JP3293172B2 - Washing machine - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a fully automatic washing machine for washing a user's favorite by learning a user's favorite washing method which differs depending on the amount of laundry and the state of dirt. It is.

[0002]

2. Description of the Related Art Conventionally, this type of washing machine has a rinsing time
When determining the washing factors such as washing water flow and dehydration time,
They had to choose from a number of pre-given steps. Alternatively, one of the several types of washing courses provided in advance is selected to uniquely determine the washing conditions.

[0003]

In order for the user to perform his / her favorite washing using the washing machine of this configuration, the rinsing time and the washing water flow should be adjusted according to the condition of the laundry every time the washing is performed. And had to set the dehydration time.

The present invention solves this problem. By learning the user's rinsing preferences, it is possible to automatically perform the desired rinsing without the user having to set the rinsing time every time. The primary purpose is to provide a washing machine that can be used.

It is another object of the present invention to provide a washing machine capable of automatically performing a desired washing water flow without learning a washing water flow condition each time by learning a user's preference of the washing water flow. It has a second purpose.

Further, it is a third object of the present invention to provide a washing machine capable of automatically performing a desired dehydration condition without learning the dehydration condition each time by learning a user's preference for dehydration. The purpose is.

[0007]

A first means of the present invention for achieving the first object is a cloth amount detecting means for detecting a cloth amount in a washing tub, and water contamination in the washing tub. Dirt detecting means for detecting the degree, rinsing time determining means for appropriately determining the rinsing time based on the detection values of the cloth amount detecting means and the dirt detecting means, and a correction rinsing time for receiving the user's preference regarding the rinsing time an input section, possess a rinsing time learning means learns modify the parameters of the rinsing time determining means by an input value from the correction rinsing time input unit, before
The rinsing time learning means may be a correction rinsing time input unit.
Parameters of the consequent part of fuzzy inference according to the input values
A washing machine that learns and corrects data.

A second means of the present invention for achieving the second object is a cloth amount detecting means for detecting a cloth amount in a washing tub, and a dirt detecting means for detecting a degree of water contamination in the washing tub. Means,
A washing water flow determining means for appropriately determining a washing water flow based on the detection values of the cloth amount detecting means and the dirt detecting means; a corrected washing water flow input unit for receiving a user's preference regarding the washing water flow; and a corrected washing water flow input unit possess a washing water flow learning means for learning modify the parameters of the washing water flow determination means by the input values from the wash water stream learning means, the correction washing
Consequence of fuzzy inference according to input value from rinsing flow input unit
This is a washing machine that learns and corrects some parameters .

A third means of the present invention for achieving the third object is a cloth amount detecting means for detecting a cloth amount in a washing tub, and a dewatering time based on a detected value of the cloth amount detecting means. Dehydration time determining means for appropriately determining, a dehydration time input unit for receiving a user's preference regarding the dehydration time, and a dehydration time for learning and correcting the parameters of the dehydration time determination means based on an input value from the corrected dehydration time input unit. With learning means
The dehydration time learning means may include the corrected dehydration time input unit.
Parameter of the consequent part of fuzzy inference according to the input value from
This is a washing machine that learns and corrects data.

[0010]

According to the first means of the present invention, the parameters for determining the rinsing time are learned and corrected in accordance with the user's input regarding the rinsing time preference. Therefore, after learning, the rinsing time is automatically set to the user's favorite rinsing time.

The second means of the present invention operates so as to learn and correct the parameters for determining the washing water flow according to the user's input regarding the preference of the washing water flow. Therefore, after the learning, the washing water flow automatically set to the user's preference.

Further, the third means of the present invention operates so as to learn and correct the parameters for determining the dehydration time according to the user's input regarding the preference of the dehydration time. Therefore, after the learning, the dehydration time is automatically set to the user's favorite time.

