Heating dynamic control method and system for clothes dryer
By using heterogeneous sensors to acquire multi-dimensional data in the clothes dryer, a dynamic heating control model is constructed, which solves the heating temperature problem caused by the failure of the clothes type of the clothes by users, improves the drying efficiency of clothes and reduces clothing damage.
Patent Information
- Application Number
- CN202411554649.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-04
- Publication Date
- 2025-01-07
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
During the heating process, existing clothes dryers do not distinguish between different clothes types, resulting in heating temperature exceeding the affordable range of clothes materials, resulting in low clothing damage and drying efficiency.
Multi-dimensional perception data is obtained based on the built-in heterogeneous sensor of the clothes dryer, and the initial temperature range is generated through fitting analysis, a dynamic heating control model is constructed, dynamic heating temperature parameters are generated, and the clothes drying task is completed through the heating control component.
Improves the drying efficiency of clothes and reduces damage to clothes.
Smart Images
Figure CN119265899A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of automation technology, and in particular to a heating dynamic control method and system for a clothes dryer. Background Art
[0002] A clothes dryer is a household appliance that dries clothes by heating air and circulating it through wet clothes to quickly remove moisture from them.
[0003] Existing clothes dryers mainly have preheating modes based on the type of clothes. However, during normal use, users do not deliberately distinguish the clothes to be dried, resulting in the heating temperature of the dryer exceeding the tolerable range of the material of the clothes to be dried, causing damage to the clothes and low drying efficiency. Summary of the invention
[0004] In order to solve the above technical problems, a dynamic heating control method and system for a dryer are provided. The technical solution solves the problem that the existing dryers mentioned above mainly preheat the heating mode according to the type of clothes, but since users do not deliberately distinguish the clothes to be dried during normal use, the heating temperature of the dryer exceeds the tolerable range of the material of the clothes to be dried, resulting in damage to the clothes and low drying efficiency.
[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:
[0006] A heating dynamic control method for a clothes dryer, comprising:
[0007] Based on the heterogeneous sensors built into the dryer, multi-dimensional perception data of the clothes to be dried in the dryer is obtained;
[0008] Perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer to generate an initialization temperature range of the clothes to be dried in the dryer;
[0009] Based on the initialization temperature range of the clothes to be dried in the clothes dryer, a dynamic heating control model of the clothes dryer is constructed to generate dynamic heating temperature parameters of the clothes to be dried in the clothes dryer;
[0010] According to the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer, the heating control component of the clothes dryer is input to complete the drying task.
[0011] Preferably, performing fitting analysis based on the multi-dimensional perception data of the clothes to be dried in the clothes dryer to generate the initialization temperature range of the clothes to be dried in the clothes dryer specifically includes:
[0012] Based on the multi-dimensional perception data of the clothes to be dried, the multi-dimensional perception data is used as observation feature parameters to construct an observation feature parameter array of the clothes to be dried; the observation feature parameters include: clothes humidity parameters, clothes temperature parameters, and clothes material parameters;
[0013] Based on the array of observed characteristic parameters of the clothes to be dried, and in accordance with the observed characteristic parameters of the clothes material, determining the upper limit of the limit range of the temperature that can be heated for the clothes to be dried;
[0014] Assigning a heating temperature safety range score to the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried;
[0015] performing normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigning a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value;
[0016] Based on the array of observed characteristic parameters of the clothes to be dried, quantifying the range of humidity levels of the clothes to be dried according to the observed characteristic parameters of the clothes humidity;
[0017] According to the humidity level range of the clothes to be dried, assigning a humidity weight to the humidity level of the clothes to be dried, and obtaining the humidity weight of the humidity level of the clothes to be dried;
[0018] Calculating the comprehensive weight of the clothes to be dried based on the weight of the safe range of the heating temperature of the clothes to be dried and the weight of the humidity level of the clothes to be dried;
[0019] Calculating an initialization temperature range of the clothes to be dried according to the comprehensive weight of the clothes to be dried and the heating temperature limit range of the clothes to be dried;
[0020] The initialization temperature range for calculating the clothes to be dried is specifically:
[0021]
[0022] Where, T i is the initialization temperature range of the i-th piece of clothing to be dried in the dryer, W i is the comprehensive weight of the i-th piece of clothing to be dried, is the weight of the safe range of heating temperature for the i-th piece of clothing to be dried, is the humidity level and humidity weight of the i-th piece of clothing to be dried, T i 限 is the upper limit of the safe range of the heating temperature of the i-th piece of clothing to be dried, W i is the comprehensive weight of the i-th piece of clothing to be dried, and n is the total number of clothing to be dried.
