Dishwasher operation control method and device

Abstract

The present application belongs to the field of computer technology, and discloses a method and device for controlling the operation of a dishwasher, the method comprising: receiving a start instruction, obtaining the initial parameters of the dishwasher; the initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image, and pressure data of a pressure sensor disposed at the bottom of the dishwasher; inputting the initial parameters into an oil stain detection model to obtain an oil stain detection result; inputting the initial parameters into a sparseness detection model to obtain a sparseness detection result; receiving the user's mode selection information, determining the first objective function corresponding to the mode selection information; inputting the first objective function, the oil stain detection result, and the sparseness detection result into a cleaning parameter calculation model to obtain operating parameters; the operating parameters include target duration, target water temperature, and target water pressure; and controlling the dishwasher to work according to the operating parameters. The present application can ensure that the operating parameters meet the user's needs for the cleaning process, and improves the applicability and user experience.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an operation control method and device for a dishwasher. Background Art

[0002] With the development of smart homes, dishwashers can provide an increasingly convenient and comfortable dishwashing experience. Existing dishwashers provide a variety of operating modes for users to choose from, but the parameter ranges specified by different operating modes are usually fixed. For example, the duration of the accelerated washing mode must be less than 1 hour, and the water consumption of the energy-saving mode is fixed at 30 to 45 liters. Since there is an upper limit to the operating parameters of the dishwasher, the cleaning effects of different modes are not consistent for different degrees of dirtiness of dishes. For example, the dishes put into the dishwasher are very dirty, and the user chooses the accelerated washing mode. At this time, even if the water consumption and flushing water pressure are adjusted to the maximum value that the dishwasher can operate, it is difficult to clean them after 1 hour of washing. If the user chooses the energy-saving mode, there may still be a lot of oil residue left after using up 45 liters of water.

[0003] Therefore, the technical problem to be solved by the present application is that the existing dishwashers are limited by the fixed parameter range of the operating mode, and it is difficult to ensure a good cleaning effect when the dishes are heavily soiled. Summary of the invention

[0004] The present application provides an operation control method and device for a dishwasher, which can ensure that the dishwasher meets the user's requirements for the operation mode on the basis of achieving a cleaning effect, thereby improving the user experience.

[0005] In a first aspect, an embodiment of the present application provides an operation control method of a dishwasher, comprising:

[0006] Receive a start instruction and obtain initial parameters of the dishwasher; the initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image and pressure data of a pressure sensor disposed at the bottom of the dishwasher;

[0007] Input the initial parameters into the oil stain detection model to obtain the oil stain detection results of the tableware;

[0008] Input the initial parameters into the density detection model to obtain the density detection results of the tableware;

[0009] Receiving mode selection information from a user, and determining a first objective function corresponding to the mode selection information;

[0010] The first objective function, the oil pollution detection result and the density detection result are input into the cleaning parameter calculation model to obtain the operation parameters; wherein the operation parameters include the target duration, the target water temperature and the target water pressure;

[0011] The dishwasher is controlled to operate according to the operating parameters.

[0012] Furthermore, if the mode selection information is the energy-saving mode, the first objective function is the sum formula of the pressurization energy consumption and the heating energy consumption; if the mode selection information is the quick wash mode, the first objective function is the washing time calculation formula.

[0013] Furthermore, the method also includes:

[0014] The current water temperature of the temperature sensor disposed at the water inlet of the dishwasher is obtained; the current water temperature, the first objective function, the oil stain detection result, and the density detection result are input into the cleaning parameter calculation model to obtain the operating parameters.

[0015] Furthermore, the method also includes:

[0016] After the dishwasher is controlled to work, a cleaning image inside the dishwasher is obtained during each water discharge pause period;

[0017] Input the cleaned image into the oil stain detection model to obtain the corresponding oil stain residue result;

[0018] When the oil residue result is less than the preset residue threshold, the cleaning time is obtained according to the collection time of the cleaning image;

[0019] The dishwasher is controlled to stop working, and the cleaning time is taken as the target time, and is put into the operation database together with the mode selection information, oil stain detection results, density detection results, target water temperature and target water pressure.

