JP2949740B2 - Washing machine - Google Patents

Description

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a washing machine that automatically determines various washing conditions from an external input by an operator and detection values of various sensors.

2. Description of the Related Art Conventionally, washing machines that determine various washing conditions using an external input by an operator and various sensors have been proposed. However, the determination of the washing conditions by an external input and the determination of the washing conditions by various sensors have been independently performed. In addition, the determination of the washing conditions is such that the water level and the water flow are determined in about four stages.

Problems to be Solved by the Invention However, the conventional techniques as described above have the following problems. That is, when the operator performs an external input, it is necessary to set various washing conditions suitable for the state of the laundry, and at the same time, there is not always a setting pattern suitable for the state of the laundry. Was.

Therefore, the present invention is to solve such a conventional problem, and determines various washing conditions finely using fuzzy inference from detection values of various sensors, and at the same time, determines an optimal washing condition by an external input of an operator. '', `` Washing of operator's preference '' is provided, the first is a water level taking advantage of the preference, the second is the same water flow, the third is the same washing and rinsing time, the fourth is the same The purpose is to obtain various washing conditions.

Means for Solving the Problems The means of the present invention for achieving the above object includes a manual input unit for receiving an input by an operator regarding a water amount, a dirt amount, and a washing method; a cloth amount sensor for detecting a cloth amount; A first fuzzy inference for determining a water level from the water amount input from the manual input unit, the input value of the soil amount, and the detection value of the cloth amount sensor, and a dirt sensor input from the manual input unit. A second fuzzy inference for determining a water flow from an input value of a washing method, a detection value of the cloth amount sensor, and a water level determined by the first fuzzy inference, and a detection value of the cloth amount sensor and a first fuzzy inference. It is composed of the determined water level, the water flow determined by the second fuzzy inference, and the third fuzzy inference that determines the washing time from the detection value of the dirt sensor, and determines various washing conditions by performing fuzzy inference in multiple stages. It is.

Operation The operation of the present invention is as follows. That is, an appropriate water level is determined from the detected value of the cloth amount sensor, and the washing water flow and the rinsing water flow are determined from the detected value of the cloth amount sensor and the appropriate water level. Further, the washing time is determined based on the detection value of the dirt sensor and the appropriate water level and water flow. The various washing conditions as described above are performed by multi-step inference using a fuzzy inference device. Based on information obtained from a manual input unit that receives manual input by an operator regarding the water amount, dirt amount, and washing method, appropriate washing conditions are determined. Various washing conditions utilizing the operator's preference are determined within the range.

Embodiment An embodiment of the present invention will be described below with reference to FIGS. First, the entire washing machine will be described with reference to FIG. 1 is a washing tub for storing laundry and washing water, and 2 is an outer tub for storing washing water. Reference numeral 3 denotes a pulsator for stirring laundry and washing water, and is rotated by a motor 4 via a belt 5. During dehydration, the washing tub 1 is driven by the motor 4. Reference numeral 6 denotes a cloth amount sensor for detecting a load applied to the pulsator 3 when the pulsator 3 rotates, and reference numeral 7 denotes a water level sensor for detecting the water level in the washing tub by detecting the air pressure in the air trap 8. Reference numeral 9 denotes a dirt sensor for detecting the degree of dirt of water in the washing tub 1 based on the transmittance of light in the drain hose. The inflow and outflow of water into and from the washing tub 1 are controlled by a water supply valve 10 and a drainage valve 11 driven by a solenoid valve. Reference numeral 12 denotes a manual input unit that receives an input from an operator, which is configured by a slide resistance or the like, and is configured to be able to be input as an analog value within a predetermined range regarding the amount of water, the amount of dirt, and the strength of washing. .

