CN111488383B - Intelligent cleaning curve recommendation method for dish washing machine - Google Patents
Intelligent cleaning curve recommendation method for dish washing machine Download PDFInfo
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- CN111488383B CN111488383B CN201910078748.6A CN201910078748A CN111488383B CN 111488383 B CN111488383 B CN 111488383B CN 201910078748 A CN201910078748 A CN 201910078748A CN 111488383 B CN111488383 B CN 111488383B
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L15/00—Washing or rinsing machines for crockery or tableware
- A47L15/0018—Controlling processes, i.e. processes to control the operation of the machine characterised by the purpose or target of the control
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B40/00—Technologies aiming at improving the efficiency of home appliances, e.g. induction cooking or efficient technologies for refrigerators, freezers or dish washers
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Abstract
The invention relates to an intelligent recommendation method for a washing curve of a dish washing machine, which is characterized in that a plurality of intelligent washing curve databases corresponding to use scenes (scenes of daily habits, self-definition, fruit and vegetable types, regional water conditions, family population conditions and fruit and vegetable tastes of users) are set so as to meet the requirements of the users on selection of different use scenes, so that the dish washing machine can call intelligent washing curves matched with different use scenes so as to improve the washing effect; when the intelligent cleaning curve database matched with the region water conditions is arranged, the self-adaptive adjusting mechanism aiming at the water conditions (water shortage condition and water quality condition) of the region position where the dish-washing machine is located is also arranged, so that the dish-washing machine can call a cleaning curve with better cleaning effect in different water condition region positions.
Description
Technical Field
The invention relates to the field of dish washing machines, in particular to an intelligent recommendation method for a washing curve of a dish washing machine.
Background
Dishwashers have been increasingly used by households as a convenient dish washing implement. With the development of intelligent technology, dishwashers with intelligent functions are also successively oriented to the market. The dish washing machines can be connected with user terminal equipment such as a smart phone and a tablet personal computer, and then a user can check a large number of official preset intelligent washing curves provided by a dish washing machine manufacturer on line by using the user terminal equipment, or directly complete the selection of a washing curve required by the user from the large number of preset intelligent washing curves provided by the dish washing machine manufacturer through the operation of the user on the dish washing machines, so that the dish washing machines execute a washing process according to the selected washing curve. The preset intelligent wash curves provided by the dishwasher manufacturer to the dishwasher user are usually recommended according to their ID ranking or curve class (if the dish wash curve or dish wash curve).
However, in the face of such a huge number of preset intelligent washing curves recommended by dishwasher manufacturers, it is difficult for dishwasher users to quickly find a washing curve adapted to the current use scenario of the user among a large number of washing curves after sorting or classification of curve categories. Therefore, the existing washing curve recommending method cannot recommend the washing curve meeting the requirements of the user to the user, and can reduce the use experience effect when the user operates the dishwasher to execute the washing operation.
