JP2021094285A - Air blower - Google Patents

Abstract

To provide a technique for increasing prediction accuracy of a time to complete drying of an object.SOLUTION: A temperature sensing unit 80 senses a temperature in a predetermined space, a moisture sensing unit 82 senses a humidity in the predetermined space, a moisture quantity calculation unit 56 calculates a moisture quantity in an object in the predetermined space, and a distance calculation unit 58 calculates a distance to the object. A moisture quantity prediction unit 60 predicts a moisture quantity transition of the object from the time of the calculation by the moisture quantity calculation unit 56 to until after a predetermined time period on the basis of the temperature, the humidity, the moisture quantity, and the distance. A dry prediction unit 62 predicts a dry completion time on the basis of the moisture quantity transition predicted by the moisture quantity prediction unit 60. An air blow control unit 57 causes air to be blown from an air outlet in accordance with the dry completion time predicted by the dry prediction unit 62.SELECTED DRAWING: Figure 3

Description

The present disclosure relates to a blower used to dry an object.

A bathroom heater / dryer is known as a blower device for preventing the generation of mold in the bathroom or indoors. A process of removing water droplets adhering to the wall surface is required to suppress the growth of mold, but it is necessary to operate for a long time to completely remove the water by blowing air control, and the high humidity air that fills the room. It takes a lot of energy to dry the wall surface, such as water droplets on the wall surface. As for the control device of this type of blower, as described in Patent Document 1, a mold determination method for determining how much mold is growing using a table of mold index values consisting of temperature, humidity and measurement time interval. There is a method of optimally controlling the drying operation by using a mold determining means using.

Japanese Unexamined Patent Publication No. 2009-186133

With the drying operation control method in such a blower, the amount of water droplets existing from the initial stage and the generation of water droplets due to dew condensation on the wall surface cannot be detected, and the water droplets remain on a part of the wall surface. Judge that mold does not occur and stop the drying operation. Since mold grows from the place where moisture exists, it is difficult to accurately determine the mold growth from the ambient temperature and humidity and the measurement time interval, and it is necessary to improve the prediction accuracy of the drying end time of the object. ..

The present disclosure has been made to solve the above problems, and an object of the present disclosure is to provide a technique for improving the accuracy of predicting the drying end time of an object.

In order to solve the above problems, the blower device of a certain aspect of the present disclosure includes a temperature detection unit that detects the temperature of a predetermined space, a humidity detection unit that detects the humidity of a predetermined space, and an object in the predetermined space. Determined from the time of calculation by the water content calculation unit based on the water content calculation unit that calculates the water content of the object, the distance calculation unit that calculates the distance to the object, and the temperature, humidity, water content, and distance. A moisture amount prediction unit that predicts the transition of the moisture content of the object until after time, a drying prediction unit that predicts the drying end time based on the transition of the moisture content predicted by the moisture content prediction unit, and a drying prediction unit. It is provided with a blower control unit for blowing air from the air outlet according to the drying end time predicted in the above.

It should be noted that any combination of the above components and the conversion of the expression of the present disclosure between methods, devices, systems, recording media, computer programs and the like are also effective as aspects of the present disclosure.

According to the present disclosure, the accuracy of predicting the drying end time of the object can be improved.

It is sectional drawing which shows the schematic structure of the bathroom dryer which concerns on this Example. It is a schematic diagram which shows the structure and the object of the light emitting part and the light receiving part of the bathroom dryer of FIG. It is a block diagram which shows the control structure of the bathroom dryer of FIG. It is a figure which shows the absorption spectrum of moisture and water vapor. It is a schematic diagram which shows the detection range and the unit area of the bathroom dryer of FIG. It is a schematic diagram which shows the scanning direction of the light emitting part and the light receiving part of the bathroom dryer of FIG. It is a figure which shows the table of the water content distribution of the bathroom dryer of FIG. It is a flowchart of the water content calculation of the bathroom dryer of FIG. It is a figure which shows the table of the distance distribution of the bathroom dryer of FIG. It is a block diagram which shows the structure of the water content prediction part of FIG. 11 (a)-(c) is a diagram showing an outline of processing by the water content prediction unit of FIG. 10. It is a figure which shows the outline of processing by the moisture content prediction part and the dryness prediction part of FIG. It is a figure which shows the processing result of the dryness prediction part of FIG. It is a flowchart which shows the prediction procedure by the bathroom dryer of FIG.

Hereinafter, the blower device according to the embodiment of the present disclosure will be described in detail with reference to the drawings. Each of the examples described below shows a preferred specific example of the present disclosure. Therefore, the numerical values, shapes, materials, components, arrangement of components, connection forms, etc. shown in the following examples are examples, and are not intended to limit the present disclosure. Therefore, among the components in the following examples, the components not described in the independent claims indicating the highest level concept of the present disclosure will be described as arbitrary components. Further, each figure is a schematic view and is not necessarily exactly illustrated. Therefore, for example, the scales and the like do not always match in each figure. Further, in each figure, substantially the same configuration is designated by the same reference numerals, and duplicate description will be omitted or simplified.

FIG. 1 is a cross-sectional view showing a schematic configuration of the bathroom dryer 91. The bathroom dryer 91 is an example of a blower and is used for drying the bathroom in the bathroom. The bathroom dryer 91 may be used for drying clothes in the bathroom. Here, the bathroom is shown as an object 100, which includes a floor 101 and a first wall 102a and a second wall 102b collectively referred to as the wall 102. The first wall 102a and the second wall 102b are arranged so as to face each other. The object 100 also includes a third wall 102c (not shown) and a fourth wall 102d (not shown) arranged so as to face each other between the first wall 102a and the second wall 102b. The bathroom dryer 91 includes a main body case 92, a blower unit 93, a heating unit 95, a wind direction control unit 96, a ventilation unit 97, a control unit 5, a display unit 6, and a moisture content detection unit 9. ..

