Clothes material intelligent identification method and system and clothes dryer

Abstract

The invention discloses a clothes material intelligent identification method and system and a clothes dryer, and relates to the technical field of smart home. The method comprises the following steps: acquiring an initial image and an initial weight of to-be-dried clothes before cleaning, and a drying video image and a time-varying weight curve of the to-be-dried clothes for a preset drying time at a preset temperature; determining a first material type of the to-be-dried clothes according to the initial image and the drying video image; according to the initial weight and the weight curve, determining a second material type of the to-be-dried clothes and a mass ratio of the to-be-dried clothes corresponding to each material in the second material type; when the first material category is consistent with the second material category, obtaining a material identification result; and when the first material category is inconsistent with the second material category and the mass ratio of the different material categories is smaller than a preset ratio threshold, taking the first material category as a material identification result. According to the invention, the clothing material identification accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a method and system for intelligently identifying clothing materials, and a clothes dryer. Background Art

[0002] With the continuous development of the smart home industry, the dryer industry has gradually made more and more innovations in the direction of intelligence, such as WIFI control, material judgment, and stop-when-dry functions. Whether the above functions can be realized or how well they are realized depends to a large extent on the effectiveness of the clothing material detection function. Therefore, clothing material recognition has become an important technology that various brands have been competing for in recent years.

[0003] Currently, when drying clothes placed in the inner drum, the dryer does not distinguish the types of clothes, but dries all the clothes to a specific temperature and for a preset time. However, it is known that the appropriate drying temperature and the required drying time for different types of clothes often vary.

[0004] Therefore, existing clothes dryers easily cause poor drying effects on some types of clothes. Summary of the invention

[0005] The object of the present invention is to provide a method, system and clothes dryer for intelligently identifying clothing materials, which can improve the accuracy of clothing material identification.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for intelligently identifying clothing materials, the method comprising:

[0008] Acquire an initial image and initial weight of the clothes to be dried before washing, as well as a drying video image of the clothes dried at a preset temperature for a preset time and a weight curve varying with time;

[0009] Determining a first material category of the clothes to be dried according to the initial image and the drying video image;

[0010] determining, according to the initial weight and the weight curve, a second material category of the clothes to be dried and a mass proportion of the clothes to be dried corresponding to each material in the second material category;

[0011] Determining whether the first material category and the second material category are consistent;

[0012] When the first material category and the second material category are consistent, the first material category or the second material category is used as the material identification result of the clothes to be dried;

[0013] When the first material category and the second material category are inconsistent, determining a different material category, and judging whether a mass proportion of the different material category is greater than or equal to a preset proportion threshold;

[0014] When the mass proportion of the different material categories is greater than or equal to a preset proportion threshold, reacquiring the first material category and the second material category;

[0015] When the mass proportion of the different material categories is less than the preset proportion threshold, the first material category is used as the material identification result of the clothes to be dried.

[0016] Optionally, determining the first material category of the clothes to be dried according to the initial image and the drying video image specifically includes:

[0017] Segmenting the drying video image to determine the segmented image corresponding to each time point; wherein the time intervals between adjacent time points are consistent;

[0018] Segmenting the images of the clothes to be dried that are larger than a preset area threshold in each of the segmented images to obtain a plurality of single clothes images corresponding to each of the time points;

[0019] Matching each of the single clothing images with the initial image;

[0020] grayscale the single clothing images and the matched initial image to obtain grayscale images of the single clothing and the corresponding initial grayscale images arranged over time;

[0021] Calculating the difference between the grayscale values ​​of each of the single clothing grayscale images arranged over time and the corresponding initial grayscale image to obtain the grayscale value change rate of each of the single clothing;

[0022] The grayscale value change rate of each of the single clothes is compared with the grayscale value change rates of clothes of multiple materials under the same drying conditions to determine the first material category of the clothes to be dried.

[0023] Optionally, matching each of the single clothing images with the initial image specifically includes:

[0024] According to each of the single clothing images, a template matching algorithm is applied to determine a corresponding initial image.

