy-saving gear combination from the energy-saving user database to improve the practicality and adaptability of the hair dryer. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the overall implementation process of the present invention.

[0018] Figure 2 This is a schematic diagram illustrating the process of obtaining the complete gear combination of the present invention.

[0019] Figure 3 This is a schematic diagram illustrating the similarity calculation process of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] For details, please refer to [link / reference]. Figure 1 As shown, the present invention provides a dynamic control method based on a smart hair dryer. The method includes: S1, collecting time-series data of temperature and wind speed settings of hair dryers used by different users, constructing a historical user database, extracting all temperature and wind speed settings from the database, and calculating the dehydration efficiency and energy consumption value of each settings combination.

[0022] Specifically, the calculation process for the dehydration efficiency includes: before the hair dryer is started, a patch-type humidity sensor located on the outside of the hair dryer outlet contacts the hair to obtain the initial moisture content of the hair, and the average of multiple initial moisture content measurements is used as the initial moisture content. During gear switching or when the hair dryer stops operating, the real-time moisture content of the hair is collected several times according to the initial moisture content method, and the average of multiple real-time moisture content measurements is used as the moisture content for that gear switching mode. Here, "several times" refers to three or more measurements.

[0023] Extract the start time of each gear combination and the stop time or gear shift time of the corresponding gear combination, and calculate the running time of the corresponding gear combination.

[0024] Calculate the difference between the initial moisture content and the moisture content at the gear switching point to obtain the moisture content change value for each gear combination. The ratio of the moisture content change value to the running time of the corresponding gear combination is used as the dehydration efficiency.

[0025] Specifically, the calculation process of the energy consumption value includes: extracting the rated power of the airflow at each speed setting and the rated power of the temperature at each temperature setting of the hair dryer.

[0026] The rated power for wind speed and rated power for temperature can both be obtained from the datasheet of the hair dryer manufacturer. The rated power for wind speed is the independent rated input power of the fan motor at each wind speed setting, and the rated power for temperature is the independent rated input power of the heating element at each temperature setting.

[0027] A hair dryer mainly consists of a fan and a heating element. During use, the primary operating mode is that the fan blows air while the heating element heats the air; in this mode, both the fan and heating element consume electrical energy. A special operating mode occurs when the fan blows air and the heating element stops working, meaning only the fan consumes electrical energy. Since the fan and heating element are connected in parallel and powered independently, the formula for the total rated power of a parallel circuit is: In the formula, This refers to the total rated power of all gear combinations. This refers to the independent rated input power of the fan motor at each wind speed setting. The independent rated input power of the heating element at each temperature setting.

[0028] The sum of the rated power for wind speed and rated power for temperature is calculated based on each gear combination, and this sum is taken as the total rated power for the corresponding gear combination.

[0029] The product of the total rated power of each power setting combination and the running time of the corresponding power setting combination is calculated, and the power factor of the hair dryer is extracted to correct the product, thus obtaining the energy consumption value. The energy consumption value is calculated based on existing electrical power calculation formulas. The total rated power of each power setting combination of the hair dryer is the apparent power. The product of the total rated power of each power setting combination and the running time of the corresponding power setting combination only yields the rated electrical power without considering actual losses. To obtain the actual power consumption, the power factor of the hair dryer (i.e., the ratio of the hair dryer's electrical power to its apparent power; electrical power is the actual power consumed by the hair dryer, and apparent power is the hair dryer's rated power) needs to be used for correction, so that the calculation result closely reflects the actual energy consumption of the hair dryer.

[0030] The formula for calculating the above energy consumption value is: In the formula, These are the energy consumption values ​​for each gear combination. The running time for each gear combination, The power factor of a hair dryer is the factor that determines its energy consumption. The higher the total rated power and the longer the operating time, the higher the power factor and the greater the energy consumption.

[0031] The above correction refers to multiplying the power factor of the hair dryer by the product.

[0032] The power factor of the aforementioned hair dryer can be obtained from the datasheet of the hair dryer manufacturer.

[0033] Considering that the ultimate goal of all hair dryer settings is to reduce the moisture content of the hair, and that different settings reduce the moisture content of the hair at different rates, i.e., different dehydration efficiencies, this is the basis for this consideration.

