Electric fan, control method and device thereof, storage medium and program product

Abstract

The invention discloses an electric fan control method and device, an electric fan, a storage medium and a computer program product, and the method comprises the following steps: carrying out data fitting according to pre-stored sample data to obtain a relational expression among a comfort parameter, a human body temperature and an electric fan wind speed; the comfort parameters are used for evaluating whether the human body is in a comfortable state; the current human body temperature and the current wind speed of the electric fan are substituted into a relational expression between the comfort parameter and the human body temperature and the wind speed of the electric fan, and a current comfort parameter is obtained through calculation; and controlling the wind speed of the electric fan according to the current comfort parameter. According to the scheme, the comfort parameter is calculated by combining the human body temperature and the wind speed of the electric fan, the wind speed of the electric fan is controlled according to the comfort parameter, a user is always in a comfortable state, and use experience is improved.

Description

Technical Field

[0001] The present invention belongs to the field of electric fans, and specifically relates to a control method, device, electric fan, storage medium and computer program product of an electric fan, and more particularly to a control method, device, electric fan, storage medium and computer program product that change the wind speed of an electric fan according to human body temperature. Background Art

[0002] For automatic adjustment of the fan speed, the relevant solution is to adjust the fan speed according to the ambient temperature. However, when a person moves from a hot environment to a colder environment where the fan is located, the human body surface temperature is high and needs to be lowered, and the fan needs to be set to a high speed. At this time, the ambient temperature is low, that is, there is a large difference between the ambient temperature and the human body surface temperature. If the fan speed is adjusted according to the ambient temperature, it cannot be accurately adjusted to the required wind speed, resulting in a poor user experience.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The object of the present invention is to provide a control method and device for an electric fan, an electric fan, a storage medium and a computer program product, so as to solve the problem in related schemes that the wind speed of the electric fan cannot be accurately adjusted to the required wind speed when the difference between the ambient temperature and the human body surface temperature is large, so as to achieve the purpose of calculating the comfort parameters by combining the human body temperature and the electric fan wind speed, and controlling the wind speed of the electric fan according to the comfort parameters, so that the user is always in a comfortable state and the use experience is improved.

[0005] The present invention provides a method for controlling an electric fan, the method comprising: when the electric fan is running, obtaining the current human body temperature and the current wind speed of the electric fan; performing data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; the current human body temperature and the current wind speed of the electric fan are introduced into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; and controlling the wind speed of the electric fan according to the size of the current comfort parameter.

[0006] In some embodiments, data fitting is performed according to pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature, and the electric fan, including: performing linear regression fitting according to a preset average thermal sensation index, a preset wind sensation index, and a preset thermal sensation voting index to obtain an evaluation model for the comfort parameter; the evaluation model for the comfort parameter is:

[0007] P = a*PMV+b*TSV+c*DR;

[0008] Wherein, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index;

[0009] According to the evaluation model of the comfort parameter and the pre-stored sample data, data fitting is performed to obtain a relationship between the comfort parameter, the current human body temperature, and the current wind speed of the electric fan; the relationship between the comfort parameter, the current human body temperature, and the current wind speed of the electric fan is:

[0010] P=a1+b1*t+c1*v

[0011] Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters; t is the human body temperature; v is the wind speed of the electric fan.

[0012] In some embodiments, the wind speed of the electric fan is controlled according to the current size of the comfort parameter, including: after obtaining the current comfort parameter, correcting the current comfort parameter to obtain the corrected comfort parameter; and controlling the wind speed of the electric fan according to the size of the corrected comfort parameter.

[0013] In some embodiments, the current comfort parameter is corrected to obtain the corrected comfort parameter, including: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0014] In some embodiments, the wind speed of the electric fan is controlled according to the size of the corrected comfort parameter, including: judging the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, reducing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value>the second preset value.

[0015] Matching the above method, the present invention provides a control device for an electric fan on the other hand, the control device comprising: an acquisition unit, configured to acquire the current human body temperature and the current wind speed of the electric fan when the electric fan is running; a calculation unit, configured to perform data fitting based on pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; the calculation unit is also configured to bring the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan to calculate the current comfort parameter; a control unit, configured to control the wind speed of the electric fan according to the size of the current comfort parameter.