[0025] Optionally, determining the second material category of the clothes to be dried and the mass proportion of the clothes to be dried corresponding to each material in the second material category specifically includes:

[0026] Determining the weight of the laundry to be dried corresponding to each time point according to the weight curve;

[0027] determining a change in the weight of the laundry to be dried according to the weight of the laundry to be dried corresponding to each of the time points and the initial weight;

[0028] Determining the second material category of the clothes to be dried and the mass of the clothes to be dried corresponding to each material in the second material category according to the weight change of the clothes to be dried and the water absorption rates of clothes of multiple materials under the same drying conditions;

[0029] According to the mass of the clothes to be dried corresponding to each material in the second material category and the initial weight of the clothes to be dried before washing, the mass proportion of each material category is calculated.

[0030] Optionally, the formula for calculating the mass proportion of each material category is:

[0031]

[0032] Among them, c i is the mass proportion of the i-th material category; m i is the mass of the clothes to be dried of the i-th material category before washing; m 0 It is the initial weight of the clothes to be dried before washing.

[0033] Optionally, a calculation formula for the mass of the clothes to be dried corresponding to each material in the second material category is:

[0034]

[0035] Among them, m i is the weight of the clothes to be dried of the i-th material category; k i0 M is the water absorption rate of the clothes to be dried of the i-th material category before drying begins; 0 k is the change between the weight of the clothes to be dried before drying and the weight of the clothes to be dried before washing; i1 is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the first time point; M 1 k is the change between the weight of the laundry to be dried corresponding to the first time point and the weight of the laundry to be dried before washing; i(n-1) is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the n-1-th time point; M n-1 It is the change between the weight of the laundry to be dried corresponding to the n-1th time point and the weight of the laundry to be dried before washing.

[0036] Optionally, the method for obtaining the water absorption rates of clothes made of multiple materials under the same drying conditions specifically includes:

[0037] Obtaining water absorption rates of various material categories of clothes to be dried in each group of multiple groups of clothes to be dried consisting of various material categories at different drying times at preset temperatures;

[0038] According to the water absorption rate of the clothes to be dried of various material categories in each group, the average water absorption rate of the clothes to be dried of various material categories is calculated;

[0039] According to the average water absorption rate, construct a clothing water absorption rate table; the clothing water absorption rate table includes the water absorption rates of clothing of various material categories at various temperatures and various drying times;

[0040] According to the clothing water absorption rate table, the water absorption rates of clothing made of multiple materials under the same drying conditions are obtained.

[0041] A clothing material intelligent identification system, using the above clothing material intelligent identification method, the system comprises:

[0042] An acquisition module, used to acquire an initial image and initial weight of the clothes to be dried before washing, as well as a drying video image of the clothes dried at a preset temperature for a preset time and a weight curve varying with time;

[0043] A first material category determination module, configured to determine a first material category of the clothes to be dried according to the initial image and the drying video image;

[0044] a second material category determination module, configured to determine, according to the initial weight and the weight curve, a second material category of the laundry to be dried and a mass proportion of the laundry to be dried corresponding to each material in the second material category;

[0045] A first judgment module is used to judge whether the first material category and the second material category are consistent; when the first material category and the second material category are consistent, the first material category or the second material category is used as the material recognition result of the clothes to be dried;

[0046] The second judgment module is used to determine the difference material category when the first material category and the second material category are inconsistent, and judge whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold; when the mass proportion of the difference material category is greater than or equal to the preset proportion threshold, re-acquire the first material category and the second material category; when the mass proportion of the difference material category is less than the preset proportion threshold, use the first material category as the material identification result of the clothes to be dried.

[0047] A clothes dryer, applying the above-mentioned intelligent clothing material identification method to identify the material of the clothes to be dried, and obtaining the material identification result and the mass proportion of the clothes to be dried corresponding to each material;

[0048] Determine drying parameters according to the material identification result and the mass ratio, and execute a corresponding drying program according to the drying parameters.

