Drying System

Abstract

To provide a drying system capable of completion of a drying operation at a more suitable timing.SOLUTION: A drying system of an embodiment comprises an information acquisition section and a determination section. The information acquisition section acquires information indicating a state of movement of cloth or a condition of cloth in a drying chamber or rotary tub upon a drying operation. The determination section decides how much a cloth drying progress progresses on the basis of the information acquired by the information acquisition section. The drying system performs the drying operation on the basis of the determination result on the degree of the progression of the drying process which decided by the determination section.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] SUMMARY OF THE DISCLOSURE FIELD OF THE DISCLOSURE Embodiments of the present invention relate to a drying system. [Background technology]

[0002] In some drying systems for drying wet fabrics, the drying operation of the dryer with a drying processing function is automatically terminated by control. In such a dryer, the drying operation may be terminated even if the wet fabric is not completely dried. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-165328 A Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present invention is to provide a drying system that can end the drying operation at a more appropriate timing. [Means for solving the problem]

[0005] The drying system of the embodiment has an information acquisition unit and a determination unit. The information acquisition unit acquires information indicating the movement or state of the cloth in a drying chamber or a rotary tub during a drying operation. The determination unit determines the progress of drying of the cloth based on the information acquired by the information acquisition unit. The drying system performs a drying operation based on the determination result of the progress of drying by the determination unit. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a first diagram showing an example of a configuration of a washing machine according to an embodiment. [Diagram 2] FIG. 2 is a second diagram showing an example of the configuration of a washing machine according to an embodiment. [Diagram 3] FIG. 2 is a diagram showing a state in which the door of the washing machine according to the embodiment is open. [Figure 4] 3A to 3C are diagrams for explaining drive control of a drum motor 5 according to an embodiment. [Diagram 5] FIG. 4 is a diagram showing a process flow of control of a drying operation according to an embodiment. [Figure 6] FIG. 4 is a diagram showing a process flow of control of a drying operation according to an embodiment. [Figure 7] 5A to 5C are diagrams for explaining images acquired in the process of an embodiment; [Figure 8] FIG. 11 is a diagram showing an example of an image obtained by simulating a state in which laundry is agitated during a drying operation. [Figure 9] FIG. 9 is a diagram for explaining feature amounts of the image shown in FIG. 8 . [Figure 10] 5A and 5B are diagrams for explaining the relationship between the color of a subject and the frequency distribution of intensity values ​​of RGB components. [Figure 11] FIG. 4 is a first diagram for explaining an example of a histogram indicating image characteristics according to an embodiment. [Figure 12] FIG. 4 is a second diagram for explaining an example of a histogram indicating image characteristics according to an embodiment. [Figure 13] FIG. 11 is a configuration diagram of a drying system according to a second embodiment. [Figure 14] FIG. 4 is a diagram showing a process flow of control of a drying operation according to an embodiment. [Figure 15] FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, the drying system of the embodiment will be described with reference to the drawings. In the following description, the same reference numerals are given to components having the same or similar functions. Then, duplicated descriptions of those components may be omitted. "Based on XX" means "based on at least XX" and may include the case of being based on another element in addition to XX. "Based on XX" is not limited to the case of directly using XX, but may also include the case of being based on XX that has been calculated or processed. "XX or YY" is not limited to either one of XX and YY, but may also include both XX and YY. This also applies to the case of three or more selective elements. "XX" and "YY" are any element (for example, any information). "Detection" is not limited to the case of directly sensing the physical quantity of the target, but may also include the case of directly or indirectly acquiring other physical quantities related to the physical quantity of the target, and estimating or identifying the physical quantity of the target from the other acquired physical quantities. "Acquisition" is not limited to the case of directly receiving the target object (including information) itself, but may also include the case of generating the target object by performing calculations or processing on the directly received object (including information).

[0008] Several embodiments will be described below. The drying system of the embodiment is a washing machine (washer-dryer or dryer) that can estimate the drying state of laundry (cloth) during drying operation with a relatively high degree of accuracy. The washing machine (washer-dryer or dryer) is a drum-type washing machine (dryer), a vertical-type washing machine (dryer), or the like. The washing machine may be a two-tub washing machine. The objects that the drying system dries during drying operation include relatively large pieces of cloth such as bath towels, bath mats, and towel blankets, in addition to cloth such as clothing. These are collectively referred to as laundry or cloth. The "movement of cloth" in the drying chamber, more specifically in the drum (rotary tub), includes being agitated by the rotation of the drum, moving in the up-down or back-and-forth directions, and changing the order of the arrangement of each piece of cloth. The "state of cloth" also includes the degree of swelling of the cloth, which changes as the drying progresses.

[0009] (First embodiment) The configuration of a washing machine 100 according to an embodiment will be described with reference to Figs. 1 to 4. Fig. 1 is a first diagram showing an example of the configuration of the washing machine 100 according to an embodiment. Fig. 2 is a second diagram showing an example of the configuration of the washing machine 100 according to an embodiment. Fig. 3 is a diagram showing a state in which a door 3 of the washing machine 100 according to an embodiment is open. The washing machine 100 has a drying function. The washing machine 100 is a drum type washing machine. The washing machine 100 includes, for example, an outer box (casing) 1, a door 3, a water receiving tub 4 (an example of a drying chamber), a drum motor 5, a drum 7 (an example of a rotating tub), a water supply valve 10, a water supply valve motor 11 (shown in FIG. 2), a water inlet case 12, a water inlet 13, a drain pipe 14, a drain valve 15, a main duct 17, a front duct 18, a fan casing 19, a fan motor 22, a fan 24, a rear duct 25, a compressor 27, a compressor motor 28, a condenser 29A, an evaporator 29B, a refrigerant pipe 30, and a refrigerant pipe 31. 、 The washing machine 100 includes an expansion valve (not shown), a drain valve motor 47 (shown in FIG. 2), a water level sensor 48 (shown in FIG. 2), an operation panel 49 (shown in FIG. 2), a rotational position sensor 82 (shown in FIG. 2), a camera module 3C, a light 3L (lighting section), temperature sensors 18TS, 25TS, 29ATS, 29BTS, and a vibration sensor 4GS. The washing machine 100 is an example of a drying system.

[0010] The outer box 1 forms the exterior of the washing machine 100. The outer box 1 is hollow and has a front panel, a rear panel, a left panel, a right panel, a bottom panel, and a top panel. A through-hole-shaped entrance 2 is formed in the front panel of the outer box 1. A door 3 is attached to the front panel of the outer box 1 and is rotatably locked via a hinge. The door 3 can be operated from the front by a user to either a closed state or an open state. When the door 3 is closed, the entrance 2 is closed. When the door 3 is open, the entrance 2 is opened. The door 3 can close the entrance 2 of the water receiving tub 4 so as to be openable and closable. The door 3 has an inner surface 3IS facing the water receiving tub 4 (drying chamber) or the drum 7 (rotating tub) described later. A camera module 3C and a light 3L for photographing the internal space of the drum 7 are provided on the inner surface 3IS of the door 3. Wiring to the camera module 3C and the light 3L is arranged to pass near the hinge. It should be noted that part of the front surface of the door 3 may include a decorated area, and the camera module 3C may be arranged so as to be hidden from the outside of the door 3 by this decoration.

[0011] A water receiving tank 4 is fixed inside the outer box 1. The water receiving tank 4 is cylindrical with a closed rear face. The water receiving tank 4 is arranged in an inclined state such that the axis line CL of the water receiving tank 4 descends from the front to the rear. The front face of the water receiving tank 4 is open. When the door 3 is closed, it closes the front face of the water receiving tank 4 in an airtight state.

[0012] A drum motor 5 is fixed to the rear plate of the water receiving tub 4, positioned outside the water receiving tub 4. The drum motor 5 is a motor used for washing and spin-drying processes in washing. The drum motor 5 is, for example, a speed-controllable DC (Direct Current) brushless motor. A rotating shaft 6 of the drum motor 5 protrudes into the water receiving tub 4. The rotating shaft 6 is arranged to overlap with the axial center line CL of the water receiving tub 4. A drum 7 is fixed to the rotating shaft 6, positioned inside the water receiving tub 4. The drum 7 is cylindrical with a closed rear face. The drum 7 rotates integrally with the rotating shaft 6 when the drum motor 5 is in operation. The front face of the drum 7 faces the entrance 2 from behind, via the front face of the water receiving tub 4. When the door 3 is open, laundry is inserted and removed from the inside of the drum 7 from the front through the entrance 2, the front face of the water receiving tub 4, and the front face of the drum 7.

