阅读说明：本技术 一种洗碗机的清洗曲线智能推荐方法及系统 (Intelligent recommendation method and system for cleaning curve of dish washing machine ) 是由 余航 于 2019-01-15 设计创作，主要内容包括：本发明涉及一种洗碗机的清洗曲线智能推荐方法及系统,该清洗曲线智能推荐方法在执行开始时就对洗碗机内待清洗对象的物体类型做出识别,以根据识别到的待清洗对象类型转入执行针对餐具类的清洗曲线推荐过程或者转入针对果蔬类的清洗曲线推荐过程,做到了根据所识别待清洗对象的物体类型而执行对应的清洗曲线推荐操作,更具有针对性以及更加符合用户对不同待清洗对象的清洗需求；在执行针对餐具类的清洗曲线推荐过程中,会对待清洗对象所含有的餐具种类数量做出判断,以推荐更加符合当前待清洗对象类型的清洗曲线,能够实现将预设的清洗曲线与实际待清洗对象的品种智能匹配,满足了用户在实际使用场景中对洗碗机的智能化清洗需要。(The invention relates to an intelligent recommendation method and system for a cleaning curve of a dish washing machine, wherein the intelligent recommendation method for the cleaning curve identifies the object type of an object to be cleaned in the dish washing machine at the beginning of execution, so that the method is switched to execute a recommendation process for the cleaning curve of tableware or a recommendation process for the cleaning curve of fruits and vegetables according to the identified type of the object to be cleaned, so that the corresponding recommendation operation for the cleaning curve is executed according to the identified type of the object to be cleaned, and the method and system have pertinence and better meet the cleaning requirements of users on different objects to be cleaned; in the process of recommending the cleaning curve aiming at the tableware, the quantity of the tableware types contained in the object to be cleaned is judged so as to recommend the cleaning curve which is more consistent with the type of the current object to be cleaned, the preset cleaning curve can be intelligently matched with the variety of the actual object to be cleaned, and the intelligent cleaning requirement of a user on the dish-washing machine in an actual use scene is met.)

1. An intelligent recommendation method for a cleaning curve of a dishwasher is characterized by comprising the following steps:

step 1, performing object type identification on an object to be cleaned placed in a dishwasher to obtain the object type of the object to be cleaned;

step 2, when the object type of the object to be cleaned belongs to the tableware class, turning to step 3; when the object type of the object to be cleaned belongs to the fruit and vegetable class, turning to step 8;

step 3, recommending the tableware cleaning curve data which is positioned in a preset tableware cleaning curve database and corresponds to the single type of tableware to a user when the object to be cleaned is judged to be the single type of tableware; otherwise, respectively calling the tableware cleaning curve data which are positioned in the preset tableware cleaning curve database and correspond to various kinds of tableware, and then turning to the step 4; wherein the dish washing curve data includes water level data, water temperature data and washing time data corresponding to the execution of the dish washing curve;

step 4, respectively obtaining the highest water temperature data of each tableware cleaning curve according to the water temperature data of each called tableware cleaning curve, and forming a tableware cleaning curve highest water temperature sub-database by all the obtained highest water temperature data;

step 5, acquiring the highest water temperature data and the lowest water temperature data in the tableware washing curve highest water temperature sub-database, and judging and processing according to the acquired highest water temperature data and the acquired lowest water temperature data:

when the difference value between the acquired highest water temperature data and the acquired lowest water temperature data is larger than a preset temperature difference threshold value, sending a prompt for separately cleaning the object to be cleaned to a user, and turning to the step 6; otherwise, go to step 7;

step 6, receiving selection feedback of the user aiming at the separate cleaning prompt and executing corresponding processing: when the user selects the separated cleaning, the step 3 is carried out; otherwise, go to step 7;