[0049] Optionally, determining drying parameters according to the material identification result and the mass ratio specifically includes:

[0050] According to the drying parameters of each material that is greater than or equal to a preset mass ratio threshold, the drying parameters of the clothes to be dried are determined; the drying parameters include drying time and drying temperature; the clothes to be dried include clothes suitable for drying, clothes not suitable for drying, and clothes suitable for drying to a preset state.

[0051] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0052] The present invention discloses a method, system and clothes dryer for intelligently identifying clothing materials. The method comprises the following steps: obtaining an initial image and initial weight of the clothing to be dried before washing, a drying video image of the clothing dried at a preset temperature for a preset time and a weight curve varying with time; determining a first material category of the clothing to be dried according to the initial image and the drying video image, and determining a second material category of the clothing to be dried and a mass proportion of the clothing to be dried corresponding to each material in the second material category according to the initial weight and the weight curve; further, comparing the consistency of the first material category and the second material category, when the first material category and the second material category are consistent, the first material category or the second material category is used as the material identification result of the clothing to be dried; when the first material category and the second material category are inconsistent, it indicates that at least one of the first material category or the second material category has a large error, determining a difference material category, and judging whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold; when the mass proportion of the difference material category is greater than or equal to the preset proportion threshold, re-obtaining the first material category and the second material category; and when the mass proportion of the difference material category is less than the preset proportion threshold, using the first material category as the material identification result of the clothing to be dried. The present invention applies two different material identification methods to perform mutual verification, and when the conclusions obtained by the two different material identification methods are consistent, the accuracy of clothing material identification is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 This is a schematic flow chart of the method for intelligently identifying clothing materials provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The purpose of the present invention is to provide a method, system and dryer for intelligently identifying clothing materials, aiming to improve the accuracy of clothing material identification.

[0057] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] Example 1

[0059] like Figure 1 As shown, the clothing material intelligent identification method in this embodiment includes:

[0060] Step S1: obtaining an initial image and initial weight of the laundry to be dried before washing, as well as a drying video image of the laundry dried at a preset temperature for a preset time and a weight curve varying with time.

[0061] In practical applications, image information is obtained before the laundry to be dried is washed, and the image information and weight of each piece of laundry to be dried are obtained, or the image information of each piece of laundry to be dried and the total weight of all the dried laundry are obtained.

[0062] When drying the clothes to be dried, first set the unit step drying mode, which refers to drying at a preset temperature for a unit time. The preset time includes multiple unit times, where the unit time can be set to seconds. The preset temperature is selected as a safety temperature, that is, the preset temperature is safe for most clothes and will not cause damage to the clothes. The manual of the dryer using this method sets the safety temperatures for clothes of various materials to facilitate user setting. When the user does not set the safety temperature, the dryer using this method automatically sets the safety temperature based on experience.

[0063] The length of the preset time is set based on experience, or based on experience, the product of the preset time length and the preset temperature is made to be within a preset range.

[0064] When performing unit step drying, a video image of the clothes to be dried is obtained in real time, and the total weight of the clothes to be dried is measured in real time. According to the total weight of the clothes to be dried obtained in real time, a relationship curve between the total weight of the clothes to be dried and time is established.

[0065] Step S2: determining a first material category of the clothes to be dried according to the initial image and the drying video image.

[0066] S2 specifically includes:

[0067] Step S21: segment the drying video image to determine the segmented images corresponding to each time point, wherein the time intervals between adjacent time points are consistent.

[0068] In practical applications, when segmenting an image, it can be segmented according to unit time, then the unit time is the time interval, or the drying video can be segmented by a time period composed of multiple unit times, wherein the time period composed of multiple unit times is used as the time interval.

[0069] Step S22: Segmenting the images of the clothes to be dried that are larger than a preset area threshold in each of the segmented images to obtain a plurality of single clothes images corresponding to each of the time points.