[0013]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the first means of the present invention are shown in FIGS.
This will be described with reference to FIG. In the figure, reference numeral 1 denotes a washing tub for storing laundry and washing water, and 2 denotes an outer tub for accommodating the washing tub 1 and storing the washing water. Reference numeral 3 denotes a pulsator for stirring the laundry and the washing water, which is provided at the inner bottom of the washing tub 1.
Reference numeral 4 denotes a motor that rotationally drives the pulsator 3 via a belt 5. Reference numeral 6 denotes a cloth amount detecting means for detecting a load applied to the pulsator 3 when the pulsator 3 rotates, thereby detecting a cloth amount. Reference numeral 7 denotes a dirt detecting means for detecting the degree of dirt of water in the washing tub 1 based on the light transmittance in the drain hose. Reference numeral 8 denotes a correction rinsing time input unit for receiving a user's favorite rinsing time, which is configured to input a longer or shorter rinsing time within a predetermined range. The rinsing time determining means 9 appropriately determines the rinsing time based on the detection values of the cloth amount detecting means 6 and the stain detecting means 7. First control unit 11
Controls at least ON / OFF of the motor 4 according to the output of the rinsing time determination means 9.

Next, the configuration of the rinsing time determining means 9 will be described with reference to FIG. In the present embodiment, the rinsing time determining means 9 comprises a basic rinsing time determining means 13 and a corrected rinsing time determining means 14. The rinsing time thus output is represented by the sum of the outputs of the basic rinsing time determining means 13 and the corrected rinsing time determining means 14. Further, the correction rinsing time determination means 14 includes a fuzzy inference operation unit 1.
5 and a rule storage unit 16. In the present embodiment, the consequent part uses real-valued fuzzy inference, and determines the correction rinsing time from the detection values of the cloth amount detecting means 6 and the stain detecting means 7. The rules of fuzzy inference use the nine rules shown in the rule table of FIG. 3, and the membership functions are as shown in FIG. The rinsing time learning unit 10 corrects the consequent part of the fuzzy inference stored in the rule storage unit 16 based on the following equation according to the input value from the corrected rinsing time input unit 8.

Wj (n + 1) = Wj (n) + K2 * Uj * T (1) Wj (n + 1): consequent part after correction of the j-th rule Wj (n): j-th Consequent part before the modification of the rule K2: Learning gain Uj: Fitness of the j-th rule T: Input value from the corrected rinsing time input unit Next, regarding the operation of the washing machine of this embodiment, the rinsing time determination means 9 The operation will be mainly described with reference to FIGS. FIG. 5A shows the input / output relationship of the basic rinsing time determination means 13.
(b) shows the input / output relationship of the correction rinsing time determination means 14. FIG. 5C shows the basic rinsing time determination means 13.
And the sum of the outputs of the corrected rinsing time determination means 14, and finally determines the rinsing time. Here, the characteristic of the correction rinsing time determination means 14 in FIG.
It is corrected by the action of the rinsing time learning means 10,
This will be described with reference to FIG. The real values of the consequent part of the fuzzy inference of the corrected rinsing time determining means 14 are all zero in the initial state before learning, and the output of the corrected rinsing time determining means 14 is zero in all spaces as shown in FIG. It is. Here, as an example, it is assumed that the detected value of the cloth amount detecting means 6 is X1, the detected value of the stain detecting means 7 is X2, and the input value from the corrected rinsing time input section 8 is T. At this time, the real value of the consequent part stored in the rule storage unit 16 is (1)
Modified based on the formula. As a result, the input / output characteristics of the correction rinsing time determination means 14 change as shown in FIG. As can be seen from FIG. 6 (b), the input / output characteristics around the sample are corrected by one input of the correction rinsing time for one sample (X1, X2). That is, according to the present embodiment, even if the user does not teach the correction rinsing time for all the amount of cloth and the degree of dirt, the preferred rinsing time for the whole amount of cloth and the degree of dirt can be realized by teaching several patterns. You. The rinsing time determining means 9, the rinsing time learning means 10, and the first control unit 11 can be easily realized by a microcomputer.