Disclosure of Invention
The invention aims to solve the technical problem of providing an intelligent recommendation method for a washing curve of a dishwasher aiming at the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: an intelligent cleaning curve recommendation method for a dishwasher is characterized by comprising the following steps 1-11:
step 1, pre-establishing an intelligent cleaning curve database for a user to select cleaning;
step 2, counting the times of selecting each intelligent cleaning curve in the intelligent cleaning curve database by a user in a preset time period, and establishing an intelligent cleaning curve use record database of the user aiming at each intelligent cleaning curve in the intelligent cleaning curve database; wherein, any intelligent cleaning curve usage record in the intelligent cleaning curve usage record database at least comprises the usage times of any intelligent cleaning curve selected by the user;
step 3, according to the size of the using times, sorting the intelligent cleaning curve using records in the intelligent cleaning curve using record database in a descending order mode to obtain a descending intelligent cleaning curve using record database, and using the descending intelligent cleaning curve using record database as an intelligent cleaning curve database matched with the daily habits of the user;
step 4, setting the intelligent cleaning curve corresponding to the intelligent cleaning curve usage record which is positioned in the intelligent cleaning curve database matched with the daily habits of the user and the usage times of which exceed a preset time threshold value as a priority display cleaning curve, and taking other intelligent cleaning curves positioned in the intelligent cleaning curve database matched with the daily habits of the user as non-priority display cleaning curves;
step 5, a self-defined intelligent cleaning curve database which is self-defined and set by a user is pre-constructed; the user-defined intelligent cleaning curve database comprises at least one user-defined intelligent cleaning curve; the parameters of the self-defined intelligent cleaning curve comprise a cleaning curve name parameter, a cleaning time parameter, a cleaning temperature parameter and a cleaning water level parameter which can be set by a user in a self-defined way;
step 6, setting a preset region position list, and constructing an intelligent cleaning curve database for cleaning fruits and vegetables which are produced in corresponding region positions according to the preset region positions; the intelligent fruit and vegetable cleaning curve database comprises a fruit intelligent cleaning curve sub-database and a vegetable intelligent cleaning curve sub-database; the fruit intelligent cleaning curve sub-database comprises at least one fruit intelligent cleaning curve for cleaning fruit varieties contained in a region position; the vegetable intelligent cleaning curve sub-database comprises at least one vegetable intelligent cleaning curve for cleaning the variety of the vegetable which is produced in the region;
step 7, constructing an intelligent cleaning curve database for the water condition of the matched region, which is adapted to the water condition of the corresponding region position, according to the water condition of each region position in the preset region position list; the intelligent cleaning curve database for the water condition of the matched region comprises at least one intelligent cleaning curve which is adaptive to the water condition of the corresponding region; the water condition comprises a water shortage condition and a water quality condition;
step 8, setting a preset family population condition information list, and constructing an intelligent cleaning curve database which is suitable for the matched family population condition and is used for the matched family population condition and is suitable for each family population condition in the family population condition information list; the intelligent cleaning curve database for matching the family population condition comprises at least one intelligent cleaning curve for cleaning beneficial fruits and vegetables, wherein the beneficial fruits and vegetables are fruits and vegetables beneficial to the body health of family members;
step 9, pre-constructing an intelligent cleaning curve database for matching fruit and vegetable tastes of fruits and vegetables with different tastes; wherein, the intelligent cleaning curve database for matching the tastes of the fruits and the vegetables comprises at least one intelligent cleaning curve for cleaning the fruits and the vegetables with the tastes;
step 10, when a request of a user for selecting an intelligent cleaning curve is received, providing calling instructions of an intelligent cleaning curve database, a self-defined intelligent cleaning curve database, an intelligent cleaning curve database for fruits and vegetables, an intelligent cleaning curve database for water conditions of matching regions, an intelligent cleaning curve database for population conditions of matching families and an intelligent cleaning curve database for fruit and vegetable taste which respectively correspond to the daily habits of the user for the user to select;
and 11, when the user selects any one of the call instructions, sequentially recommending the intelligent cleaning curves in the intelligent cleaning curve database corresponding to the call instruction selected by the user to the user according to the recommendation priority level corresponding to the call instruction selected by the user.
In an improved way, in the intelligent recommendation method for the washing curve of the dishwasher, the method further comprises steps a1 to a2 after the step 11:
step a1, receiving a recommendation priority setting instruction of a user to the intelligent cleaning curve database matched with the daily habits of the user, the self-defined intelligent cleaning curve database, the intelligent cleaning curve database for fruits and vegetables, the intelligent cleaning curve database matched with regional water conditions, the intelligent cleaning curve database matched with family population conditions and the intelligent cleaning curve database matched with fruit and vegetable flavors;
and a2, respectively displaying all the intelligent cleaning curves in the intelligent cleaning curve database corresponding to each recommendation priority in sequence according to the recommendation priority setting instruction and the high-low order of the recommendation priority.
