CN116262024A - Dirt condition judging method in cleaning machine, intelligent cleaning method of cleaning machine and cleaning machine - Google Patents

Abstract

The invention relates to a method for judging the dirt condition in a cleaning machine, which is characterized in that when the cleaning machine performs cleaning operation, the motor power N in a clean water flushing state before heating is detected and obtained, the motor power data P in a cleaning state after heating is detected and obtained, the change condition of P relative to N is compared, and the fluctuation condition of the motor power P along with the time is compared, so that the dirt condition in the cleaning machine is determined. The invention also relates to an intelligent cleaning method of the cleaning machine, which is applied to the method for judging the dirt condition, so that the cleaning parameters of the cleaning machine in the subsequent cleaning process are determined according to the dirt condition in the cleaning process. The invention also relates to a cleaning machine applying the method for judging the dirt condition in the cleaning machine and/or the intelligent cleaning method of the cleaning machine. The method and the cleaning machine only adopt necessary working parameters in the working of the cleaning machine, and can accurately realize the detection of the dirt condition without special equipment for collecting dirt information in the cleaning machine, so that the cleaning work is more intelligent and effective.

Description

Dirt condition judging method in cleaning machine, intelligent cleaning method of cleaning machine and cleaning machine

Technical Field

The invention relates to a method for judging the dirt condition in a cleaning machine, an intelligent cleaning method of the cleaning machine applying the method for judging the dirt condition, and the cleaning machine.

Background

In order to ensure the cleaning effect, the cleaning machine can detect the degree of dirt in the cleaning machine, further adjust the cleaning parameters of the cleaning machine, and further improve the cleaning effect. In the prior art, a turbidity sensor is commonly used for detecting the turbidity degree in a cleaning machine, and then cleaning control is performed according to detection data of the turbidity sensor. However, the turbidity sensor and the data line matched with the turbidity sensor have high cost, and the turbidity sensor has different sensitivity to different pollutants, so that erroneous judgment is very easy to cause. In addition, in the long-term use process, scale is easy to accumulate on the turbidity sensor, and the detection precision is affected. The device such as a camera is also used for detecting the dirt condition in the cleaning machine, the camera also has the problems during use, the calculated amount in the use process is large, the requirement on a control chip is high, and the cost of the control chip is correspondingly increased.

Disclosure of Invention

The first technical problem to be solved by the invention is to provide a method for judging the dirt condition in the cleaning machine, which can accurately realize the detection of the dirt condition in the cleaning machine by only adopting necessary working parameters in the working of the cleaning machine without specially setting a device for collecting the dirt information in the cleaning machine.

The second technical problem to be solved by the invention is to provide an intelligent cleaning method of a cleaning machine, which is used for judging the dirt condition in the cleaning machine and further realizing intelligent and effective cleaning, aiming at the prior art.

The third technical problem to be solved by the present invention is to provide a cleaning machine applying the above-mentioned method for judging the dirt condition and/or the intelligent cleaning method in the cleaning machine.

The technical scheme adopted by the invention for solving the first technical problem is as follows: a method for judging the dirt condition in a cleaning machine is characterized in that: when the cleaning machine performs a cleaning operation, detecting and acquiring motor power N in a clean water flushing state before heating, detecting and acquiring motor power data P in a cleaning state after heating, comparing the change condition of P relative to N and the fluctuation condition of the motor power P along with time, and further determining the dirt condition in the cleaning machine.

In order to more accurately judge the dirt grade in the cleaning machine, calculating the average value of motor power data in the clean water flushing state before heating as the motor power N in the unheated cleaning stage;

in a cleaning state after heating, calculating the average power P0 of the motor in unit time, and simultaneously obtaining a maximum motor power value Pmax and a minimum motor power value Pmin corresponding to the unit time;

the duty ratio A of the difference between N and P0 relative to N and the duty ratio k of the difference between Pmax and Pmin relative to N are calculated, and then the dirt grade in the cleaning machine is determined according to the A and the k.