[0070] In practical applications, there may be multiple pieces of clothing to be dried in each of the segmented images. The multiple pieces of clothing captured in the image are segmented to obtain separate images of the multiple pieces of clothing contained in the image. For the segmented images within a preset time period, the different pieces of clothing in the image are segmented to obtain separate images of the multiple pieces of clothing contained in each segmented image, that is, a single clothing image. In order to avoid the situation where the area of ​​a single clothing image is too small, which is prone to errors when matching with the initial image later, an area threshold is set, for example, a clothing image that is larger than 30% of the segmented image is segmented out as a single clothing image.

[0071] Step S23: Matching each of the single clothing images with the initial image.

[0072] Specifically, according to each of the single clothing images, a template matching algorithm is applied to determine the corresponding initial image.

[0073] In practical applications, template matching algorithms, feature matching algorithms or deep learning methods can be used for matching.

[0074] Step S24: grayscale processing is performed on each of the single clothing images and the matched initial image to obtain each of the single clothing grayscale images and the corresponding initial grayscale image arranged over time.

[0075] In practical applications, a single clothing image is grayed, and an initial image matching the single clothing image is grayed, and finally, the grayed single clothing images arranged in time and the grayed initial images matching each grayed single clothing image are obtained.

[0076] Step S25: Calculate the difference between the grayscale values ​​of each of the single clothing grayscale images arranged over time and the corresponding initial grayscale image to obtain the grayscale value change rate of each of the single clothing.

[0077] In practical applications, the difference in grayscale value between the grayscaled single clothing image and the corresponding grayscaled initial image is calculated, and the grayscale value change rate of the single clothing is calculated according to the time interval. The formula used is:

[0078]

[0079] Among them, e ij is the gray value change rate of the jth single clothing item in the segmented image at the i-th time point; g ij is the difference between the grayscale value of the jth single clothing grayscale image in the segmented image at the i-th time point and the corresponding initial grayscale image; t i is the time length corresponding to the i-th time point; wherein, taking the starting time of the preset time as the 0 point, the time length corresponding to the i-th time point is i×T, where T is the time interval.

[0080] The present invention can also use the difference between the grayscale values ​​of a single clothing grayscale image at the i-th time point and the grayscale value of a single clothing grayscale image at the i+1-th time point to calculate the grayscale value change rate. In this case, t i is the time interval T.

[0081] Step S26: Compare the grayscale value change rate of each of the single clothes with the grayscale value change rate of clothes of multiple materials under the same drying conditions to determine the first material category of the clothes to be dried.

[0082] In actual applications, a relationship curve is established between the calculated grayscale value change rate and the preset time, and becomes the first relationship curve. The first relationship curve is compared with the second relationship curve corresponding to the grayscale value change rate of multiple material clothes under the same drying conditions, so as to determine the material corresponding to the single clothing.

[0083] The present invention determines the clothing material corresponding to the first relationship curve by calculating the correlation between the first relationship curve and the second relationship curve. Specifically, when the correlation between the first relationship curve and the second relationship curve is greater than a preset correlation threshold, it is considered that the clothing material corresponding to the second relationship curve is the material of the single clothing, and based on the initial image corresponding to the single clothing, it is determined which clothing the clothing material corresponds to.

[0084] Step S3: determining the second material category of the clothes to be dried and the mass proportion of the clothes to be dried corresponding to each material in the second material category according to the initial weight and the weight curve.

[0085] S3 specifically includes:

[0086] Step S31: determining the weight of the laundry to be dried corresponding to each time point according to the weight curve.

[0087] In practical applications, the weight curve is a curve showing the change of weight over time. According to the weight curve, the weight corresponding to each time point can be obtained in real time. The time point corresponding to the preset time starting point is the time point when the weight of the clothes to be dried is the largest. As time goes by, the weight of the clothes to be dried will decrease.

[0088] Step S32: determining a change in the weight of the laundry to be dried according to the weight of the laundry to be dried corresponding to each time point and the initial weight.