[0023] Preferably, heating the dryer according to the initialization temperature range of the clothes to be dried in the dryer, building a dynamic heating control model for the dryer, and generating dynamic heating temperature parameters for the clothes to be dried in the dryer specifically include:
[0024] Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, collecting real-time operating data in the dryer, and predicting the heating time of the clothes to be dried in the dryer;
[0025] Based on the initialization temperature range of the clothes to be dried of the clothes dryer, the initialization temperature range of the clothes to be dried per unit time is used as a heating restriction condition;
[0026] Based on the heating restriction condition and the real-time humidity of the clothes to be dried, an objective function is constructed to maximize the optimal heating temperature for all the clothes to be dried;
[0027] Based on RNN recurrent neural network, a dynamic heating control model of the dryer is constructed;
[0028] According to the dynamic heating control model of the clothes dryer, under the heating restriction condition and in accordance with the objective function, the real-time operating environment data in the clothes dryer and the heating time of the clothes to be dried are used as input, and the dynamic heating temperature parameters of the clothes to be dried of the clothes dryer are used as output;
[0029] The dynamic heating control model of the clothes dryer is specifically as follows:
[0030]
[0031] Where, T hcat (t) is the dynamic heating temperature parameter of the clothes to be dried in the dryer, f RNN () is the objective function, X(t) is the real-time operating environment data in the dryer at t unit time, T i (t) is the initialization temperature range of the i-th piece of clothing to be dried in the dryer under t unit time, H(t) is the humidity data of the i-th piece of clothing to be dried in the dryer under t unit time, θ is the bias of the model, T heat (t) is the heating temperature parameter of the clothes dryer under t unit time, T final To predict the heating time of clothes to be dried in a clothes dryer, H target is the target humidity of the clothes to be dried, H(0) is the initial humidity of the clothes to be dried, T opt (t) is the optimal heating temperature of the dryer under t unit time, The upper limit of the initial temperature range for the clothes to be dried. is the lower limit of the initialization temperature range of the clothes to be dried, and α and β are weight coefficients.
[0032] Preferably, heating the dryer based on the real-time dynamic heating temperature parameter of the dryer, collecting real-time operation data in the dryer, and predicting the heating time of the clothes to be dried in the dryer specifically include:
[0033] Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, and collecting real-time operation data in the dryer; the real-time operation data includes: heating temperature, clothing humidity;
[0034] Based on the real-time operation data in the clothes dryer, predict the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data;
[0035] Substituting the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time;
[0036] Taking the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, a heating time estimation model for the clothes to be dried is constructed to predict the heating time of the clothes to be dried in the dryer;
[0037] The specific model for estimating the heating time of clothes to be dried is:
[0038]
[0039] Where, T final To predict the heating time of clothes to be dried in a clothes dryer, T hcat (t+1) is the dynamic heating temperature parameter of the clothes to be dried in the dryer at t+1 unit time, H(t+1) is the humidity data of the clothes to be dried at t+1 unit time, are all autoregressive coefficients.
[0040] Furthermore, a heating dynamic control system for a clothes dryer is proposed, which is used to implement the above-mentioned heating dynamic control method for a clothes dryer, comprising:
[0041] A data acquisition module, which is used to obtain multi-dimensional perception data of the clothes to be dried in the clothes dryer based on the heterogeneous sensors built into the clothes dryer;
[0042] An initialization temperature module, which is used to perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer, and generate an initialization temperature range for the clothes to be dried in the dryer;
[0043] A dynamic temperature generation module, the dynamic temperature generation module is electrically connected to the initialization temperature module, and the dynamic temperature generation module is used to perform fitting analysis based on the multi-dimensional perception data of the clothes to be dried in the dryer, and generate an initialization temperature range for the clothes to be dried in the dryer;
[0044] The execution module is electrically connected to the dynamic temperature generation module, and is used to input the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer into the heating control component of the clothes dryer to complete the drying task.