[0016] In some embodiments, the calculation unit performs data fitting according to pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature, and the electric fan, including: performing linear regression fitting according to a preset average thermal sensation index, a preset blowing sensation index, and a preset thermal sensation voting index to obtain an evaluation model for the comfort parameter; the evaluation model for the comfort parameter is:

[0017] P = a*PMV+b*TSV+c*DR;

[0018] Wherein, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index;

[0019] According to the evaluation model of the comfort parameter and the pre-stored sample data, data fitting is performed to obtain a relationship between the comfort parameter, the current human body temperature, and the current wind speed of the electric fan; the relationship between the comfort parameter, the current human body temperature, and the current wind speed of the electric fan is:

[0020] P=a1+b1*t+c1*v

[0021] Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters; t is the human body temperature; v is the wind speed of the electric fan.

[0022] In some embodiments, the control unit controls the wind speed of the electric fan according to the current size of the comfort parameter, including: after obtaining the current comfort parameter, correcting the current comfort parameter to obtain the corrected comfort parameter; controlling the wind speed of the electric fan according to the size of the corrected comfort parameter.

[0023] In some embodiments, the control unit corrects the current comfort parameter to obtain the corrected comfort parameter, including: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0024] In some embodiments, the control unit controls the wind speed of the electric fan according to the size of the corrected comfort parameter, including: judging the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, reducing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value>the second preset value.

[0025] Matching the above device, the present invention provides an electric fan on another aspect, including: the control device of the electric fan described above.

[0026] Matching the above method, the present invention provides a storage medium on another aspect, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the above-mentioned electric fan control method.

[0027] Matching the above method, the present invention provides a computer program product on another aspect, wherein the computer program product includes a computer program, and when the computer program product is processed and executed, the steps of the above electric fan control method are implemented.

[0028] The solution of the present invention performs data fitting based on pre-stored sample data of human body temperature and electric fan wind speed to obtain a relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by calculating the comfort parameter in combination with the human body temperature and the electric fan wind speed, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0029] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present invention.

[0030] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic flow chart of an embodiment of a method for controlling an electric fan of the present invention;

[0032] Figure 2 It is a structural schematic diagram of an embodiment of a control device for an electric fan of the present invention;

[0033] Figure 3 It is a structural block diagram of the control system of the electric fan of the present invention;

[0034] Figure 4 It is a flow chart of the wind speed control method of the electric fan of the present invention.

[0035] In conjunction with the accompanying drawings, the reference numerals in the embodiments of the present invention are as follows:

[0036] 101 - acquisition unit; 102 - calculation unit; 103 - control unit. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. 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 making creative work are within the scope of protection of the present invention.

[0038] According to an embodiment of the present invention, a method for controlling an electric fan is provided. Figure 1 The flowchart of an embodiment of the method of the present invention is shown in FIG. The control method of the electric fan may include: steps S110 to S140.

[0039] In step S110, when the electric fan is running, the current human body temperature and the current wind speed of the electric fan are obtained.

[0040] In step S120, data fitting is performed based on pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state.

[0041] The pre-stored human body temperature and pre-stored electric fan wind speed for data fitting may be experimental data, historical data, simulation data, user-input data, etc., or may be real-time detected data.

[0042] In some implementations, in step S120, the specific process of performing data fitting based on pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature, and the electric fan includes: step S210 and step S220.

[0043] Step S210, performing linear regression fitting according to a preset average thermal sensation index, a preset wind sensation index, and a preset thermal sensation voting index to obtain an evaluation model of the comfort parameter.

[0044] The evaluation model of the comfort parameter is:

[0045] P = a*PMV+b*TSV+c*DR;

[0046] Among them, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index.

[0047] In order to accurately determine the impact of electric fan wind speed on user comfort, this scheme combines the average thermal sensation index PMV, thermal sensation voting index TSV, and wind sensation index DR for linear regression fitting to obtain a comfort parameter evaluation model.