step 7, respectively obtaining a water level mean value of water level data corresponding to each tableware cleaning curve, a water temperature mean value of water temperature data corresponding to each tableware cleaning curve and a cleaning time mean value of cleaning time data corresponding to each tableware cleaning curve, and recommending the tableware cleaning curve formed by the obtained water level mean value, water temperature mean value and cleaning time mean value to a user as an optimal tableware cleaning curve for a current object to be cleaned;

step 8, identifying and obtaining the quantity of the varieties of the fruits and vegetables of the object to be cleaned and the health conditions of the fruits and vegetables of all the fruits and vegetables in the object to be cleaned;

step 9, judging whether the health of the user is endangered according to the obtained health state of the fruits and vegetables: when the object to be cleaned is judged to have fruits and vegetables which are harmful to the health of the user, a fruit and vegetable replacement prompt is sent to the user, and the step 10 is carried out; otherwise, turning to 11;

step 10, judging and processing according to the feedback of the user aiming at the fruit and vegetable replacement prompt: when the user does not continue to wash, turning to step 8; otherwise, go to step 11;

step 11, recommending the fruit and vegetable cleaning curve data which are positioned in a preset fruit and vegetable cleaning curve database and correspond to the variety of fruits and vegetables to a user when the object to be cleaned is judged to be a single variety of fruits and vegetables; otherwise, respectively calling fruit and vegetable cleaning curve data which are positioned in a preset fruit and vegetable cleaning curve database and correspond to various kinds of fruits and vegetables, and turning to the step 12; the fruit and vegetable cleaning curve data comprises water level data, cleaning time data and cleaning mode data corresponding to the fruit and vegetable cleaning curve;

step 12, when different cleaning mode data exist in all the called fruit and vegetable cleaning curve data, sending a prompt for separately cleaning the object to be cleaned to a user, and turning to step 13; otherwise, go to step 14;

step 13, receiving the selection feedback of the user for the separate cleaning prompt and executing the corresponding processing: when the user selects the separate cleaning, the step 11 is carried out; otherwise, go to step 8;

and step 14, respectively obtaining a water level mean value of the water level data corresponding to each fruit and vegetable cleaning curve and a cleaning time mean value of the cleaning time data corresponding to each fruit and vegetable cleaning curve, and recommending the fruit and vegetable cleaning curve formed by the obtained water level mean value and the cleaning time mean value to a user as an optimal fruit and vegetable cleaning curve for a current object to be cleaned.

2. The intelligent recommendation method for the washing curve of the dishwasher according to claim 1, further comprising the step 14: and (5) sending the health condition of the fruits and vegetables obtained in the step (8) to the user again for prompting.

3. The intelligent recommendation method for the washing curve of the dishwasher according to claim 1, wherein the tableware is a bowl or a dish or a spoon or chopsticks or any combination of the bowl, the dish, the spoon and the chopsticks.

4. The intelligent recommendation method for the washing curve of the dish washing machine according to any one of claims 1 to 4, wherein the preset temperature difference threshold value in the step 5 is 20 ℃.

5. The intelligent cleaning curve recommendation system for realizing the intelligent cleaning curve recommendation method of any one of claims 1-4 comprises a dishwasher (1), and is characterized by further comprising a user terminal (2) and a processing terminal (3) for executing judgment and processing work in the intelligent cleaning curve recommendation method and providing a cleaning curve to the dishwasher, wherein the dishwasher (1) is respectively connected with the user terminal (2) and the processing terminal (3).

6. The intelligent cleaning curve recommendation system according to claim 5, characterized in that the processing terminal (3) is a cloud platform at a remote end; alternatively, the processing terminal (3) is integrated on the dishwasher (1).

7. The intelligent cleaning curve recommendation system according to claim 5, wherein the user terminal (2) is a smart phone or a tablet computer.

Technical Field

The invention relates to the field of dish washing machines, in particular to an intelligent recommendation method and system for a washing curve of a dish washing machine.