[0045] Optionally, the initialization temperature module includes:
[0046] A feature unit, based on the multi-dimensional sensing data of the clothes to be dried, uses the multi-dimensional sensing data as observation feature parameters to construct an observation feature parameter array of the clothes to be dried;
[0047] The upper temperature limit unit determines the upper limit of the heating temperature limit range of the drying clothes based on the observed characteristic parameter array of the clothes to be dried and the observed characteristic parameters of the clothes material;
[0048] A safety range unit, which assigns a safety range score of the heating temperature of the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried;
[0049] a temperature weight unit, which performs normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigns a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value;
[0050] A humidity level unit, based on an array of observed characteristic parameters of the clothes to be dried, quantifies the humidity level range of the clothes to be dried according to the observed characteristic parameters of the clothes humidity;
[0051] A humidity weight unit, which assigns a humidity weight to the humidity level of the clothes to be dried according to the humidity level range of the clothes to be dried, and obtains the humidity weight of the humidity level of the clothes to be dried;
[0052] A comprehensive weight unit, which calculates a comprehensive weight of the clothes to be dried based on a weight of a safe range of a heating temperature of the clothes to be dried and a weight of a humidity level of the clothes to be dried;
[0053] The initialization temperature unit calculates an initialization temperature range of the clothes to be dried according to a comprehensive weight of the clothes to be dried and a heating temperature limit range of the clothes to be dried.
[0054] Optionally, the dynamic temperature generation module includes:
[0055] A preheating time unit, which heats the dryer based on the real-time dynamic heating temperature parameters of the dryer, collects real-time operating data in the dryer, and predicts the heating time of the clothes to be dried in the dryer;
[0056] A restriction condition unit, based on an initialization temperature range of the clothes to be dried of the clothes dryer, taking the initialization temperature range of the clothes to be dried per unit time as a heating restriction condition;
[0057] An objective function unit, based on the heating restriction condition and in accordance with the real-time humidity of the clothes to be dried, constructs an objective function to maximize the optimal heating temperature for all the clothes to be dried;
[0058] The model building unit builds a dynamic heating control model of the dryer based on the RNN recursive neural network;
[0059] The dynamic temperature generation unit, based on the dynamic heating control model of the dryer, takes the real-time operating environment data in the dryer and the heating time of the clothes to be dried as input and the dynamic heating temperature parameters of the clothes to be dried in the dryer as output according to the objective function under the heating restriction condition.
[0060] Optionally, the preheating duration unit includes:
[0061] An environmental data collection subunit heats the dryer based on the real-time dynamic heating temperature parameters of the dryer and collects real-time operating data in the dryer;
[0062] A humidity prediction subunit, based on the real-time operation data in the clothes dryer, predicts the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data;
[0063] The temperature prediction subunit substitutes the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time;
[0064] The regression prediction subunit takes the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, constructs a heating time estimation model for the clothes to be dried, and predicts the heating time of the clothes to be dried in the dryer.
[0065] Compared with the prior art, the present invention has the following beneficial effects:
[0066] The present invention proposes a heating dynamic control scheme for a clothes dryer. Based on the heterogeneous sensors built into the clothes dryer, the multi-dimensional perception data of the clothes is obtained, and the initialization temperature range is generated through fitting analysis, thereby constructing a dynamic heating control model and generating dynamic heating temperature parameters. At the same time, the heating time is predicted based on the real-time operation data, and finally the dynamic heating temperature parameters and the predicted heating time are generated to complete the drying task through the heating component control API interface. The beneficial effects are: improving the drying efficiency of clothes and reducing damage to clothes. BRIEF DESCRIPTION OF THE DRAWINGS
[0067] Figure 1 A flow chart of a heating dynamic control method for a clothes dryer;
[0068] Figure 2 A flow chart of a method for generating an initialization temperature range for clothes to be dried in a clothes dryer;
[0069] Figure 3 A flow chart of a method for generating dynamic heating temperature parameters of clothes to be dried in a clothes dryer;
[0070] Figure 4A flow chart of a method for predicting the heating time of clothes to be dried in a clothes dryer;
[0071] Figure 5 The present invention is a framework diagram of a heating dynamic control system for a clothes dryer. DETAILED DESCRIPTION
[0072] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.
[0073] Reference Figure 1 As shown, a heating dynamic control method for a clothes dryer comprises:
[0074] Based on the heterogeneous sensors built into the dryer, multi-dimensional perception data of the clothes to be dried in the dryer is obtained;
[0075] Perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer to generate an initialization temperature range of the clothes to be dried in the dryer;
[0076] Based on the initialization temperature range of the clothes to be dried in the clothes dryer, a dynamic heating control model of the clothes dryer is constructed to generate dynamic heating temperature parameters of the clothes to be dried in the clothes dryer;
[0077] According to the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer, the heating control component of the clothes dryer is input to complete the drying task.
[0078] The implementation principle of this solution is to obtain multi-dimensional perception data of clothes (including humidity, temperature and material) based on the heterogeneous sensors built into the dryer, generate the initial temperature range through fitting analysis, and then build a dynamic heating control model and generate dynamic heating temperature parameters. At the same time, the heating time is predicted based on real-time operation data, and finally the dynamic heating temperature parameters and the predicted heating time are generated to complete the drying heating task through the heating component control API interface. The beneficial effects are: improving the drying efficiency of clothes and reducing clothing damage.