[0048] The Predicted Mean Vote (PMV) index is a comprehensive evaluation index based on the basic equation of human thermal balance and the level of subjective thermal sensation in psychophysiology, and takes into account many factors related to human thermal comfort. Its theoretical basis is that when the human body is in a steady-state thermal environment, the greater the heat load of the human body, the further the human body deviates from the state of thermal comfort. That is, the greater the positive value of the human body's heat load, the hotter the person feels, and the greater the negative value, the colder the person feels. The calculation formula of PMV is:

[0049]

[0050] In the formula, M is the energy metabolism rate of the human body, which depends on the amount of human activity and is expressed in W / m 2 ; W is the mechanical work done by the human body, the unit is W / m 2 ;P a is the partial pressure of water vapor around the human body, in kPa; t a is the air temperature around the human body, in °C; t cl is the clothing surface temperature, in °C; cl It is the ratio of a person's body surface area when clothed to that when naked; is the mean radiation temperature, in °C; h c is the convective heat transfer coefficient, in W / (m2 ℃); l cl is the thermal resistance of clothing, in units of (m 2 ℃ / W); v ar is the air velocity in m / s.

[0051] The draft rating index (DR) is an indicator of the user's dissatisfaction caused by the draft. The draft rating index depends on the airflow speed, temperature, turbulence intensity, and the user's activity and clothing. The calculation formula of the draft rating index DR is:

[0052] DR j =(34-t a )(v a -0.05) 0.62 (3.37×v a ×T u +3.14);

[0053] In the formula, t a is the average air temperature around the human body, in °C; v a is the air velocity in m / s. If v a ≤0.05m / s, then take v a =0.05m / s; T u is the local turbulence intensity, %, that is, the ratio of the standard deviation of the local air velocity to the local average air velocity, between 10% and 60%. If it is unknown, it can be taken as 40%. The calculation method is:

[0054]

[0055] Among them, N v is the number of wind speeds recorded at the measuring point within the specified time, v ai is the local instantaneous air velocity at the i-th moment, in m / s.

[0056] The Thermal Sensation Vote (TSV) is obtained through a questionnaire survey, where participants are asked to rate the current environment and find the average value: 3, hot; 2, warm; 1, slightly warm; 0, moderate, -1, slightly cool; -2, cool, -3, cold. The TSV is calculated by fitting the questionnaire results at different temperatures and the wind speed during the experience. The TSV data fitting process is as follows:

[0057]

[0058] By combining the average thermal sensation index PMV, the thermal sensation voting index TSV, and the blowing sensation index DR for linear regression fitting, an evaluation model of comfort parameters is obtained. Then, the comfort parameters are calculated according to the human body temperature and environmental conditions to control the speed of the electric fan, thereby improving the accuracy of control and making users feel comfortable.

[0059] Step S220, performing data fitting according to the evaluation model of the comfort parameter and the pre-stored sample data, and obtaining a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan.

[0060] The relationship between the comfort parameter, the current human body temperature and the current wind speed of the electric fan is:

[0061] P=a1+b1*t+c1*v

[0062] Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters, and the value range is related to the ambient humidity; t is the human body temperature; v is the wind speed of the electric fan.

[0063] The comfort parameter P is regressed with the human body temperature t and the fan speed v to obtain the calculation formula of the comfort parameter. Under different humidity ranges, the value ranges of parameters a1, b1, and c1 are different, specifically:

[0064] When the ambient humidity is less than 30%, a1∈[-7.2, -6.9), b1∈[0.2, 0.32], c1∈[-0.04, -0.06].

[0065] When the ambient humidity is in the interval of [30%, 40%], a1∈[-7.25, -7.06), b1∈[0.22, 0.34], c1∈[-0.059, -0.048].

[0066] When the ambient humidity is in the interval of [40%, 50%], a1∈[-7.38, -7.12), b1∈[0.28, 0.35], c1∈[-0.058, -0.049].

[0067] When the ambient humidity is in the interval of [50%, 60%], a1∈[-7.32, -7.19), b1∈[0.26, 0.31], c1∈[-0.057, -0.05].

[0068] When the ambient humidity is in the interval of [60%, 70%], a1∈[-7.45, -7.3), b1∈[0.29, 0.36], c1∈[-0.056, -0.051].

[0069] When the ambient humidity is in the interval of [70%, 80%], a6∈[-7.52, -7.39), b6∈[0.27, 0.41], c6∈[-0.053, -0.052].