Next, determination of the washing water level by the first means will be described. FIG. 1 shows an embodiment of the first means. The determination of the washing water level is performed by determining the correction amount of the water level based on input information such as the amount of water and the amount of dirt from the manual input unit 12, and the correction amount and the cloth amount. It consists of two steps of determining an appropriate water level based on the detection value of the quantity sensor 6. Both the correction amount and the appropriate water level are determined by the water level determination means 15 by fuzzy inference. The fuzzy inference in the first step is performed based on a general judgment such as "if the amount of water is large and the amount of dirt is large, the correction amount is very large". The inference rules consist of nine rules shown in FIG. 2 (a). Qualitative concepts such as "large amount of water", "large amount of dirt", and "very large amount of correction" are determined by membership functions as shown in FIGS. 3 (a), (b) and (c). It is expressed in a typical way. The fuzzy inference has a configuration shown in FIG. 4, and the water volume adaptability calculating means 21 obtains the external input relating to the water volume and the adaptability to the membership function by taking both MAX. The dirt amount conformity calculating means 22 similarly obtains the degree of conformity with respect to the dirt amount. Antecedent part minimum calculation means 19
Then, the MIN of the two conformances is taken as the conformity of the antecedent part. The consequent part minimum calculating means 20 takes the antecedent part conformity and the MIN of the correction amount membership function of the consequent part and determines the conclusion of the rule.

After obtaining the respective conclusions for all the rules, the center of gravity calculating means 46 takes the MAX of all the conclusions and calculates the center of gravity to finally obtain the correction amount.

The membership functions relating to the water amount, the dirt amount, and the correction amount are obtained by referring to the water amount membership function storage unit 23, the dirt amount membership function storage unit 24, and the correction amount membership function storage unit 26, respectively.
The inference rule can be obtained by referring to the correction amount inference rule storage unit 25.

The fuzzy inference of the second step is performed based on a general judgment such as "If the cloth amount is large and the correction amount is large, the water level will be very high". Fig. 2 (b)
The four rules shown in FIG. A qualitative concept, such as a large amount of cloth, a large amount of correction, or a high water level, is quantitatively expressed by a membership function as in the first step. The fuzzy inference has a configuration shown in FIG. 5, and obtains a water level in the same procedure as in the first step. The control unit 13 determines the water level based on the detection value of the water level sensor 7 so that the water level is determined by the two steps described above.
This is done by controlling 10.

The functions of the water level determining means 15 and the control unit 13 can be easily realized by the microcomputer 14. The determination of the water flow by the second means will be described. FIG. 6 shows an embodiment of the second means, in which the water flow is determined by fuzzy inference in the water flow determining means 16 from the detected value of the cloth amount sensor 6 and the input information on the strength of washing from the manual input unit 12. This is done by: Fuzzy inference is based on a general judgment such as "If the amount of cloth is large and the washing method is strong, the water flow is very strong". The rules for inference are 9 shown in Fig. 7.
Consists of rules. A qualitative concept such as “the amount of cloth is large” or “strengthening” is quantitatively expressed by a membership function as shown in FIGS. 8 (a) and 8 (b). The concept such as "strengthen the water flow" corresponds to the expression "long ON time and short OFF time" of the motor 4, and the qualitative concept such as "long" ON time and "short" OFF time is Similarly, it is quantitatively expressed by a membership function. The fuzzy inference has the configuration shown in FIG. 9, and the cloth-fit-degree calculating means 27 obtains the fitness of the membership function relating to the detected value of the cloth-quantity sensor and the cloth-quantity by taking the maximum of both. Washing compatibility calculation means 3
In step 3, the degree of fitness between the manual input and the membership function regarding the washing method is obtained in the same manner. Antecedent part minimum calculation means
In step 19, the MIN of the above two degrees of conformity is obtained, and is taken as the degree of conformity of the antecedent. In the consequent part minimum calculating means 20, the conformity of the antecedent part and the MIN of the ON / OFF time membership function of the consequent part are calculated.
And take that rule as the conclusion.

After obtaining the respective conclusions for all the rules, the center-of-gravity calculating means 46 obtains the MAX of all the conclusions, calculates the center of gravity, and finally obtains the ON / OFF time.

The membership functions relating to the amount of cloth, how to wash, and the ON / OFF time are respectively stored in the cloth amount membership function storage means 29.
・ Membership function storage means 34 and ON / OFF
It is obtained by referring to the time membership function storage means 36. The inference rule can be obtained by referring to the ON / OFF time inference rule storage means 35.

ON / OFF of the motor determined by the inference explained above
Based on the time, the controller 13 turns on and off the motor 4 to obtain a water stream of appropriate strength. The water flow determining means 16 and the control unit 13 can be easily realized by the microcomputer 14.