[0020] Furthermore, the method also includes:

[0021] If the oil residue result obtained after the target running time is greater than or equal to the preset residue threshold, the dishwasher is controlled to continue to work according to the target water temperature and the target water pressure until the oil residue result is less than the preset residue threshold, and the delay time is recorded;

[0022] The sum of the target duration and the delay duration is taken as the target duration, and is put into the operation database together with the mode selection information, oil pollution detection results, density detection results, target water temperature and target water pressure.

[0023] Furthermore, the method also includes:

[0024] If the mode selection information is the quick wash mode, after the dishwasher stops working, the cleaning rate corresponding to the density detection result is calculated according to the oil stain detection result and the target time;

[0025] Determine whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database;

[0026] If so, the cleaning rate is put into the operation database as the fastest cleaning rate of the density detection result.

[0027] Furthermore, the method also includes: after receiving the mode selection information of the quick wash mode, determining whether there is a density detection result in the operation database; if so, directly obtaining the target water temperature and target water pressure corresponding to the density detection result, and calculating the target time according to the oil detection result and the fastest cleaning rate.

[0028] Furthermore, the method also includes:

[0029] The cleaning parameter calculation model is trained using the running database according to the preset cycle.

[0030] Furthermore, the cleaning parameter calculation model is a MOPSO algorithm model; the first objective function, the oil pollution detection result and the density detection result are input into the cleaning parameter calculation model to obtain the operating parameters, including:

[0031] Construct the second objective function of cleaning water temperature, cleaning water pressure, cleaning time, density and oil pollution degree;

[0032] Determine the model parameters of the MOPSO algorithm model and initialize the number of iterations; the model parameters include the maximum number of population iterations, acceleration factor, iteration weight factor and mapping iteration number;

[0033] Construct the initial population and the initial position of each particle in the initial population based on chaos theory;

[0034] The second objective function is used to calculate the second fitness of each particle;

[0035] The particles whose second fitness is smaller than the oil pollution detection result are taken as target particles;

[0036] Randomly generate the initial speed of each target particle within a preset speed range;

[0037] Optimization step: Optimize each target particle based on the acceleration factor and the iterative weight factor;

[0038] The first objective function is used to calculate the first fitness of each target particle;

[0039] Determine whether the minimum first fitness is less than the first fitness of the optimal particle in the previous iteration;

[0040] If so, the target particle corresponding to the smallest first fitness is taken as the optimal particle;

[0041] Let the number of iterations increase by 1, and determine whether the number of iterations is greater than the maximum number of iterations of the population;

[0042] If yes, the position of the optimal particle is used as the operating parameter; otherwise, return to the optimization step.

[0043] Furthermore, the initial population and the initial position of each particle in the initial population are constructed based on chaos theory, including:

[0044] Generate a preset number of random numbers within a preset random range;

[0045] Iterate each random number based on the Logistic mapping equation and the number of mapping iterations to obtain a preset number of particles;

[0046] Map each particle to the value range corresponding to the dishwasher calibration parameter to obtain the initial position of each particle.

[0047] Furthermore, the method also includes: after obtaining the initial parameters, inputting them into an image recognition model to determine whether there are items that do not belong to the preset dishwashing items; if so, generating foreign object prompt information.

[0048] Furthermore, the method also includes:

[0049] When the oil residue result is less than the preset residue threshold, the target duration is added to the cumulative cleaning duration;

[0050] Determine whether the cumulative cleaning time exceeds the preset maintenance threshold;

[0051] If it exceeds, a maintenance reminder message will be generated, and after receiving the maintenance instruction, the accumulated cleaning time will be cleared.

[0052] Furthermore, the method also includes:

[0053] During the operation of the dishwasher, the water level value of the water level monitor inside the dishwasher is obtained in real time;

[0054] Determine whether the water level value exceeds the preset drainage threshold; if so, generate a drainage fault prompt message.

[0055] Furthermore, the preset residual threshold, the preset maintenance threshold, the preset drainage threshold and the preset cycle are all adjustable.

[0056] In a second aspect, an embodiment of the present application provides an operation control device for a dishwasher, comprising:

[0057] An image acquisition module, used to receive a start instruction and obtain initial parameters of the dishwasher;

[0058] The initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image, and pressure data of a pressure sensor disposed at the bottom of the dishwasher;

[0059] The first detection module is used to input the initial parameters into the oil stain detection model to obtain the oil stain detection result of the tableware;

[0060] The second detection module is used to input the initial parameters into the density detection model to obtain the density detection result of the tableware;

[0061] A selection module, configured to receive mode selection information from a user and determine a first objective function corresponding to the mode selection information;

[0062] A calculation module, used to input the first objective function, the oil pollution detection result and the density detection result into a cleaning parameter calculation model to obtain operation parameters; wherein the operation parameters include target duration, target water temperature and target water pressure;

[0063] The control module is used to control the operation of the dishwasher according to operating parameters.