[0079] Reference Figure 2 As shown, the initialization temperature range of the clothes to be dried in the clothes dryer is generated by fitting analysis based on the multi-dimensional perception data of the clothes to be dried in the clothes dryer, and specifically includes:
[0080] Based on the multi-dimensional perception data of the clothes to be dried, the multi-dimensional perception data is used as observation feature parameters to construct an observation feature parameter array of the clothes to be dried; the observation feature parameters include: clothes humidity parameters, clothes temperature parameters, and clothes material parameters;
[0081] Based on the array of observed characteristic parameters of the clothes to be dried, and in accordance with the observed characteristic parameters of the clothes material, determining the upper limit of the limit range of the temperature that can be heated for the clothes to be dried;
[0082] Assigning a heating temperature safety range score to the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried;
[0083] performing normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigning a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value;
[0084] Based on the array of observed characteristic parameters of the clothes to be dried, quantifying the range of humidity levels of the clothes to be dried according to the observed characteristic parameters of the clothes humidity;
[0085] According to the humidity level range of the clothes to be dried, assigning a humidity weight to the humidity level of the clothes to be dried, and obtaining the humidity weight of the humidity level of the clothes to be dried;
[0086] Calculating the comprehensive weight of the clothes to be dried based on the weight of the safe range of the heating temperature of the clothes to be dried and the weight of the humidity level of the clothes to be dried;
[0087] Calculating an initialization temperature range of the clothes to be dried according to the comprehensive weight of the clothes to be dried and the heating temperature limit range of the clothes to be dried;
[0088] The initialization temperature range for calculating the clothes to be dried is specifically:
[0089]
[0090] Where, T i is the initialization temperature range of the i-th piece of clothing to be dried in the dryer, W i is the comprehensive weight of the i-th piece of clothing to be dried, is the weight of the safe range of heating temperature for the i-th piece of clothing to be dried, is the humidity level and humidity weight of the i-th piece of clothing to be dried, T i 限 is the upper limit of the safe range of the heating temperature of the i-th piece of clothing to be dried, W i is the comprehensive weight of the i-th piece of clothing to be dried, and n is the total number of clothing to be dried.
[0091] It is understandable that when the dryer heats and dries clothes of different materials according to the conventional preset mode, clothes of leather type may be damaged, and the related factors affecting whether the clothes are damaged also include the humidity of the clothes to be dried. Therefore, the initialization temperature range of each piece of clothing to be dried is calculated by considering the tolerable temperature, humidity state, and clothing material of the clothes to be dried in multiple dimensions to ensure that the material will not be damaged when facing multiple types of clothes to be dried.
[0092] Reference Figure 3As shown, the dryer is heated according to the initialization temperature range of the clothes to be dried in the dryer, a dynamic heating control model of the dryer is constructed, and the dynamic heating temperature parameters of the clothes to be dried in the dryer are generated, which specifically include:
[0093] Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, collecting real-time operating data in the dryer, and predicting the heating time of the clothes to be dried in the dryer;
[0094] Based on the initialization temperature range of the clothes to be dried of the clothes dryer, the initialization temperature range of the clothes to be dried per unit time is used as a heating restriction condition;
[0095] Based on the heating restriction condition and the real-time humidity of the clothes to be dried, an objective function is constructed to maximize the optimal heating temperature for all the clothes to be dried;
[0096] Based on RNN recurrent neural network, a dynamic heating control model of the dryer is constructed;
[0097] According to the dynamic heating control model of the clothes dryer, under the heating restriction condition and in accordance with the objective function, the real-time operating environment data in the clothes dryer and the heating time of the clothes to be dried are used as input, and the dynamic heating temperature parameters of the clothes to be dried of the clothes dryer are used as output;
[0098] The dynamic heating control model of the clothes dryer is specifically as follows:
[0099]
[0100] Where, T hcat (t) is the dynamic heating temperature parameter of the clothes to be dried in the dryer, f RNN () is the objective function, X(t) is the real-time operating environment data in the dryer at t unit time, T i (t) is the initialization temperature range of the i-th piece of clothing to be dried in the dryer under t unit time, H(t) is the humidity data of the i-th piece of clothing to be dried in the dryer under t unit time, θ is the bias of the model, T heat (t) is the heating temperature parameter of the clothes dryer under t unit time, T final To predict the heating time of clothes to be dried in a clothes dryer, H target is the target humidity of the clothes to be dried, H(0) is the initial humidity of the clothes to be dried, T opt (t) is the optimal heating temperature of the dryer under t unit time, The upper limit of the initial temperature range for the clothes to be dried. is the lower limit of the initialization temperature range of the clothes to be dried, and α and β are weight coefficients.