[0089] Specifically, the difference between the weight of the clothes to be dried corresponding to each time point and the initial weight is the change in the weight of the clothes to be dried.

[0090] Step S33: determining the second material category of the clothes to be dried and the mass of the clothes to be dried corresponding to each material in the second material category according to the weight change of the clothes to be dried and the water absorption rates of clothes of multiple materials under the same drying conditions.

[0091] The calculation formula for the mass of the clothes to be dried corresponding to each material in the second material category is:

[0092]

[0093] Among them, m i is the weight of the clothes to be dried of the i-th material category; k i0 M is the water absorption rate of the clothes to be dried of the i-th material category before drying begins; 0 k is the change between the weight of the clothes to be dried before drying and the weight of the clothes to be dried before washing; i1 is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the first time point; M 1k is the change between the weight of the laundry to be dried corresponding to the first time point and the weight of the laundry to be dried before washing; i(n-1) is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the n-1-th time point; M n-1 It is the change between the weight of the laundry to be dried corresponding to the n-1th time point and the weight of the laundry to be dried before washing.

[0094] As a specific implementation, a method for obtaining the water absorption rate of clothes made of multiple materials under the same drying conditions specifically includes:

[0095] Step S331: obtaining the water absorption rate of the clothes to be dried of various material categories in each group of multiple groups of clothes to be dried consisting of various material categories at different drying times at a preset temperature.

[0096] In practical applications, the materials included in each group may be all materials used in the known clothing, or may be part of the materials used in the clothing.

[0097] In this step, the water absorption rates of multiple groups of clothes to be dried consisting of multiple material categories at preset temperatures and different drying times are used. This is because, at the preset temperature and preset drying time, a single piece of clothing will have different moisture contents at the preset temperature and preset time because there is no other clothing to block it or there is no other clothing of different materials or clothing of different water absorption rates to block it, and each piece of clothing will interfere with each other. The present invention uses clothes to be dried consisting of clothes of multiple materials to conduct experiments to obtain water absorption rates, so as to obtain water absorption rate data of different materials that are more in line with actual conditions.

[0098] In practical applications, the clothes dryer using the present invention needs to include water absorption rate data of various materials at various preset temperatures, so that the user can accurately judge the water absorption rate of the clothes to be dried when setting different preset temperatures.

[0099] Step S332: Calculate the average water absorption rate of the clothes to be dried of various material categories according to the water absorption rate of the clothes to be dried of various material categories in each group.

[0100] Due to the errors caused by the different materials or mixing methods of the clothes to be dried in each group, the different contact areas between clothes of different materials, the different materials of the contacting clothes, or the different contact times, the averaging method is adopted to reduce the errors. Alternatively, the weighted averaging method can be used to obtain more accurate water absorption data based on the number of clothes of materials with high water absorption.

[0101] Step S333: constructing a clothing water absorption rate table according to the average water absorption rate, wherein the clothing water absorption rate table includes the water absorption rates of clothing of various material categories at various temperatures and various drying times.

[0102] In practical applications, the constructed clothing water absorption table may also include more factors according to actual conditions, such as the maximum and minimum values ​​of the water absorption.

[0103] Step S334: According to the clothing water absorption rate table, the water absorption rates of clothing made of multiple materials under the same drying conditions are obtained.

[0104] Specifically, according to the current drying conditions, the water absorption rate of each material is obtained from the clothing water absorption rate table.

[0105] When determining the second material category of the clothes to be dried, all known clothes materials that can be used as clothes materials can be used as the materials of the clothes to be dried to be determined, and used as m in the calculation formula of the mass of the clothes to be dried. The number L of clothes materials included in the clothes water absorption rate table is used, and L is the number of time points. When the material X does not exist, the calculated mass of the material X is 0 or a relatively small value. In actual applications, when the calculated mass of the material X is less than a preset mass threshold, it is considered that the material X does not belong to the materials included in the clothes to be dried.