[0034] S2. Divide the gear combinations into efficiency levels according to the dehydration efficiency, merge gear combinations belonging to the same efficiency level to obtain the complete gear combinations corresponding to each efficiency level, determine the optimal energy-saving gear combination from the complete gear combinations corresponding to each efficiency level based on the energy consumption value, and update it to the historical user database to form an energy-saving user database.

[0035] Specifically, please refer to Figure 2 As shown, the process of obtaining the complete gear combination includes: classifying the efficiency level according to the dehydration efficiency of each gear combination, into a high dehydration efficiency level range, a medium dehydration efficiency level range, and a low dehydration efficiency level range.

[0036] If the dehydration efficiency of a certain gear combination is greater than or equal to the first efficiency threshold, then the dehydration efficiency of that gear combination is in the high dehydration efficiency range.

[0037] If the dehydration efficiency of a certain gear combination is less than the first efficiency threshold but greater than or equal to the second efficiency threshold, then the dehydration efficiency of that gear combination is in the medium dehydration efficiency range.

[0038] If the dehydration efficiency of a certain gear combination is less than the second efficiency threshold, then the dehydration efficiency of that gear combination is in the low dehydration efficiency range.

[0039] It should be added that the process of obtaining the first efficiency threshold and the second efficiency threshold is as follows: First, extract the dehydration efficiency of each gear combination under the same rated voltage from the historical user database, sort the dehydration efficiency in ascending order, construct a dehydration efficiency sequence, and calculate the quartile of the dehydration efficiency sequence. The third quartile of the dehydration efficiency sequence is used as the first efficiency threshold, and the quarter quartile of the dehydration efficiency sequence is used as the second efficiency threshold.

[0040] By eliminating redundant and duplicate gear combinations within the same dehydration efficiency level range, complete gear combinations corresponding to the high, medium, and low dehydration efficiency level ranges are obtained respectively.

[0041] Specifically, the analysis process of the optimal energy-saving gear combination includes: selecting the gear combination with the lowest energy consumption value from all gear combinations corresponding to the same dehydration efficiency level range as the optimal energy-saving gear combination for that dehydration efficiency level range.

[0042] S3. After the user turns on the hair dryer, record the sequence and time of the switching gear combination in real time, calculate the similarity between the sequence and the sequences of each historical user, and calculate the deviation value between the current user and each historical user at the switching time point.

[0043] Specifically, please refer to Figure 3 As shown, the similarity calculation process includes: recording the gear combinations of each user in the historical user database as historical user gear combinations, extracting the temperature gear value and wind speed gear value of a single gear combination as gear features, and constructing a feature vector.

[0044] It should be added that the above feature vectors are two-dimensional feature vectors, denoted as . ,in, This refers to the temperature setting value for a single gear combination. For example, the wind speed setting value for a single gear combination is 1 for low temperature, 2 for medium temperature, 3 for high temperature, 1 for low wind speed, 2 for medium wind speed, and 3 for high wind speed.

[0045] If both the current user and the historical user have a single gear combination, then extract the feature vector of the current user's gear combination and the feature vector of the historical user's gear combination, respectively, and denote them as the current feature vector and the historical feature vector.

[0046] Calculate the temperature gradient and wind speed gradient of the current feature vector and each historical feature vector respectively, and calculate the gradient magnitude of both as the gradient magnitude of the gear combination of the current user and the historical users.

[0047] It should be noted that the formula for calculating the above temperature gradient amplitude is: In the formula, This represents the amplitude of the temperature gradient. This represents the temperature setting value of the current feature vector. The temperature level value is the historical feature vector.

[0048] The formula for calculating the magnitude of the wind speed gradient is as follows: In the formula, This represents the wind speed gradient magnitude. This represents the wind speed setting value of the current feature vector. The wind speed level is the historical feature vector.

[0049] Furthermore, the formula for calculating the gradient magnitude is as follows: In the formula, This represents the gradient magnitude.

[0050] If the current user or a historical user has multiple gear combinations, then the gear combinations of the current user and historical users are matched pairwise to obtain a matching combination.

[0051] Similarly, the gradient magnitude of the matching combination is obtained by calculating the gradient magnitude of the gear combination of the current user and the historical user. The average gradient magnitude of all matching combinations is then calculated as the comprehensive gradient magnitude of the gear combination of the current user and the historical user.