The invention solves the second technical problem by adopting the technical proposal that: an intelligent cleaning method of a cleaning machine is characterized by comprising the following steps: the method is applied to the method for judging the dirt condition in the cleaning machine;

the cleaning process of the cleaning machine sequentially comprises an unheated cleaning stage, a heated cleaning stage and a unheated cleaning stage;

when the cleaning machine performs a cleaning operation, the motor power N in the unheated cleaning stage is obtained and used as the motor power N in the clean water flushing state before heating;

collecting and acquiring real-time motor power data P in a non-heating cleaning stage as motor power data P in a cleaning state after heating, comparing the change condition of P relative to N and the fluctuation condition of motor power P along with time, further determining the dirt condition in the cleaning machine, and determining the cleaning parameters in the subsequent cleaning working process of the cleaning machine according to the dirt condition in the cleaning machine.

As a further improvement, calculating the average value of the real-time motor power data in the unheated cleaning stage as the motor power N in the unheated cleaning stage;

calculating the average power P0 of the motor in unit time according to the real-time motor power P acquired in real time, and simultaneously acquiring the corresponding maximum motor power value Pmax and minimum motor power value Pmin in the unit time;

if (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, judging that the dirt in the current cleaning machine is less, and further determining that the corresponding cleaning parameters are the set light-load cleaning parameters; wherein A is more than 0 and less than 50%, and k is more than 0 and less than 50%.

As a further improvement, when the cleaning machine performs a cleaning operation, water temperature data in the cleaning machine is collected in real time in a heating cleaning stage, heating time T required by heating the water temperature to a target temperature W0 is counted, cleaning parameters determined in a non-heating cleaning stage are adjusted according to the T, and then subsequent cleaning operations of the cleaning machine are performed according to the adjusted cleaning parameters.

In order to have uniform judgment standards for different environment temperatures, the heating time T adopts the time required by heating the water temperature from the set temperature W1 to the target temperature W0, wherein W2 is less than W1 and less than W0, and W2 is the highest environment temperature of the use place of the cleaning machine.

As an improvement, the cleaning parameters are increased as T increases.

Preferably, the cleaning parameters of the cleaning machine comprise preset light-load cleaning parameters and heavy-load cleaning parameters, and the light-load cleaning parameters are smaller than the heavy-load cleaning parameters;

and comparing the T with a preset time threshold value T0, and controlling the cleaning machine to carry out subsequent cleaning according to the light-load cleaning parameter only under the conditions that T is less than T0, (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, or else carrying out subsequent cleaning according to the heavy-load cleaning parameter.

The technical scheme adopted by the invention for solving the third technical problem is as follows: a cleaning machine, characterized in that: the method for judging the dirt condition in the cleaning machine and/or the intelligent cleaning method are/is applied.

Compared with the prior art, the invention has the advantages that: the method for judging the dirt condition in the cleaning machine is based on the characteristic of property change of the dirt along with cleaning in the cleaning process, and further the power change of the motor in the cleaning machine caused by the property change of the dirt, so as to determine the dirt condition in the cleaning machine. The intelligent cleaning method applying the dirt condition judging method in the cleaning machine can perform more intelligent and effective cleaning work, and the failure rate of the cleaning machine is low. The cleaning machine applying the method for judging the dirt condition in the cleaning machine and/or the intelligent cleaning method has the advantages of low cost and high reliability of detection results.

Drawings

Fig. 1 is a flowchart of an intelligent cleaning method of a cleaning machine according to an embodiment of the invention.

Detailed Description

The invention is described in further detail below with reference to the embodiments of the drawings.

The cleaning machine in the invention is a cleaning machine such as a dish washer, and comprises a base body with a cleaning cavity, a motor arranged below the base body, an impeller connected with the driving end of the motor, and a spray arm positioned in the cleaning cavity. The lower part of the impeller is of an axial flow type structure, the upper part of the impeller is of a centrifugal structure and is positioned in the spray arm, the lower part of the impeller is positioned in water and can drive water flow to the upper part of the impeller along the axial direction, and under the centrifugal effect of the impeller, the spray arm is driven to rotate and spray cleaning water to bowls and chopsticks in the cleaning cavity.

When the washing machine is operated in a clean water state without placing the dish washing powder, the impeller extending into the water can be regarded as applying a stable load on the impeller due to the stable property of the clean water, and the power of the motor is stabilized at a relatively stable power point. However, after the cleaning water contacts with common pollutants such as greasy dirt, egg liquid and the like on the bowls and chopsticks in daily kitchens, the pollutants exist in the back flow water flow, and a large amount of bubbles can be generated under the dual functions of heating and impeller stirring when the cleaning work is carried out, so that the property of the cleaning water is changed. I.e. the density of the cleaning water is reduced, and the property of the cleaning water is uneven because the water flow in the cleaning cavity continuously moves, which can be seen as that a lower and unstable load is applied on the impeller, and the power of the motor is obviously reduced and severely fluctuates when compared with the cleaning water.