[0101] Reference Figure 4As shown, the dryer is heated based on the real-time dynamic heating temperature parameters of the dryer, real-time operation data in the dryer is collected, and the heating time of the clothes to be dried in the dryer is predicted, which specifically includes:
[0102] Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, and collecting real-time operation data in the dryer; the real-time operation data includes: heating temperature, clothing humidity;
[0103] Based on the real-time operation data in the clothes dryer, predict the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data;
[0104] Substituting the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time;
[0105] Taking the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, a heating time estimation model for the clothes to be dried is constructed to predict the heating time of the clothes to be dried in the dryer;
[0106] The specific model for estimating the heating time of clothes to be dried is:
[0107]
[0108] Where, T final To predict the heating time of clothes to be dried in a clothes dryer, T hcat (t+1) is the dynamic heating temperature parameter of the clothes to be dried in the dryer at t+1 unit time, H(t+1) is the humidity data of the clothes to be dried at t+1 unit time, are all autoregressive coefficients.
[0109] Reference Figure 5 As shown, based on the same inventive concept of a heating dynamic control method for a clothes dryer, a heating dynamic control system for a clothes dryer is proposed, comprising:
[0110] A data acquisition module, which is used to obtain multi-dimensional perception data of the clothes to be dried in the clothes dryer based on the heterogeneous sensors built into the clothes dryer;
[0111] An initialization temperature module, which is used to perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer, and generate an initialization temperature range for the clothes to be dried in the dryer;
[0112] A dynamic temperature generation module, the dynamic temperature generation module is electrically connected to the initialization temperature module, and the dynamic temperature generation module is used to perform fitting analysis based on the multi-dimensional perception data of the clothes to be dried in the dryer, and generate an initialization temperature range for the clothes to be dried in the dryer;
[0113] The execution module is electrically connected to the dynamic temperature generation module, and is used to input the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer into the heating control component of the clothes dryer to complete the drying task.
[0114] The initialization temperature module includes:
[0115] A feature unit, based on the multi-dimensional sensing data of the clothes to be dried, uses the multi-dimensional sensing data as observation feature parameters to construct an observation feature parameter array of the clothes to be dried;
[0116] The upper temperature limit unit determines the upper limit of the heating temperature limit range of the drying clothes based on the observed characteristic parameter array of the clothes to be dried and the observed characteristic parameters of the clothes material;
[0117] A safety range unit, which assigns a safety range score of the heating temperature of the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried;
[0118] a temperature weight unit, which performs normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigns a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value;
[0119] A humidity level unit, based on an array of observed characteristic parameters of the clothes to be dried, quantifies the humidity level range of the clothes to be dried according to the observed characteristic parameters of the clothes humidity;
[0120] A humidity weight unit, which assigns a humidity weight to the humidity level of the clothes to be dried according to the humidity level range of the clothes to be dried, and obtains the humidity weight of the humidity level of the clothes to be dried;
[0121] A comprehensive weight unit, which calculates a comprehensive weight of the clothes to be dried based on a weight of a safe range of a heating temperature of the clothes to be dried and a weight of a humidity level of the clothes to be dried;
[0122] The initialization temperature unit calculates an initialization temperature range of the clothes to be dried according to a comprehensive weight of the clothes to be dried and a heating temperature limit range of the clothes to be dried.
[0123] The dynamic temperature generation module includes:
[0124] A preheating time unit, which heats the dryer based on the real-time dynamic heating temperature parameters of the dryer, collects real-time operating data in the dryer, and predicts the heating time of the clothes to be dried in the dryer;
[0125] A restriction condition unit, based on an initialization temperature range of the clothes to be dried of the clothes dryer, taking the initialization temperature range of the clothes to be dried per unit time as a heating restriction condition;
[0126] An objective function unit, based on the heating restriction condition and in accordance with the real-time humidity of the clothes to be dried, constructs an objective function to maximize the optimal heating temperature for all the clothes to be dried;
[0127] The model building unit builds a dynamic heating control model of the dryer based on the RNN recursive neural network;
[0128] The dynamic temperature generation unit, based on the dynamic heating control model of the dryer, takes the real-time operating environment data in the dryer and the heating time of the clothes to be dried as input and the dynamic heating temperature parameters of the clothes to be dried in the dryer as output according to the objective function under the heating restriction condition.