In a further improvement, in the intelligent cleaning curve recommendation method for a dishwasher, in step 7, any one of the intelligent cleaning curves in the intelligent cleaning curve database for matching the regional water conditions further has an adaptive adjustment process for the regional water condition.
Further, the adaptive adjustment process for the water quality condition of the region position comprises the following steps S1 to S5:
step S1, presetting a water shortage step adjustment value aiming at each preset region position and a water quality condition fine adjustment value aiming at each preset region position;
s2, acquiring a current region position of the dish-washing machine, and acquiring a current water shortage step adjustment value corresponding to the current region position and a current water quality condition fine adjustment value corresponding to the current region position; wherein, the current water-lacking step adjustment value corresponding to the current location position is marked as a, a belongs to [0,1]; the current water quality condition fine adjustment value corresponding to the current location is marked as b, b ∈ [ -1,1];
s3, searching an intelligent cleaning curve corresponding to the current region position in the intelligent cleaning curve database for the water condition of the matched region, and acquiring a preset cleaning water level parameter value of the searched intelligent cleaning curve; wherein the preset washing water level parameter value is marked as V 0 ；
S4, processing to obtain a self-adaptive adjusted cleaning water level parameter value of the intelligent cleaning curve adapting to the current regional position according to the obtained current water shortage step adjustment value, the current water quality condition fine adjustment value and the preset water level parameter value; wherein the adjusted washing water level parameter value is marked as V, and V = V 0 ×a+b；
And S5, taking the washing water level parameter value after the self-adaptive adjustment as a washing water level parameter value when the intelligent washing curve is executed, so that the intelligent washing curve after the self-adaptive adjustment can be called by the dish washing machine.
Preferably, in the intelligent washing curve recommending method for the dishwasher, the current water shortage step adjustment value a =1, and the current water quality condition fine adjustment value b =0.
Compared with the prior art, the invention has the advantages that:
firstly, the intelligent cleaning curve database corresponding to a plurality of use scenes (scenes of daily habits, self-definition, fruit and vegetable types, regional water conditions, family population conditions and fruit and vegetable taste of a user) is set so as to meet the selection of the user on different use scenes, so that the dishwasher can call intelligent cleaning curves matched with different use scenes to improve the cleaning effect;
secondly, when the intelligent cleaning curve database matched with the region water conditions is arranged, the self-adaptive adjusting mechanism aiming at the water conditions (water shortage condition and water quality condition) of the region position where the dish-washing machine is located is also arranged, so that the dish-washing machine can call a cleaning curve with better cleaning effect at different water condition region positions;
finally, the intelligent cleaning curve recommendation method provided by the invention is provided with a user-defined intelligent cleaning curve database so as to meet the personalized customization requirements of users for cleaning curves.
Drawings
FIG. 1 is a flow chart of an intelligent cleaning curve recommendation method for a dishwasher according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the following examples of the drawings.