Based on the characteristic of property change of the cleaning water in the cleaning process of the cleaning machine, the method for judging the dirt condition in the cleaning machine in the embodiment comprises the following steps: when the cleaning machine performs a cleaning operation, the motor power N in the clean water flushing state before heating is detected and obtained, in this case, as the influence of the dish washing powder, the detergent and the heating temperature on the property of the cleaning water is avoided, the substances such as greasy dirt, protein and the like in the cleaning machine do not foam or foam very slightly under the action of the impeller, and the motor power is stable and basically maintained near the rated output power. In order to ensure that the calculated motor power N can more truly reflect the actual power situation, according to the power data acquired in real time, calculating the average value of the motor power data in the clean water flushing state before heating as the motor power N in the unheated cleaning stage.

Detecting and acquiring motor power data P in a cleaning state after heating, wherein cleaning water in the cleaning machine is heated, pollutants such as greasy dirt, protein and the like in the cleaning water are fully foamed, accordingly, the motor power is reduced due to the existence of the pollutants, the pollution of the pollutants to the cleaning water is more serious, the corresponding motor power P is lower, fluctuation of the motor power is caused due to uneven distribution of the pollutants in the cleaning water, and the pollution of the pollutants to the cleaning water is more serious generally, so that the fluctuation of the motor power is more. And comparing the change condition of P relative to N and the fluctuation condition of the motor power P along with the time so as to determine the dirt condition in the cleaning machine.

In this embodiment, in the cleaning state after heating, the average power P0 of the motor in a unit time is calculated, and the maximum motor power value Pmax and the minimum motor power value Pmin corresponding to each unit time are obtained. The duty ratio A of the difference between N and P0 relative to N and the duty ratio k of the difference between Pmax and Pmin relative to N are calculated, and then the dirt grade in the cleaning machine is determined according to the A and the k. In the equipment research and development stage, a plurality of difference duty ratio intervals can be preset for A and a plurality of fluctuation duty ratio intervals can be preset for k according to specific test conditions, and then corresponding dirt grades are preset for different combinations of different difference duty ratio intervals and fluctuation duty ratio intervals. And combining the calculated difference duty ratio interval and fluctuation duty ratio interval according to the calculated A, k, so as to further determine the corresponding dirt grade. When the cleaning machine works, the cleaning parameters can be directly determined according to the dirt grade, and the cleaning parameters can be adjusted based on the influence of other factors on the basis.

As shown in fig. 1, the foregoing cleaning machine may be operated by an intelligent cleaning method of the cleaning machine, in which the foregoing method for determining the contamination condition in the cleaning machine is applied. The intelligent cleaning method of the cleaning machine is mainly suitable for the cleaning process which is not added with foaming cleaning agents such as dishwashing powder and has a heating cleaning stage. Generally, the cleaning machine has a pre-cleaning process before the cleaning agent is added, and the intelligent cleaning method of the cleaning machine is particularly suitable for the pre-cleaning process of the cleaning machine.

As shown in fig. 1, the intelligent cleaning method of the cleaning machine is specifically as follows.

The cleaning process of the cleaning machine sequentially comprises an unheated cleaning stage, a heated cleaning stage and an unheated cleaning stage. The non-heating cleaning stage is a washing stage directly connected with clean water and not heated, the heating cleaning stage is a stage for heating and cleaning water in the cleaning cavity by using a heating device such as a heating plate, and the non-heating cleaning stage is a heated cleaning stage.

When the cleaning machine performs a cleaning operation, the motor power N in the unheated cleaning stage is obtained and used as the motor power N in the clean water flushing state before heating, and as the heating operation is not performed in the stage, substances such as greasy dirt, protein and the like in the cleaning machine do not foam or foam very slightly under the action of the impeller, and at the moment, the motor power is relatively stable and basically maintained near the rated output power. In order to ensure that the calculated motor power N can more truly reflect the actual power situation, the average value of the real-time motor power data in the unheated cleaning stage is calculated and used as the motor power N in the unheated cleaning stage.