[0129] The preheating time unit includes:
[0130] An environmental data collection subunit heats the dryer based on the real-time dynamic heating temperature parameters of the dryer and collects real-time operating data in the dryer;
[0131] A humidity prediction subunit, based on the real-time operation data in the clothes dryer, predicts the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data;
[0132] The temperature prediction subunit substitutes the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time;
[0133] The regression prediction subunit takes the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, constructs a heating time estimation model for the clothes to be dried, and predicts the heating time of the clothes to be dried in the dryer.
[0134] The use process of a heating dynamic control system for a clothes dryer is as follows:
[0135] Step 1: Based on the heterogeneous sensors built into the dryer, obtain multi-dimensional perception data of the clothes to be dried in the dryer;
[0136] Step 2: Based on the multi-dimensional perception data of the clothes to be dried, the multi-dimensional perception data is used as the observation feature parameter to construct an observation feature parameter array of the clothes to be dried;
[0137] Step 3: Based on the array of observed characteristic parameters of the clothes to be dried and according to the observed characteristic parameters of the clothes material, determine the upper limit of the heating temperature limit range of the clothes to be dried;
[0138] Step 4: assigning a heating temperature safety range score to the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried;
[0139] Step 5: performing normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigning a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value;
[0140] Step 6: Based on the array of observed characteristic parameters of the clothes to be dried, quantify the humidity level range of the clothes to be dried according to the observed characteristic parameters of the clothes humidity;
[0141] Step 7: assigning a humidity weight to the humidity level of the clothes to be dried according to the humidity level range of the clothes to be dried, and obtaining the humidity weight of the humidity level of the clothes to be dried;
[0142] Step 8: Calculate the comprehensive weight of the clothes to be dried based on the weight of the safe range of the heating temperature of the clothes to be dried and the weight of the humidity level of the clothes to be dried;
[0143] Step 9: Calculate the initialization temperature range of the clothes to be dried according to the comprehensive weight of the clothes to be dried and the heating temperature limit range of the clothes to be dried;
[0144] Step 10: heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, and collecting real-time operation data in the dryer;
[0145] Step 11: Based on the real-time operation data in the clothes dryer, predict the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data;
[0146] Step 12: Substitute the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the dryer to determine the heating temperature of the clothes to be dried in the next unit time;
[0147] Step 13: Taking the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, a heating time estimation model for the clothes to be dried is constructed to predict the heating time of the clothes to be dried in the dryer;
[0148] Step 14: Based on the initialization temperature range of the clothes to be dried of the clothes dryer, the initialization temperature range of the clothes to be dried per unit time is used as a heating restriction condition;
[0149] Step 15: Based on the heating restriction condition and in accordance with the real-time humidity of the clothes to be dried, construct an objective function to maximize the optimal heating temperature for all the clothes to be dried;
[0150] Step 16: Based on the RNN recursive neural network, a dynamic heating control model of the dryer is constructed;
[0151] Step 17: According to the dynamic heating control model of the dryer, under the heating restriction condition and in accordance with the objective function, the real-time operating environment data in the dryer and the heating time of the clothes to be dried are used as input, and the dynamic heating temperature parameters of the clothes to be dried in the dryer are used as output.
[0152] In summary, the advantages of the present invention are: based on the heterogeneous sensors built into the clothes dryer, the multi-dimensional perception data of the clothes (including humidity, temperature and material) is obtained, and the initialization temperature range is generated through fitting analysis, and then a dynamic heating control model is constructed and dynamic heating temperature parameters are generated. At the same time, the heating time is predicted according to the real-time operation data, and finally the dynamic heating temperature parameters and the predicted heating time are generated to complete the drying heating task through the heating component control API interface. The beneficial effects are: improving the drying efficiency of clothes and reducing damage to clothes.
[0153] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.
Claims
1. A heating dynamic control method for a clothes dryer, characterized in that: include: Based on the heterogeneous sensors built into the dryer, multi-dimensional perception data of the clothes to be dried in the dryer is obtained; Perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer to generate an initialization temperature range of the clothes to be dried in the dryer; Based on the initialization temperature range of the clothes to be dried in the clothes dryer, a dynamic heating control model of the clothes dryer is constructed to generate dynamic heating temperature parameters of the clothes to be dried in the clothes dryer; According to the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer, the heating control component of the clothes dryer is input to complete the drying task.