Referring to fig. 1, the present embodiment provides a method for intelligently recommending a washing curve for a dishwasher, including the following steps 1 to 11:
step 1, pre-establishing an intelligent cleaning curve database for a user to select cleaning;
step 2, counting the times of selecting each intelligent cleaning curve in the intelligent cleaning curve database by a user in a preset time period, and establishing an intelligent cleaning curve use record database of the user aiming at each intelligent cleaning curve in the intelligent cleaning curve database; wherein, any intelligent cleaning curve usage record in the intelligent cleaning curve usage record database at least comprises the usage times of any intelligent cleaning curve selected by the user;
step 3, according to the size of the using times, sorting the intelligent cleaning curve using records in the intelligent cleaning curve using record database in a descending order mode to obtain a descending intelligent cleaning curve using record database, and using the descending intelligent cleaning curve using record database as an intelligent cleaning curve database matched with the daily habits of the user;
that is, the intelligent cleaning curve corresponding to the intelligent cleaning curve usage record with the largest number of times of usage in the intelligent cleaning curve usage record database is placed at the forefront of the intelligent cleaning curve database, the intelligent cleaning curve corresponding to the intelligent cleaning curve usage record with the smallest number of times of usage in the intelligent cleaning curve usage record database is placed at the rearmost end of the intelligent cleaning curve database, and the intelligent cleaning curves corresponding to the other intelligent cleaning curve usage records are sequenced by analogy in sequence;
step 4, setting the intelligent cleaning curve corresponding to the intelligent cleaning curve usage record which is positioned in the intelligent cleaning curve database matching the daily habits of the user and the usage times of which exceed a preset time threshold value as a priority display cleaning curve, and taking other intelligent cleaning curves positioned in the intelligent cleaning curve database matching the daily habits of the user as non-priority display cleaning curves;
for example, the preset number threshold may be set to 5, that is, once the number of times that any one of the intelligent cleaning curves in the intelligent cleaning curve database is used (or called) exceeds 5, the intelligent cleaning curve is set to preferentially display a cleaning curve, so that when the intelligent cleaning curve database matching the daily habit of the user is displayed, the intelligent cleaning curve set to preferentially display the cleaning curve is preferentially displayed to the user, thereby meeting the daily cleaning habit of the user; those intelligent cleaning curves with the use times less than 5 times are set as non-priority display cleaning curves, namely when the intelligent cleaning curve database matching the daily habits of the user is displayed, the intelligent cleaning curves which are set as the non-priority display cleaning curves are arranged behind the priority display cleaning curves for display; after all, the non-priority display cleaning curves belong to cleaning curves which are not used by the user or are frequently used by the user, so that the daily cleaning habits of the user can be better met by setting the priority display cleaning curve and the non-priority display cleaning curve, and the accuracy and the recommendation efficiency of cleaning curve recommendation for the user are improved;
step 5, a user-defined intelligent cleaning curve database for user-defined setting is constructed in advance; the user-defined intelligent cleaning curve database contains at least one user-defined intelligent cleaning curve; the parameters of the customized intelligent cleaning curve comprise a cleaning curve name parameter, a cleaning time parameter, a cleaning temperature parameter and a cleaning water level parameter which can be customized by a user;
because the parameters corresponding to the customized intelligent cleaning curves in the customized intelligent cleaning curve database can be set according to the user's own will, therefore, since the parameters of the cleaning curves are set by the user himself, the user will like to try to clean once on the will, and follow-up operations are continuously executed after observing the cleaning effect, or the user uses the cleaning curves corresponding to the parameters and the cleaning effect is good, so that the user is more willing to continuously use the parameters, the cleaning curves are recommended to the user, and the user can find the curve cleaning curves which the user wants to use more quickly;
step 6, setting a preset region position list, and constructing an intelligent cleaning curve database for cleaning fruits and vegetables of fruits and vegetables produced in corresponding region positions according to each preset region position; the intelligent fruit and vegetable cleaning curve database comprises a fruit intelligent cleaning curve sub-database and a vegetable intelligent cleaning curve sub-database; the fruit intelligent cleaning curve sub-database comprises at least one fruit intelligent cleaning curve for cleaning the fruit varieties contained in the region and the position; the vegetable intelligent cleaning curve sub-database comprises at least one vegetable intelligent cleaning curve for cleaning the variety of the vegetable which is produced in the region; the term "fruits and vegetables" in this embodiment is a general term for fruits and vegetables;
assuming that the preset region position list comprises a first place and a second place, the first place produces kiwi fruits abundantly, and the second place produces tomatoes abundantly, so that an intelligent cleaning curve for the kiwi fruits is included in the fruit intelligent cleaning curve sub-database in the constructed intelligent cleaning curve database for the fruits and the vegetables, and an intelligent cleaning curve for the tomatoes is included in the vegetable intelligent cleaning curve sub-database in the constructed intelligent cleaning curve database for the fruits and the vegetables; therefore, the actual cleaning requirements of users on the geographical positions where different fruits and vegetables are produced can be met, and the method is more targeted to meet the fruit and vegetable cleaning requirements of all users to the greatest extent;