The main body case 92 constitutes the exterior of the bathroom dryer 91. The main body case 92 is provided with a suction port 10 for sucking bathroom air into the bathroom dryer 91 and an outlet 11 for blowing out the air sucked from the suction port 10 to the outside of the main body case 92. .. The suction port 10 and the air outlet 11 are provided below the main body case 92. The heating unit 95 is provided in the air passage connecting the suction port 10 and the air outlet 11, and heats the air sucked from the suction port 10. The air blowing unit 93 is provided in the air blowing path and circulates air from the suction port 10 to the air outlet 11. The wind direction control unit 96 changes the wind direction of the wind blown from the air outlet. The ventilation unit 97 ventilates the bathroom. The bathroom dryer 91 has a drying mode for controlling the heating amount, the air blowing amount, the wind direction, and the like for the purpose of drying the bathroom or clothes.

In a drying mode such as bathroom drying or clothes drying, the material, position, size, etc. of the object 100 to be dried are different, so that the bathroom dryer 91 needs to appropriately detect the drying state and control the operation. Therefore, the bathroom dryer 91 includes a water content detecting unit 9 that detects the water content of the object 100 to be dried. The water content detecting unit 9 has a light emitting unit 7 and a light receiving unit 8, the light emitting unit 7 emits light toward the object 100, and the light receiving unit 8 receives the light reflected by the object 100. ..

The control unit 5 includes a light source control unit 51 (see FIG. 3) and a water content calculation unit 56 (see FIG. 3). The light source control unit 51 controls the light emitted from the light emitting unit 7. The water content calculation unit 56 detects the light received by the light receiving unit 8 and calculates the water content. Here, the water content calculation unit 56 calculates the water content of the object 100 by comparing the intensities of two lights having different wavelengths received by the light receiving unit 8. Details will be described later. The control unit 5 controls the heating amount, the air blowing amount, the wind direction, etc. of the bathroom dryer 91 according to the calculated water content.

The control unit 5 includes at least one microcontroller, a non-volatile memory in which the overall operation program of the bathroom dryer 91 is stored, and a volatile memory which is a temporary storage area for executing the program. It has an input / output port and a processor that executes a program.

In the following, the configuration of the bathroom dryer 91 is described as follows: (1) calculation of water content, (2) acquisition of distance, temperature, humidity, (3) prediction of transition of water content, (4) prediction of drying end time, ( 5) Blower control and (6) Drying end time display will be described in this order.

(1) Calculation of Moisture Content FIG. 2 is a schematic view showing the configurations and objects of the light emitting unit 7 and the light receiving unit 8 of the bathroom dryer 91. FIG. 3 is a block diagram showing a control configuration of the bathroom dryer 91. In this embodiment, as shown in FIG. 2, the light emitting unit 7 irradiates light toward the object 100 existing at a space. The light emitted from the light emitting unit 7 is reflected by the object 100. The reflected light RA1 which is the reflected light is detected by the light receiving unit 8. Based on the reflected light RA1 detected by the light receiving unit 8, the water content calculation unit 56 shown in FIG. 3 calculates the water content contained in the object 100. The amount of water contained in the object 100 is the water accumulated on the object 100 and the water permeating the surface portion of the object 100.

The light emitting unit 7 includes a detection light including a first wavelength band which is light having a wavelength absorbed by water, and a reference light including a second wavelength band which is light having a wavelength absorbed by water less than the first wavelength band. Is emitted toward the object 100. Specifically, the light emitting unit 7 includes a light projecting lens 21 and a light source 22. The light projecting lens 21 is a condensing lens that collects the light emitted by the light source 22 on the object 100. The floodlight lens 21 is a convex lens made of resin, but is not limited to this. The light source 22 is an LED (Light Emitting Mode) light source that includes a first wavelength band that forms a detection light and a second wavelength band that forms a reference light, and emits continuous light having a peak wavelength on the second wavelength band side. Specifically, the light source 22 is an LED light source made of a compound semiconductor.

FIG. 4 shows the absorption spectra of water and water vapor. As shown in FIG. 4, water has absorption peaks at wavelengths of about 1450 nm and about 1940 nm. Water vapor has absorption peaks at wavelengths slightly lower than the absorption peak of water, specifically at wavelengths of about 1350 nm to 1400 nm and about 1800 nm to 1900 nm. Therefore, as the first wavelength band that forms the detection light, a wavelength band having a high absorbance of water is selected, and as the second wavelength band that forms the reference light, a wavelength band having a smaller absorbance of water than the first wavelength band is selected. select.

As an example, the average wavelength of the second wavelength band is longer than the average wavelength of the first wavelength band. Further, regarding the center wavelength defined by the center value of the wavelength which is the half value of the maximum transmittance of the optical bandpass filter, for example, the center wavelength of the first wavelength band is 1450 nm and the center wavelength of the second wavelength band is 1700 nm. To do. Since the light source 22 irradiates light that continuously includes the first wavelength band and the second wavelength band, the object 100 is subjected to detection light including the first wavelength band that is largely absorbed by water and absorption by water. Reference light including a second wavelength band smaller than the first wavelength band is irradiated.

The light receiving unit 8 of FIG. 2 receives the reflected light RA1 that is irradiated from the light emitting unit 7 and reflected by the object 100. That is, the light receiving unit 8 receives the detection light and the reference light that are irradiated from the light emitting unit 7 and reflected by the object 100. The light receiving unit 8 includes a light receiving lens 71, a half mirror 34, a first light receiving element 73, a second light receiving element 43, a first bandpass filter 72, and a second bandpass filter 42. The reflected light RA1 is condensed by the light receiving lens 71, and is divided into light passing through the first optical path LR01 and light passing through the second optical path LR02 by the half mirror 34.

The light receiving lens 71 is a condensing lens for condensing the reflected light RA1 reflected by the object 100 on the first light receiving element 73 and the second light receiving element 43. The light receiving lens 71 is fixed to the light receiving portion 8 so that the focus is located on the light receiving surface of the first light receiving element 73, for example. The light receiving lens 71 is, for example, a convex lens made of resin, but is not limited to this.