2. A heating dynamic control method for a clothes dryer according to claim 1, characterized in that: The fitting analysis is performed based on the multi-dimensional perception data of the clothes to be dried in the clothes dryer to generate the initialization temperature range of the clothes to be dried in the clothes dryer, which specifically includes: Based on the multi-dimensional perception data of the clothes to be dried, the multi-dimensional perception data is used as observation feature parameters to construct an observation feature parameter array of the clothes to be dried; the observation feature parameters include: clothes humidity parameters, clothes temperature parameters, and clothes material parameters; Based on the array of observed characteristic parameters of the clothes to be dried, and in accordance with the observed characteristic parameters of the clothes material, determining the upper limit of the limit range of the temperature that can be heated for the clothes to be dried; Assigning a heating temperature safety range score to the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried; performing normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigning a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value; Based on the array of observed characteristic parameters of the clothes to be dried, quantifying the range of humidity levels of the clothes to be dried according to the observed characteristic parameters of the clothes humidity; According to the humidity level range of the clothes to be dried, assigning a humidity weight to the humidity level of the clothes to be dried, and obtaining the humidity weight of the humidity level of the clothes to be dried; Calculating the comprehensive weight of the clothes to be dried based on the weight of the safe range of the heating temperature of the clothes to be dried and the weight of the humidity level of the clothes to be dried; Calculating an initialization temperature range of the clothes to be dried according to the comprehensive weight of the clothes to be dried and the heating temperature limit range of the clothes to be dried; The initialization temperature range for calculating the clothes to be dried is specifically: Where, T i is the initialization temperature range of the i-th piece of clothing to be dried in the dryer, W i is the comprehensive weight of the i-th piece of clothing to be dried, is the weight of the safe range of heating temperature for the i-th piece of clothing to be dried, is the humidity level and humidity weight of the i-th piece of clothing to be dried, W is the upper limit of the safe range of the heating temperature of the f-th piece of clothing to be dried, i is the comprehensive weight of the i-th piece of clothing to be dried, and n is the total number of clothing to be dried.
3. A heating dynamic control method for a clothes dryer according to claim 2, characterized in that: The dryer is heated according to the initialization temperature range of the clothes to be dried in the dryer, a dynamic heating control model of the dryer is constructed, and the dynamic heating temperature parameters of the clothes to be dried in the dryer are generated, specifically including: Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, collecting real-time operating data in the dryer, and predicting the heating time of the clothes to be dried in the dryer; Based on the initialization temperature range of the clothes to be dried of the clothes dryer, the initialization temperature range of the clothes to be dried per unit time is used as a heating restriction condition; Based on the heating restriction condition and the real-time humidity of the clothes to be dried, an objective function is constructed to maximize the optimal heating temperature for all the clothes to be dried; Based on RNN recurrent neural network, a dynamic heating control model of the dryer is constructed; According to the dynamic heating control model of the clothes dryer, under the heating restriction condition and in accordance with the objective function, the real-time operating environment data in the clothes dryer and the heating time of the clothes to be dried are used as input, and the dynamic heating temperature parameters of the clothes to be dried of the clothes dryer are used as output; The dynamic heating control model of the clothes dryer is specifically as follows: Where, T hcat (t) is the dynamic heating temperature parameter of the clothes to be dried in the dryer, f RNN () is the objective function, X(t) is the real-time operating environment data in the dryer at t unit time, T i (t) is the initialization temperature range of the i-th piece of clothing to be dried in the dryer under t unit time, H(t) is the humidity data of the i-th piece of clothing to be dried in the dryer under t unit time, θ is the bias of the model, T heat (t) is the heating temperature parameter of the clothes dryer under t unit time, T final To predict the heating time of clothes to be dried in a clothes dryer, H target is the target humidity of the clothes to be dried, H(0) is the initial humidity of the clothes to be dried, T opt (t) is the optimal heating temperature of the dryer under t unit time, The upper limit of the initial temperature range for the clothes to be dried. is the lower limit of the initialization temperature range of the clothes to be dried, and α and β are weight coefficients.
4. A heating dynamic control method for a clothes dryer according to claim 3, characterized in that: The dryer is heated based on the real-time dynamic heating temperature parameters of the dryer, and the real-time operation data in the dryer is collected to predict the heating time of the clothes to be dried in the dryer. Specifically, the following steps are performed: Heating the dryer based on the real-time dynamic heating temperature parameters of the dryer, and collecting real-time operation data in the dryer; the real-time operation data includes: heating temperature, clothing humidity; Based on the real-time operation data in the clothes dryer, predict the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data; Substituting the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time; Taking the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, a heating time estimation model for the clothes to be dried is constructed to predict the heating time of the clothes to be dried in the dryer; The specific model for estimating the heating time of clothes to be dried is: Where, T final To predict the heating time of clothes to be dried in a clothes dryer, T hcat (t+1) is the dynamic heating temperature parameter of the clothes to be dried in the dryer at t+1 unit time, H(t+1) is the humidity data of the clothes to be dried at t+1 unit time, are all autoregression coefficients.