Background

In the current field of kitchen appliances, dishwashers are used by more and more households as a convenient dish washing tool. With the development of intelligent technology, dishwashers with intelligent functions are also successively oriented to the market. These dishwashers can be connected to user terminals such as smartphones and tablets, and then the user can use the user terminals to check the official preset intelligent cleaning curves provided by dishwasher manufacturers on-line or the user can use the user terminals to customize the intelligent cleaning curves for the dishwashers, so as to control the whole cleaning process of the dishwashers.

The intelligent washing curve is predetermine to official authority that dish washer firm provided is the washing curve that obtains through a large amount of experimental data verification, dish washer water level data in the cleaning process, water temperature data and washing time data etc. are all set well in advance by the dish washer firm, and these official authorities predetermine that the object of treating that intelligent washing curve corresponds also is fixed, if the official authority predetermines that the object of treating that intelligent washing curve corresponds is when the dish utensil, in case the user need abluent object is fruit or vegetables in the in-service use process, the dish washer just this moment does not have the washing curve to fruit or vegetables, use experience effect when reducing the user and using dish washer.

Of course, if the user uses his/her own user terminal to customize the washing curve, most users lack the expertise in setting the washing curve, so that the washing curve they define cannot achieve the desired satisfactory washing effect even if the washing curve is followed by the dishwasher. That is to say, the existing washing curve recommendation method for the dish washing machine is difficult to meet the washing requirements of users in actual use scenes, and is difficult to achieve the intellectualization meeting the washing requirements of the users.

Disclosure of Invention

The first technical problem to be solved by the present invention is to provide an intelligent recommendation method for a washing curve of a dishwasher in view of the above prior art.

The second technical problem to be solved by the present invention is to provide an intelligent cleaning curve recommendation system for implementing the intelligent cleaning curve recommendation method in view of the above prior art.

The technical scheme adopted by the invention for solving the first technical problem is as follows: an intelligent recommendation method for a cleaning curve of a dishwasher is characterized by comprising the following steps:

step 1, performing object type identification on an object to be cleaned placed in a dishwasher to obtain the object type of the object to be cleaned;

step 2, when the object type of the object to be cleaned belongs to the tableware class, turning to step 3; when the object type of the object to be cleaned belongs to the fruit and vegetable class, turning to step 8;

step 3, recommending the tableware cleaning curve data which is positioned in a preset tableware cleaning curve database and corresponds to the single type of tableware to a user when the object to be cleaned is judged to be the single type of tableware; otherwise, respectively calling the tableware cleaning curve data which are positioned in the preset tableware cleaning curve database and correspond to various kinds of tableware, and then turning to the step 4; wherein the dish washing curve data includes water level data, water temperature data and washing time data corresponding to the execution of the dish washing curve;

step 4, respectively obtaining the highest water temperature data of each tableware cleaning curve according to the water temperature data of each called tableware cleaning curve, and forming a tableware cleaning curve highest water temperature sub-database by all the obtained highest water temperature data;

step 5, acquiring the highest water temperature data and the lowest water temperature data in the tableware washing curve highest water temperature sub-database, and judging and processing according to the acquired highest water temperature data and the acquired lowest water temperature data:

when the difference value between the acquired highest water temperature data and the acquired lowest water temperature data is larger than a preset temperature difference threshold value, sending a prompt for separately cleaning the object to be cleaned to a user, and turning to the step 6; otherwise, go to step 7;

step 6, receiving selection feedback of the user aiming at the separate cleaning prompt and executing corresponding processing: when the user selects the separated cleaning, the step 3 is carried out; otherwise, go to step 7;

step 7, respectively obtaining a water level mean value of water level data corresponding to each tableware cleaning curve, a water temperature mean value of water temperature data corresponding to each tableware cleaning curve and a cleaning time mean value of cleaning time data corresponding to each tableware cleaning curve, and recommending the tableware cleaning curve formed by the obtained water level mean value, water temperature mean value and cleaning time mean value to a user as an optimal tableware cleaning curve for a current object to be cleaned;