[0013] Drum 7 is formed with a plurality of through holes 8. The internal space of drum 7 is connected to the internal space of water receiving tub 4 through each of the plurality of through holes 8. A plurality of baffles 9 are provided or fixed to the inner surface of drum 7. Each of the plurality of baffles 9 moves in the circumferential direction about axis line CL as drum 7 rotates. The laundry in drum 7 moves in the circumferential direction while being caught by each of the plurality of baffles 9, and then falls by gravity, thereby being agitated.

[0014] A water supply valve 10 is fixed inside the outer box 1. The water supply valve 10 has an inlet and an outlet. The inlet of the water supply valve 10 is connected to a water faucet. The water supply valve 10 is driven by a water supply valve motor 11. The outlet of the water supply valve 10 is switched between an open state and a closed state according to the amount of rotation of the water supply valve motor 11. The outlet of the water supply valve 10 is connected to a water supply case 12. When the water supply valve 10 is in the open state, tap water is injected into the water supply case 12 through the water supply valve 10. On the other hand, when the water supply valve 10 is in the closed state, tap water is not injected into the water supply case 12. The water supply case 12 is fixed inside the outer box 1 at a higher position than the water receiving tank 4. The water supply case 12 has a cylindrical water injection port 13. The water injection port 13 is inserted into the water receiving tank 4. Tap water injected into water inlet case 12 from water inlet valve 10 is injected into water receiving tank 4 from water inlet port 13 .

[0015] The upper end of drain pipe 14 is connected to water receiving tank 4 at its bottommost position. Drain valve 15 is provided on drain pipe 14. Drain valve 15 is driven by drain valve motor 47. Drain valve 15 is switched between an open state and a closed state depending on the amount of rotation of drain valve motor 47. When drain valve 15 is in the closed state, tap water poured into water receiving tank 4 from water inlet 13 is stored in water receiving tank 4. On the other hand, when drain valve 15 is in the open state, tap water in water receiving tank 4 is discharged outside water receiving tank 4 through drain pipe 14.

[0016] A main duct 17 located below the water receiving tank 4 is fixed to the bottom plate of the outer box 1. The main duct 17 is shaped like a cylinder that is oriented in the front-rear direction. The lower end of a front duct 18 is connected to the front end of the main duct 17. The front duct 18 is shaped like a cylinder that is oriented in the up-down direction. The upper end of the front duct 18 is connected to the front end of the water receiving tank 4 and to the internal space of the water receiving tank 4. A fan casing 19 is fixed to the rear end of the main duct 17. The fan casing 19 has a through-hole-shaped air intake 20 and a cylindrical exhaust port 21. The internal space of the fan casing 19 is connected to the internal space of the main duct 17 via the air intake 20.

[0017] A fan motor 22 is fixed to the fan casing 19, located outside the fan casing 19. The fan motor 22 has a rotating shaft 23 that protrudes into the fan casing 19. A fan 24, located inside the fan casing 19, is fixed to the rotating shaft 23. The fan motor 22 rotates the fan 24. The fan 24 is, for example, a centrifugal fan. That is, the fan 24 sucks in air from the axial direction and discharges it in the radial direction as it rotates. An intake port 20 provided in the fan casing 19 faces the fan 24 from the axial direction of the fan 24. An exhaust port 21 provided in the fan casing 19 faces the fan 24 from the radial direction of the fan 24.

[0018] The lower end of the rear duct 25 is connected to the exhaust port 21 of the fan casing 19. The rear duct 25 is tubular and oriented in the vertical direction. The upper end of the rear duct 25 is connected to the rear end of the water receiving tank 4 and the internal space of the water receiving tank 4. The rear duct 25, the fan casing 19, the main duct 17, the front duct 18, and the water receiving tank 4 form a ring-shaped circulation duct 26 that starts and ends in the internal space of the water receiving tank 4. When the fan motor 22 is operated with the door 3 closed, the fan 24 rotates in a certain direction, so that the air in the water receiving tank 4 is sucked from the front duct 18 through the main duct 17 into the fan casing 19, and is returned from the fan casing 19 through the rear duct 25 into the water receiving tank 4. The front duct 18 is provided with a temperature sensor 18TS that detects the temperature in the front duct 18. The rear duct 25 is provided with a temperature sensor 25TS that detects the temperature inside the rear duct 25. When the temperature sensor 18TS or 25TS detects that the temperature inside each duct exceeds a predetermined temperature, the power supply to a compressor 27, which will be described later, is cut off. The detection results of the temperature sensors 18TS and 25TS may be used for protection purposes as described above, and may also be used for controlling the drying process.

[0019] A compressor 27 is fixed inside the outer box 1. The compressor 27 is disposed outside the circulation duct 26. The compressor 27 has a discharge port for discharging the refrigerant and a suction port for sucking the refrigerant. The compressor 27 is driven by a compressor motor 28. The compressor motor 28 is, for example, a speed-controllable DC brushless motor.

[0020] A condenser 29A and an evaporator 29B are fixed inside the main duct 17. For example, the compressor 27, the condenser 29A, the evaporator 29B, an expansion valve (not shown), and a refrigerant pipe 30 for circulating the refrigerant therethrough form a drying unit 31 that functions as a heat pump. The drying unit 31 generates heat from the condenser 29A by the operation of the compressor 27. For example, the condenser 29A heats the air circulating inside the main duct 17 by heat exchange with the refrigerant. The evaporator 29B vaporizes the refrigerant by the heat of the air circulating inside the main duct 17. The drying unit 31 is an example of a drying function that dries laundry. The drying unit 31 may be formed including the main duct 17, the fan casing 19, the fan motor 22, the fan 24, and the like, which will be described later. The condenser 29A may be provided with a temperature sensor 29ATS that detects the temperature of the condenser 29A, and the evaporator 29B may be provided with a temperature sensor 29BTS that detects the temperature of the evaporator 29B.

[0021] The water level sensor 48 is provided in the water receiving tub 4. The water level sensor 48 detects the water level in the water receiving tub 4. The operation panel 49 includes a display unit 49a (not shown) and an operation input unit 49b (not shown). For example, the display unit 49a and the operation input unit 49b are a panel equipped with a button and a display device that can be pressed by the user, or a touch panel that can be operated by the user. The user can operate the operation panel 49 to select the operation course of washing and drying, start the operation, and the like. Examples of the operation courses of washing include a standard course, a speedy course, a delicate course (careful washing course), a room drying course, and a stubbornly soiled course. The amount of water poured into the water receiving tub 4 during washing, the water flow in the water receiving tub 4 during rinsing, and the contents of the washing process are different for each operation course of washing. In addition, the operation panel 49 displays the washing process, the remaining time until the end of the operation, the set water level, and the like.

[0022] The camera module 3C of the embodiment is, for example, a camera equipped with an imaging element having sensitivity characteristics in the visible light region and capable of generating a color image, and a wide-angle optical system (wide-angle lens). The imaging element of the camera module 3C has an optical filter that blocks the infrared light region. The optical axis AX of the optical system is directed into the drum 7. More specifically, the optical axis AX is directed in a direction in which the laundry in the drum 7 can be photographed. The camera module 3C is configured with a lighting 3L, and may be integrated with the lighting 3L.

[0023] The lighting 3L, when turned on, increases the illuminance of the subject inside the drum 7. Therefore, it is preferable to turn on the lighting 3L when photographing with the camera module 3C. The period during which the lighting is turned on may include the period of the drying process, may extend over the period of the drying process, or may be adjusted so as to be turned on in synchronization with photographing with the camera module 3C. The position where the lighting 3L is disposed is not limited to within the camera module 3C, and may be a position separated from the camera module 3C as long as it is a position where the illuminance of the subject inside the drum 7 can be increased.

[0024] The control circuit 50 may include a hardware processor such as a CPU (Central Processing Unit) and may execute a program (software) to realize the above control. However, some or all of the above control may be realized by including hardware (including circuitry) such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), or may be realized by a combination of software and hardware.