The real-time motor power data P obtained in the non-heating washing stage is collected and used as the motor power data P in the washing state after heating, at this time, the washing water in the washing machine is already subjected to the heating washing stage, and pollutants such as greasy dirt, protein and the like in the washing water are fully foamed, accordingly, the motor power can be reduced due to the existence of the pollutants, the more serious the pollution of the pollutants to the washing water is, the lower the corresponding motor power P is, and the fluctuation of the motor power can be caused due to uneven distribution of the pollutants in the washing water, generally, the more serious the pollution of the pollutants to the washing water is, and the larger the fluctuation of the motor power is caused. The change condition of P relative to N and the fluctuation condition of the motor power P along with time are compared, so that the dirt condition in the cleaning machine is determined, and the cleaning parameters in the subsequent cleaning working process of the cleaning machine are determined according to the dirt condition in the cleaning machine.

In this embodiment, the specific analysis method for the variation of P with respect to N and the fluctuation of the motor power P with time is as follows. And calculating the average power P0 of the motor in unit time according to the real-time motor power P acquired in real time, wherein the unit time is specifically set according to the needs, and if the unit time is 1 minute, calculating the average value P0 of the motor power data acquired in a period of one minute from the current time including the current time. And simultaneously obtaining the corresponding maximum motor power value Pmax and minimum motor power value Pmin in the unit time.

If (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, judging that the dirt in the current cleaning machine is less, and further determining that the corresponding cleaning parameters are the set light-load cleaning parameters; wherein 0 < a < 50%,0 < k < 50%, in this example a=10%, k=10%. Namely (N-P0)/N is less than or equal to 10%, which shows that the pollutant in the cleaning water is less, and further, the bubbling amount of the pollutant is also small, and the average power P0 of the corresponding motor is not changed much compared with the power N of the motor when the motor is flushed by unheated clean water in the unheated cleaning stage. Meanwhile, pmax-Pmin is less than or equal to 10% N, which indicates that the power fluctuation of the motor is not large in the non-heating cleaning stage, and correspondingly, the condition of less pollutants in the cleaning water is further proved. In this way it can be essentially determined that the cleaning machine is less contaminated. For the cleaning machine with simple control program, the cleaning parameters can be directly determined according to the result, and then the cleaning machine is controlled to carry out subsequent cleaning work according to the cleaning parameters.

However, in this embodiment, it is necessary to further determine the number of dishes in the washer during the heated washing process. When the cleaning machine performs a cleaning operation, water temperature data in the cleaning machine is collected in real time in a heating and cleaning stage, heating time T required by heating the water temperature to a target temperature W0 is counted, cleaning parameters determined in a non-heating and cleaning stage are adjusted according to the T, and then subsequent cleaning operation of the cleaning machine is performed according to the adjusted cleaning parameters. The more dishes in the washing machine, the greater the amount of heat exchange required, and the longer the heating time T required for the same target temperature.

However, the different water inlet temperatures also affect the change of the heating time, and the ambient temperature is an important factor affecting the water inlet temperature, so that in order to have a uniform judgment standard for different ambient temperatures, the heating time T adopts the time required by the water temperature to heat from the set temperature W1 to the target temperature W0, wherein W2 is less than W1 and less than W0, and W2 is the highest ambient temperature of the use place of the cleaning machine. In the four-season environment, the water inlet temperature can be from minus to above 30 ℃, and normally W1 can be about 33 ℃, so W1 can be set to 35 ℃, and the acquisition standard of the heating time can be better unified. The target temperature W0 is usually higher than 40 ℃ to ensure the cleaning effect.

As T increases, the number of dishes placed in the washer is increased, thus the washing parameters are correspondingly increased based on the washing parameters determined based on the judgment that (N-P0)/N.ltoreq.A and Pmax-Pmin.ltoreq.kN. According to the conditions, the corresponding rule for improving the cleaning parameters can be specifically set, and then the cleaning parameters of the cleaning machine are finally determined.

In this embodiment, the simplest method for determining the cleaning parameters is adopted, and specifically, the cleaning parameters of the cleaning machine include a preset light-load cleaning parameter and a heavy-load cleaning parameter, where the light-load cleaning parameter is smaller than the heavy-load cleaning parameter. The cleaning parameters may include at least one parameter of motor speed, water intake, heating temperature, cleaning duration, etc., depending on the specific product conditions of the cleaning machine.

And comparing the T with a preset time threshold value T0, and controlling the cleaning machine to carry out subsequent cleaning according to the light-load cleaning parameter only under the conditions that T is less than T0, (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, or else carrying out subsequent cleaning according to the heavy-load cleaning parameter.