[0070] When performing linear regression fitting on the comfort parameters, human body temperature, and fan speed, in order to reflect the difference between the predicted results and the actual data, a loss function can be introduced to guide the model training process, and then adjust the model to improve the accuracy of the model. Specifically, if the objective function is P(x) = ap(x) + b, the loss function is:

[0071]

[0072] The loss function is derived with respect to a and b respectively, so that the derivative result is equal to 0, which is the extreme value, then:

[0073]

[0074] Optimization using gradient descent:

[0075]

[0076] α is the learning rate. By calculating the gradient of the loss function to the model parameters, the update direction and step size of the parameters can be determined to optimize the model.

[0077] In step S130, the current human body temperature and the current wind speed of the electric fan are brought into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan, and the current comfort parameter is calculated.

[0078] In step S140, the wind speed of the electric fan is controlled according to the current size of the comfort parameter.

[0079] In some implementations, in step S140, the specific process of controlling the wind speed of the electric fan according to the current size of the comfort parameter includes: step S310 and step S320.

[0080] Step S310: after obtaining the current comfort parameter, correct the current comfort parameter to obtain the corrected comfort parameter.

[0081] In some embodiments, in step S310, the current comfort parameters are corrected to obtain the corrected comfort parameters, and the specific process includes: determining whether the current comfort parameters are within a preset range; if the current comfort parameters are within the preset range, the corrected comfort parameters are equal to the current comfort parameters; if the current comfort parameters are not within the preset range and are greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameters; if the current comfort parameters are not within the preset range and are less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameters.

[0082] The value range of the comfort parameter is [-3, 3]. If the comfort parameter calculated based on the current human body temperature and the fan speed is within [-3, 3], the fan speed is controlled according to the comfort parameter. If the calculated comfort parameter is greater than 3, the comfort parameter is adjusted to 3; if the calculated comfort parameter is less than -3, the comfort parameter is adjusted to -3. By limiting the range of the comfort parameter, the user experience is not affected by the amplitude of adjusting the fan speed.

[0083] Step S320: controlling the wind speed of the electric fan according to the corrected comfort parameter.

[0084] In some embodiments, in step S320, the specific process of controlling the wind speed of the electric fan according to the size of the corrected comfort parameter includes: judging the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, reducing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value>the second preset value.

[0085] The first preset value can be set to 1, and the second preset value can be set to -1. The numerical value of the comfort parameter reflects the current body temperature state of the user. When the comfort parameter is greater than 1, it is considered that the user's body surface temperature is high, and the wind speed of the electric fan is increased to quickly cool down; when the comfort parameter is less than -1, it is considered that the user's body surface temperature is low, and the wind speed of the electric fan is reduced to avoid the user feeling uncomfortable; when 1 ≥ comfort parameter ≥ -1, it is considered that the user's body surface temperature is normal, and the wind speed of the electric fan can be maintained unchanged. The adjustment amount for increasing and decreasing the wind speed of the electric fan can be set according to actual conditions, for example, the adjustment amount is one wind gear.

[0086] After adjusting the wind speed of the electric fan according to the size of the comfort parameter, the user's body surface temperature and the ambient temperature and humidity are re-detected after a period of time, and the comfort parameter is calculated to determine whether to adjust the wind speed of the electric fan.

[0087] By real-time monitoring of human body temperature and ambient temperature and humidity, the fan speed is dynamically adjusted to ensure that the user feels neither too cold nor too hot, thus achieving the best comfort state. Not only the impact of temperature on comfort is taken into account, but also the effect of humidity, making the adjustment of the fan more intelligent and meeting the user's comfort needs under various temperature and humidity conditions.

[0088] Figure 4 FIG. 1 is a flow chart of a method for controlling the wind speed of an electric fan according to the present invention. Figure 4 As shown, the method includes:

[0089] Step 1: The infrared image sensor on the electric fan obtains the human body temperature and the current wind speed value of the electric fan, and calculates the comfort parameter P according to the human body temperature and the wind speed value.

[0090] Step 2, determine the range of the comfort parameter P. If P>1, increase the wind speed of the electric fan; if P<-1, reduce the wind speed of the electric fan; if 1≥P≥-1, keep the current wind speed unchanged.

[0091] The technical solution of this embodiment is adopted to perform data fitting based on the pre-stored sample data of human body temperature and electric fan wind speed to obtain the relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by combining the human body temperature and the electric fan wind speed to calculate the comfort parameter, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0092] According to an embodiment of the present invention, a control device for an electric fan corresponding to the control method for an electric fan is also provided. Figure 2 The schematic diagram of the structure of an embodiment of the device of the present invention is shown. The control device of the electric fan may include: an acquisition unit 101, a calculation unit 102, and a control unit 103.