[0025] For example, the control circuit 50 includes a dryness detection unit 510, a storage unit 520, a processing unit 530, an interface unit 540, and a communication unit 550. The dryness detection unit 510, the storage unit 520, the processing unit 530, the interface unit 540, and the communication unit 550 are connected via a bus or the like within the control circuit 50. Some or all of the dryness detection unit 510, the storage unit 520, the processing unit 530, the interface unit 540, and the communication unit 550 may be mounted together in one or more semiconductor devices.

[0026] The interface section 540 is connected to the drum motor 5, the drain valve motor 47, the water supply valve motor 11, and the drying unit 31. The interface section 540 may be configured to include drive circuits for driving the drum motor 5, the drain valve motor 47, the water supply valve motor 11, and the drying unit 31, respectively, or a part or all of the drive circuits may be provided outside the interface section 540. The drum motor 5, the drain valve motor 47, the water supply valve motor 11, and the drying unit 31 are controlled via the interface section 540.

[0027] The interface unit 540 is further connected to various sensors and the operation panel 49. The various sensors include temperature sensors 29ATS, 29BTS, 18TS, 25TS, a water level sensor (not shown), a rotational position sensor 82, a vibration sensor 4GS, a door switch (not shown), and the like. The temperature sensors 29ATS, 29BTS detect the temperatures of the condenser 29A and the evaporator 29B, respectively. The temperature sensors 18TS, 25TS detect the temperatures of the air discharged from the water receiving tank 4 and the air supplied to the water receiving tank 4, respectively. The water level sensor detects the water level in the water receiving tank 4. The rotational position sensor 82 detects the rotational position of the drum motor 5. The current sensor detects the current flowing through the windings of the drum motor 5. The door switch detects whether the door 3 is open or closed. The processing unit 530, which will be described later, acquires information from the various sensors via the interface unit 540 and exchanges information with the operation panel 49.

[0028] The dryness detection section 510 includes, for example, an information acquisition section 511, an arithmetic processing section 512, and a determination section 513. In the following description, the functions of the dryness detection section 510 are assigned to the above-mentioned sections, but the functions may be assigned to any divided functional sections without being limited thereto. For example, a part or all of the arithmetic processing performed by the arithmetic processing section 512 may be performed by the information acquisition section 511.

[0029] For example, the input of the information acquisition unit 511 is connected to the output of the camera module 3C. The information acquisition unit 511 acquires an image output by the camera module 3C, and adds the acquired image data to the storage unit 520 described later as image data. The calculation processing unit 512 performs calculation processing on the image data (information) acquired by the information acquisition unit 511 according to a predetermined calculation procedure. The judgment unit 513 judges the progress of drying of the laundry (cloth) based on the calculation result of the calculation processing unit 512 according to a predetermined judgment rule. The judgment unit 513 makes the above judgment result available as data for controlling the drying operation described later.

[0030] The dryness detection section 510 may be activated by a processing section 530 (described later) while the drying operation is being performed, and set to a suspended state during other periods.

[0031] The storage unit 520 has semiconductor memories such as a random access memory (RAM), a read only memory (ROM), and an electrically erasable ROM (EEPROM). The EEPROM is an example of an electrically erasable non-volatile semiconductor memory, and is used as a non-volatile storage area. The storage unit 520 stores image data of a plurality of images output by the camera module 3C, data showing differences in characteristics of the plurality of images, detection results of various sensors, data defining judgment criteria used in the judgment process, user management information, various programs, and various information used to execute the various programs. The user management information includes identification information for identifying a user or the washing machine 100. For example, the user management information is used when the washing machine 100 attempts to communicate with the server 200.

[0032] The processing unit 530 controls the drum motor 5, the drain valve motor 47, the water supply valve motor 11, and the drying unit 31 in response to control information based on the user's operation received by the operation panel 49. For example, the processing unit 530 controls each of the above to control the washing operation, the spin-drying operation, the rinsing operation, and the drying operation. The processing unit 530 may control each of the above based on the state detected by various sensors. In addition, the processing unit 530 uses the result of the determination by the determination unit 513 as data for controlling the drying operation when controlling the end of the drying operation by the drying unit 31.

[0033] The communication unit 550 is formed to be connectable to, for example, a network NW. For example, the communication unit 550 is connected to a server 200 (described later) via the network NW. An embodiment using the communication unit 550 will be described later.

[0034] Further, the rotor of drum motor 5 is provided with a rotational position sensor 82. A position signal indicating the position of the rotor outputted from rotational position sensor 82 is outputted to control circuit 50. For example, upon starting drum motor 5, washing machine 100 performs vector control using rotational position sensor 82 up to a rotational speed at which the rotor position can be estimated (e.g., about 30 rpm). After reaching a rotational speed at which the rotor position can be estimated, the control switches to sensorless vector control in which rotational position sensor 82 is not used.

[0035] As described above, the control circuit 50 controls the entire washing machine 100. For example, the control circuit 50 also has a protection function of cutting off the power supply to the drum motor 5 when an overcurrent is detected in the current flowing through the windings of the drum motor 5, when a temperature equal to or higher than a predetermined temperature is detected during a drying operation, or the like.

[0036] FIG. 4 is a diagram for explaining the drive control of the drum motor 5 in one embodiment. The interface section 540 of the control circuit 50 includes, as a drive circuit for the drum motor 5, an inverter circuit 32, shunt resistors 35u, 35v, 35w, a level shift circuit 36, a drive circuit 44, and a drum motor control section 541.

[0037] The drum motor control unit 541 estimates the phase θ and rotational angular velocity ω of the rotating magnetic field in the drum motor 5 based on the detection result of the rotational position sensor 82 or the detection value of the current flowing through the windings described below. This estimation may be performed using a general method.

[0038] For example, the drum motor control unit 541 receives a speed command for the drum motor 5 and generates a current command Idref and a current command Iqref by speed control using the rotational angular velocity ω as a control feedback value. For example, the speed command for the drum motor 5 is determined by each operation control by the processing unit 530. The speed control may use a vector control method.

[0039] The drum motor control unit 541 detects the current Iau flowing through the winding 5u of the drum motor 5, the current Iav flowing through the winding 5v of the drum motor 5, and the current Iaw flowing through the winding 5w of the drum motor 5 through the level shift circuit 36. Specifically, the drum motor control unit 541 detects the current through the level shift circuit 36 ​​during a period when the overcurrent is not detected through the overcurrent comparison circuit 38. The currents detected by the drum motor control unit 541 through the level shift circuit 36 ​​during a period when the overcurrent is not detected are the currents Iau, Iav, and Iaw. The drum motor control unit 541 performs an orthogonal coordinate transformation and a dq (direct-quadrature) coordinate transformation of the three-phase current based on the current values ​​and phase θ of the detected currents Iau to Iaw to obtain the current Id of the excitation current component and the current Iq of the torque current component. As described above, the shunt resistors 35u, 35v, and 35w, the level shift circuit 36, and the drum motor control unit 541 are an example of an electric wire sensor.

[0040] Then, drum motor control unit 541 generates voltage commands Vd, Vq by current control based on the estimated phase θ, current Id of the excitation current component, current Iq of the torque current component, current command Idref, and current command Iqref.

[0041] For example, in the above current control, the drum motor control unit 541 subtracts the current Id from the current command Idref. The drum motor control unit 541 performs PI control so that the subtraction result becomes 0. This generates a voltage command Vd. The drum motor control unit 541 also subtracts the current Iq from the current command Iqref. The drum motor control unit 541 performs PI control so that the subtraction result becomes 0. This generates a voltage command Vq. Then, the drum motor control unit 541 performs inverse dq coordinate transformation and three-phase coordinate transformation based on the voltage commands Vd, Vq and the phase θ to generate signals for three phases. The inverse dq coordinate transformation is a transformation that is the reverse of the above-mentioned dq coordinate return. Finally, a drive signal that drives the inverter circuit 32 is generated as a PWM signal.

[0042] Drive circuit 44 generates gate pulses for each IGBT of inverter circuit 32 from the PWM signal output by drum motor control unit 541, performs level conversion on the gate pulses and supplies them to inverter circuit 32. Inverter circuit 32 passes a current for driving drum motor 5 through windings 5u-5w of drum motor 5. The level conversion may be configured separately from drive circuit 44.