[0052] The gradient magnitude or the combined gradient magnitude is subjected to minimum-maximum linear normalization to obtain the normalized value. The difference between 1 and this value is used as the similarity.

[0053] It should be added that the maximum and minimum values ​​of the gradient magnitude or the combined gradient magnitude are selected from all gradient magnitudes or all combined gradient magnitudes, and are used as the maximum and minimum values ​​required for the normalization, respectively. The minimum-maximum linear normalization process is an existing technology and will not be described in detail in this invention.

[0054] For example, the hair dryer temperature settings are set as follows: low temperature setting is 1, medium temperature setting is 2, high temperature setting is 3; low fan speed setting is 1, medium fan speed setting is 2, and high fan speed setting is 3.2. For a single setting combination scenario, the current user feature vector is set as follows. The feature vector of a certain historical user is Preset maximum gradient magnitude The temperature gradient is 3. =1, wind speed gradient The gradient magnitude is 1. The value is 1.4. After min-max normalization, the value is 0.4, and the similarity is 0.6.

[0055] For multi-gear combination scenarios, assuming the current user has 2 gear combinations, the feature vector is... and Historical users have 2 gear combinations, and the feature vector is: and After pairwise matching, four matching combinations are obtained: and , and , and , and The gradient magnitudes for each group were calculated as 1.4, 1, 2.8 and 1 respectively. The average gradient magnitude was calculated as 1.6, which was used as the comprehensive gradient magnitude. After min-max normalization, the value was 0.5, and the similarity was 0.5.

[0056] Specifically, the calculation process of the deviation value includes: counting the number of times the user switches gear combinations during use, and the number of switching time points is the number of gear switching times. It should be noted that the initial gear setting and the power off action of the hair dryer are not included in the number of gear combination switching times.

[0057] Calculate the absolute value of the difference between the current user's switching count and the switching count of a historical user in the historical user database.

[0058] Select the minimum value from the number of times the current user switches to a certain historical user in the historical user database, and denote it as k. Extract the first k time nodes from the switching time nodes between the current user and the historical user, and calculate the mean of the absolute value of the time difference of the corresponding time nodes. If k is 0, the mean of the absolute value of the time difference is directly assigned to 0.

[0059] The mean of the absolute values ​​of the handover number differences and the absolute values ​​of the time differences are respectively subjected to minimum-maximum linear normalization, and the normalized results are weighted and summed to obtain the deviation value.

[0060] It should be added that the selection method for the maximum and minimum values ​​required to normalize the absolute value of the difference in the number of switching times and the mean value of the time difference is the same as the selection method for the maximum and minimum values ​​required to normalize the gradient magnitude or the comprehensive gradient magnitude.

[0061] It should be noted that in the actual use of a hair dryer, the number of times the power level combination is switched reflects the user's usage habits and directly indicates the overall difference in the user's power level switching behavior. Therefore, it is given a higher weight. The switching time point reflects the instantaneous operation in terms of timing, so its weight is less than the number of times the power level combination is switched. Moreover, the weight of the absolute value of the difference in the number of switching times and the weight of the average time difference are combined to 1. For example, the weights of the absolute value of the difference in the number of switching times and the average time difference after normalization are 0.6 and 0.4, respectively.

[0062] The formula for calculating the deviation value is: In the formula, This is the deviation value. The absolute value of the difference in the number of switching times. To select the maximum value from the absolute values ​​of all handover differences, ensure that the normalized range of the absolute values ​​of handover differences is [0,1]. The mean of the absolute values ​​of the time differences. To select the maximum value from the mean of all time difference absolute values, and to ensure that the normalized range of the mean of the time difference absolute values ​​is [0,1], the larger the absolute value of the switching number difference and the larger the mean of the time difference absolute values, the larger the deviation value.

[0063] S4. Determine whether the current user is a user in the historical user database based on the similarity and deviation values.

[0064] Specifically, the judgment process includes: weighted summing of the complement of the deviation value of each user in the historical user database and the similarity to obtain a comprehensive matching index. The complement of the deviation value is the difference between 1 and the deviation value.