[0064] Furthermore, the device also includes:

[0065] A real-time acquisition module is used to obtain cleaning images inside the dishwasher during each water-discharging pause period;

[0066] The residue detection module is used to input the cleaning image into the oil stain detection model to obtain the corresponding oil stain residue result;

[0067] The duration update module is used to obtain the cleaning duration according to the acquisition time of the cleaning image when the oil residue result is less than the preset residue threshold; control the dishwasher to stop working, and use the cleaning duration as the target duration, and put it into the operation database together with the mode selection information, oil residue detection results, density detection results, target water temperature and target water pressure.

[0068] Furthermore, the device also includes:

[0069] A delay module is used to control the dishwasher to continue to work according to the target water temperature and the target water pressure, if the oil residue result is greater than or equal to the preset residue threshold after the target running time, until the oil residue result is less than the preset residue threshold, and record the delay time;

[0070] The storage module is used to take the sum of the target duration and the delay duration as the target duration, and put it into the operation database together with the mode selection information, the oil pollution detection result, the density detection result, the target water temperature and the target water pressure.

[0071] Furthermore, the device also includes:

[0072] A rate calculation module, used to calculate the cleaning rate corresponding to the density detection result according to the oil stain detection result and the target time after the dishwasher stops working when the mode selection information is the quick wash mode;

[0073] The rate update module is used to determine whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database; and when the cleaning rate is greater than the fastest cleaning rate, the cleaning rate is put into the operation database as the fastest cleaning rate of the density detection result.

[0074] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of a dishwasher operation control method as in any of the above embodiments are performed.

[0075] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of a method for controlling operation of a dishwasher as in any of the above embodiments are implemented.

[0076] In summary, compared with the prior art, the technical solution provided in the embodiment of the present application has at least the following beneficial effects:

[0077] The embodiment of the present application provides an operation control method for a dishwasher, which firstly collects initial parameters to identify and detect the oil stain level and density of tableware in the dishwasher, and then uses the user's mode selection information as the first objective function of the cleaning parameter calculation model to calculate the operation parameters required to clean the tableware under the conditions of the density detection results and the oil stain detection results. The above method solves the problem that the dishwasher of the prior art is limited to the fixed parameter range of the mode, resulting in unstable cleaning effect. By using the mode selection information as the first objective function to analyze the oil stain detection results and the density detection results, it can meet the user's requirements for cleaning energy consumption or cleaning efficiency as much as possible on the basis of achieving the cleaning of dishes and chopsticks, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 A flowchart of an operation control method of a dishwasher is provided as an exemplary embodiment of the present application.

[0079] Figure 2 A flow chart of cleaning process monitoring steps provided for an exemplary embodiment of the present application.

[0080] Figure 3 A flowchart of the cleaning rate calculation steps in the quick wash mode is provided for an exemplary embodiment of the present application.

[0081] Figure 4 A flowchart of dishwasher maintenance determination steps provided for an exemplary embodiment of the present application.

[0082] Figure 5 A structural diagram of an operation control device of a dishwasher provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0083] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0084] Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of this application.

[0085] See also Figure 1 , the embodiment of the present application provides an operation control method of a dishwasher, comprising:

[0086] Step S11, receiving a start instruction and obtaining initial parameters of the dishwasher; the initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image and pressure data of a pressure sensor disposed at the bottom of the dishwasher.

[0087] Among them, in addition to receiving the start command through the button on the dishwasher, it can also be remotely received through the communication module of the dishwasher. The first phase angle image, the second phase angle image, the third phase angle image and the fourth phase angle image are respectively obtained by four camera modules arranged on the inner wall of the dishwasher. The four camera modules can be respectively arranged at the four vertex corners of the inner wall of the dishwasher, or at the center points of the remaining four surfaces except the dishwasher door and the surface corresponding to the dishwasher door.