[0043] Next, a description will be given of processes related to washing in the washing machine 100. Fig. 5 is a diagram showing a process flow of the washing machine 100. Here, a description will be given of processes performed by the washing machine 100 when the user selects, via the operation panel 49, an operation course in which a washing process including each of the processes of washing, rinsing, spin-drying, and drying is performed.

[0044] A user loads laundry into washing machine 100 and starts washing. When washing machine 100 starts the determined operation course, control circuit 50 (processing unit 530; the same applies below) identifies the weight of the laundry (referred to as the laundry amount) (step S1). This identification of the laundry amount is performed before water is poured in. For example, as described in Japanese Patent No. 3962668 and the like, control circuit 50 generates a PWM signal as a laundry amount detection operation before water is poured in, thereby identifying the laundry amount from the magnitude of q-axis current Iq that contributes to the torque of drum motor 5 when drum motor 5 is rotated via inverter circuit 32 to rotate laundry in drum 7.

[0045] Also, for example, the washing machine 100 may store each amount of poured water in association with the laundry amount of the laundry corresponding to each amount of poured water, and the control circuit 50 may, as a pre-water-pouring laundry amount detection operation, specify an amount of poured water equivalent to the amount of poured water set by the user when deciding the operation course from among the amounts of poured water stored in the washing machine 100, and specify the laundry stored in association with the specified amount of poured water as the laundry amount in this case. Then, detergent is poured in. This pouring of detergent may be performed by the user. Also, if the washing machine 100 is equipped with an automatic detergent dispenser, the washing machine 100 may dispense the detergent.

[0046] The control circuit 50 controls the drain valve motor 47 to close the drain valve 15, and controls the water supply valve motor 11 to execute a water supply step of pouring water into the drum 7 (step S2). After the water supply step is completed, the control circuit 50 generates a PWM signal to rotate the drum motor 5 via the inverter circuit 32, thereby executing a wash step (step S3). Specifically, under the control of the control circuit 50, the drum motor 5 rotates forward and backward repeatedly, thereby agitating the laundry and detergent water in the drum 7, in which detergent is dissolved in water, and removing dirt from the laundry. At this time, the control circuit 50 determines the fabric type by identifying the fluctuation in the current Iq flowing through the drum motor 5 (step S4).

[0047] When the washing cycle is completed, the control circuit 50 controls the drain valve motor 47 to open the drain valve 15, thereby executing a drain cycle to drain water from the drum 7 (step S5). When the drain cycle is completed, the control circuit 50 generates a PWM signal to rotate the drum motor 5 via the inverter circuit 32, thereby executing a first spin cycle to perform spin-drying (step S6). When the spin cycle is completed, the control circuit 50 controls the drain valve motor 47 to close the drain valve 15, and controls the water supply valve motor 11 to execute a water supply cycle to inject water into the drum 7 (step S7).

[0048] After the water supply step is completed, the control circuit 50 generates a PWM signal to rotate the drum motor 5 via the inverter circuit 32, thereby executing a rinsing step to rinse out the detergent (step S8). After the rinsing step is completed, the control circuit 50 controls the drain valve motor 47 to open the drain valve 15, thereby executing a draining step to drain water from the drum 7 (step S9).

[0049] When the drainage cycle is completed, the control circuit 50 generates a PWM signal to rotate the drum motor 5 via the inverter circuit 32, thereby executing a second dehydration cycle (an example of the first dehydration operation) to perform dehydration (step S10).

[0050] The control circuit 50 judges whether the predetermined condition is satisfied based on information about the laundry acquired before the second spin cycle (step S11). Specifically, the control circuit 50 judges that the predetermined condition is satisfied when the laundry amount obtained based on the laundry amount detection operation before water pouring, which is the process of step S1, is equal to or greater than a threshold value. The control circuit 50 also judges that the predetermined condition is not satisfied when the laundry amount obtained based on the laundry amount detection operation before water pouring is less than the threshold value.

[0051] When the control circuit 50 determines that the predetermined condition is satisfied (i.e., the laundry amount determined by the process of step S1 is equal to or greater than the threshold value) (YES in step S11), it determines the laundry amount (step S12). Note that the determination of the laundry amount here may be based on the current Iq, as in the process of step S1. Note that the laundry amount may be determined using a method that uses the current Iq, that is, the moment of inertia when the drum 7 rotates (see Japanese Patent No. 3962668, etc.). Alternatively, the laundry quality may be determined in step S12 by increasing the moisture content of the laundry to increase the density of the laundry, thereby making it easier for the weight to be biased radially outward of the drum 7, and increasing the moment of inertia, thereby improving the accuracy of determining the laundry amount.

[0052] Furthermore, when the control circuit 50 determines that the predetermined condition is not satisfied (i.e., the laundry amount determined by the process of step S1 is less than the threshold value) (NO in step S11), it executes the spin-drying process (step S13) without executing the process of step S12. The rotation speed of the drum motor 5 in the third spin-drying process is preferably set to be faster than the rotation speed of the drum motor 5 in the second spin-drying process.

[0053] Next, the control circuit 50 determines the content of the drying operation based on the result of identifying the amount of laundry (step S14). An example of the content of the drying operation is the operation time of the heat pump 300. That is, the control circuit 50 lengthens the time of the drying operation as the identified amount of laundry increases. The operation time may be determined by correcting the rotation speed of the drum 7 in the second dehydration step, the duration of rotation, the degree of imbalance of the laundry, and the like.

[0054] The control circuit 50 executes the drying process according to the determined content of the drying operation (step S15). The control circuit 50 ends the drying process and ends the process.

[0055] The control of the drying operation of the embodiment will be described with reference to Fig. 6 and Fig. 7. Fig. 6 is a diagram showing a process flow of the control of the drying operation of the embodiment. Fig. 7 is a diagram for explaining images acquired during the process of the embodiment.

[0056] When starting the drying operation, information acquisition unit 511 of drying state detection unit 510 acquires information on the initial state of the laundry placed in drum 7 (step SA11) and adds the acquired information to memory unit 520. For example, the information on the initial state of the laundry includes image information (image data) captured by camera module 3C.

[0057] For example, an image as shown in (a) in FIG. 7 is captured as an image showing an initial state, and image data of that image is included here. The image shown in (a) in FIG. 7 shows the inner surface of the drum 7 and the laundry in a wet state. In contrast to (a) in FIG. 7, (b) in FIG. 7 shows a state in which the laundry has progressed in drying. It can be seen from the image that the laundry is less bulging at the stage shown in (a) in FIG. 7, and that the laundry is more bulging at the stage shown in (b) in FIG. 7. Such a change is detected by the following processing or the like. In order to distinguish between the inner surface of the drum 7 and the laundry, a region segmentation method or a method such as background difference may be used.

[0058] 6, next, processing unit 530 controls water supply valve motor 11 to close water supply valve 10 in response to control information based on the user's operation received by operation panel 49. Processing unit 530 controls drum motor 5 and drying unit 31 to start the drying operation (step SA12).

[0059] The calculation processing unit 512 acquires image data (status information) for detecting the state of the laundry during the drying operation (step SA13), and performs a predetermined calculation process based on the acquired image data (step SA14). The state of the laundry includes, for example, the movement of the cloth or the state of the cloth in the drum 7 during the drying operation. When using information from various sensors other than the image data, it is preferable to acquire detection values ​​from the various sensors together with acquiring the image data.

[0060] The determination unit 513 determines the result of the above calculation processing, and determines whether or not the drying operation needs to be continued based on the determination result (step SA18). If it is determined that the drying operation needs to be continued, the processing unit 530 continues the drying operation and repeats the processing from step S13. If it is determined that the drying operation does not need to be continued, the processing unit 530 ends the drying operation (step SA19).

[0061] Next, a method for detecting the movement or state of the cloth in the drum 7 during the drying operation will be described. The detection method described below basically uses image data of the image captured by the camera module 3C. Depending on the conditions, data of the detection results of various sensors may be used without using image data output by the camera module 3C, or instead, image data output by the camera module 3C and data of the detection results of various sensors may be used. The above various sensors may include temperature sensors 18TS, 25TS, 29ATS, 29BTS, vibration sensor 4GS, etc. Although the above various sensors are not sensors that directly detect physical quantities, they may include a weight sensor that indirectly detects the amount of cloth (cloth amount detection process of the control circuit 50) or a current sensor that detects the current flowing through the winding (a combination of shunt resistors 35u, 35v, 35w, a level shift circuit 36, and a drum motor control unit 541).