The determination of the washing time by the third means will be described. No.
FIG. 10 shows an embodiment of the third means, in which the washing time is determined by the detection values of the cloth amount sensor 6 and the stain sensor 7 and the manual input unit.
The washing time determination means 17 performs fuzzy inference from the input information indicating the amount of dirt from the washing machine 12. Here, the detection value of the dirt sensor 7 becomes two pieces of information, that is, the time until the transmittance is saturated and the transmittance at that time, and is input to the washing time determination means.

Fuzzy inference states that “the amount of cloth is large and the transmittance is small,
In addition, if the saturation time is long and the amount of dirt is large, the washing time is very long ". The inference rules consist of the 24 rules shown in FIG. The qualitative concepts such as "large" cloth amount, "small" transmittance, "saturation time" and "small amount" are shown in FIGS. 12 (a) to 12 (d). It is quantitatively expressed by a membership function. The fuzzy inference has the structure shown in FIG.
Then, the degree of suitability of the membership function relating to the detected value of the cloth amount sensor and the cloth amount is obtained by taking the MAX of both.
The washing degree adaptability calculating means 33 calculates the degree of adaptation between the manual input and the membership function in the same manner. Similarly, the transmittance adaptability calculating means 38 and the saturation time adaptability calculating means
In step 39, a predetermined degree of conformity is obtained. In the antecedent part minimum calculating means 19, the MIN of the four conformances is taken, and is taken as the conformity of the antecedent part. The consequent part minimum calculating means 20 calculates the degree of conformity between the antecedent part and the washing time membership function of the consequent part.
Take MIN as the conclusion of the rule.

After obtaining the respective conclusions for all the rules, the center of gravity calculating means 46 obtains the MAX of all the conclusions and calculates the center of gravity to finally obtain the washing time.

The membership functions relating to the amount of laundry, washing method, permeability, saturation time, and washing time are respectively stored in the clothing amount membership function storage means 29 and the washing method membership function storage means 3.
4. It can be obtained by referring to the transmittance membership function storage means 37, the saturation time membership function storage means 40, and the washing time membership function storage means. Further, the inference rule can be obtained by referring to the washing time inference rule storage means 41.

The control unit 13 controls the motor 4 based on the washing time determined by the fuzzy inference described above, and turns off the motor at a predetermined time. The washing time determining means 17 and the control section 13 can be easily realized by the microcomputer 14.

Next, determination of various washing conditions by the fourth means will be described. FIG. 14 shows an embodiment of the fourth means, in which various washing conditions are determined by the detection values of the cloth amount sensor 6 and the dirt sensor 7, the amount of water from the manual input unit, the amount of dirt, and the washing method. This is performed by fuzzy inference in the fuzzy inference unit 18 from information such as the strength of Fuzzy inference is a three-step multi-step inference as shown in FIG.

The first step is to determine an appropriate water level in the same manner as in the embodiment of the first means. In the second step, the water flow is determined by fuzzy inference from the information on the strength of washing from the manual input unit, the detection value of the cloth amount sensor, and the water level determined in the first step. The fuzzy inference is such as "If the amount of cloth is large, the water level is high, and the washing method is strong, the water flow is strong", and is composed of 12 rules shown in FIG. The fuzzy inference has the configuration shown in FIG. 17, and the cloth quantity suitability calculating means 27 calculates the detected value of the cloth quantity sensor and the fitness of the membership function relating to the cloth quantity between the two.
Ask by taking MAX. Washing compatibility calculation means 33
Then, the degree of fitness between the manual input regarding the washing method and the membership function is obtained in the same manner. Similarly, water level conformity calculation means
In step 43, a predetermined degree of conformity is obtained. In the antecedent part minimum calculating means 19, the MIN of the above three degrees of conformity is obtained, and is taken as the antecedent part's conformity. The consequent part minimum calculation means 20 takes the degree of conformity of the antecedent part and the MIN of the ON / OFF time membership function of the consequent part and determines the conclusion of the rule.

After obtaining the respective conclusions for all the rules, the center of gravity calculating means 46 obtains the MAX of all the conclusions and calculates the center of gravity to finally obtain the ON / OFF time.