The half mirror 34 is arranged between the light receiving lens 71 and the first light receiving element 73, for example, transmits half of the light collected by the light receiving lens 71, and reflects the rest. A first bandpass filter 72 and a first light receiving element 73 are provided at the tip of the first optical path LR01, which is an optical path of light transmitted through the half mirror 34.

The first bandpass filter 72 is a bandpass filter that extracts light in the first wavelength band, which is detection light, from the reflected light RA1. Specifically, the first bandpass filter 72 is arranged between the half mirror 34 and the first light receiving element 73, and the reflected light RA1 that passes through the half mirror 34 and is incident on the first light receiving element 73. It is provided on the optical path of. The first bandpass filter 72 transmits light in the first wavelength band and reflects or absorbs light in other wavelength bands.

The first light receiving element 73 is a light receiving element that is reflected by the object 100, passes through the half mirror 34, receives light in the first wavelength band that has passed through the first bandpass filter 72, and converts it into a first electric signal. is there. The first light receiving element 73 generates a first electric signal according to the amount of received light (that is, the intensity) of the received light by photoelectric conversion of the received light in the first wavelength band. The generated first electric signal is output to the control unit 5. The first light receiving element 73 is, for example, a photodiode, but is not limited thereto. For example, the first light receiving element 73 may be a phototransistor or an image sensor.

The second bandpass filter 42 is a bandpass filter that extracts light in the second wavelength band, which is reference light, from the light reflected by the half mirror 34. Specifically, the second bandpass filter 42 is arranged between the half mirror 34 and the second light receiving element 43, and is the light of light that reflects the half mirror 34 and is incident on the second light receiving element 43. It is installed on the street. The second bandpass filter 42 transmits light in the second wavelength band and reflects or absorbs light in other wavelength bands.

The second light receiving element 43 is a light receiving element that receives light in the second wavelength band that is reflected by the object 100 and has passed through the second bandpass filter 42 and converts it into a second electric signal. The second light receiving element 43 generates a second electric signal according to the amount of received light (that is, the intensity) of the light received by photoelectric conversion of the received light in the second wavelength band. The generated second electric signal is output to the control unit 5. The second light receiving element 43 is a light receiving element having the same shape as the first light receiving element 73. That is, when the first light receiving element 73 is a photodiode, the second light receiving element 43 is also a photodiode.

The control unit 5 of FIG. 3 includes a light source control unit 51, a first amplification unit 52, a second amplification unit 53, a first signal processing unit 54, a second signal processing unit 55, and a water content calculation unit 56. , A blower control unit 57, a distance calculation unit 58, a water content prediction unit 60, and a dryness prediction unit 62. The control unit 5 may be housed in the main body case 92, or may be attached to the outer surface of the main body case 92. Alternatively, the control unit 5 may be divided into a plurality of units.

The light source control unit 51 controls the lighting of the light source 22 of the light emitting unit 7. The light source control unit 51 includes a drive circuit and a microcontroller. The light source control unit 51 includes a non-volatile memory in which the control program of the light source 22 is stored, a volatile memory which is a temporary storage area for executing the program, an input / output port, a processor for executing the program, and the like. Have. The light source control unit 51 controls the light source 22 so that the light source 22 is turned on and off repeatedly at a predetermined light emission cycle. Specifically, the light source control unit 51 outputs a pulse signal of a predetermined frequency (for example, 1 kHz) to the light source 22, so that the light source 22 is turned on and off at a predetermined light emission cycle.

The control unit 5 receives the first electric signal from the first light receiving element 73 and the second electric signal from the second light receiving element 43. The first amplification unit 52 amplifies the first electric signal output by the first light receiving element 73 and outputs it to the first signal processing unit 54. Specifically, the first amplification unit 52 is an operational amplifier that amplifies the first electric signal. The first signal processing unit 54 is composed of a microcontroller. The first signal processing unit 54 executes the program, the non-volatile memory in which the processing program for the first electric signal is stored, the volatile memory which is a temporary storage area for executing the program, the input / output port, and the program. Has a processor or the like. The first signal processing unit 54 limits the pass band of the first electric signal, corrects the phase delay due to the pass band limitation, and then performs multiplication processing with the light emission period of the light source 22. The processing for this first electric signal is a so-called lock-in amplifier processing. As a result, noise based on the disturbance light generated in the first electric signal is suppressed.

The second amplification unit 53 amplifies the second electric signal output by the second light receiving element 43 and outputs it to the second signal processing unit 55. Specifically, the second amplification unit 53 is an operational amplifier that amplifies the second electric signal. The second signal processing unit 55 is composed of a microcontroller. The second signal processing unit 55 executes the program, the non-volatile memory in which the processing program for the second electric signal is stored, the volatile memory which is a temporary storage area for executing the program, the input / output port, and the program. Has a processor or the like. The second signal processing unit 55 limits the pass band of the second electric signal, corrects the phase delay due to the pass band limitation, and then performs multiplication processing with the light emission period of the light source 22. The processing for this second electric signal is a so-called lock-in amplifier processing. As a result, noise based on the disturbance light generated in the second electric signal is suppressed.

The water content calculation unit 56 detects the water content contained in the object 100 based on the first electric signal output from the first light receiving element 73 and the second electric signal output from the second light receiving element 43. Specifically, the water content calculation unit 56 calculates the water content of the object 100 based on the ratio (signal ratio) between the voltage level of the first electric signal and the voltage level of the second electric signal. Here, the water content calculation process in the water content calculation unit 56 will be described in more detail. The water content calculation unit 56 detects the water content contained in the object 100 by comparing the light energy Pd of the detection light contained in the reflected light RA1 with the light energy Pr of the reference light. The light energy Pd of the detection light corresponds to the intensity of the first electric signal output from the first light receiving element 73, and the light energy Pr of the reference light corresponds to the intensity of the second electric signal output from the second light receiving element 43. Corresponds to.