[0062] In this way, the judgment unit 513 may judge the progress of drying based on information obtained from one or more of the vibration sensor 4GS, each temperature sensor, weight sensor, or current sensor (current detection unit) provided in the washing machine 100, in addition to information indicating the movement or condition of the cloth.

[0063] For example, when temperature data is used, the gradient of the temperature change of the air circulating through the drum 7 or the temperature of the air exceeding a predetermined temperature may be used to detect the progress of drying. As the drying progresses, the gradient of the temperature change becomes steeper at a certain point. The determination unit 513 may determine that the drying is sufficient by detecting the change in the gradient or the temperature change and exceeding a predetermined temperature.

[0064] When using vibration data, it is advisable to use a comparison with the start of drying or a change amount at each detection time point. For example, as the drying of the cloth progresses, the amount of water soaked into the cloth decreases, and the weight of the cloth decreases accordingly. When the drum 7 is rotated with the cloth being comparatively heavy, the weight of the cloth is biased with respect to the axis CL of the drum 7, and the cloth is stirred and moves inside the drum 7, causing the vibration of the washing machine 100 to become comparatively large. This vibration becomes comparatively small as the drying of the cloth progresses. Therefore, it is possible to detect the degree of drying by comparing with the start of drying or detecting the change amount based on the vibration data detected by the vibration sensor 4GS.

[0065] When image data is used, the movement or condition of the fabric may be detected using one or more of the techniques described below.

[0066] As a first technique, there is a technique of acquiring the movement or state of the cloth by using two or more image data images of the cloth inside the drum 7 taken with a predetermined time difference. A second technique involves obtaining the movement or state of the fabric by using two or more sets of image data captured with a predetermined time difference during the drying operation. A third technique involves obtaining the movement or condition of the fabric by using both one or more images taken of the fabric in the drum 7 before the drying operation or before a certain time has elapsed since the start of the drying operation, and one or more images taken during the drying operation. A fourth technique involves obtaining the movement or condition of the cloth by using both a plurality of first images taken before the drying operation of the cloth in the drum 7 or before a certain time has elapsed since the start of the drying operation, and a plurality of second images taken after a certain time has elapsed since the start of the drying operation.

[0067] Each of the above techniques using image data will now be described in order.

[0068] First, with reference to FIG. 8 and FIG. 9, an example of an image used in each of the above techniques will be described. FIG. 8 is a diagram showing an example of an image obtained by simulating a state in which laundry is agitated during a drying operation. The colors of the fabrics that occupy a relatively large area in a specific region of the image have the following characteristics, starting from the top of FIG. 8. The image (a) in FIG. 8 has relatively more brown, white, and blue. The image (b) in FIG. 8 has relatively more white, but also includes some brown, gray, etc. The image (c) in FIG. 8 has relatively more brown. The image (d) in FIG. 8 has relatively more white. The image (e) in FIG. 8 has relatively more white and gray. The image (f) in FIG. 8 has relatively more brown and blue, and also includes some white, etc. Note that the specific region in the above image is set to be filled with an image of laundry, but is not limited to this. This image may also include a portion of the drum 7 as shown in FIG. 7.

[0069] Fig. 9 is a diagram for explaining the feature amount of the image shown in Fig. 8. The graph shown in Fig. 9 is an example of a histogram of the R component among the RGB components for each pixel in a specific region of each image.

[0070] In the case of the RGB color system, the color of each pixel constituting an image is defined by the intensity value of the three primary color components of RGB. For example, the intensity value of the color component of each pixel is quantized with 8-bit resolution for each RGB component. In this case, the intensity value of the color component of each pixel takes a value of 256 gradations, for example, R0-R255, G0-G255, and B0-B255. However, the intensity value of each color component may be normalized to have a maximum value of 1.

[0071] For each RGB component, the intensity value is divided into multiple ranges. For example, each RGB component is divided into seven ranges: Rz1-Rz7, Gz1-Gz7, and Bz1-Bz7. The Rz1 range is assigned to 0-35, the Rz2 range to 36-70, the Rz3 range to 71-105, the Rz4 range to 106-140, the Rz5 range to 141-175, the Rz6 range to 176-210, and the Rz7 range to 211-255. The above divisions are merely examples and may be changed as appropriate.

[0072] The washing machine 100 acquires each image by repeatedly capturing images at a predetermined cycle using the camera module 3C. Each image is indicated by PICx. x is an identifier for identifying each image corresponding to the time calendar, and is, for example, an arbitrary integer. When each image is not distinguished, it is simply called an image PIC. A specific image PIC may be called an image PICx.

[0073] For example, the frequency of color components of pixels in a specific area among the multiple pixels constituting the image PICx is tallied to generate a histogram. Here, a function indicating the frequency of intensity values ​​of color components of pixels in a specific area among the multiple pixels constituting the image PICx is defined using the following formula (1). The example shown below is for the R component.

[0074] YRz1(PICx) = fRz1(PICx) YRz2(PICx) = fRz2(PICx) YRz3(PICx) = fRz3(PICx) | | YRz7(PICx) = fRz7(PICx) (1)

[0075] In the above equation, the function fRz1(PICx) on the right side extracts the frequency of pixels whose R component intensity values ​​of pixels in a specific region among the multiple pixels that make up the image PICx are included in the range Rz1. YRz1(PICx) on the left side indicates the resulting frequency. Functions fRz2(PICx) to fRz7(PICx) are similar to the above function fRz1(PICx), but have different ranges that define the R component intensity values. The calculated R component intensity distribution YR(PICx) is shown in the following equation (2).

[0076] YR(PICx)=[YRz1(PICx), YRz2(PICx), YRz3(PICx),..., YRz7(PICx)] (2)

[0077] The above is an explanation of the intensity distribution YR(PICx) of the R component, but the intensity distribution YG(PICx) of the G component and the intensity distribution YB(PICx) of the B component can also be defined using the following equations (3) and (4), in the same way as the R component.

[0078] YG(PICx)=[YGz1(PICx), YGz2(PICx), YGz3(PICx),..., YGz7(PICx)] (3) YB(PICx)=[YBz1(PICx), YBz2(PICx), YBz3(PICx),..., YBz7(PICx)] (4)

[0079] The intensity distribution of these components is summarized as shown in equation (5) and defined as Y(PICx), which is an example of the feature amount of each image.

[0080] Y(PICx) = [YR(PICx), YG(PICx), YB(PICx)] (5)

[0081] The relationship between the color of the subject and the frequency distribution of the intensity values ​​of the RGB components will be further explained with reference to Fig. 10. Fig. 10 is a diagram for explaining the relationship between the color of the subject and the frequency distribution of the intensity values ​​of the RGB components. A typical example will be given below to explain how the frequency distribution of the intensity values ​​of the RGB components changes when the color of each subject changes.

[0082] FIG. 10(a) shows the case where the area is covered in a relatively bright white. FIG. 10(b) shows the case where the area is covered in black. FIG. 10(c) shows the case where the area is covered in grayscale (achromatic color with gradually changing brightness). FIG. 10(d) to (f) show the cases where the achromatic area contains partly blue areas, partly red, and partly green, respectively. FIG. 10(g) and (h) show the cases where the achromatic area contains partly relatively light brown areas and partly relatively dark brown areas, respectively. In this way, when the color tendency within the image changes, the distribution of each RGB component changes.

[0083] For example, when a light brown cloth is dry, its brightness becomes darker when it gets wet. In other words, the brightness of the cloth changes depending on the degree of dryness. This difference in brightness can be reproduced in the image captured by the camera module 3C. By utilizing this feature, the dryness state of the laundry can be identified based on the change in color components shown in the image of the laundry.

[0084] When laundry is wet, it is relatively heavy and easily tangled with other things, so that even if the drum 7 is rotated, the change in the obtained image is relatively small. Therefore, a histogram of the feature amount of each pixel of the two images is obtained, and attention is paid to the magnitude of the difference value between them. For example, FIG. 11 shows a histogram when there is a lot of change in the image, and FIG. 12 shows a histogram when there is little change in the image. FIG. 11 and FIG. 12 are diagrams for explaining examples of histograms showing the features of the image in one embodiment.