step 7, constructing an intelligent cleaning curve database for the water condition of the matched region, which is adaptive to the water condition of the corresponding region position, according to the water condition of each region position in the preset region position list; the intelligent cleaning curve database for matching the water conditions of the regions comprises at least one intelligent cleaning curve which is adaptive to the water conditions of the corresponding region positions; the water condition comprises a water shortage condition and a water quality condition; that is to say, whether a certain set region position is lack of water or not and the water quality of the certain region position is salty or sweet or sour or alkaline;
by constructing an intelligent cleaning curve database which is suitable for water conditions of different regions, the cleaning effect can be improved to the greatest extent on the basis of meeting the local water condition;
step 8, setting a preset family population condition information list, and constructing an intelligent cleaning curve database which is suitable for the family population conditions and is used for matching the family population conditions in the family population condition information list; the intelligent cleaning curve database for matching the family population condition comprises at least one intelligent cleaning curve for cleaning beneficial fruits and vegetables, wherein the beneficial fruits and vegetables are fruits and vegetables beneficial to the body health of family members;
supposing that, in a family population status included in the preset family population status information list, if the family population has old people, children and middle-aged people, because apples are fruits beneficial to special people such as the old people and the children, the intelligent cleaning curve for the apples is stored in the intelligent cleaning curve database for matching the family population status; of course, if there are fruits and vegetables (fruits and/or vegetables) beneficial to corresponding users in other families, the intelligent cleaning curves specific to the fruits and vegetables are also stored in the intelligent cleaning curve database for the matched family population condition;
step 9, pre-constructing an intelligent cleaning curve database for matching fruit and vegetable tastes of fruits and vegetables with different tastes; wherein, the intelligent cleaning curve database for matching the fruit and vegetable flavors comprises at least one intelligent cleaning curve for cleaning the flavor fruit and vegetable;
because different fruits and vegetables usually have different tastes, for example, the tastes of sweetish (tomatoes) or sour (hawthorns) exist, the intelligent cleaning curve for the sweeter fruits and vegetables and the intelligent cleaning curve for the sour fruits and vegetables are stored in the intelligent cleaning curve database for matching the tastes of the fruits and vegetables;
step 10, when a request of a user for selecting an intelligent cleaning curve is received, calling instructions of an intelligent cleaning curve database, a self-defined intelligent cleaning curve database, an intelligent cleaning curve database for fruits and vegetables, an intelligent cleaning curve database for water conditions of matching regions, an intelligent cleaning curve database for population conditions of matching families and an intelligent cleaning curve database for fruit and vegetable taste which respectively correspond to the daily habits of the user are simultaneously provided for the user to select;
and step 11, when the user selects any one of the call instructions, recommending the intelligent cleaning curves in the intelligent cleaning curve database corresponding to the call instruction selected by the user to the user in sequence according to the recommendation priority level corresponding to the call instruction selected by the user. For example, the user only selects a calling instruction A of the intelligent cleaning curve database corresponding to the daily habits of the user and an instruction B of the intelligent cleaning curve database corresponding to the tastes of the fruits and vegetables, the recommendation priority of the calling instruction A is higher than that of the calling instruction B, the intelligent cleaning curves in the intelligent cleaning curve database corresponding to the calling instruction A and matching the daily habits of the user are recommended to the user in sequence, and then the intelligent cleaning curves in the intelligent cleaning curve database corresponding to the calling instruction B and matching the tastes of the fruits and vegetables are recommended to the user.
Of course, in order to provide more selection rights and setting rights for the intelligent cleaning curve for the user, step 11 of the present embodiment further includes steps a1 to a2:
step a1, receiving a recommendation priority setting instruction of a user to the intelligent cleaning curve database matched with the daily habits of the user, the self-defined intelligent cleaning curve database, the intelligent cleaning curve database for fruits and vegetables, the intelligent cleaning curve database matched with regional water conditions, the intelligent cleaning curve database matched with family population conditions and the intelligent cleaning curve database matched with fruit and vegetable flavors;
and a2, respectively displaying all the intelligent cleaning curves in the intelligent cleaning curve database corresponding to each recommendation priority in sequence according to the recommendation priority setting instruction and the high and low order of the recommendation priority.