5. A heating dynamic control system for a clothes dryer, characterized in that: A method for dynamically controlling heating of a clothes dryer according to any one of claims 1 to 4, comprising: A data acquisition module, which is used to obtain multi-dimensional perception data of the clothes to be dried in the clothes dryer based on the heterogeneous sensors built into the clothes dryer; An initialization temperature module, which is used to perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer, and generate an initialization temperature range for the clothes to be dried in the dryer; A dynamic temperature generation module, the dynamic temperature generation module is electrically connected to the initialization temperature module, and the dynamic temperature generation module is used to perform fitting analysis based on multi-dimensional perception data of the clothes to be dried in the dryer to generate an initialization temperature range for the clothes to be dried in the dryer; The execution module is electrically connected to the dynamic temperature generation module, and is used to input the dynamic heating temperature parameters of the clothes to be dried in the clothes dryer into the heating control component of the clothes dryer to complete the drying task.
6. A heating dynamic control system for a clothes dryer according to claim 5, characterized in that: The initialization temperature module includes: A feature unit, based on the multi-dimensional sensing data of the clothes to be dried, uses the multi-dimensional sensing data as observation feature parameters to construct an observation feature parameter array of the clothes to be dried; The upper temperature limit unit determines the upper limit of the heating temperature limit range of the drying clothes based on the observed characteristic parameter array of the clothes to be dried and the observed characteristic parameters of the clothes material; A safety range unit, which assigns a safety range score of the heating temperature of the clothes to be dried based on the upper limit of the heating temperature range of the clothes to be dried; a temperature weight unit, which performs normalization processing according to the score of the safe range of the heating temperature of the clothes to be dried, and assigns a weight to the safe range of the heating temperature of the clothes to be dried according to the normalized value; A humidity level unit, based on an array of observed characteristic parameters of the clothes to be dried, quantifies the humidity level range of the clothes to be dried according to the observed characteristic parameters of the clothes humidity; A humidity weight unit, which assigns a humidity weight to the humidity level of the clothes to be dried according to the humidity level range of the clothes to be dried, and obtains the humidity weight of the humidity level of the clothes to be dried; A comprehensive weight unit, which calculates a comprehensive weight of the clothes to be dried based on a weight of a safe range of a heating temperature of the clothes to be dried and a weight of a humidity level of the clothes to be dried; The initialization temperature unit calculates an initialization temperature range of the clothes to be dried according to a comprehensive weight of the clothes to be dried and a heating temperature limit range of the clothes to be dried.
7. A heating dynamic control system for a clothes dryer according to claim 5, characterized in that: The dynamic temperature generation module includes: A preheating time unit, which heats the dryer based on the real-time dynamic heating temperature parameters of the dryer, collects real-time operating data in the dryer, and predicts the heating time of the clothes to be dried in the dryer; A restriction condition unit, based on an initialization temperature range of the clothes to be dried of the clothes dryer, taking the initialization temperature range of the clothes to be dried per unit time as a heating restriction condition; An objective function unit, based on the heating restriction condition and in accordance with the real-time humidity of the clothes to be dried, constructs an objective function to maximize the optimal heating temperature for all the clothes to be dried; The model building unit builds a dynamic heating control model of the dryer based on the RNN recursive neural network; The dynamic temperature generation unit, based on the dynamic heating control model of the dryer, takes the real-time operating environment data in the dryer and the heating time of the clothes to be dried as input and the dynamic heating temperature parameters of the clothes to be dried in the dryer as output according to the objective function under the heating restriction condition.
8. A heating dynamic control system for a clothes dryer according to claim 5, characterized in that: The preheating time unit includes: An environmental data collection subunit heats the dryer based on the real-time dynamic heating temperature parameters of the dryer and collects real-time operating data in the dryer; A humidity prediction subunit, based on the real-time operation data in the clothes dryer, predicts the humidity data of the clothes to be dried in the next unit time according to the heating temperature per unit time in the real-time operation data; The temperature prediction subunit substitutes the humidity data of the clothes to be dried in the next unit time into the dynamic heating control model of the clothes dryer to determine the heating temperature of the clothes to be dried in the next unit time; The regression prediction subunit takes the unit time as the observation window, the heating temperature of the clothes to be dried in the next unit time as the independent variable, and the humidity data of the clothes to be dried in the next unit time as the dependent variable, constructs a heating time estimation model for the clothes to be dried, and predicts the heating time of the clothes to be dried in the dryer.