[0106] Step S34: Calculate the mass proportion of each material category according to the mass of the clothes to be dried corresponding to each material in the second material category and the initial weight of the clothes to be dried before washing.

[0107] Specifically, the formula for calculating the mass proportion of each material category is:

[0108]

[0109] Among them, c i is the mass proportion of the i-th material category; m i is the mass of the clothes to be dried of the i-th material category before washing; m 0 It is the initial weight of the clothes to be dried before washing.

[0110] In actual applications, if the calculated mass proportion of material Y is very small, less than the preset mass proportion, it is considered that the material will not affect the normal drying of clothes of other materials. When selecting the drying program, the drying effect of the material can be ignored.

[0111] Step S4: Determine whether the first material category and the second material category are consistent.

[0112] Step S5: When the first material category and the second material category are consistent, the first material category or the second material category is used as the material identification result of the clothes to be dried.

[0113] Step S6: When the first material category and the second material category are inconsistent, determine the difference material category, and judge whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold.

[0114] In actual applications, the difference material may belong to the first material category. When the difference material category belongs to the first material category, the water absorption rate corresponding to the material category and other materials with similar water absorption rates to the difference material category are searched from the clothing water absorption rate table, and the difference material is replaced by other materials as the updated first material category, and then the first material category is compared with the second material category to see if they are consistent. If they are still inconsistent, the first material category is re-acquired. When the number of times the first material category is re-acquired is greater than the preset number of times, for example, the preset number of times is set to three times, the difference material is taken as one of the items of the second material category and the second material category is re-calculated. If the result of the calculation shows that the second material category still does not include the difference material, it is considered that the difference material does not exist.

[0115] When the difference material belongs to the second material category, it is determined whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold.

[0116] Step S7: when the mass proportion of the difference material category is greater than or equal to a preset proportion threshold, the first material category and the second material category are reacquired.

[0117] If the situation still exists after the preset number of updates, for example, three times, since the mass of the different material accounts for a large proportion, the loss of the user cannot be avoided, and the task is that the different material exists in the clothes to be dried.

[0118] Step S8: When the mass proportion of the different material categories is less than the preset proportion threshold, the first material category is used as the material identification result of the clothes to be dried.

[0119] Example 2

[0120] The present invention also provides a clothing material intelligent identification system, which applies the clothing material intelligent identification method of Example 1, and the system includes: an acquisition module, a first material category determination module, a second material category determination module, a first judgment module and a second judgment module.

[0121] The acquisition module is used to acquire the initial image and initial weight of the clothes to be dried before washing, as well as the drying video image of the clothes dried at a preset temperature for a preset time and the weight curve changing with time.

[0122] The first material category determination module is used to determine the first material category of the clothes to be dried according to the initial image and the drying video image.

[0123] The second material category determination module is used to determine the second material category of the clothes to be dried and the mass proportion of the clothes to be dried corresponding to each material in the second material category according to the initial weight and the weight curve.

[0124] The first judgment module is used to judge whether the first material category and the second material category are consistent; when the first material category and the second material category are consistent, the first material category or the second material category is used as the material identification result of the clothes to be dried.

[0125] The second judgment module is used to determine the difference material category when the first material category and the second material category are inconsistent, and judge whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold; when the mass proportion of the difference material category is greater than or equal to the preset proportion threshold, re-acquire the first material category and the second material category; when the mass proportion of the difference material category is less than the preset proportion threshold, use the first material category as the material identification result of the clothes to be dried.

[0126] Example 3

[0127] The present invention also provides a clothes dryer, which uses the clothing material intelligent identification method of Example 1 to identify the material of the clothes to be dried, and obtains the material identification result and the mass proportion of the clothes to be dried corresponding to each material.

[0128] Determine the drying parameters according to the material identification result and the mass ratio, and execute the corresponding drying program according to the drying parameters. Specifically include:

[0129] The drying parameters of the clothes to be dried are determined according to the drying parameters of each material that is greater than or equal to a preset mass ratio threshold; the drying parameters include drying time and drying temperature; the clothes to be dried include clothes suitable for drying, clothes not suitable for drying, and clothes suitable for drying to a preset state.