The light energy Pd is represented by the following (Equation 1).
Pd = Pd0 × Gd × Rd × Td × Aad × Ivd (Equation 1)
Here, Pd0 is the light energy of the light in the first wavelength band that forms the detection light among the light emitted by the light source 22. Gd is the coupling efficiency (condensing rate) of light in the first wavelength band with respect to the first light receiving element 73. Specifically, Gd corresponds to the proportion of the portion of the light emitted by the light source 22 that becomes a part of the component diffusely reflected by the object 100 (that is, the detection light contained in the reflected light).

Rd is the reflectance of the detected light by the object 100. Td is the transmittance of the light detected by the first bandpass filter 72. Ivd is the light receiving sensitivity to the detection light contained in the reflected light RA1 in the first light receiving element 73. Aad is the absorption rate of the detected light by the component (moisture) contained in the object 100, and is represented by the following (Equation 2).
Aad = 10-αa × Ca × D (Equation 2)
Here, αa is a predetermined absorption coefficient, and specifically, is the absorption coefficient of the detection light by the component (moisture). Ca is the volume concentration of the component (moisture) contained in the object 100. D is a contribution thickness that is twice the thickness of the component that contributes to the absorption of the detection light.

More specifically, in the object 100 in which the water content is uniformly dispersed, Ca is the volume contained in the component of the object 100 when the light is incident on the object 100, reflected and emitted from the object 100. Corresponds to the concentration. Further, D corresponds to the optical path length from reflection to emission from the object 100. For example, Ca is the concentration of water contained in the liquid phase covering the object 100. Further, D is a contribution thickness converted as an average thickness of the liquid phase covering the object 100. Therefore, αa × Ca × D corresponds to the amount of components (water content) contained in the object 100. From the above, it can be seen that the light energy Pd corresponding to the intensity of the first electric signal changes according to the amount of water contained in the object 100. The absorbance of moisture is extremely low compared to that of moisture and can be ignored.

Similarly, the light energy Pr of the reference light incident on the second light receiving element 43 is represented by the following (Equation 3).
Pr = Pr0 × Gr × Rr × Tr × Ivr (Equation 3)
In this embodiment, the reference light can be considered to be substantially not absorbed by the components contained in the object 100, and therefore, as can be seen in comparison with (Equation 1), it corresponds to the absorption rate Aad due to water. The term is not included in (Equation 3).

In (Equation 3), Pr0 is the light energy of the light in the second wavelength band forming the reference light among the light emitted by the light source 22. Gr is the coupling efficiency (condensing rate) of the reference light emitted by the light source 22 with respect to the second light receiving element 43. Specifically, Gr corresponds to the proportion of the portion of the reference light that becomes a part of the component diffusely reflected by the object 100 (that is, the reference light contained in the reflected light). Rr is the reflectance of the reference light by the object. Tr is the transmittance of the reference light by the second bandpass filter 42. Ivr is the light receiving sensitivity of the second light receiving element 43 with respect to the reflected light.

In this embodiment, the light emitted from the light source 22, that is, the detection light and the reference light are irradiated coaxially and with the same spot size, so that the coupling efficiency Gd of the detection light and the coupling efficiency Gr of the reference light are abbreviated. Become equal. Further, since the peak wavelengths of the detection light and the reference light are relatively close to each other, the reflectance Rd of the detection light and the reflectance Rr of the reference light are substantially equal to each other.

Therefore, the following (Equation 4) is derived by taking the ratio (signal ratio) between (Equation 1) and (Equation 3).
Pd / Pr = Z × Aad (Equation 4)
Here, Z is a constant term and is represented by (Equation 5).
Z = (Pd0 / Pr0) × (Td / Tr) × (Ivd / Ivr) (Equation 5)
The light energies Pd0 and Pr0 are each predetermined as the initial output of the light source 22. Further, the transmittance Td and the transmittance Tr are predetermined by the transmission characteristics of the first bandpass filter 72 and the second bandpass filter 42, respectively. The light receiving sensitivity Ivd and the light receiving sensitivity Ivr are predetermined by the light receiving characteristics of the first light receiving element 73 and the second light receiving element 43, respectively. Therefore, Z represented by (Equation 5) can be regarded as a constant.

The water content calculation unit 56 calculates the light energy Pd of the detection light based on the first electric signal, and calculates the light energy Pr of the reference light based on the second electric signal. Specifically, the signal level (voltage level) of the first electric signal corresponds to the light energy Pd, and the signal level (voltage level) of the second electric signal corresponds to the light energy Pr. Therefore, the water content calculation unit 56 can calculate the water absorption rate Aad contained in the object based on (Equation 4). As a result, the water content calculation unit 56 can calculate the water content based on (Equation 2). Moisture (water vapor) also exists in the space, but it is assumed that the detection light and reference light may be absorbed by the water vapor. The control unit 5 may be provided with a correction unit that corrects the first electric signal and the second electric signal so as to cancel the absorption by the water vapor.

Such processing is performed for each unit region R shown in FIG. FIG. 5 is a schematic view showing a detection range and a unit area of the bathroom dryer 91. The detection range A is preferably equal to or wider than the light receiving range of the light receiving unit 8, and is preferably set to be equal to or wider than the range in which the air dehumidified by the bathroom dryer 91 is blown. Further, the unit region R is a region in which light is individually detected by the light receiving unit 8. The unit area R may have the same size as the detection range A or may be smaller than the detection range A. In the latter, the detection range A is divided into a plurality of unit regions R. For example, the unit area R is a size obtained by dividing the detection range A into 6 in the vertical direction and 6 in the horizontal direction. As a method of performing detection for each of S11 to S66 of the unit region R, for example, an image sensor may be adopted for the first light receiving element 73 and the second light receiving element 43.