[0085] The histograms (a) to (d) in Fig. 11 correspond to the images shown in (a) to (d) in Fig. 8 above, and respectively show the distribution of RGB intensity values ​​shown by each pixel in a partial area. Based on this, the difference between the histograms (a) and (b) in Fig. 11 is shown in (d) in Fig. 11, the difference between the histograms (b) and (c) in Fig. 11 is shown in (e) in Fig. 11, and the difference between the histograms (c) and (d) in Fig. 11 is shown in (f) in Fig. 11.

[0086] In creating FIG. 12 shown as a sample here, two images (not shown) that model a case where there is no significant change from image (a) in FIG. 8 described above are prepared in place of (b) and (c) in FIG. 8. Histograms (a) to (d) in FIG. 12 were created based on these images using the same method as in FIG. 11. In the case of FIG. 12, (e) to (g) in FIG. 12 are generated in the same way as in FIG. 11. It can be seen that the frequencies shown in (e) and (f) in FIG. 12 are clearly lower than those shown in (e) to (g) in FIG. 11 and (g) in FIG. 12.

[0087] Therefore, the movement and state of the cloth are detected by focusing on the difference value of the histograms of the two images. For example, when there is little change in the image, the difference between the maximum and minimum values ​​of the difference value is relatively small, and when there is much change in the image, the difference between the maximum and minimum values ​​of the difference value is relatively large. The determination unit 513 may detect the movement and state of the cloth using the difference between the maximum and minimum values ​​of the difference value of the histograms.

[0088] Alternatively, the same results can be obtained by using the average value of the absolute values ​​of the difference values ​​of the histograms for each of the three color components, or the sum of the absolute values ​​of the difference values. The determination unit 513 may use any of the results of statistical processing such as the magnitude, average value, or sum of the difference values ​​of the histograms as the subject of the determination processing described below.

[0089] The first method will be described with reference to Fig. 8 and Fig. 11. Assume that each image shown in (a) to (f) in Fig. 8 is an image captured at a predetermined period, for example. The feature amount obtained from this image is as shown in Fig. 11. The method described with reference to Fig. 11 is an example of the first method.

[0090] According to the first method, the arithmetic processing unit 512 may obtain information indicating the movement or state of the cloth based on information obtained based on a first image taken at a first time and a second image taken at a second time later than the first time. The arithmetic processing unit 512 may periodically repeat this calculation. As described above, the time difference between the first time and the second time may be determined to be a predetermined length. In this example, the length is set to one minute, but is not limited to this and may be appropriately determined so as to facilitate detection. The same applies below.

[0091] More specifically, the information acquisition unit 511 acquires data (image data) of an image captured by the camera module 3C once every minute. The calculation processing unit 512 compares an image from one minute ago (e.g., PICx) with the latest image (e.g., PIC(x+1)), extracts the amount of change (RGB or brightness change (e.g., ΔYx)) between the two images, and obtains the progress of drying as output information based on the extracted amount of change.

[0092] When comparing two images, it is advisable to use the histograms of the color components of each image as the image features, as described above. The above process is shown in equation (6).

[0093] ΔY1 = [Y(PIC1) - Y(PIC2)] ΔY2 = [Y(PIC2) - Y(PIC3)] | | ΔYx = [Y(PICx) - Y(PIC(x+1)] (6)

[0094] Instead of the histogram of each color component, a luminance histogram may be used as an image feature amount, and a histogram of a specific color (color component) among the color components may be used in a similar manner.

[0095] This allows the amount of change in color components (e.g., RGB values) or brightness to be extracted as the amount of change between the two images, and the progress of drying can be obtained as output information by a determination process based on this amount of change. The details of this example will be described later. The same applies below.

[0096] The period during which the above information is acquired may include the period during which the cloth in the drum 7 is being dried, and may also include periods during which soapy water, rinsing water, etc. is not being poured into the water receiving tub 4 (or drum 7), such as before the start of washing or after spin-drying. By not limiting the period during which the above information is acquired to the period during which the cloth in the drum 7 is being dried, as described above, the information acquiring unit 511 can acquire more information regarding the cloth in the drum 7.

[0097] The second method may be realized in a manner similar to the first method described above. For example, according to the second technique, the arithmetic processor 512 may obtain information indicating the movement or state of the cloth based on information obtained from the first and second images taken at a predetermined time interval during the drying operation. The arithmetic processor 512 may periodically repeat this calculation. The predetermined time interval may be, for example, one minute.

[0098] More specifically, the information acquisition unit 511 sequentially acquires images captured by the camera module 3C. The calculation processing unit 512 compares an image taken one minute ago with the latest image, for example, to extract the amount of change (amount of change in RGB or brightness) between the two images, and obtains the progress of drying as output information based on the extracted amount of change. In the case of the second method described above, images may be sequentially acquired as a moving image or quasi-moving image. In this case, the density of the information acquired in the time axis direction becomes high, making it easier to acquire information on the movement of the cloth.

[0099] According to the above third technique, the calculation processing unit 512 may obtain information indicating the movement or condition of the cloth based on information obtained from a first image taken before the start of the drying operation or before a certain time has elapsed since the start of the drying operation, and a second image taken after a certain time has elapsed since the start of the drying operation.

[0100] More specifically, the information acquisition unit 511 sequentially acquires images captured by the camera module 3C. The calculation processing unit 512 acquires the progress of drying as output information, for example, based on a first image (e.g., PIC1) before or immediately after the start of the drying operation (initial state) and the latest image (e.g., PIC(x+1): second image). The above is summarized in equation (7).

[0101] ΔY1 = [Y(PIC1) - Y(PIC2)] ΔY2 = [Y(PIC1) - Y(PIC3)] | | ΔYx = [Y(PIC1) - Y(PIC(x+1)] (7)

[0102] In the case of the third method described above, by comparing the image of the initial state with the most recently acquired image, it is possible to obtain information indicating how much the fabric has been switched back and forth or how much the fabric has expanded. Since it is possible to compare the state of the fabric when time has passed from the initial stage when the fabric is wet to the state of the fabric as time has passed since that initial stage, it becomes easier to obtain information on the expansion of the fabric.

[0103] According to the fourth method, the calculation processor 512 uses both a plurality of first images taken before the drying operation of the cloth in the drum 7 or before a certain time has elapsed since the start of the drying operation, and a plurality of second images taken after a certain time has elapsed since the start of the drying operation, to obtain information on the difference between the amount of change in one minute before or immediately after the start of the drying operation (initial state) and the amount of change in the most recent one minute. The above is summarized in equation (8).

[0104] ΔY1 = [Y(PIC1) - Y(PIC2)] ΔY2 = [Y(PIC2) - Y(PIC3)] | | ΔYx = [Y(PICx) - Y(PIC(x+1)] ΔY(x+1) = [Y(PIC(x+1) - Y(PIC(x+2))] (8)

[0105] In the fourth method, for example, all of the four feature amounts (the pair of ΔY1, ΔY2 and the pair of ΔYx, ΔY(x+1)) shown in the above formula (8) are used at the timing of judgment.

[0106] As described above, the ease of detecting the necessary information may be used as a selection criterion to appropriately select the set of images to be used during the drying operation and the detection method.

[0107] Next, an example of an indicator for detecting the progression of a dry state based on the detection results of the above-mentioned technique will be described.

[0108] As described above, when the laundry is wet, it is relatively heavy and easily entangled with other fabrics. Therefore, even if the drum 7 is rotated, the image obtained changes relatively little. As described above, the determination unit 513 may use the results of statistical processing such as the magnitude, average, and sum of the difference values ​​of the histograms obtained from the detection results of each of the above methods as the subject of the determination processing.

[0109] The washing machine 100 (drying system) according to one embodiment has been described above. According to the above embodiment, washing machine 100 includes information acquisition unit 511 and determination unit 513. Information acquisition unit 511 acquires information indicating the movement or state of the cloth in drum 7 during the drying operation. Determination unit 513 determines the progress of drying of the cloth based on the information acquired by information acquisition unit 511. Washing machine 100 can end the drying operation at a more appropriate timing by performing the drying operation based on the determination result of determination unit 513 on the progress of drying. For example, the determination of the information acquired by information acquisition unit 511 may be performed by using a predetermined threshold value and comparing it with this threshold value.