step 8, identifying and obtaining the quantity of the varieties of the fruits and vegetables of the object to be cleaned and the health conditions of the fruits and vegetables of all the fruits and vegetables in the object to be cleaned;

step 9, judging whether the health of the user is endangered according to the obtained health state of the fruits and vegetables: when the object to be cleaned is judged to have fruits and vegetables which are harmful to the health of the user, a fruit and vegetable replacement prompt is sent to the user, and the step 10 is carried out; otherwise, turning to 11;

step 10, judging and processing according to the feedback of the user aiming at the fruit and vegetable replacement prompt: when the user does not continue to wash, turning to step 8; otherwise, go to step 11;

step 11, recommending the fruit and vegetable cleaning curve data which are positioned in a preset fruit and vegetable cleaning curve database and correspond to the variety of fruits and vegetables to a user when the object to be cleaned is judged to be a single variety of fruits and vegetables; otherwise, respectively calling fruit and vegetable cleaning curve data which are positioned in a preset fruit and vegetable cleaning curve database and correspond to various kinds of fruits and vegetables, and turning to the step 12; the fruit and vegetable cleaning curve data comprises water level data, cleaning time data and cleaning mode data corresponding to the fruit and vegetable cleaning curve;

step 12, when different cleaning mode data exist in all the called fruit and vegetable cleaning curve data, sending a prompt for separately cleaning the object to be cleaned to a user, and turning to step 13; otherwise, go to step 14;

step 13, receiving the selection feedback of the user for the separate cleaning prompt and executing the corresponding processing: when the user selects the separate cleaning, the step 11 is carried out; otherwise, go to step 8;

and step 14, respectively obtaining a water level mean value of the water level data corresponding to each fruit and vegetable cleaning curve and a cleaning time mean value of the cleaning time data corresponding to each fruit and vegetable cleaning curve, and recommending the fruit and vegetable cleaning curve formed by the obtained water level mean value and the cleaning time mean value to a user as an optimal fruit and vegetable cleaning curve for a current object to be cleaned.

In an improved manner, in the intelligent recommendation method for the cleaning curve of the dishwasher, the step 14 further includes a step of sending the health condition of the fruits and vegetables obtained in the step 8 to the user again for prompting.

Optionally, in the intelligent washing curve recommendation method for the dishwasher, the tableware is a bowl or a dish or a spoon or chopsticks or any combination of the bowl, the dish, the spoon and the chopsticks.

Further, in the intelligent recommendation method for the washing curve of the dishwasher, the preset temperature difference threshold value in the step 5 is 20 ℃.

The technical scheme adopted by the invention for solving the second technical problem is as follows: the intelligent cleaning curve recommendation system for realizing the intelligent cleaning curve recommendation method comprises a dish washing machine and is characterized by further comprising a user terminal and a processing terminal for executing judgment processing and work in the intelligent cleaning curve recommendation method and providing a cleaning curve for the dish washing machine, wherein the dish washing machine is respectively connected with the user terminal and the processing terminal.

Further, the processing terminal is a remote cloud platform; alternatively, the processing terminal is integrated on the dishwasher.

Optionally, the user terminal is a smart phone or a tablet computer.

Compared with the prior art, the invention has the advantages that:

firstly, the intelligent cleaning curve recommending method identifies the object type of the object to be cleaned at the beginning of execution, so that the method is switched to execute a cleaning curve recommending process for tableware or a cleaning curve recommending process for fruits and vegetables according to the identified object type to be cleaned, the corresponding cleaning curve recommending operation is executed according to the identified object type of the object to be cleaned, and the intelligent cleaning curve recommending method is more targeted and better meets the cleaning requirements of users on different objects to be cleaned;