[0093] The acquisition unit 101 is configured to acquire the current human body temperature and the current wind speed of the electric fan when the electric fan is running. The specific functions and processing of the acquisition unit 101 refer to step S110.

[0094] The calculation unit 102 is configured to perform data fitting according to the pre-stored sample data to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state. The specific functions and processing of the calculation unit 102 refer to step S120.

[0095] The pre-stored human body temperature and pre-stored electric fan wind speed for data fitting may be experimental data, historical data, simulation data, user-input data, etc., or may be real-time detected data.

[0096] In some implementations, the calculation unit 102 performs data fitting according to pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature, and the electric fan, including:

[0097] The calculation unit 102 is further configured to perform linear regression fitting according to the preset average thermal sensation index, the preset wind sensation index, and the preset thermal sensation voting index to obtain the evaluation model of the comfort parameter. The specific functions and processing of the calculation unit 102 refer to step S210.

[0098] The evaluation model of the comfort parameter is:

[0099] P = a*PMV+b*TSV+c*DR;

[0100] Among them, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index.

[0101] In order to accurately determine the impact of electric fan wind speed on user comfort, this scheme combines the average thermal sensation index PMV, thermal sensation voting index TSV, and wind sensation index DR for linear regression fitting to obtain a comfort parameter evaluation model.

[0102] The Predicted Mean Vote (PMV) index is a comprehensive evaluation index based on the basic equation of human thermal balance and the level of subjective thermal sensation in psychophysiology, and takes into account many factors related to human thermal comfort. Its theoretical basis is that when the human body is in a steady-state thermal environment, the greater the heat load of the human body, the further the human body deviates from the state of thermal comfort. That is, the greater the positive value of the human body's heat load, the hotter the person feels, and the greater the negative value, the colder the person feels. The calculation formula of PMV is:

[0103]

[0104] In the formula, M is the energy metabolism rate of the human body, which depends on the amount of human activity and is expressed in W / m 2; W is the mechanical work done by the human body, the unit is W / m 2 ;P a is the partial pressure of water vapor around the human body, in kPa; t a is the air temperature around the human body, in °C; t cl is the clothing surface temperature, in °C; cl It is the ratio of a person's body surface area when clothed to that when naked; is the mean radiation temperature, in °C; h c is the convective heat transfer coefficient, in W / (m 2 ℃); l cl is the thermal resistance of clothing, in units of (m 2 ℃ / W); v ar is the air velocity in m / s.

[0105] The draft rating index (DR) is an indicator of the user's dissatisfaction caused by the draft. The draft rating index depends on the airflow speed, temperature, turbulence intensity, and the user's activity and clothing. The calculation formula of the draft rating index DR is:

[0106] DR j =(34-t a )(v a -0.05) 0.62 (3.37×v a ×T u +3.14);

[0107] In the formula, t a is the average air temperature around the human body, in °C; v a is the air velocity in m / s. If v a ≤0.05m / s, then take v a =0.05m / s; T u is the local turbulence intensity, %, that is, the ratio of the standard deviation of the local air velocity to the local average air velocity, between 10% and 60%. If it is unknown, it can be taken as 40%. The calculation method is:

[0108]

[0109] Among them, N v is the number of wind speeds recorded at the measuring point within the specified time, v ai is the local instantaneous air velocity at the i-th moment, in m / s.

[0110] The Thermal Sensation Vote (TSV) index is obtained through a questionnaire survey, where participants are asked to rate the current environment and find the average value: 3, hot; 2, warm; 1, slightly warm; 0, moderate, -1, slightly cool; -2, cool, -3, cold. The TSV is calculated by fitting the questionnaire results at different temperatures and the wind speed during the experience. The data fitting process is as follows:

[0111]

[0112] By combining the average thermal sensation index PMV, the thermal sensation voting index TSV, and the blowing sensation index DR for linear regression fitting, an evaluation model of comfort parameters is obtained. Then, the comfort parameters are calculated according to the human body temperature and environmental conditions to control the speed of the electric fan, thereby improving the accuracy of control and making users feel comfortable.