[0065] Similarity represents a user's habit of choosing the combination of windshield settings when blowing hair, which is a static feature. Deviation value represents a user's behavior of switching windshield settings when blowing hair, which is a dynamic feature. Both reflect the overall characteristics of a user's hair blowing behavior from the static and dynamic dimensions, respectively. They are equally important, and the weight of similarity and the weight of deviation value are combined to 1. For example, the weight of both similarity and deviation value is 0.5.

[0066] The average comprehensive matching index is calculated, and users whose comprehensive matching index is greater than or equal to the average comprehensive matching index are recorded as candidate users. If a candidate user exists, the user is determined to be a user in the historical user database.

[0067] If no candidate user exists, then the user is determined not to be a user in the historical user database.

[0068] Similarity reflects the similarity of the gear combination itself, representing the user's preference for temperature and wind speed settings. Deviation value quantifies the differences in switching behavior, representing the timing and frequency characteristics of the user's operation during the hair drying process. By jointly determining whether a user is in the historical user database from both similarity and deviation value, it can distinguish between two easily confused categories of users: those with similar gear combinations but different switching behaviors and those with similar switching behaviors but different gear selections. This avoids misjudgment and omission, thus more comprehensively and accurately determining whether the current user is in the historical user database, improving the accuracy and reliability of the determination results.

[0069] S5. If so, the optimal energy-saving gear combination corresponding to the user will be directly retrieved from the energy-saving user database.

[0070] Specifically, if candidate users exist, when there are multiple candidate users, the optimal energy-saving level combination of the candidate user with the highest comprehensive matching index in the energy-saving user database is directly retrieved: If the largest comprehensive matching index corresponds to multiple candidate users, then the optimal energy-saving gear combination in the energy-saving user database is directly retrieved from the candidate user with the smaller deviation value.

[0071] S6. If not, calculate the dehydration efficiency of the current gear combination in real time, determine its efficiency level, and call the optimal energy-saving gear combination of that level in the energy-saving user database.

[0072] Specifically, the calculation process of the dehydration efficiency corresponding to the current gear combination includes: if the current gear combination can be extracted from the complete gear combination, then the optimal energy-saving gear combination of the efficiency level corresponding to the gear combination is directly extracted.

[0073] If the current gear combination cannot be extracted from the complete gear combination, the energy consumption value of the current gear combination is calculated.

[0074] Based on the actual temperature value corresponding to the temperature setting and the actual wind speed value corresponding to the wind speed setting, if the temperature difference between the two settings is less than or equal to a preset temperature difference threshold, it is recorded as a temperature-similar combination. The preset temperature difference threshold can be set according to the temperature difference value corresponding to each temperature setting of the hair dryer. For example, the preset temperature difference threshold is 10 degrees Celsius. When the temperature difference between the two settings is less than or equal to 10 degrees Celsius, it is recorded as a temperature-similar combination. The implementer can also define it himself.

[0075] If the wind speed difference between two speed settings is less than or equal to a preset wind speed threshold, it is recorded as a wind speed similar combination. The preset wind speed threshold can be set according to the wind speed difference corresponding to each speed setting of the hair dryer. For example, the preset wind speed threshold is 4 meters per second. When the wind speed difference between two speed settings is less than or equal to 4 meters per second, it is recorded as a wind speed similar combination. The implementer can also define it himself.

[0076] Extract gear combinations from complete gear combinations that have the same wind speed and similar temperature, or the same temperature and similar wind speed, and denot them as similar gear combinations.

[0077] Calculate the ratio of the energy consumption of the current gear combination to the average energy consumption of similar gear combinations to obtain the correction coefficient.

[0078] The system collects the real-time moisture content of the user's hair at the current setting and the moisture content of the previous setting or the initial setting, and records it as the baseline moisture content. The relative deviation between the baseline moisture content and the real-time moisture content is used as the dehydration ratio corresponding to the running time of the current setting.

[0079] The dehydration efficiency corresponding to similar gear combinations is retrieved and its average value is calculated. Combined with the correction coefficient and the dehydration ratio, the dehydration efficiency of the current gear combination is calculated, and the optimal energy-saving gear combination corresponding to the efficiency level of this gear combination is extracted.

[0080] The formula for calculating the dehydration efficiency of the current gear combination is: In the formula, This represents the dehydration efficiency of the current gear combination. This represents the dehydration ratio corresponding to the duration of operation of the current gear combination. For correction factor, This represents the average dehydration efficiency corresponding to similar gear combinations. The equivalent dehydration efficiency is obtained by adjusting the average dehydration efficiency of similar combinations. The larger the dehydration ratio, the larger the correction coefficient, and the larger the average dehydration efficiency, the greater the dehydration efficiency of the current gear combination.