Hereinafter, an embodiment of the second means of the present invention will be described with reference to FIGS. In the figure, 17 is a washing tub for storing laundry and washing water, and 18 is an outer tub for accommodating the washing tub 1 and storing the washing water. Reference numeral 19 denotes a pulsator for stirring the laundry and the washing water, which is provided on the inner bottom of the washing tub 17. Reference numeral 20 denotes a motor that rotationally drives the pulsator 19 via a belt 21. 22 is the pulsator 1
This is a cloth amount detecting means for detecting a cloth amount by detecting a load applied to the pulsator 19 at the time of rotation of the cloth 9. 23
Is a dirt detecting means for detecting the degree of dirt of water in the washing tub 17 based on the transmittance of light in the drain hose. Reference numeral 24 denotes a correction washing water flow input unit for receiving a user's favorite washing water flow, which is configured to input a stronger or weaker washing water flow within a predetermined range. The washing water flow determining means 25 appropriately determines the washing water flow based on the detection values of the cloth amount detecting means 22 and the stain detecting means 23. The second control unit 27 controls at least the motor 20 according to the output of the washing water flow determination unit 25.
Control ON / OFF.

Next, the configuration of the washing water flow determining means 25 will be described with reference to FIG. In the present embodiment, the washing water flow determining means 25 comprises a basic washing water flow determining means 29 and a corrected washing water flow determining means 30. The washing water flow thus output is represented by the sum of the outputs of the basic washing water flow determining means 29 and the corrected washing water flow determining means 30. Further, the correction washing water flow determining means 30 includes a fuzzy inference operation unit 31 and a rule storage unit 32. In the present embodiment, the consequent part uses real-valued fuzzy inference, and
And the correction washing water flow is determined from the detection value of the dirt detection means 23. The rules of fuzzy inference use nine rules shown in the rule table of FIG. 9, and the membership functions are as shown in FIG. Washing water flow learning means 26
Corrects the consequent part of the fuzzy inference stored in the rule storage unit 32 based on the following expression according to the input value from the corrected washing water flow input unit 24.

Wj (n + 1) = Wj (n) + K2 * Uj * T (2) Wj (n + 1): consequent part after correction of the j-th rule Wj (n): j-th Consequent part before correction of rule K2: Learning gain Uj: Fitness of j-th rule T: Input value from corrected washing water flow input unit The operation of washing water flow determining means 25 is the same as that of the first embodiment. Even if the user does not teach the corrected washing water flow for all the amount of cloth and the degree of dirt, the preferred washing water flow for the whole amount of cloth and the degree of dirt can be realized by teaching several patterns. The washing water flow determining means 25, the washing time learning means 26, and the second control unit 27 can be easily realized by a microcomputer.

Next, an embodiment of the third means of the present invention will be described with reference to FIGS. In the figure, reference numeral 33 denotes a washing tub for storing laundry and washing water, and reference numeral 34 denotes an outer tub which accommodates the washing tub 33 and stores the washing water. Reference numeral 35 denotes a pulsator for stirring the laundry and the washing water, which is provided on the inner bottom of the washing tub 33. 36 is a belt 37 with a pulsator 35
Is a motor that is driven to rotate through the motor. Numeral 38 denotes a cloth amount detecting means for detecting a cloth amount by detecting a load applied to the pulsator 35 when the pulsator 35 rotates. 3
Reference numeral 9 denotes a corrected dehydration time input unit that receives a user's preferred corrected dehydration time, and is configured to input a longer or shorter dehydration time within a predetermined range. The dewatering time determining means 40 appropriately determines the dewatering time based on the detection value of the cloth amount detecting means 38. The third control unit 42 controls at least ON / OFF of the motor according to the output of the dehydration time determination unit 40.
Control to achieve an appropriate dehydration time. In this embodiment,
As shown in FIG. 12, the dehydrating time determining means 40 includes a basic dehydrating time determining means 43 and a corrected dehydrating time determining means 44. The dehydration time is represented by the sum of the output of the basic dehydration time determination means 43 and the output of the corrected dehydration time determination means 44. Further, the corrected dehydration time determination means 44 is composed of a fuzzy inference operation unit 45 and a rule storage unit 46.
In the present embodiment, the consequent part uses real-valued fuzzy inference, and determines the corrected dewatering time from the detection value of the cloth amount detecting means 38. The dehydration time learning means 41 corrects the consequent part of the fuzzy inference stored in the rule storage unit 46 based on the following equation according to the input value from the corrected dehydration time input unit 39.