[0113] The calculation unit 102 is further configured to perform data fitting according to the evaluation model of the comfort parameter and the pre-stored sample data to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan. The specific functions and processing of the calculation unit 102 refer to step S220.

[0114] The relationship between the comfort parameter, the current human body temperature and the current wind speed of the electric fan is:

[0115] P=a1+b1*t+c1*v

[0116] Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters, and the value range is related to the ambient humidity; t is the human body temperature; v is the wind speed of the electric fan.

[0117] The comfort parameter P is regressed with the human body temperature t and the fan speed v to obtain the calculation formula of the comfort parameter. Under different humidity ranges, the value ranges of parameters a1, b1, and c1 are different, specifically:

[0118] When the ambient humidity is less than 30%, a1∈[-7.2, -6.9), b1∈[0.2, 0.32], c1∈[-0.04, -0.06].

[0119] When the ambient humidity is in the interval of [30%, 40%], a1∈[-7.25, -7.06), b1∈[0.22, 0.34], c1∈[-0.059, -0.048].

[0120] When the ambient humidity is in the interval of [40%, 50%], a1∈[-7.38, -7.12), b1∈[0.28, 0.35], c1∈[-0.058, -0.049].

[0121] When the ambient humidity is in the interval of [50%, 60%], a1∈[-7.32, -7.19), b1∈[0.26, 0.31], c1∈[-0.057, -0.05].

[0122] When the ambient humidity is in the interval of [60%, 70%], a1∈[-7.45, -7.3), b1∈[0.29, 0.36], c1∈[-0.056, -0.051].

[0123] When the ambient humidity is in the interval of [70%, 80%], a6∈[-7.52, -7.39), b6∈[0.27, 0.41], c6∈[-0.053, -0.052].

[0124] When performing linear regression fitting on the comfort parameters, human body temperature, and fan speed, in order to reflect the difference between the predicted results and the actual data, a loss function can be introduced to guide the model training process, and then adjust the model to improve the accuracy of the model. Specifically, if the objective function is P(x) = ap(x) + b, the loss function is:

[0125]

[0126] The loss function is derived with respect to a and b respectively, so that the derivative result is equal to 0, which is the extreme value, then:

[0127]

[0128] Optimization using gradient descent:

[0129]

[0130]

[0131] α is the learning rate. By calculating the gradient of the loss function to the model parameters, the update direction and step size of the parameters can be determined to optimize the model.

[0132] The calculation unit 102 is further configured to bring the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan, and calculate the current comfort parameter. The specific function and processing of the calculation unit 102 refer to step S130.

[0133] The control unit 103 is configured to control the wind speed of the electric fan according to the current size of the comfort parameter. The specific functions and processing of the control unit 103 refer to step S140.

[0134] In some implementations, the control unit 103 controls the wind speed of the electric fan according to the current size of the comfort parameter, including:

[0135] The control unit 103 is further configured to correct the current comfort parameter after obtaining the current comfort parameter to obtain the corrected comfort parameter. The specific functions and processing of the control unit 103 refer to step S310.

[0136] In some embodiments, the control unit 103 corrects the current comfort parameter to obtain the corrected comfort parameter, including: determining whether the current comfort parameter is within a preset range; if the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; if the current comfort parameter is not within the preset range and is greater than the upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; if the current comfort parameter is not within the preset range and is less than the lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

[0137] The value range of the comfort parameter is [-3, 3]. If the comfort parameter calculated based on the current human body temperature and the fan speed is within [-3, 3], the fan speed is controlled according to the comfort parameter. If the calculated comfort parameter is greater than 3, the comfort parameter is adjusted to 3; if the calculated comfort parameter is less than -3, the comfort parameter is adjusted to -3. By limiting the range of the comfort parameter, the user experience is not affected by the amplitude of adjusting the fan speed.

[0138] The control unit 103 is further configured to control the wind speed of the electric fan according to the corrected comfort parameter. The specific functions and processing of the control unit 103 refer to step S320.

[0139] In some embodiments, the control unit 103 controls the wind speed of the electric fan according to the size of the corrected comfort parameter, including: judging the size of the corrected comfort parameter; if the corrected comfort parameter is greater than a first preset value, increasing the wind speed of the electric fan; if the corrected comfort parameter is less than a second preset value, reducing the wind speed of the electric fan; if the corrected comfort parameter is between the first preset value and the second preset value, keeping the wind speed of the electric fan unchanged; the first preset value>the second preset value.