[0110] For example, the information indicating the movement of the cloth may be information indicating a change in color element or brightness included in the image in response to a change in the position of the cloth inside the drum 7. Furthermore, the information indicating the state of the cloth may be information indicating a change in color element or brightness included in the image in response to a change in the proportion of the cloth inside the drum 7 in the image.

[0111] Second embodiment The second embodiment will be described with reference to FIGS. In the first embodiment, a case where the washing machine 100 performs the drying control by itself has been described. In the present embodiment, a case where an external device performs part of the processing related to the drying control will be described.

[0112] FIG. 13 is a configuration diagram of a drying system 1000 according to the second embodiment. The drying system 1000 includes a server 200 configured to be able to communicate with the washing machine 100A. The drying system 1000 may be configured to include the washing machine 100A. The washing machine 100A and the server 200 are configured to be able to communicate with each other via a network NW.

[0113] Washing machine 100A includes a dry state detection unit 510A instead of dry state detection unit 510. Dry state detection unit 510A includes a determination unit 513A instead of determination unit 513. Dry state detection unit 510A does not necessarily include arithmetic processing unit 512.

[0114] The server 200 includes, for example, a communication unit 250, a storage unit 270, and a control unit 290.

[0115] The communication unit 250 communicates with the washing machine 100 via the network NW under the control of the control unit 290. When the communication unit 250 detects a request from the washing machine 100, it notifies the control unit 290 of the detection.

[0116] The storage unit 270 has a semiconductor memory such as a RAM and a ROM, and a storage device such as a hard disk drive (HDD). The storage unit 270 stores user management information, image data acquired from the washing machine 100A or information generated based on an image, various programs, and various information used for executing the various programs.

[0117] The control unit 290 includes a processor such as a CPU. Each functional unit of the control unit 290 is realized by the processor executing a program. Note that some or all of the functional units of the control unit 290 may be hardware functional units such as an LSI, an ASIC, or an FPGA.

[0118] For example, control unit 290 acquires user management information from another device and adds it to storage unit 270. Control unit 290 permits communication with washing machine 100A that is registered in advance in the user management information, and executes processing based on various information acquired from washing machine 100A.

[0119] For example, control unit 290 performs part of the processing of dryness detection unit 510 described above in place of dryness detection unit 510. Control unit 290 includes, for example, information acquisition unit 291, arithmetic processing unit 292, and determination unit 293. For example, arithmetic processing unit 292 and determination unit 293 perform processing equivalent to that of arithmetic processing unit 512 and determination unit 513 described above.

[0120] FIG. 14 is a diagram showing a process flow of controlling the drying operation in one embodiment. When starting the drying operation, information acquisition unit 511 of drying state detection unit 510A acquires information relating to the initial state of the laundry placed in drum 7 (step SB11) and adds the acquired information to memory unit 520. Processing unit 530 closes water supply valve 10 in response to control information based on the user's operation. Processing unit 530 controls drum motor 5 and drying unit 31 to start the drying operation (step SB12).

[0121] Information acquiring unit 511 acquires image data (status information) for detecting the state of the laundry during the drying operation (step SA13), and notifies server 200 of the image data via communication unit 550 (step SB15). When information acquiring unit 511 executes the process of step SA13 for the first time, it also notifies server 200 of the information stored in storage unit 520 in step SB11.

[0122] Information acquisition unit 291 of server 200 acquires image data and the like transmitted from washing machine 100A (step SB21). Calculation processing unit 292 performs a predetermined calculation process based on the acquired image data (step SB22). This calculation process may be the one shown in the first embodiment. Determination unit 293 determines whether or not the drying operation needs to be continued based on the result of the calculation process (step SB23), and notifies washing machine 100A of the result of the determination (step SB24).

[0123] Communication unit 550 acquires the result of the judgment (step SB16). Judgment unit 513A judges whether or not the result of the judgment in step SB16 has been received, and if not, continues the drying process and proceeds to the process of step SB13. If the result of the judgment has been received, judgment unit 513A identifies whether or not continuation of the drying operation is necessary based on the received result of the judgment process (step SB18). If it is identified that continuation of the drying operation is necessary, processing unit 530 continues the drying operation and repeats the process from step S13. If it is determined that continuation of the drying operation is unnecessary, processing unit 530 ends the drying operation (step SB19).

[0124] According to the above embodiment, server 200 of drying system 1000 performs a predetermined calculation process based on the acquired image data, and determines whether or not the drying operation needs to be continued based on the result of the calculation process. Washing machine 100A terminates the drying control based on the result of the determination by server 200, thereby achieving the same effect as in the first embodiment.

[0125] (Third embodiment) A third embodiment will now be described. In the first and second embodiments, examples have been described in which drying control is performed mainly based on images from the camera module 3C. In the present embodiment, an example will be described in which drying control is performed using information other than images from the camera module 3C.

[0126] For example, the server 200 estimates the drying state of the cloth using an inference rule or an inference model (learning model) based on either or both of information indicating the movement of the cloth and information indicating the state of the cloth. For example, the server 200 may use a method such as machine learning to determine in advance parameters that define the characteristics of the inference rule or the inference model (learning model). Data such as the parameters of the inference rule or the inference model (learning model) is stored in the memory unit 270 of the server 200.

[0127] The calculation processing unit 292 of the control unit 290 uses the feature amount (Yx) or the amount of change (ΔYx) extracted from the image as information indicating the movement of the cloth and information indicating the state of the cloth. In addition, the calculation processing unit 292 may use some or all of the following as input information: the weight of the cloth (cloth weight W) detected before water is poured in the washing process, the result of cloth quality judgment (cloth quality Q) extracted based on the change in current (ΔIx) of the drum motor 5 during the washing process, the amount of change (ΔGx) in the detected value of vibration during the drying process, and the detected values ​​(temperature Tx) of each temperature sensor during drying operation. The above input information is organized into equations (9) and (10), respectively, using the above symbols.

[0128] [Yx, W, Q, ΔGx, Tx] (9) [ΔYx, W, Q, ΔGx, Tx] (10)

[0129] For example, drying system 1000 receives information such as image data from one or more washing machines 100A, and notifies each washing machine 100A of the result of the judgment on the image data. The laundry (cloth) of each washing machine 100A is generally determined by the user, and therefore, various types of laundry are included in one wash. Even in a wash that includes various types of laundry, the movement or state of the cloth during the drying operation differs between the wet and dry stages, and this tendency does not tend to depend on the type of laundry.

[0130] Therefore, in this embodiment, the input information is used as teacher data to optimize parameters of the inference rules or the inference model (learning model), thereby making it possible to apply machine learning to the processing of the control unit 290. Note that a part or all of the processing by the arithmetic processing unit 292 of the control unit 290 in this embodiment may be performed by the determination unit 293.

[0131] In each of the embodiments described below, examples using deep learning type artificial intelligence will be described.

[0132] Example 1: The deep learning type artificial intelligence in the case of Example 1 includes a feedforward type multilayer neural network (DNN). By associating and combining the above input information with information on the actual drying state of laundry, it can be used as learning data for the deep learning type artificial intelligence.

[0133] For example, when the above-mentioned change amount (ΔYx) is used as the input information, the control unit 290 may have a DNN. When the control unit 290 supplies input information to the trained DNN a predetermined number of times, the DNN outputs an estimated value indicating the dry state. The control unit 290 determines whether the estimated value is a desired value or not, and determines the timing of the end of the drying process.

[0134] Example 2: Instead, when the above feature (Yx) is used as input information, it is necessary to at least make available information on the previously detected image and information on the currently detected image so that the components of the change amount related to the feature of the image can be used in the calculation. In this case, it is also preferable to apply a DNN that can use the above input information as one input data by collectively including information on the previously detected image and information on the currently detected image. In the case of this embodiment 2, it is also preferable that the control unit 290 has a DNN. The number of input nodes of the DNN in this embodiment 2 is greater than that in the first embodiment.

[0135] Example 3: In contrast, when the image feature (Yx) is included in the input information for each detection, a recurrent neural network (RNN) may be applied. The RNN has a node that treats the state value of a hidden layer as an input variable of a node of a hidden layer at a previous stage. This allows the hidden layer to perform calculations according to the state value of the hidden layer. By using this, even if the image feature (Yx) treated as time-series data is used as input information, it becomes possible to calculate the above-mentioned change amount (ΔYx) inside the RNN. Whether or not to calculate the above-mentioned change amount (ΔYx) depends on the learning result and cannot be specified, but it can be selected according to conditions. In the case of this embodiment 3, the control unit 290 may have an RNN.