In order to meet the requirement that the dishwasher can call a cleaning curve with better cleaning effect when being used in different region positions, in step 7 of the embodiment, any one of the intelligent cleaning curves in the intelligent cleaning curve database for matching the region water conditions further has an adaptive adjustment process for the region position water quality conditions. Specifically, the adaptive adjustment process for the water quality condition of the region position comprises the following steps of S1 to S5:
step S1, presetting a water shortage step adjustment value aiming at each preset region position and a water quality condition fine adjustment value aiming at each preset region position;
s2, acquiring a current region position of the dish-washing machine, and acquiring a current water shortage step adjustment value corresponding to the current region position and a current water quality condition fine adjustment value corresponding to the current region position; wherein, the current water-lacking step adjustment value corresponding to the current location position is marked as a, a belongs to [0,1]; the current water quality condition fine adjustment value corresponding to the current location is marked as b, b ∈ [ -1,1];
s3, searching an intelligent cleaning curve corresponding to the current region position in the intelligent cleaning curve database for the water condition of the matched region, and acquiring a preset cleaning water level parameter value of the searched intelligent cleaning curve; wherein the preset washing water level parameter value is marked as V 0 ；
S4, according to the obtained current water shortage step adjustment value a, the current water quality condition fine adjustment value b and the preset water level parameter value V 0 Processing to obtain a self-adaptive adjusted cleaning water level parameter value of the intelligent cleaning curve adaptive to the current location position; wherein the adjusted washing water level parameter value is marked as V, and V = V 0 ×a+b；
S5, taking the cleaning water level parameter value V after the self-adaptive adjustment as the cleaning when the intelligent cleaning curve is executedWashing water level parameter value, namely replacing original water level parameter V of the intelligent washing curve by V 0 And the intelligent cleaning curve after the self-adaptive adjustment is called by the dishwasher. Wherein, under the water shortage situation and the quality of water condition that do not consider the region position of locating, can make current water shortage ladder adjustment value a =1 and current quality of water situation fine setting value b =0 as required to directly use the original washing water level after a large amount of cleaning performance experiments verify, ensure better intelligent cleaning performance.
Claims (5)
1. An intelligent cleaning curve recommendation method for a dishwasher is characterized by comprising the following steps 1-11:
step 1, pre-establishing an intelligent cleaning curve database for a user to select cleaning;
step 2, counting the times of selecting each intelligent cleaning curve in the intelligent cleaning curve database by the user in a preset time period, and establishing an intelligent cleaning curve use record database of the user for each intelligent cleaning curve in the intelligent cleaning curve database; wherein, any intelligent cleaning curve usage record in the intelligent cleaning curve usage record database at least comprises the usage times of any intelligent cleaning curve selected by the user;
step 3, according to the size of the using times, sorting the intelligent cleaning curve using records in the intelligent cleaning curve using record database in a descending order mode to obtain a descending intelligent cleaning curve using record database, and using the descending intelligent cleaning curve using record database as an intelligent cleaning curve database matched with the daily habits of the user;
step 4, setting the intelligent cleaning curve corresponding to the intelligent cleaning curve usage record which is positioned in the intelligent cleaning curve database matched with the daily habits of the user and the usage times of which exceed a preset time threshold value as a priority display cleaning curve, and taking other intelligent cleaning curves positioned in the intelligent cleaning curve database matched with the daily habits of the user as non-priority display cleaning curves;