[0140] The first preset value can be set to 1, and the second preset value can be set to -1. The numerical value of the comfort parameter reflects the current body temperature state of the user. When the comfort parameter is greater than 1, it is considered that the user's body surface temperature is high, and the wind speed of the electric fan is increased to quickly cool down; when the comfort parameter is less than -1, it is considered that the user's body surface temperature is low, and the wind speed of the electric fan is reduced to avoid the user feeling uncomfortable; when 1 ≥ comfort parameter ≥ -1, it is considered that the user's body surface temperature is normal, and the wind speed of the electric fan can be maintained unchanged. The adjustment amount for increasing and decreasing the wind speed of the electric fan can be set according to actual conditions, for example, the adjustment amount is one wind gear.

[0141] After adjusting the wind speed of the electric fan according to the size of the comfort parameter, the user's body surface temperature and the ambient temperature and humidity are re-detected after a period of time, and the comfort parameter is calculated to determine whether to adjust the wind speed of the electric fan.

[0142] By real-time monitoring of human body temperature and ambient temperature and humidity, the fan speed is dynamically adjusted to ensure that the user feels neither too cold nor too hot, thus achieving the best comfort state. Not only the impact of temperature on comfort is taken into account, but also the effect of humidity, making the adjustment of the fan more intelligent and meeting the user's comfort needs under various temperature and humidity conditions.

[0143] Figure 4 FIG. 1 is a flow chart of a method for controlling the wind speed of an electric fan according to the present invention. Figure 4 As shown, the method includes:

[0144] Step 1: The infrared image sensor on the electric fan obtains the human body temperature and the current wind speed value of the electric fan, and calculates the comfort parameter P according to the human body temperature and the wind speed value.

[0145] Step 2, determine the range of the comfort parameter P. If P>1, increase the wind speed of the electric fan; if P<-1, reduce the wind speed of the electric fan; if 1≥P≥-1, keep the current wind speed unchanged.

[0146] Since the processing and functions implemented by the device of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for the details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments, and no further elaboration will be made here.

[0147] The technical solution of the present invention is adopted to perform data fitting based on the pre-stored sample data of human body temperature and electric fan wind speed to obtain the relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by combining the human body temperature and the electric fan wind speed to calculate the comfort parameter, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0148] According to an embodiment of the present invention, an electric fan corresponding to the control device of the electric fan is also provided. The electric fan may include: the control device of the electric fan described above.

[0149] Since the processing and functions implemented by the electric fan of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned device, for the details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments, and no further elaboration will be made here.

[0150] The technical solution of the present invention is adopted to perform data fitting based on the pre-stored sample data of human body temperature and electric fan wind speed to obtain the relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by combining the human body temperature and the electric fan wind speed to calculate the comfort parameter, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0151] According to an embodiment of the present invention, a storage medium corresponding to the electric fan control method is also provided, wherein the storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the electric fan control method described above.

[0152] Since the processing and functions implemented by the storage medium of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for the details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments, and no further elaboration will be made here.

[0153] The technical solution of the present invention is adopted to perform data fitting based on the pre-stored sample data of human body temperature and electric fan wind speed to obtain the relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by combining the human body temperature and the electric fan wind speed to calculate the comfort parameter, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0154] According to an embodiment of the present invention, a computer program product corresponding to the electric fan control method is also provided. The computer program product includes a computer program. When the computer program product is processed and executed, the steps of the electric fan control method are implemented.

[0155] Since the processing and functions implemented by the computer program product of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for the details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here.

[0156] The technical solution of the present invention is adopted to perform data fitting based on the pre-stored sample data of human body temperature and electric fan wind speed to obtain the relationship between the comfort parameter, human body temperature and electric fan wind speed; then the current human body temperature and the current electric fan wind speed are introduced into the relationship to obtain the current comfort parameter; the wind speed of the electric fan is controlled according to the size of the comfort parameter. Thus, by combining the human body temperature and the electric fan wind speed to calculate the comfort parameter, and controlling the wind speed of the electric fan according to the comfort parameter, the user is always in a comfortable state, and the use experience is improved.