FIG. 6 is a schematic view showing the scanning directions of the light emitting unit 7 and the light receiving unit 8 of the bathroom dryer 91. Further, as another method, as shown in FIG. 6, a method of irradiating light while scanning the irradiation region of the light emitting unit 7 and at the same time scanning the light receiving region of the light receiving unit 8 to receive the reflected light RA1 in each region is adopted. You may. As a scanning method, for example, there is a method in which a pedestal on which a light emitting unit 7 and a light receiving unit 8 are fixed is rotatably arranged on two orthogonal axes by using two stepping motors (not shown). One stepping motor is arranged at an angle capable of scanning the irradiation area in the main scanning direction of FIG. 6, and the other stepping motor is arranged at an angle capable of scanning the irradiation area in the sub-scanning direction of FIG. In FIGS. 5 and 6, 6 locations are detected at equal intervals per row, and 6 locations are detected at equal intervals per column.

FIG. 7 shows a table of water content distribution of the bathroom dryer 91. When the detection operation is completed, the water content calculation unit 56 temporarily records the calculation result of the water content for each unit region R in the table T as shown in FIG. 7. “T11” indicates the amount of water calculated in the unit region “R11”. In the following, the unit area “R11” may be referred to as a unit area “T11” for the sake of clarity. That is, "T11" may indicate a unit region or may indicate a water content. The same applies to "T12" and the like. The information in the table T may be individually determined for each unit area R, or may be averaged and processed into one or a small number of pieces of information.

FIG. 8 is a flowchart for calculating the water content of the bathroom dryer 91. Here, the position of the unit region R in the n rows and 6 columns is defined as Sn6 (n = 1 to 6). That is, S11 is a position in one row and one column of the unit area R. First, the irradiation region of the light emitting unit 7 and the light receiving region of the light receiving unit 8 are moved to S11 in FIG. 6 (n = 1). Next, the designated positions of each region (irradiation region and light receiving region) are set to Sn6 (Step 1). The stepping motor is driven to move the pedestal parallel to the main scanning direction of FIG. 6, and the irradiation region and the light receiving region are positioned at Sn6 (Step 2). At the same time, it is determined whether or not the irradiation region and the light receiving region are located at the center of the unit region R. The determination of whether or not the unit region R is located at the center is calculated from, for example, the number of drive steps of the stepping motor. If the irradiation region and the light receiving region are not located at the center of the unit region R, the process returns to Step 2 and the stepping motor continues to be driven. When the irradiation region and the light receiving region are located at the center of the unit region R, the light receiving intensity is acquired, the ratio of the intensities, that is, the water content is calculated and stored in the table T. After that, it is determined whether or not the unit area R currently located is Sn6, which is the designated position (Step 3). If the unit region R currently located is not Sn6, the process returns to Step 2 and the stepping motor continues to be driven. Here, if the unit region R currently located is Sn6, the driving of the stepping motor is stopped (Step 4). After that, 1 is added to n to move the irradiation region and the light receiving region toward Sn6 in parallel with the sub-scanning direction of FIG.

Next, the designated position is set to Sn1 (Step 5). The irradiation region and the light receiving region are moved in the direction opposite to Step 2 in parallel with the main scanning direction in FIG. 6, and the stepping motor is driven so as to be located at the designated position Sn1 (Step 6). At the same time, it is determined whether or not the irradiation region and the light receiving region are located at the center of the unit region R. The determination of whether or not the unit region R is located at the center is calculated from, for example, the number of drive steps of the stepping motor. If the irradiation region and the light receiving region are not located at the center of the unit region R, the process returns to Step 6 and the stepping motor continues to be driven. When the irradiation region and the light receiving region are located at the center of the unit region R, the light receiving intensity is acquired, the ratio of the intensities, that is, the water content is calculated and stored in the table T.

Next, it is determined whether or not the unit area R at which the current position is currently located is Sn1, which is the designated position (Step 7). If the unit region R currently located is not Sn1, the process returns to Step 6 and the stepping motor continues to be driven. Here, if the unit region R currently located is Sn1, the driving of the stepping motor is stopped (Step 8). If n is not 6, the irradiation region and the light receiving region are moved toward the designated position Sn1 in parallel with the sub-scanning direction of FIG. 6 by adding 1 to n (Step 9). After that, it returns to Step 1 and repeats the operation. If n is 6, the detection operation is terminated. Return to FIG.

The water content calculation unit 56 outputs the calculated water content to the water content prediction unit 60 as a table of FIG. Such a water content calculation unit 56 is, for example, a microcontroller. The water content calculation unit 56 includes a non-volatile memory in which a signal processing program is stored, a volatile memory which is a temporary storage area for executing the program, an input / output port, a processor for executing the program, and the like. ..

(2) Acquisition of distance, temperature, and humidity The temperature detection unit 80 detects the temperature of a predetermined space, that is, the bathroom. The temperature detection unit 80 outputs the detected temperature to the water content prediction unit 60. The humidity detection unit 82 detects the humidity in the bathroom. The humidity detection unit 82 outputs the detected humidity to the water content prediction unit 60. Since known techniques may be used for temperature detection and humidity detection, description thereof will be omitted here.

The distance calculation unit 58 calculates the distance to the floor 101, the wall 102, etc. of the bathroom. Specifically, the distance calculation unit 58 receives the second electric signal from the second signal processing unit 55 and calculates the distance by executing the triangular ranging method on the second electric signal. Since the triangular distance measuring method may be performed, for example, as in JP-A-2017-161424, the description thereof is omitted here, but a known distance measuring sensor may be used to calculate the distance. .. Here, the distance calculation unit 58 calculates the distance for each unit region R in the same manner as the water content prediction unit 60.

FIG. 9 shows a table of distance distribution of the bathroom dryer 91. When the calculation operation is completed, the distance calculation unit 58 temporarily records the calculation result of the distance for each unit region R in the table H as shown in FIG. 9, similarly to the water content prediction unit 60. “H11” indicates the amount of water calculated in the unit region “R11”. In the following, the unit area “R11” may be referred to as a unit area “H11” for the sake of clarity. That is, "H11" may indicate a unit region or may indicate a water content. The same applies to "H12" and the like. The information in the table H may be individually determined for each unit area R, or may be averaged and processed into one or a small number of pieces of information. Return to FIG.