[0136] Although several examples have been shown, for example, the determination unit 293 of the control unit 290 may be configured to make a determination using a learning model trained by machine learning to output the drying progress of the laundry (cloth) when information indicating the movement or state of the laundry (cloth) is input as the above-mentioned input information, based on the information acquired by the information acquisition unit 291.

[0137] In the above embodiment, a configuration example of the server 200 has been described. The application example of the present technology is not limited to the above embodiment, and each washing machine 100 may be configured to execute machine learning type and artificial intelligence type arithmetic processing and determination processing as described above. In this case, the arrangement of the processor that actually executes the arithmetic processing and the method of dividing the functions when multiple processors cooperate to execute the arithmetic processing are not limited to the above example, and can be changed as appropriate.

[0138] The drying system 1000 according to one embodiment has been described above. The drying system 1000 (e.g., server 200) of the embodiment includes an information acquisition unit 291 and a determination unit 293. The information acquisition unit 291 acquires information indicating the movement or state of the cloth in the drum 7 during the drying operation. The determination unit 293 determines the progress of drying of the cloth based on the information acquired by the information acquisition unit 291. The drying system 1000 performs the drying operation based on the determination result of the progress of drying by the determination unit 293, thereby making it possible to end the drying operation at a more appropriate timing.

[0139] (First Modification Common to All Embodiments) A modified example common to the embodiments will be described with reference to Fig. 15. Fig. 15 is a configuration diagram of a washing machine of a modified example. In the configuration shown in Fig. 15(a), one camera module 3C is provided on the inner surface 3IS of the door 3. In contrast, in the configuration shown in Fig. 15(b), multiple (e.g., two) camera modules 3C are provided on the inner surface 3IS of the door 3.

[0140] As shown in (b) of Fig. 15, it is preferable to provide a plurality of camera modules 3C to complement the blind spots of each camera module 3C. In this case, even if the viewing angle of the optical system of each camera module 3C is narrowed, the blind spots in the drum 7 can be reduced by combining the images of each camera module 3C. The calculation processing unit 512 may perform calculation processing for extracting features on the image of each camera module 3C individually, or may first combine the images and then perform calculation processing for extracting features on the combined image.

[0141] In addition, the multiple camera modules 3C may be divided into those mainly used to detect the movement of the cloth and those mainly used to detect the state (bulge) of the cloth. For example, the upper camera module 3C may be used to detect the former, and the lower camera module 3C may be used to detect the latter.

[0142] (Second Modification Common to All Embodiments) In the example shown in the above embodiment, the feature amount of each image is used to detect the movement or state of the cloth, without identifying the individual laundry items themselves in each image. Alternatively, in this modification, the control unit 290 may, for example, identify each laundry item in each image and detect the movement or state of the cloth from the identification result of each laundry item in the image. For example, the control unit 290 may directly compare the image data of the first image and the second image by using the image data of the first image and the second image, respectively, to detect that the same cloth appears as a subject in each image, and comparing this.

[0143] In each of the above methods, instead of comparing the feature amounts of the two images, the two images may be directly compared to detect the movement of the cloth and the degree of change in the state of the cloth. In this case, the first image and the second image themselves may be used to detect the movement or state of the cloth.

[0144] According to at least one of the embodiments described above, washing machine 100 or drying system 1000 has an information acquisition unit and a determination unit. The information acquisition unit acquires information indicating the movement or state of the cloth in the drying chamber or spin tub during the drying operation. The determination unit determines the progress of drying of the cloth based on the information acquired by the information acquisition unit. Washing machine 100 or drying system 1000 performs the drying operation based on the determination result of the progress of drying by the determination unit, thereby making it possible to end the drying operation at a more appropriate timing.

[0145] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0146] 1...outer box (housing), 2...through-hole-shaped entrance / exit, 3...door, 4...water receiving tank (drying chamber), 5...drum motor, 6...rotating shaft, 7...drum (rotating tank), 8...through hole, 9...multiple baffles, 10...water supply valve, 11...water supply valve motor, 12...water injection case, 13...water injection port, 14...drain pipe, 15...drain valve, 17...main duct, 18...front duct, 19...fan casing, 20...intake port, 21...exhaust port, 22...fan motor, 23...rotating shaft, 24...fan, 25...rear duct, 26...circulation duct, 27...compressor, 28...compressor motor, 29A...condenser, 29B...evaporator, 30...refrigerant pipe, 31...drying unit, 32...inverter circuit, 35u, 35v, 35w...shunt resistor, 36...level shift circuit, 44...drive circuit, 47...drain valve motor, 48...water level sensor, 49...operation panel, 82...rotation position sensor, 100...washing machine (drying system or dryer), 1000...drying system

Claims

1. a camera module capable of photographing an internal space of a rotating drum disposed in a drying chamber; an information acquisition unit that acquires image information for each color component captured by the camera module as information indicating the movement or state of the cloth in the rotary tub before or during the start of a drying operation in the drying chamber; a determination unit that generates, for each color component, information on a frequency distribution of intensity values ​​of each pixel of the image for each of the color components acquired by the information acquisition unit, and determines a drying progress state of the cloth based on the information on the frequency distribution of the intensity values ​​of the image for each of the color components; Equipped with the determination unit is capable of identifying a change in color element or brightness included in the image corresponding to a change in the position of the cloth in the spin tub and a change in the ratio of the cloth in the spin tub from information on a change in a frequency distribution of the intensity values; A drying operation is performed based on the determination result of the drying progress state by the determination unit. Drying system.

2. The information indicating the movement or state of the cloth is information obtained from an image captured by the camera module, or the image itself. The drying system of claim 1 .

3. The information indicating the movement or state of the cloth is information obtained based on a first image taken at a first time and a second image taken at a second time later than the first time, or is the first image and the second image themselves. The drying system of claim 2.

4. The information indicating the movement or state of the cloth is information obtained based on a first image and a second image taken at a predetermined time interval during the drying operation, or is the first image and the second image themselves. The drying system of claim 2.

5. The information indicating the movement or state of the cloth is information obtained based on a first image taken before the start of the drying operation or before a certain time has elapsed since the start of the drying operation and a second image taken after the certain time has elapsed since the start of the drying operation, or the first image and the second image themselves. The drying system of claim 2.

6. The information indicating the movement or state of the cloth is information obtained based on a plurality of first images taken before the start of the drying operation or before a certain time has elapsed since the start of the drying operation and a plurality of second images taken after the certain time has elapsed since the start of the drying operation, or is the plurality of first images and the plurality of second images themselves. The drying system of claim 2.

7. The information indicating the movement of the cloth is information indicating a change in color element or brightness included in the image in response to a change in the position of the cloth in the rotating tub. A drying system according to any one of claims 2 to 6.

8. the information indicating the state of the cloth is information indicating a change in color element or brightness included in the image corresponding to a change in the ratio of the cloth in the rotating tub; A drying system according to any one of claims 2 to 7.

9. The camera module has a wide-angle lens. A drying system according to any one of claims 2 to 8.

10. The camera module includes a plurality of camera modules; The information indicating the movement or state of the cloth is information obtained from images captured by the multiple camera modules, or is the image itself captured by the multiple camera modules. A drying system according to any one of claims 2 to 9.

11. A housing that houses the drying chamber; A door for closing the entrance of the drying chamber in an openable and closable manner is further provided, The door has an inner surface facing the drying chamber or the rotating tank, The camera module is provided on the inner surface of the door. A drying system according to any one of claims 2 to 10.

12. Further comprising a lighting unit that turns on a light when the camera module is used for photographing. A drying system according to any one of claims 2 to 11.

13. The determination unit determines the progress of the drying based on information indicating the movement or state of the cloth, as well as information obtained from one or more of a vibration sensor, a temperature sensor, a weight sensor, and a current detection unit included in the drying system. A drying system according to any one of claims 1 to 12.

14. The determination unit performs a determination based on the information acquired by the information acquisition unit by using a learning model that has been trained to output the drying progress state when information indicating the movement or state of the cloth is input. A drying system according to any one of claims 1 to 13.

15. A control unit that performs the drying operation based on a result of the determination of the drying progress by the determination unit. A drying system according to any one of claims 1 to 14, comprising:

Images