[0157] In summary, it is easy for those skilled in the art to understand that, under the premise of no conflict, the above-mentioned advantageous methods can be freely combined and superimposed.

[0158] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of the claims of the present invention.

Claims

1. A method for controlling an electric fan, characterized in that: The method comprises: When the electric fan is running, obtaining the current human body temperature and the current wind speed of the electric fan; Performing data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; the sample data includes human body temperature sample data and electric fan wind speed sample data; Substituting the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan, and calculating the current comfort parameter; The wind speed of the electric fan is controlled according to the current size of the comfort parameter.

2. The control method of the electric fan according to claim 1, characterized in that: Data fitting is performed according to the pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature and the electric fan, including: According to the preset average thermal sensation index, the preset wind sensation index, and the preset thermal sensation voting index, a linear regression fitting is performed to obtain the evaluation model of the comfort parameter; the evaluation model of the comfort parameter is: P = a*PMV+b*TSV+c*DR; Wherein, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index; According to the evaluation model of the comfort parameter and the pre-stored sample data, data fitting is performed to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is: P=a1+b1*t+c1*v Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters; t is the human body temperature; v is the wind speed of the electric fan.

3. The control method of the electric fan according to claim 1 or 2, characterized in that: Controlling the wind speed of the electric fan according to the current size of the comfort parameter includes: After obtaining the current comfort parameter, correcting the current comfort parameter to obtain the corrected comfort parameter; The wind speed of the electric fan is controlled according to the size of the corrected comfort parameter.

4. The control method of the electric fan according to claim 3, characterized in that: Correcting the current comfort parameter to obtain the corrected comfort parameter includes: Determining whether the current comfort parameter is within a preset range; If the current comfort parameter is within the preset range, the corrected comfort parameter is equal to the current comfort parameter; If the current comfort parameter is not within the preset range and is greater than an upper limit value of the preset range, the upper limit value of the preset range is determined as the corrected comfort parameter; If the current comfort parameter is not within the preset range and is less than a lower limit value of the preset range, the lower limit value of the preset range is determined as the corrected comfort parameter.

5. The control method of the electric fan according to claim 3 or 4, characterized in that: Controlling the wind speed of the electric fan according to the corrected comfort parameter includes: Determining the magnitude of the modified comfort parameter; If the modified comfort parameter is greater than the first preset value, increasing the wind speed of the electric fan; If the modified comfort parameter is less than the second preset value, reducing the wind speed of the electric fan; If the modified comfort parameter is between the first preset value and the second preset value, the wind speed of the electric fan is kept unchanged; the first preset value>the second preset value.

6. A control device for an electric fan, characterized in that: The control device comprises: An acquisition unit is configured to acquire a current human body temperature and a current wind speed of the electric fan when the electric fan is running; A calculation unit is configured to perform data fitting according to pre-stored sample data to obtain a relationship between a comfort parameter and the current human body temperature and the current wind speed of the electric fan; the comfort parameter is used to evaluate whether the human body is in a comfortable state; The calculation unit is further configured to bring the current human body temperature and the current wind speed of the electric fan into the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan, and calculate the current comfort parameter; The control unit is configured to control the wind speed of the electric fan according to the current size of the comfort parameter.

7. The control device for the electric fan according to claim 6, characterized in that: The calculation unit performs data fitting according to the pre-stored sample data to obtain a relationship between the comfort parameter, the human body temperature and the electric fan, including: According to the preset average thermal sensation index, the preset wind sensation index, and the preset thermal sensation voting index, a linear regression fitting is performed to obtain the evaluation model of the comfort parameter; the evaluation model of the comfort parameter is: P = a*PMV+b*TSV+c*DR; Wherein, P is the comfort parameter; a, b, c are all preset parameters; PMV is the average thermal sensation index; TSV is the thermal sensation voting index; DR is the wind sensation index; According to the evaluation model of the comfort parameter and the pre-stored sample data, data fitting is performed to obtain a relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan; the relationship between the comfort parameter and the current human body temperature and the current wind speed of the electric fan is: P=a1+b1*t+c1*v Among them, P is the comfort parameter; a1, b1, c1 are all preset parameters; t is the human body temperature; v is the wind speed of the electric fan.

8. An electric fan, characterized in that: include: A control device for an electric fan as claimed in claim 6 or 7.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the control method of the electric fan according to any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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