[0081] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A dynamic control method based on a smart hair dryer, characterized in that, The method includes: Collect time-series data on the temperature and wind speed settings of hair dryers used by different users, build a historical user database, extract all temperature and wind speed settings, and calculate the dehydration efficiency and energy consumption of each settings combination. Based on the dehydration efficiency, the gear combinations are divided into efficiency levels. Gear combinations belonging to the same efficiency level are merged to obtain the complete gear combinations corresponding to each efficiency level. Based on the energy consumption value, the optimal energy-saving gear combination is determined from the complete gear combinations corresponding to each efficiency level and updated to the historical user database to form an energy-saving user database. After a user turns on the hair dryer, the sequence and time points of their switching gear combinations are recorded in real time. The similarity between this sequence and the sequences of each historical user are calculated, and the deviation between the current user and each historical user at the switching time points is calculated. Based on the similarity and deviation values, determine whether the current user is a user in the historical user database; If so, the optimal energy-saving gear combination corresponding to that user will be retrieved directly from the energy-saving user database; If not, the dehydration efficiency of the current gear combination is calculated in real time, its efficiency level is determined, and the optimal energy-saving gear combination of that level is called from the energy-saving user database.

2. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The calculation process for the dehydration efficiency includes: Before the hair dryer is turned on, a patch-type humidity sensor located on the outside of the hair dryer's air outlet comes into contact with the hair to obtain the initial moisture content of the hair. The average of the initial moisture content collected multiple times is used as the initial moisture content. When the speed combination is switched or stopped, the real-time moisture content of the hair is collected several times in the same way as the initial moisture content. The average of the real-time moisture content collected multiple times is used as the moisture content when the speed combination is switched. Extract the start time of each gear combination and the stop time or gear shift time of the corresponding gear combination, and calculate the running time of the corresponding gear combination; Calculate the difference between the initial moisture content and the moisture content at the gear switching point to obtain the moisture content change value for each gear combination. The ratio of the moisture content change value to the running time of the corresponding gear combination is used as the dehydration efficiency.

3. The dynamic control method based on a smart hair dryer as described in claim 2, characterized in that: The calculation process for the energy consumption value includes: Extract the rated power of the airflow at each speed setting and the rated power of the temperature at each temperature setting of the hair dryer; The sum of the rated power for wind speed and rated power for temperature is calculated based on each gear combination, and this sum is taken as the total rated power for the corresponding gear combination. Calculate the product of the total rated power of each gear combination and the running time of the corresponding gear combination, and extract the power factor of the hair dryer to correct the product to obtain the energy consumption value.

4. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The process of obtaining the complete gear combination includes: Based on the dehydration efficiency of each gear combination, the efficiency levels are divided into high dehydration efficiency level range, medium dehydration efficiency level range, and low dehydration efficiency level range. If the dehydration efficiency of a certain gear combination is greater than or equal to the first efficiency threshold, then the dehydration efficiency of that gear combination is in the high dehydration efficiency range. If the dehydration efficiency of a certain gear combination is less than the first efficiency threshold and greater than or equal to the second efficiency threshold, then the dehydration efficiency of that gear combination is in the medium dehydration efficiency range. If the dehydration efficiency of a certain gear combination is less than the second efficiency threshold, then the dehydration efficiency of that gear combination is in the low dehydration efficiency range. By eliminating redundant and duplicate gear combinations within the same dehydration efficiency level range, complete gear combinations corresponding to the high, medium, and low dehydration efficiency level ranges are obtained respectively.

5. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The analysis process for the optimal energy-saving gear combination includes: The combination with the lowest energy consumption value is selected from all combinations of gears corresponding to the same dehydration efficiency level range as the optimal energy-saving combination for that dehydration efficiency level range.

6. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The similarity calculation process includes: Record the gear combinations of each user in the historical user database as historical user gear combinations, extract the temperature gear value and wind speed gear value of a single gear combination as gear features, and construct a feature vector; If both the current user and the historical user have a single gear combination, then extract the feature vector of the current user's gear combination and the feature vector of the historical user's gear combination, and denote them as the current feature vector and the historical feature vector, respectively. Calculate the temperature gradient and wind speed gradient of the current feature vector and each historical feature vector respectively, and calculate the gradient magnitude of both as the gradient magnitude of the gear combination of the current user and the historical users. If the current user or a historical user has multiple gear combinations, then the gear combinations of the current user and historical users are matched pairwise to obtain a matching combination; Similarly, the gradient magnitude of the matching combination is obtained by calculating the gradient magnitude of the gear combination of the current user and the historical user, and the average gradient magnitude of all matching combinations is calculated as the comprehensive gradient magnitude of the gear combination of the current user and the historical user. The gradient magnitude or the combined gradient magnitude is subjected to minimum-maximum linear normalization to obtain the normalized value. The difference between 1 and this value is used as the similarity.

7. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The calculation process for the deviation value includes: The number of times a user switches gear combinations during use is counted, and the number of switching time points is the gear switching count. Calculate the absolute value of the difference between the current user's switching count and the switching count of a historical user in the historical user database; Filter out the minimum value from the number of switching between the current user and a certain historical user in the historical user database, and denote it as k. Extract the first k time nodes from the switching time nodes between the current user and the historical user, and calculate the mean of the absolute value of the time difference of the corresponding time nodes. The mean of the absolute values ​​of the handover number differences and the absolute values ​​of the time differences are respectively subjected to minimum-maximum linear normalization, and the normalized results are weighted and summed to obtain the deviation value.

8. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The judgment process includes: The comprehensive matching index is obtained by weighted summing of the complement of the deviation value of each user in the historical user database and the similarity. The average comprehensive matching index is calculated, and users whose comprehensive matching index is greater than or equal to the average comprehensive matching index are recorded as candidate users. If there are candidate users, the user is determined to be a user in the historical user database. If no candidate user exists, then the user is determined not to be a user in the historical user database.

9. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: If candidate users exist, and there are multiple candidate users, the optimal energy-saving level combination of the candidate user with the highest comprehensive matching index in the energy-saving user database is directly retrieved. If the largest comprehensive matching index corresponds to multiple candidate users, then the optimal energy-saving gear combination in the energy-saving user database is directly retrieved from the candidate user with the smaller deviation value.

10. The dynamic control method based on a smart hair dryer as described in claim 1, characterized in that: The calculation process for the dehydration efficiency corresponding to the current gear combination includes: If the current gear combination can be extracted from the complete gear combination, then the optimal energy-saving gear combination corresponding to the efficiency level of the current gear combination is directly extracted. If the current gear combination cannot be extracted from the complete gear combination, the energy consumption value of the current gear combination is calculated. Based on the actual temperature value corresponding to the temperature setting and the actual wind speed value corresponding to the wind speed setting, if the temperature difference between the two settings is less than or equal to the preset temperature difference threshold, it is recorded as a temperature similar combination. If the wind speed difference between the two gear combinations is less than or equal to the preset wind speed threshold, it is recorded as a wind speed similar combination. Extract gear combinations with the same wind speed and similar temperature, or the same temperature and similar wind speed, from the complete gear combination and record them as similar gear combinations. Calculate the ratio of the energy consumption value of the current gear combination to the average energy consumption value of similar gear combinations to obtain the correction coefficient; Collect the real-time moisture content of the user's hair in the current gear combination and the moisture content of the previous gear combination or the initial moisture content, and record it as the baseline moisture content. The difference between the baseline moisture content and the real-time moisture content is used as the dehydration ratio corresponding to the running time of the current gear combination. The dehydration efficiency corresponding to similar gear combinations is retrieved and its average value is calculated. Combined with the correction coefficient and the dehydration ratio, the dehydration efficiency of the current gear combination is calculated, and the optimal energy-saving gear combination corresponding to the efficiency level of the gear combination is extracted. The formula for calculating the dehydration efficiency of the current gear combination is: In the formula, This represents the dehydration efficiency of the current gear combination. This represents the dehydration ratio corresponding to the duration of operation of the current gear combination. For correction factor, This represents the average dehydration efficiency corresponding to similar gear combinations. This is the equivalent dehydration efficiency obtained by adjusting the average dehydration efficiency of similar combinations for the progress.

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