(3) Prediction of transition of water content The water content prediction unit 60 receives the water content for each unit region R from the water content calculation unit 56, and receives the distance for each unit region R from the distance calculation unit 58. Further, the water content prediction unit 60 receives the temperature of the bathroom from the temperature detection unit 80 and the humidity of the bathroom from the humidity detection unit 82. The water content prediction unit 60 predicts the transition of the water content of the object 100 from the time of calculation by the water content calculation unit 56 to a predetermined time after the calculation based on the temperature, humidity, water content, and distance.

FIG. 10 is a block diagram showing the configuration of the water content prediction unit 60. The water content prediction unit 60 includes a region division unit 200, a feature amount storage unit 202, a learning unit 204, a prediction execution unit 206, and a prediction result storage unit 208. The area dividing unit 200 groups two or more unit areas into a group based on the distance for each unit area R and the amount of water for each unit area R. For example, the region dividing unit 200 groups two or more unit regions whose similarity is smaller than the threshold value based on the similarity between the distance and the water content (correlation matrix, etc.). For the similarity between the distance and the water content, for example, the distance and the water content in any one unit region (hereinafter referred to as "first unit region") are set to "A1" and "B1", respectively, and another unit. When the distance and the amount of water in the region (hereinafter referred to as "second unit region") are "A2" and "B2", respectively, they are shown as follows.
Similarity = C * | A1-A2 | + D * | B1-B2 |
Here, "C" and "D" are arbitrary constants. Further, "+" may be "x".

As a result, T22 to T25, T32 to T35, T42 to T45, and T52 to T55 in FIG. 7 are grouped together as the floor 101 in FIG. Further, T11, T21, T31, T41, T51, and T61 in FIG. 7 are grouped as the first wall 102a in FIG. 1, and T16, T26, T36, T46, T56, and T66 in FIG. 7 are the second wall 102b in FIG. It is summarized as. Further, T12 to T15 in FIG. 7 are grouped as the third wall 102c, and T62 to T65 in FIG. 7 are grouped as the fourth wall 102d. That is, the materials such as the wall 102 (four sides), the door, the bathtub, and the floor 101 are grouped into different parts. The area division unit 200 outputs the group information to the learning unit 204. The feature quantity storage unit 202 stores the moisture content, temperature, and humidity, that is, actually measured data. The feature quantity storage unit 202 outputs the water content, temperature, and humidity to the learning unit 204 and the prediction execution unit 206.

Here, the water content prediction unit 60 executes machine learning for each group. 11 (a)-(c) show the outline of the treatment by the water content prediction unit 60. FIG. 11A shows a machine learning processing procedure in the water content prediction unit 60, and shows a convolutional neural network as an example. In the convolutional neural network, the input layer 300, the first convolutional layer 302a, the first pooling layer 304a, the second convolutional layer 302b, the second pooling layer 304b, and the fully connected layer 306 are executed in this order. The first convolution layer 302a and the second convolution layer 302b are collectively referred to as the convolution layer 302, and the first pooling layer 304a and the second pooling layer 304b are collectively referred to as the pooling layer 304. The number of convolution layers 302, the number of pooling layers 304, and the combination of the respective treatments are not limited to this. Further, the convolution layer 302 and the pooling layer 304 do not have to be a pair, the convolution layer 302 may be continuously arranged, and an activation function may be inserted.

FIG. 11B shows the data used in the convolutional neural network. When the current time is set to "T1", the learning unit 204 trains the past time series data (X1) starting from T1 and the time series data (Y1) after T1. X1 contains the time data of "-n1 + 1 to 0", and Y1 contains the data of the time of "1 to n3". Further, when the current time is shifted from "T1" to "T2", the past time series data (X2) starting from T2 and the time series data (Y2) after T2 are learned.

FIG. 11C shows data input to the input layer 300. The input layer 300 receives the water content, temperature, and humidity from the feature quantity storage unit 202 as learning input data. The input data for learning corresponds to, for example, the time series data (X1) of FIG. 11B, and includes data for n1 hours for the three components of water content, temperature, and humidity, so that it is a 3 × n1 matrix. Indicated by. As described above, since the water content prediction unit 60 executes machine learning for each group, for example, the learning input data for the floor 101 includes the water content of the floor 101, the temperature of the bathroom, and the humidity of the bathroom. Here, since the water content is derived for each unit region, the input layer 300 derives the water content for the group based on the water content in the two or more unit regions included in the group. The water content for a group may be the average value, the median value, the maximum value, or the minimum value of the water content in two or more unit regions contained in the group. May be good. Further, the learning input data of the three components are given by shifting p1 times as shown in FIG. 11 (b).

The first convolution layer 302a has a filter for extracting pattern features. The filter has, for example, a weight of 1 × m1, and each weight in the filter is created so as to have a total of 1. Also, the number of rows in the filter is set to 1 because the row data affects the prediction. The first convolution layer 302a outputs the total weight of the data × filter while shifting the 1 × m1 filter one by one in the row direction with respect to the input data of 3 × n1.

The first pooling layer 304a absorbs deformation due to information compression by leaving only valid data from the processing result matrix of the first convolution layer 302a. The first pooling layer 304a has, for example, a 1 × m2 filter. In the first pooling layer 304a, maximum pooling and average pooling are performed.

The second convolution layer 302b and the second pooling layer 304b perform the same processing as the first convolution layer 302a and the first pooling layer 304a. On the other hand, the size of the filter of the second convolution layer 302b is different from the size of the filter of the first convolution layer 302a, and the size of the filter of the second pooling layer 304b is different from the size of the filter of the first pooling layer 304a.

The fully connected layer 306 is a multi-layer perceptron and receives data from the second pooling layer 304b. The number of nodes and the number of intermediate layers in the fully connected layer 306 may be arbitrary, and n3 data strings are output from the output layer in the fully connected layer 306. This corresponds to the time series data (Y1) and the like in FIG. 11 (b).