step 5, a user-defined intelligent cleaning curve database for user-defined setting is constructed in advance; the user-defined intelligent cleaning curve database comprises at least one user-defined intelligent cleaning curve; the parameters of the self-defined intelligent cleaning curve comprise a cleaning curve name parameter, a cleaning time parameter, a cleaning temperature parameter and a cleaning water level parameter which can be set by a user in a self-defined way;
step 6, setting a preset region position list, and constructing an intelligent cleaning curve database for cleaning fruits and vegetables which are produced in corresponding region positions according to the preset region positions; the intelligent fruit and vegetable cleaning curve database comprises a fruit intelligent cleaning curve sub-database and a vegetable intelligent cleaning curve sub-database; the fruit intelligent cleaning curve sub-database comprises at least one fruit intelligent cleaning curve for cleaning fruit varieties contained in regional positions; the vegetable intelligent cleaning curve sub-database comprises at least one vegetable intelligent cleaning curve for cleaning the variety of the vegetables which are produced in the region;
step 7, constructing an intelligent cleaning curve database for the water condition of the matched region, which is adapted to the water condition of the corresponding region position, according to the water condition of each region position in the preset region position list; the intelligent cleaning curve database for the water condition of the matched region comprises at least one intelligent cleaning curve which is adaptive to the water condition of the corresponding region; the water condition conditions comprise water shortage conditions and water quality conditions;
step 8, setting a preset family population condition information list, and constructing an intelligent cleaning curve database which is suitable for the family population conditions and is used for matching the family population conditions in the family population condition information list; the intelligent cleaning curve database for matching the family population condition comprises at least one intelligent cleaning curve for cleaning beneficial fruits and vegetables, wherein the beneficial fruits and vegetables are fruits and vegetables beneficial to the body health of family members;
step 9, pre-constructing an intelligent cleaning curve database for matching fruit and vegetable tastes of fruits and vegetables with different tastes; wherein, the intelligent cleaning curve database for matching the tastes of the fruits and the vegetables comprises at least one intelligent cleaning curve for cleaning the fruits and the vegetables with the tastes;
step 10, when a request of selecting an intelligent cleaning curve by a user is received, providing calling instructions of an intelligent cleaning curve database, a self-defined intelligent cleaning curve database, an intelligent cleaning curve database for fruits and vegetables, an intelligent cleaning curve database for water conditions of matching regions, an intelligent cleaning curve database for population conditions of matching households and an intelligent cleaning curve database for fruit and vegetable flavors respectively corresponding to daily habits of the user for selection by the user;
and 11, when the user selects any one of the call instructions, sequentially recommending the intelligent cleaning curves in the intelligent cleaning curve database corresponding to the call instruction selected by the user to the user according to the recommendation priority level corresponding to the call instruction selected by the user.
2. The washing curve intelligent recommendation method for a dishwasher according to claim 1, further comprising steps a 1-a 2 after step 11:
step a1, receiving a recommendation priority setting instruction of a user to the intelligent cleaning curve database matched with the daily habits of the user, the self-defined intelligent cleaning curve database, the intelligent cleaning curve database for fruits and vegetables, the intelligent cleaning curve database matched with regional water conditions, the intelligent cleaning curve database matched with family population conditions and the intelligent cleaning curve database matched with fruit and vegetable flavors;
and a2, respectively displaying all the intelligent cleaning curves in the intelligent cleaning curve database corresponding to each recommendation priority in sequence according to the recommendation priority setting instruction and the high and low order of the recommendation priority.
3. The intelligent recommendation method for washing curve of dishwasher according to claim 1, wherein in step 7, any one of the intelligent washing curves in the database of matching regional water condition intelligent washing curves further has an adaptive adjustment process for regional water condition.