Wi (n + 1) = Wi (n) + K1 * Ui * E (3) Wi (n + 1): Consequent part after modification of i-th rule Wi (n): i-th Consequent part before the modification of the rule K1: Learning gain Ui: Conformity of the i-th rule E: Input value from the corrected dehydration time input part The operation of the washing machine of the present embodiment and the operation of the dehydration time determination means 40 This will be mainly described with reference to FIG. FIG. 7A shows the relationship between the input and output of the basic dehydration time determination means 43. Same figure
(b) represents the membership function of the antecedent part of fuzzy inference, and in this embodiment, the amount of cloth is “small”, “normal”,
Three membership functions representing "many" are used. The following rules are used for fuzzy inference.

Rule 1: if the amount of cloth is small then the corrected dehydration time is
W1 Rule 2: if the amount of cloth is normal then the corrected dehydration time is
W2 Rule 3: if large amount of cloth then compensated dehydration time is
The consequent real values (W1, W2, W3) of W3 fuzzy inference are all zero in the initial state before learning. As an example, the cloth amount detected by the cloth amount detecting means 6 is x, and the input value from the corrected dehydration time input unit 39 is E. At this time, since the membership value of the cloth quantity x is “low” for U1 and “normal” for U2, the real value of the consequent part after learning once is W1 = K1 * U1 * E W2 = K1 * U2 * E W3 = 0. FIG. 13C shows the input / output relationship of the corrected dehydration time determination means 44 at this time. Correction dehydration time when the cloth amount is x, by making the learning gain and the number of times of learning appropriate,
Get as close as you like to your preferred dehydration time E. FIG. 13D shows the relationship between the final cloth weight obtained by adding the basic dewatering time and the corrected dewatering time and the dewatering time. As can be seen from FIG. 13 (d), by learning the desired dehydration time for the cloth amount x, the dehydration time is also corrected for the surrounding cloth amount. That is, according to the present embodiment, even if the user does not teach the desired dehydration time for all the cloth amounts, the desired dehydration time for the entire cloth amount can be realized by teaching several patterns. Note that the dehydration time determination unit 40, the dehydration time learning unit 41, and the third control unit 42 can be easily realized by a microcomputer.

In the first embodiment of the present invention, the parameters for determining the rinsing time are operated in accordance with the user's input regarding the preference of the rinsing time, and the learning amount is automatically adjusted after the learning. The rinsing time set by the user is set according to the degree of dirt. Further, the second means of the present invention operates so as to learn and correct the parameters for determining the washing water flow according to the user's input regarding the preference of the washing water flow, and after learning, automatically adjusts the amount of cloth and the degree of dirt. In accordance with the user's preference, the washing water flow is set. Further, the third means of the present invention operates to learn and correct the parameters for determining the dehydration time according to the user's input regarding the preference of the dehydration time, and after learning, automatically adjusts the user according to the cloth amount. Set to your preferred dehydration time. Here, a cloth quality detecting means for detecting the quality of the cloth is provided, and an element for determining the washing conditions of each means (input of the rinsing time determining means and the corrected rinsing time determining means of the first means, the washing water flow of the second means). (Determination means and correction water flow input, and dehydration time determination means and correction dewatering time determination means input of the third means), washing can be performed more finely to the user's preference. As the cloth quality detecting means, there is a method of detecting based on an output difference of the cloth amount detecting means when the water level is low and when the water level is high.

[0023]

According to the first means of the present invention, the rinsing time learning means uses the fuzzy inference of the rinsing time determining means .
This is for learning and correcting the parameters of the consequent part, so that the user's favorite rinsing time can be easily learned, and the user can automatically perform the washing with the desired rinsing time without setting the rinsing condition every time. It is possible to realize a washing machine that can perform the washing.

According to the second means of the present invention, after the washing water flow learning means performs fuzzy inference of the washing water flow determining means.
This is for learning and correcting the parameters of the subject part, so that the user's favorite washing water flow can be easily learned, and the user can automatically perform the washing with the favorite washing water flow without setting the washing water flow condition every time. It is possible to realize a washing machine that can perform the washing.