The membership functions relating to the cloth amount, washing method, water level, and ON / OFF time are as follows: the cloth amount membership function storage means 29, the washing method membership function storage means 34, the water level membership function storage means 32, and the ON / OFF time members. It is obtained by referring to the ship function storage means 36. The inference rules are stored in the ON / OFF time inference rule storage means 35.
Can be obtained by referring to

The third step is to determine the washing time by fuzzy inference from the detected values of the cloth amount sensor 6 and the dirt sensor 7, the water level determined in the first step, and the water flow determined in the second step. Here, the detection value of the dirt sensor 7 becomes two pieces of information, that is, the time until the transmittance is saturated and the transmittance at that time, and is input to the fuzzy inference unit 18. The fuzzy inference is such that "if the amount of cloth is large, the water level is high, the water flow is strong, the saturation time is long, and if the permeability is small, the washing time is very long", and it is composed of 32 rules. The fuzzy inference has the structure shown in FIG. 18, and the washing time is obtained in the same procedure as in the second step.

The control unit 13 controls the water supply valve 9 and the motor 4 to perform water supply control, water flow control, and washing time control according to the results of the three stages described above. The fuzzy inference unit 18 and the control unit 13 can be easily realized by the microcomputer 14.

Effects of the Invention The effects of the present invention described above will be described below. According to the means of the present invention, the proper water level, the washing water flow and the rinsing water flow
Since the various washing conditions of the washing time are performed by multi-stage inference using a fuzzy inference device, and the information obtained from the manual input unit that receives the manual input by the operator regarding the amount of water, the amount of dirt, and the washing method is configured to be appropriate. It is possible to determine various washing conditions that take advantage of the operator's preference in a range of various washing conditions. That is, it is possible to appropriately determine various washing conditions taking into account the operator's subjectivity. In addition, by performing multi-stage inference, it is possible to determine various washing conditions with a high degree of detail.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an embodiment of the first means, and FIG.
The figure shows the rules of the inference, FIG. 3 shows the membership function, FIGS. 4 and 5 are block diagrams of the fuzzy inferencer, respectively, and FIG. 6 shows one implementation of the second means. FIG. 7 is a block diagram showing the same inference rule, FIG. 8 is a diagram showing the membership function, FIG. 9 is a block diagram of the fuzzy inference device, and FIG. 10 is a third means. FIG. 11 is a block diagram showing the same inference rule, FIG. 12 is a diagram showing the membership function, FIG. 13 is a block diagram of the fuzzy inference device, and FIG. FIG. 15 is a block diagram showing one embodiment of the fourth means, FIG. 15 is a block diagram showing multi-stage inference by the fuzzy inference device, FIG. 16 is a diagram showing rules of inference by the same means, FIG. 17 and FIG. Block diagram of the fuzzy inference device, respectively. Fig. 19 is a schematic configuration showing the overall configuration of the washing machine of each means. It is. 1 ... washing tub, 2 ... outer tub, 3 ... pulsator, 4 ...
Motor, 6 ... cloth amount sensor, 7 ... water level sensor, 9 ...
Dirt sensor, 10 Water valve, 12 Manual input unit, 13
Control unit, 14 microcomputer, 15 water level determining means, 16 water flow determining means, 17 washing time determining means,
18 ... Fuzzy inference device.

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-1-274797 (JP, A) JP-A-57-55196 (JP, A) (58) Fields investigated (Int. Cl. ⁶ , DB name) D06F 33/02

Claims (1)

(57) [Claims] 1. A manual input unit for receiving an input by an operator regarding a water amount, a dirt amount, and a washing method, a cloth amount sensor for detecting a cloth amount, a dirt sensor for detecting dirt, and input from the manual input unit. First fuzzy inference for determining the water level from the input values of the water amount and dirt amount and the detection value of the cloth amount sensor, the input value of the washing method input from the manual input unit, the detection value of the cloth amount sensor, and the A second fuzzy inference that determines a water flow from the water level determined by one fuzzy inference, a water flow determined by the detected value of the cloth amount sensor and the water level determined by the first fuzzy inference and the second fuzzy inference, A washing machine, comprising: a third fuzzy inference for determining a washing time from a detection value of a dirt sensor; and performing fuzzy inference in multiple stages to determine various washing conditions.