The learning unit 204 creates a water content prediction model used in the convolutional neural network of the water content prediction unit 60. The water content prediction model is a model that outputs time-series data of a certain period of water content in the future when it receives time-series data of a certain period of water content and time-series data of a certain length of temperature and humidity. The learning unit 204 gives the input data for learning to the input layer 300, and uses the prediction data output from the fully connected layer 306 and the output data for learning, for example, by the error back propagation method, the convolution layer 302 and all. The weight of the bond layer 306 is updated. Here, the learning output data is actual time-series data following the learning input data in time. The learning unit 204 creates a water content prediction model by carrying out this for one data p1 time staggered.

The prediction execution unit 206 predicts the future transition of the water content using the water content prediction model created by the learning unit 204. FIG. 12 shows an outline of processing by the water content prediction unit 60 and the dryness prediction unit 62. This shows the transition of the water content predicted by the prediction execution unit 206. The horizontal axis shows the drying time, and the vertical axis shows the amount of water. Further, FIG. 12 shows the transition of the water content with respect to any three groups among the plurality of groups, but the transition of the water content with respect to the other unit regions is also shown in the same manner. Return to FIG. That is, the water content prediction unit 60 groups two or more unit regions based on the distance as a group, and predicts the transition of the water content for the group based on the temperature, humidity, and water content. The prediction execution unit 206 outputs the predicted transition of the water content to the drying prediction unit 62 and the prediction result storage unit 208. The prediction result storage unit 208 stores the transition of the water content for each group and the temperature and humidity.

(4) Prediction of Drying End Time The drying prediction unit 62 predicts the drying end time based on the transition of the water content predicted by the water content prediction unit 60. Such predictions are made on a group-by-group basis. The drying prediction unit 62 defines a drying judgment threshold value in advance, compares the transition of the water content for each group with the drying judgment threshold value, and sets a time during which the water content becomes smaller than the drying judgment threshold value. Specify as the drying end time. This can be said to be an absolute value judgment. In FIG. 12, the drying end times Ta, Tb, and Tc are specified.

Further, the drying prediction unit 62 may derive the rate of change of the transition of the water content by differentiating the transition of the water content for each group. The drying prediction unit 62 defines the ratio threshold value in advance, compares the rate of change in the transition of the water content for each group with the ratio threshold value, and the time when the rate of change becomes smaller than the ratio threshold value May be specified as the drying end time. This can be said to be a relative value judgment. Further, the drying prediction unit 62 may specify the drying end time by combining the absolute value determination and the relative value determination. For example, the dryness prediction unit 62 may execute the absolute value determination and then the relative value determination. FIG. 13 shows the processing result of the drying prediction unit 62. This is also called table K. In FIG. 13, the drying end time for each unit region is shown as K11 or the like, but the drying end time for two or more unit regions included in one group has the same value. Here, too, K11 and the like may be referred to as a unit area.

FIG. 14 is a flowchart showing a prediction procedure by the bathroom dryer 91. The water content calculation unit 56 finishes calculating the water content (table T), and the distance calculation unit 58 finishes calculating the distance (table H) (S100). The water content prediction unit 60 stores the (mth) water content table T, the distance table H, the temperature, and the humidity in the feature quantity storage unit 202 (S102). The water content prediction unit 60 predicts the water content after the m + 1th time from the data of the feature amount storage unit 202 and the water content prediction model (S104). The water content prediction unit 60 stores the prediction result in the prediction result storage unit 208 (S106). The drying prediction unit 62 calculates the drying end time of each group from the water content time series data of the prediction result storage unit 208 (S108). The learning unit 204 modifies the water content prediction model based on the previous prediction result and the actual measurement result (S110). Return to FIG.

(5) Blower control The blower control unit 57 blows air from the air outlet 11 according to the drying end time predicted by the drying prediction unit 62. At that time, the blower control unit 57 controls the wind direction so as to face the unit region where the drying end time is late. Specifically, the blower control unit 57 blows air at an angle of the wind direction control unit 96 with respect to a place in K11 to K66 where the drying end time is late. The blower control unit 57 may control the heating unit 95 of FIG. 1 based on the table K of the drying end time. That is, the blower control unit 57 controls the angle of the wind direction control unit 96 with respect to the unit region where the drying end time is late, and blows the heated air concentrated on the unit region. As a result, evaporation of water is promoted in the unit region having a large amount of water. This corresponds to preferentially blowing air to a place that is difficult to dry. The blower control unit 57 may change the amount of air blown by the blower unit 93 by controlling the angle of the wind direction control unit 96 or by changing to controlling the angle of the wind direction control unit 96. Further, a motion sensor (not shown) is connected to the bathroom dryer 91, and when the motion sensor detects a person in the bathroom, the ventilation control unit 57 may stop blowing air.

(6) Display of Drying End Time The drying prediction unit 62 displays the predicted drying end time for each group, that is, the table K on the display unit 6. The display unit 6 is a display and displays a table K as shown in FIG. The display unit 6 may display the latest drying end time in the table K, that is, the time when the drying operation is stopped or the remaining time of the drying operation.

The subject of the device, system, or method in the present disclosure comprises a computer. By executing the program by this computer, the function of the subject of the device, system, or method in the present disclosure is realized. A computer has a processor that operates according to a program as a main hardware configuration. The type of processor does not matter as long as the function can be realized by executing the program. The processor is composed of one or more electronic circuits including a semiconductor integrated circuit (IC) or an LSI (Large Scale Integration). The plurality of electronic circuits may be integrated on one chip or may be provided on a plurality of chips. A plurality of chips may be integrated in one device, or may be provided in a plurality of devices. The program is recorded on a non-temporary recording medium such as a computer-readable ROM, optical disc, or hard disk drive. The program may be stored in the recording medium in advance, or may be supplied to the recording medium via a wide area communication network including the Internet or the like.