secondly, in the process of executing the washing curve recommendation for the tableware, the intelligent washing curve recommendation method can judge the quantity of the types of the tableware contained in the object to be washed, namely when the object to be washed only contains a single variety of tableware, only the corresponding tableware washing curve data in the preset tableware washing curve data needs to be recommended to a user; once the object to be cleaned contains a plurality of varieties of tableware, the object to be cleaned needs to be treated according to the water level, the water temperature and the cleaning time which correspond to each variety of tableware respectively, namely, the actual situation of the object to be cleaned in the actual process is considered to be combined on the basis of the original preset cleaning curve data which is successfully tested and verified by a dishwasher manufacturer for numerous times, so that a new tableware cleaning curve is formed and is recommended to users as the optimal tableware cleaning curve aiming at the current object to be cleaned, the defect that most users lack professional experience in the aspect of cleaning curve setting is avoided, the preset tableware cleaning curve is combined with the varieties of the tableware of the actual object to be cleaned, and the tableware cleaning curve recommended to the users is more suitable for the cleaning needs of the current object to be cleaned;

thirdly, in the process of executing the cleaning curve recommendation for the fruits and vegetables, the intelligent cleaning curve recommendation method can judge the types and the quantity of the fruits and vegetables contained in the object to be cleaned, namely when the object to be cleaned only contains a single variety of fruits and vegetables, the corresponding fruit and vegetable cleaning curve data in the preset fruit and vegetable cleaning curve data and the condition that whether the variety of fruits and vegetables harm the body health of the user are only required to be provided for the user; once the object to be cleaned contains a plurality of varieties of fruits and vegetables, extracting and processing the fruit and vegetable cleaning curve data corresponding to various varieties of fruits and vegetables in the preset fruit and vegetable cleaning curve data according to the cleaning requirements of users, processing according to the water level and the cleaning time of the fruit and vegetable cleaning curve data to form a new fruit and vegetable cleaning curve which is recommended to the users as the optimal fruit and vegetable cleaning curve for the current object to be cleaned, and combining the preset fruit and vegetable cleaning curve with the fruit and vegetable varieties of the actual object to be cleaned is also realized, so that the fruit and vegetable cleaning curve recommended to the users is more suitable for the cleaning requirements of the users for the current object to be cleaned;

finally, the intelligent cleaning curve recommending method can realize intelligent matching of the object to be cleaned in the actual scene and the cleaning curve, and can inform the harm situation of the current fruits and vegetables to the body health of the user when the fruits and vegetables are cleaned, thereby realizing intelligent reminding of the health condition of the fruits and vegetables of the user and cleaning taboo prompt aiming at various fruits and vegetables.

Drawings

Fig. 1 is a schematic diagram of an intelligent cleaning curve recommendation system in an embodiment of the present invention.

Detailed Description

The invention is described in further detail below with reference to the accompanying examples.

The embodiment provides an intelligent recommendation method for a washing curve of a dishwasher, which specifically comprises the following steps:

step 1, performing object type identification on an object to be cleaned placed in a dishwasher to obtain the object type of the object to be cleaned; the identification process aiming at the object to be cleaned can be carried out by adopting the image identification technology which is mature at present;

step 2, when the object type of the object to be cleaned belongs to the tableware class, the step 3 is carried out; when the object type of the object to be cleaned belongs to the fruit and vegetable class, the step 8 is carried out; wherein, the term "fruits and vegetables" is a general term for fruits and vegetables; in addition, the tableware can be set into a bowl, a dish, a soup ladle, chopsticks or any combination of the bowl, the dish, the soup ladle and the chopsticks as required;

step 3, when the object to be cleaned is judged to be a single variety of tableware, namely the object to be cleaned is a single kind of tableware, or the object to be cleaned is a plurality of tableware, but the kinds of the tableware are one, such as all bowls or all dishes, recommending the tableware cleaning curve data which is positioned in the preset tableware cleaning curve database and corresponds to the single kind of tableware to the user; otherwise, respectively calling the tableware cleaning curve data which are positioned in the preset tableware cleaning curve database and correspond to various kinds of tableware, and then turning to the step 4; wherein the dish washing curve data includes water level data, water temperature data and washing time data corresponding to the execution of the dish washing curve;