[0130] In actual applications, since the clothes to be dried include clothes suitable for drying, clothes not suitable for drying, and clothes suitable for drying to a preset state, in order to protect the user's clothes, when materials not suitable for drying are detected, an alarm is promptly sent to the user to remind that there are clothes not suitable for drying in the clothes to be dried. When clothes suitable for drying to a preset state are detected, for example, the clothes need to be dried to a semi-dry state, a humidity detection device is set in the dryer to detect the humidity in the dryer in real time, and the humidity of the clothes in the dryer is judged according to the humidity. When the humidity requirement is met, an alarm signal is sent to the user.

[0131] According to the correspondence between the single clothing images of clothes of different materials and the initial image, the clothes corresponding to each single clothing image are determined, thereby determining the clothes corresponding to each clothing material. When an alarm is triggered, the corresponding clothing image is sent to the user, so that the user can take out the clothes of the alarm material from the dryer, thereby completing the subsequent drying work of the clothes to be dried.

[0132] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for intelligently identifying clothing materials. It is characterized in that The method comprises: Acquire an initial image and initial weight of the clothes to be dried before washing, as well as a drying video image of the clothes dried at a preset temperature for a preset time and a weight curve varying with time; Determining a first material category of the clothes to be dried according to the initial image and the drying video image; determining, according to the initial weight and the weight curve, a second material category of the clothes to be dried and a mass proportion of the clothes to be dried corresponding to each material in the second material category; Determining whether the first material category and the second material category are consistent; When the first material category and the second material category are consistent, the first material category or the second material category is used as the material identification result of the clothes to be dried; When the first material category and the second material category are inconsistent, determining a different material category, and judging whether a mass proportion of the different material category is greater than or equal to a preset proportion threshold; When the mass proportion of the different material categories is greater than or equal to a preset proportion threshold, reacquiring the first material category and the second material category; When the mass proportion of the different material categories is less than the preset proportion threshold, the first material category is used as the material identification result of the clothes to be dried.

2. The method for intelligently identifying clothing materials according to claim 1, It is characterized in that Determining the first material category of the clothes to be dried according to the initial image and the drying video image specifically includes: Segmenting the drying video image to determine the segmented image corresponding to each time point; wherein the time intervals between adjacent time points are consistent; Segmenting the images of the clothes to be dried that are larger than a preset area threshold in each of the segmented images to obtain a plurality of single clothes images corresponding to each of the time points; Matching each of the single clothing images with the initial image; grayscale the single clothing images and the matched initial image to obtain grayscale images of the single clothing and the corresponding initial grayscale images arranged over time; Calculating the difference between the grayscale values ​​of each of the single clothing grayscale images arranged over time and the corresponding initial grayscale image to obtain the grayscale value change rate of each of the single clothing; The grayscale value change rate of each of the single clothes is compared with the grayscale value change rates of clothes of multiple materials under the same drying conditions to determine the first material category of the clothes to be dried.

3. The intelligent clothing material identification method according to claim 2, It is characterized in that Matching each of the single clothing images with the initial image specifically includes: According to each of the single clothing images, a template matching algorithm is applied to determine a corresponding initial image.

4. The method for intelligently identifying clothing materials according to claim 2, It is characterized in that Determining the second material category of the clothes to be dried and the mass proportion of the clothes to be dried corresponding to each material in the second material category specifically includes: Determining the weight of the laundry to be dried corresponding to each time point according to the weight curve; determining a change in the weight of the laundry to be dried according to the weight of the laundry to be dried corresponding to each of the time points and the initial weight; Determining the second material category of the clothes to be dried and the mass of the clothes to be dried corresponding to each material in the second material category according to the weight change of the clothes to be dried and the water absorption rates of clothes of multiple materials under the same drying conditions; According to the mass of the clothes to be dried corresponding to each material in the second material category and the initial weight of the clothes to be dried before washing, the mass proportion of each material category is calculated.