According to the third aspect of the present invention, the dehydration time learning means performs the fuzzy inference of the dehydration time determination means.
Learning and correcting the parameters of the subject part, it is easy to learn the user's favorite dehydration time, and washing is performed automatically at the desired dehydration time without the user having to set the dehydration conditions every time. It is possible to realize a washing machine that can perform washing.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a washing machine showing an embodiment of a first means of the present invention.

FIG. 2 is a block diagram showing a configuration of a rinsing time determination unit;

FIG. 3 is a diagram showing a rule table which is a rule of the fuzzy inference.

FIG. 4 is a diagram showing the membership function.

FIG. 5 is a view for explaining the operation of the rinsing time determining means;

FIG. 6 is a diagram for explaining the operation of the correction rinsing time determination means;

FIG. 7 is a configuration diagram of a washing machine showing an embodiment of the second means of the present invention.

FIG. 8 is a block diagram showing a configuration of the washing water flow determining means.

FIG. 9 is a view showing a rule table which is a rule of the fuzzy inference.

FIG. 10 shows the membership function.

FIG. 11 is a configuration diagram of a washing machine showing an embodiment of a third means of the present invention.

FIG. 12 is a block diagram showing a configuration of a dehydration time determination unit.

FIG. 13 is a view for explaining the operation of the correction dehydration time determining means.

[Explanation of symbols]

 1.17.33 Washing tub 2.18.34 Outer tub 3.19.35 Pulsator 4.20.36 Motor 6.22.38 Cloth amount detecting means 7.23 Soil detecting means 8 Correction rinsing time input section 9 Rinsing time Determining means 10 Rinse time learning means 24 Corrected washing water flow input unit 25 Washing water flow determining means 26 Washing water flow learning means 39 Corrected dehydration time input unit 40 Dehydration time determining means 41 Dehydration time learning means

──────────────────────────────────────────────────続 き Continued on the front page (72) Inventor Masafumi Sadahira 1006 Kadoma Kadoma, Osaka Prefecture Inside Matsushita Electric Industrial Co., Ltd. (56) References JP-A-4-170997 (JP, A) JP-A-3-131904 (JP, A) JP-A-1-274797 (JP, A) JP-A-3-158190 (JP, A) JP-A-6-71081 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) D06F 33/02 D06F 49/04

Claims (3)

(57) [Claims] 1. A cloth amount detecting means for detecting a cloth amount in a washing tub, a dirt detecting means for detecting a degree of dirt of water in the washing tub,
Based on the detected value of the cloth amount detecting means and the stain detecting means,
A rinsing time determining means for appropriately determining a rinsing time, a corrected rinsing time input section for accepting a user's preference regarding the rinsing time, and learning correction of parameters of the rinsing time determining means by an input value from the corrected rinsing time input section. to rinse have a time and learning means, the rinse time learning
The means is responsive to an input value from the correction rinsing time input section.
A washing machine that learns and corrects the consequent parameters of fuzzy inference . 2. A cloth amount detecting means for detecting a cloth amount in the washing tub, a dirt detecting means for detecting a degree of contamination of water in the washing tub,
A washing water flow determining means for appropriately determining a washing water flow based on the detection values of the cloth amount detecting means and the dirt detecting means; a corrected washing water flow input unit for receiving a user's preference regarding the washing water flow; and a corrected washing water flow input unit possess a washing water flow learning means for learning modify the parameters of the washing water flow determination means by the input values from the wash water stream learning means, the correction washing
Consequence of fuzzy inference according to input value from rinsing flow input unit
A washing machine that learns and corrects some parameters . 3. A cloth amount detecting means for detecting a cloth amount in a washing tub, a dewatering time determining means for appropriately determining a dewatering time based on a detected value of the cloth amount detecting means, and a user preference regarding the dewatering time. A dehydration time input unit for receiving the dehydration time, and a dehydration time learning unit for learning and correcting the parameters of the dehydration time determination unit based on an input value from the corrected dehydration time input unit.
The dehydration time learning means may include the corrected dehydration time input unit.
Parameter of the consequent part of fuzzy inference according to the input value from
A washing machine that learns and corrects data.