that is, once it is determined that the object to be cleaned includes a plurality of varieties of tableware, the data of the tableware cleaning curve corresponding to each variety of tableware in the preset tableware cleaning curve database needs to be retrieved;

step 4, respectively obtaining the highest water temperature data of each tableware cleaning curve according to the water temperature data of each called tableware cleaning curve, and forming a tableware cleaning curve highest water temperature sub-database by all the obtained highest water temperature data; that is, the formed dish washing curve maximum water temperature sub-database includes a plurality of maximum water temperature data extracted from each original dish washing curve;

step 5, acquiring the highest water temperature data and the lowest water temperature data in the highest water temperature sub-database of the tableware cleaning curve, and judging and processing according to the acquired highest water temperature data and the acquired lowest water temperature data:

when the difference value between the acquired highest water temperature data and the acquired lowest water temperature data is larger than a preset temperature difference threshold value, a prompt for separately cleaning the object to be cleaned is sent to a user, and the step 6 is carried out; otherwise, go to step 7; when the difference value between the highest water temperature data and the lowest water temperature data is greater than a preset temperature difference threshold value, it is indicated that a plurality of tableware contained in the object to be cleaned have obviously different proper water temperatures for cleaning, and once the proper water temperature required by any tableware is not reached, even if the tableware is cleaned by the dishwasher, the cleaning effect for the tableware is still poor; for example, the preset temperature difference threshold value here may be set to 20 ℃ as needed;

step 6, receiving selection feedback of the user aiming at the separate cleaning prompt and executing corresponding processing: when the user selects the separated cleaning, the step 3 is carried out; otherwise, the user still requires that the different kinds of tableware are put in the dish-washing machine to be washed together, and then the step 7 is carried out;

step 7, respectively obtaining a water level mean value of water level data corresponding to each tableware cleaning curve, a water temperature mean value of water temperature data corresponding to each tableware cleaning curve and a cleaning time mean value of cleaning time data corresponding to each tableware cleaning curve, and recommending the tableware cleaning curve formed by the obtained water level mean value, water temperature mean value and cleaning time mean value to a user as an optimal tableware cleaning curve for a current object to be cleaned; wherein:

assuming that the object to be cleaned contains three kinds of tableware a, B and C through identification and judgment, correspondingly, a tableware cleaning curve A, a tableware cleaning curve B and a tableware cleaning curve C which respectively correspond to the three kinds of tableware are retrieved from a preset tableware cleaning curve database;

the water level data corresponding to the dish washing curve A is L_AWater temperature data is T_AAnd the cleaning time data is t_A；

The water level data corresponding to the dish washing curve B is L_BWater temperature data is T_BAnd the cleaning time data is t_B；

The water level data corresponding to the dish washing curve C is L_CWater temperature data is T_CAnd the cleaning time data is t_C；

Thus, the water level data corresponding to the optimal dish washing curve recommended to the user is (L)_A+L_B+L_C) (T) is the water temperature data corresponding to the optimal dish washing curve_A+T_B+T_C) And/3, the cleaning time data corresponding to the optimal dish cleaning curve is (t)_A+t_B+t_C)/3；

Step 8, identifying and obtaining the quantity of the varieties of the fruits and vegetables of the object to be cleaned and the health conditions of the fruits and vegetables of all the fruits and vegetables in the object to be cleaned;

step 9, judging whether the health of the user is endangered according to the obtained health state of the fruits and vegetables: when the object to be cleaned is judged to have fruits and vegetables which are harmful to the health of the user, a fruit and vegetable replacement prompt is sent to the user to remind the user to replace the current fruits and vegetables and then clean the fruits and vegetables, and then the step 10 is carried out; otherwise, turning to 11;

step 10, judging and processing according to the feedback of the user to the fruit and vegetable replacement prompt: when the user does not continue to wash, turning to step 8; otherwise, if the user still does not replace the fruits and vegetables and insists on continuously cleaning the fruits and vegetables in the object to be cleaned, the step 11 is carried out;