5. The intelligent clothing material identification method according to claim 1, It is characterized in that The formula for calculating the mass percentage of each of the material categories is: Among them, c i is the mass proportion of the i-th material category; m i is the mass of the clothes to be dried of the i-th material category before washing; m 0 It is the initial weight of the clothes to be dried before washing.

6. The intelligent clothing material identification method according to claim 4, It is characterized in that The calculation formula for the mass of the clothes to be dried corresponding to each material in the second material category is: Among them, m i is the weight of the clothes to be dried of the i-th material category; k i0 M is the water absorption rate of the clothes to be dried of the i-th material category before drying begins; 0 k is the change between the weight of the clothes to be dried before drying and the weight of the clothes to be dried before washing; i1 is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the first time point; M 1 k is the change between the weight of the laundry to be dried corresponding to the first time point and the weight of the laundry to be dried before washing; i(n-1) is the water absorption rate of the clothes to be dried of the i-th material category corresponding to the n-1-th time point; M n-1 It is the change between the weight of the laundry to be dried corresponding to the n-1th time point and the weight of the laundry to be dried before washing.

7. The method for intelligently identifying clothing materials according to claim 4, It is characterized in that The method for obtaining the water absorption rate of clothes made of multiple materials under the same drying conditions specifically includes: Obtaining water absorption rates of various material categories of clothes to be dried in each group of multiple groups of clothes to be dried consisting of various material categories at different drying times at preset temperatures; According to the water absorption rate of the clothes to be dried of various material categories in each group, the average water absorption rate of the clothes to be dried of various material categories is calculated; According to the average water absorption rate, construct a clothing water absorption rate table; the clothing water absorption rate table includes the water absorption rates of clothing of various material categories at various temperatures and various drying times; According to the clothing water absorption rate table, the water absorption rates of clothing made of multiple materials under the same drying conditions are obtained.

8. An intelligent clothing material recognition system, It is characterized in that The method for intelligently identifying clothing materials according to any one of claims 1 to 8 is applied, wherein the system comprises: An acquisition module, used to acquire an initial image and initial weight of the clothes to be dried before washing, as well as a drying video image of the clothes dried at a preset temperature for a preset time and a weight curve varying with time; A first material category determination module, configured to determine a first material category of the clothes to be dried according to the initial image and the drying video image; a second material category determination module, configured to determine, according to the initial weight and the weight curve, a second material category of the laundry to be dried and a mass proportion of the laundry to be dried corresponding to each material in the second material category; A first judgment module is used to judge whether the first material category and the second material category are consistent; when the first material category and the second material category are consistent, the first material category or the second material category is used as the material recognition result of the clothes to be dried; The second judgment module is used to determine the difference material category when the first material category and the second material category are inconsistent, and judge whether the mass proportion of the difference material category is greater than or equal to a preset proportion threshold; when the mass proportion of the difference material category is greater than or equal to the preset proportion threshold, re-acquire the first material category and the second material category; when the mass proportion of the difference material category is less than the preset proportion threshold, use the first material category as the material identification result of the clothes to be dried.

9. A clothes dryer, It is characterized in that The clothes dryer uses the intelligent clothing material identification method according to any one of claims 1 to 8 to identify the material of the clothes to be dried, and obtains the material identification result and the mass proportion of the clothes to be dried corresponding to each material; Determine drying parameters according to the material identification result and the mass ratio, and execute a corresponding drying program according to the drying parameters.

10. The clothes dryer according to claim 9, It is characterized in that Determine drying parameters according to the material identification result and the mass ratio, including: The drying parameters of the clothes to be dried are determined according to the drying parameters of each material that is greater than or equal to a preset mass ratio threshold; the drying parameters include drying time and drying temperature; the clothes to be dried include clothes suitable for drying, clothes not suitable for drying, and clothes suitable for drying to a preset state.

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