According to the intelligent cleaning method of the cleaning machine, based on the characteristic that the property of dirt is changed along with cleaning in the cleaning process, the power of the motor in the cleaning machine is changed due to the property change of the dirt, and then the condition of the dirt in the cleaning machine is determined.

Claims (9)

1. A method for judging the dirt condition in a cleaning machine is characterized in that: when the cleaning machine performs a cleaning operation, detecting and acquiring motor power N in a clean water flushing state before heating, detecting and acquiring motor power data P in a cleaning state after heating, comparing the change condition of P relative to N and the fluctuation condition of the motor power P along with time, and further determining the dirt condition in the cleaning machine.

2. The method for determining a contamination condition in a cleaning machine according to claim 1, wherein: calculating an average value of motor power data in a clean water flushing state before heating as motor power N in an unheated cleaning stage;

in a cleaning state after heating, calculating the average power P0 of the motor in unit time, and simultaneously obtaining a maximum motor power value Pmax and a minimum motor power value Pmin corresponding to the unit time;

the duty ratio A of the difference between N and P0 relative to N and the duty ratio k of the difference between Pmax and Pmin relative to N are calculated, and then the dirt grade in the cleaning machine is determined according to the A and the k.

3. An intelligent cleaning method of a cleaning machine is characterized by comprising the following steps: use of the soil condition determining method in a cleaning machine according to claim 1 or 2;

the cleaning process of the cleaning machine sequentially comprises an unheated cleaning stage, a heated cleaning stage and a unheated cleaning stage;

when the cleaning machine performs a cleaning operation, the motor power N in the unheated cleaning stage is obtained and used as the motor power N in the clean water flushing state before heating;

collecting and acquiring real-time motor power data P in a non-heating cleaning stage as motor power data P in a cleaning state after heating, comparing the change condition of P relative to N and the fluctuation condition of motor power P along with time, further determining the dirt condition in the cleaning machine, and determining the cleaning parameters in the subsequent cleaning working process of the cleaning machine according to the dirt condition in the cleaning machine.

4. The intelligent cleaning method of the cleaning machine according to claim 1, wherein: calculating a real-time motor power data average value in an unheated cleaning stage as a motor power N in the unheated cleaning stage;

calculating the average power P0 of the motor in unit time according to the real-time motor power P acquired in real time, and simultaneously acquiring the corresponding maximum motor power value Pmax and minimum motor power value Pmin in the unit time;

if (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, judging that the dirt in the current cleaning machine is less, and further determining that the corresponding cleaning parameters are the set light-load cleaning parameters; wherein A is more than 0 and less than 50%, and k is more than 0 and less than 50%.

5. The intelligent cleaning method of the cleaning machine according to claim 4, wherein: when the cleaning machine performs a cleaning operation, water temperature data in the cleaning machine are collected in real time in a heating and cleaning stage, heating time T required by heating the water temperature to a target temperature W0 is counted, cleaning parameters determined in a non-heating and cleaning stage are adjusted according to the T, and then subsequent cleaning operation of the cleaning machine is performed according to the adjusted cleaning parameters.

6. The intelligent cleaning method of the cleaning machine according to claim 5, wherein: the heating time T is the time required by heating the water temperature from the set temperature W1 to the target temperature W0, wherein W2 is less than W1 and less than W0, and W2 is the highest environmental temperature of the use place of the cleaning machine.

7. The intelligent cleaning method of the cleaning machine according to claim 6, wherein: the cleaning parameters are increased as T increases.

8. The intelligent cleaning method of the cleaning machine according to claim 6, wherein: the cleaning parameters of the cleaning machine comprise preset light-load cleaning parameters and heavy-load cleaning parameters, and the light-load cleaning parameters are smaller than the heavy-load cleaning parameters;

and comparing the T with a preset time threshold value T0, and controlling the cleaning machine to carry out subsequent cleaning according to the light-load cleaning parameter only under the conditions that T is less than T0, (N-P0)/N is less than or equal to A and Pmax-Pmin is less than or equal to kN, or else carrying out subsequent cleaning according to the heavy-load cleaning parameter.

9. A cleaning machine, characterized in that: use of a soil condition judgment method in a cleaning machine as claimed in claim 1 or 2 and/or an intelligent cleaning method as claimed in any one of claims 3 to 8.

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