step 11, when the object to be cleaned is judged to be a single variety of fruits and vegetables, namely the object to be cleaned is a single kind of fruits and vegetables, or the object to be cleaned is a plurality of fruits and vegetables, but the varieties of the fruits and vegetables are one, for example, all the fruits and vegetables are apples or all the celery, recommending the fruit and vegetable cleaning curve data which is positioned in a preset fruit and vegetable cleaning curve database and corresponds to the variety of fruits and vegetables to a user; otherwise, respectively calling fruit and vegetable cleaning curve data which are positioned in a preset fruit and vegetable cleaning curve database and correspond to various kinds of fruits and vegetables, and turning to the step 12; the fruit and vegetable cleaning curve data comprises water level data, cleaning time data and cleaning mode data corresponding to the fruit and vegetable cleaning curve;

step 12, when different cleaning mode data exist in all the called fruit and vegetable cleaning curve data, sending a prompt for separately cleaning the object to be cleaned to a user, and turning to step 13; otherwise, go to step 14;

step 13, receiving the selection feedback of the user for the separate cleaning prompt and executing the corresponding processing: when the user selects the separate cleaning, the step 11 is carried out; otherwise, if the user still insists on cleaning all kinds of fruits and vegetables in the object to be cleaned, the step 8 is carried out;

and step 14, respectively obtaining a water level mean value of water level data corresponding to each fruit and vegetable cleaning curve and a cleaning time mean value of cleaning time data corresponding to each fruit and vegetable cleaning curve, and recommending the fruit and vegetable cleaning curve formed by the obtained water level mean value and the cleaning time mean value to a user as an optimal fruit and vegetable cleaning curve for a current object to be cleaned.

Assuming that the object to be cleaned contains a fruit d and a vegetable e through identification and judgment; correspondingly, a fruit and vegetable cleaning curve D corresponding to the fruit D and a fruit and vegetable cleaning curve E corresponding to the vegetable E are called in a preset fruit and vegetable cleaning curve database;

the water level data corresponding to the fruit and vegetable cleaning curve D is L_DAnd the cleaning time data is t_D；

The water level data corresponding to the fruit and vegetable cleaning curve E is L_EAnd the cleaning time data is t_E；

Then, the water level data corresponding to the optimal fruit and vegetable cleaning curve recommended to the user is (L)_D+L_E) And/2, the cleaning time data corresponding to the optimal fruit and vegetable cleaning curve is (t)_D+t_E)/2；

Of course, in order to ensure the physical health of the user, as an improvement, step 14 of the present embodiment further includes: and (4) the health condition of the fruits and vegetables obtained in the step (8) is sent to the user again for prompting.

Referring to fig. 1, the present embodiment further provides a washing curve intelligent recommendation system for implementing the above washing curve intelligent recommendation method, where the washing curve intelligent recommendation system includes a dishwasher 1, a user terminal 2, and a processing terminal 3 that performs judgment and processing operations in the above washing curve intelligent recommendation method and provides a washing curve for the dishwasher, and the dishwasher 1 is connected to the user terminal 2 and the processing terminal 3 respectively. The dishwasher 1 can perform a washing job for the object to be washed according to the washing profile selected by the user (via the washing profile provided or recommended by the processing terminal). The dishwasher 1 in this embodiment is a water tank type dishwasher. The user terminal 2 may be a smartphone or a tablet computer.

Of course, the processing terminal 3 here may be provided as a remotely located cloud platform, which may be managed by the dishwasher manufacturer, for the purpose of managing the update of the washing curve. In addition, the treatment terminal 3 can be integrated on the dishwasher according to actual needs. It should be noted that the integrated dishwasher may be connected to a server managed by a dishwasher manufacturer as needed to update the preset washing curve database stored in the integrated dishwasher in time.