According to this embodiment, based on the temperature, humidity, water content, and distance, the transition of the water content of the object 100 from the time of calculation to the predetermined time is predicted, and the transition of the water content is used. Since the drying end time is predicted, the accuracy of predicting the drying end time of the object 100 can be improved. Further, since two or more unit areas are grouped based on the distance and the amount of water and the prediction is executed for the group, the prediction accuracy can be improved. Further, since the wind direction is controlled so as to face the unit region where the drying end time is late, the air can be blown preferentially to the one with the late drying end time. In addition, since the air is preferentially blown to the one with the later drying end time, the drying end time can be shortened. Moreover, since the drying end time is shortened, the power consumption can be reduced. Further, since the amount of air blown is controlled based on the drying end time, the amount of air blown can be increased when the drying end time is late.

Further, since the ventilation is stopped when the human sensor detects a person, the ventilation can be executed when the person is absent. In addition, since the air is blown when the person is absent, the amount of air blown can be increased when the person is absent. Further, since the ventilation is stopped when a person is detected by the motion sensor, it is possible to suppress the discomfort. Further, since the heating unit 95 is provided, high temperature air can be blown. In addition, since high-temperature air is blown, water droplets can be evaporated in a short time. In addition, since the predicted drying end time is displayed, the user can know a guideline for the time required for drying the object 100. In addition, since the user knows a guideline for the time required for drying the object 100, it is possible to manage the schedule of housework.

The outline of one aspect of the present disclosure is as follows. The blower of a certain aspect of the present disclosure includes a temperature detection unit (80) that detects the temperature of a predetermined space, a humidity detection unit (82) that detects the humidity of a predetermined space, and an object in the predetermined space. A water content calculation unit (56) that calculates the water content, a distance calculation unit (58) that calculates the distance to the object, and a water content calculation unit (56) based on the temperature, humidity, water content, and distance. ), The moisture content prediction unit (60) that predicts the transition of the moisture content of the object from the time of calculation to the predetermined time later, and the moisture content prediction unit (60) predict the transition of the moisture content, and the drying is performed. It includes a drying prediction unit (62) that predicts the end time, and a blower control unit (57) that blows air from the air outlet according to the drying end time predicted by the drying prediction unit (62).

The water content calculation unit (56) calculates the water content for each of the plurality of unit regions in which the detection range is divided, and the water content prediction unit (60) calculates two or more based on the distance and the water content. The unit areas of are grouped together, and the transition of the water content may be predicted for the group based on the temperature, humidity, and water content.

The blower control unit (57) may control the wind direction so as to face the unit region where the drying end time is late.

The blast control unit (57) may control the blast amount based on the drying end time.

A motion sensor may be further provided. The blast control unit (57) may stop the blast when a person is detected by the motion sensor.

A heating unit (95) arranged in the ventilation path from the suction port to the air outlet may be further provided.

A display unit (6) that displays the drying end time predicted by the drying prediction unit (62) may be further provided.

The present disclosure has been described above based on the examples. This embodiment is an example, and it will be understood by those skilled in the art that various modifications are possible for each of these components or combinations of each processing process, and that such modifications are also within the scope of the present disclosure. ..

In the initial stage, the water content prediction unit 60 in this embodiment searches for and predicts a tendency similar to the water content transition pattern stored in advance with respect to the transition of the water content for each group. You may. According to this modified example, the transition of the water content can be predicted even in the initial stage.

5 Control unit, 6 Display unit, 7 Light emitting unit, 8 Light receiving unit, 9 Moisture content detection unit, 10 Suction port, 11 Air outlet, 21 Floodlight lens, 22 Light source, 34 Half mirror, 42 Second band pass filter, 43 Second light receiving element, 51 Light source control unit, 52 First amplification unit, 53 Second amplification unit, 54 First signal processing unit, 55 Second signal processing unit, 56 Moisture content calculation unit, 57 Blower control unit, 58 Distance calculation Unit, 60 Moisture content prediction unit, 62 Dryness prediction unit, 71 Light receiving lens, 72 First band pass filter, 73 First light receiving element, 80 Temperature detection unit, 82 Humidity detection unit, 91 Bathroom dryer, 92 Body case, 93 Blower, 95 Heating unit, 96 Wind direction control unit, 97 Ventilation unit, 100 Object, 200 Area division unit, 202 Feature storage unit, 204 Learning unit, 206 Prediction execution unit, 208 Prediction result storage unit, 300 Input layer, 302 folding layer, 304 pooling layer, 306 fully bonded layer.

Claims (7)

A temperature detector that detects the temperature of a predetermined space,
A humidity detection unit that detects the humidity of the predetermined space, and
A water content calculation unit that calculates the water content of the object in the predetermined space,
A distance calculation unit that calculates the distance to the object,
Based on the temperature, the humidity, the water content, and the distance, the water content prediction unit predicts the transition of the water content of the object from the time of calculation by the water content calculation unit to a predetermined time.
A drying prediction unit that predicts the drying end time based on the transition of the water content predicted by the water content prediction unit, and a drying prediction unit.
A blower control unit that blows air from the air outlet according to the drying end time predicted by the dryness prediction unit.
A blower equipped with. The water content calculation unit calculates the water content for each of the plurality of unit regions in which the detection range is divided.
The water content prediction unit groups two or more unit regions based on the distance and the water content into a group, and the water content for the group is based on the temperature, the humidity, and the water content. The blower according to claim 1, which predicts a change in quantity. The blower according to claim 2, wherein the blower control unit controls the wind direction so as to face a unit region having a slow drying end time. The blower according to any one of claims 1 to 3, wherein the blower control unit controls the amount of blown air based on the drying end time. Equipped with a motion sensor
The blower according to any one of claims 1 to 4, wherein the blower control unit stops blowing when a person is detected by the motion sensor. The blower according to any one of claims 1 to 5, further comprising a heating unit arranged in a ventilation path from a suction port to the air outlet. The blower according to any one of claims 1 to 6, further comprising a display unit that displays the drying end time predicted by the drying prediction unit.

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