4. The intelligent recommendation method for the washing curve of the dish washing machine as claimed in claim 3, wherein the adaptive adjustment process for the regional water quality condition comprises steps S1-S5:
step S1, presetting a water shortage step adjustment value aiming at each preset region position and a water quality condition fine adjustment value aiming at each preset region position;
s2, acquiring the current region position of the dish washing machine, and acquiring a current water shortage step adjustment value corresponding to the current region position and a current water quality condition fine adjustment value corresponding to the current region position; wherein, the current water-lacking step adjustment value corresponding to the current location position is marked as a, a belongs to [0,1]; the current water quality condition fine adjustment value corresponding to the current location is marked as b, b ∈ [ -1,1];
s3, searching an intelligent cleaning curve corresponding to the current region position in the intelligent cleaning curve database for the water condition of the matched region, and acquiring a preset cleaning water level parameter value of the searched intelligent cleaning curve; wherein the preset washing water level parameter value is marked as V 0 ；
S4, processing to obtain a self-adaptive adjusted cleaning water level parameter value of the intelligent cleaning curve adapting to the current location according to the obtained current water shortage step adjustment value, the current water quality condition fine adjustment value and the preset cleaning water level parameter value; wherein the adjusted washing water level parameter value is marked as V, and V = V 0 ×a+b；
And S5, taking the washing water level parameter value after the self-adaptive adjustment as a washing water level parameter value when the intelligent washing curve is executed, so that the dishwasher can call the self-adaptive adjusted intelligent washing curve.
5. The intelligent recommendation method for the washing curve of the dishwasher according to claim 4, wherein the current water shortage step adjustment value a =1 and the current water quality condition fine adjustment value b =0.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1190570A (en) * | 1996-11-19 | 1998-08-19 | 三星电子株式会社 | Bowl-washing machine with fruit-washing function and method thereof |
| WO2001014625A2 (en) * | 1999-08-26 | 2001-03-01 | Henkel Ecolab Gmbh & Co. Ohg | Washing method and dishwasher |
| CN105231468A (en) * | 2015-08-28 | 2016-01-13 | 河海大学常州校区 | Automatic ultrasound cleaning machine based on image processing and operating method thereof |
| CN107609046A (en) * | 2017-08-17 | 2018-01-19 | 无锡小天鹅股份有限公司 | System of selection, device, device for clothing processing and the server of washing mode |
| CN108836211A (en) * | 2018-06-27 | 2018-11-20 | 北京小米移动软件有限公司 | tableware cleaning device and method |
| CN110051300A (en) * | 2018-01-19 | 2019-07-26 | 青岛海尔洗碗机有限公司 | A kind of dish washer control method and dish-washing machine |
| CN110251034A (en) * | 2019-06-19 | 2019-09-20 | 佛山市百斯特电器科技有限公司 | A kind of control method and dish-washing machine of sterilizing operation |
| CN114190857A (en) * | 2021-12-22 | 2022-03-18 | 珠海格力电器股份有限公司 | Method and device for controlling operation of dish washing machine and dish washing machine |
-
2019
- 2019-01-28 CN CN201910078748.6A patent/CN111488383B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1190570A (en) * | 1996-11-19 | 1998-08-19 | 三星电子株式会社 | Bowl-washing machine with fruit-washing function and method thereof |
| WO2001014625A2 (en) * | 1999-08-26 | 2001-03-01 | Henkel Ecolab Gmbh & Co. Ohg | Washing method and dishwasher |
| CN105231468A (en) * | 2015-08-28 | 2016-01-13 | 河海大学常州校区 | Automatic ultrasound cleaning machine based on image processing and operating method thereof |
| CN107609046A (en) * | 2017-08-17 | 2018-01-19 | 无锡小天鹅股份有限公司 | System of selection, device, device for clothing processing and the server of washing mode |
| CN110051300A (en) * | 2018-01-19 | 2019-07-26 | 青岛海尔洗碗机有限公司 | A kind of dish washer control method and dish-washing machine |
| CN108836211A (en) * | 2018-06-27 | 2018-11-20 | 北京小米移动软件有限公司 | tableware cleaning device and method |
| CN110251034A (en) * | 2019-06-19 | 2019-09-20 | 佛山市百斯特电器科技有限公司 | A kind of control method and dish-washing machine of sterilizing operation |
| CN114190857A (en) * | 2021-12-22 | 2022-03-18 | 珠海格力电器股份有限公司 | Method and device for controlling operation of dish washing machine and dish washing machine |
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