[0088] Further, after obtaining the pressure data of the pressure sensor disposed at the bottom of the dishwasher, it is determined whether the pressure data is greater than 0 and less than a preset pressure threshold; if so, step S12 is performed. This ensures that there are an appropriate number of dishes to be washed in the four acquired phase angle images, thereby avoiding the user from accidentally touching the start button and causing an error in starting.

[0089] Step S12, inputting the initial parameters into the oil stain detection model to obtain the oil stain detection result of the tableware.

[0090] The oil pollution detection result may be the area ratio covered by the oil pollution or the weight of the oil pollution.

[0091] Specifically, the oil pollution detection model can use the Long Short-Term Memory (LSTM) network. The training method of the LSTM network model is similar to that of the traditional RNN. Both use the back-propagation algorithm. In the back-propagation algorithm, the gradient of the loss function to the network parameters needs to be calculated. However, due to the presence of gated units in the LSTM network model, the calculation of the gradient is relatively complicated. In order to solve this problem, the back-propagation weighted method can be used. The core idea of ​​back-propagation weighted is to multiply the gradient of the gated unit by a weight so that it contributes more to the gradient. Specifically, the output of the gated unit can be multiplied by the input of the gated unit to obtain a weight, which can be multiplied by the gradient of the gated unit.

[0092] Step S13, inputting the initial parameters into the density detection model to obtain the density detection result of the tableware.

[0093] The density detection result may specifically be the density of bowls and chopsticks per unit area or the proportion of the bowls and chopsticks area.

[0094] Specifically, the density detection model can also be obtained by training the long short-term memory network LSTM mentioned above. The density detection model is used to detect the density of the tableware in the reference image. In the prior art, the density of the tableware inside the dishwasher is usually determined by calculating the area ratio or volume ratio. However, for a dishwasher, even if there are only a few small dishes, if they are placed closely in a corner of the dishwasher, it will still affect the cleaning effect. Therefore, the present application uses a trained density detection model to detect the density of the tableware, which can ensure the accuracy of the density detection results.

[0095] By acquiring images at four different phase angles, the present application can ensure that the oil stain detection model and the density detection model can fully identify and detect each tableware placed in the dishwasher, thereby improving the accuracy of the oil stain detection results and the density detection results.

[0096] Step S14, receiving the mode selection information of the user, and determining the first objective function corresponding to the mode selection information.

[0097] Specifically, if the mode selection information is the energy-saving mode, the first objective function is the sum formula of the pressurization energy consumption and the heating energy consumption; if the mode selection information is the quick wash mode, the first objective function is the washing time calculation formula.

[0098] When the first objective function is the cleaning time calculation formula:

[0099]

[0100] Among them, S is the oil pollution detection result; R is the preset residual threshold, the unit is the same as S; W is the target water temperature, the unit is Celsius; P is the target water pressure, the unit is Pascal; D is the density detection result. is the weight coefficient.

[0101] Step S15, inputting the first objective function, the oil pollution detection result and the density detection result into the cleaning parameter calculation model to obtain the operation parameters; wherein the operation parameters include the target duration, the target water temperature and the target water pressure.

[0102] Step S16, controlling the dishwasher to operate according to the operating parameters.

[0103] The above embodiment provides an operation control method for a dishwasher, which first identifies and detects the oiliness and density of the dishes in the dishwasher by collecting initial parameters, and then uses the user's mode selection information as the first objective function of the cleaning parameter calculation model to calculate the operation parameters required to clean the dishes under the conditions of the density detection results and the oiliness detection results. The above method solves the problem that the dishwasher of the prior art is limited by the fixed parameter range of the mode, resulting in unstable cleaning effects. By using the mode selection information as the first objective function to analyze the oiliness detection results and the density detection results, it is possible to meet the user's requirements for cleaning energy consumption or cleaning efficiency as much as possible on the basis of achieving dishwashing, thereby improving the user experience.

[0104] In some embodiments, the present application may also add water quality test results to the input data of the cleaning parameter calculation model. Since the performance and effect of the dishwasher under different water quality conditions are different: the mineral reserves in hard water may affect the efficiency and cleaning power of the dishwasher, while soft water can better solve these problems. Therefore, the present application obtains the water quality test results of hard water or soft water through a sensor installed at the water outlet of the dishwasher, and inputs it together with the oil detection results and the density detection results into the cleaning parameter calculation model, so that the model generates operating parameters according to different water qualities and cleaning objects.

[0105] The above embodiment further adds water quality detection results in the process of calculating the operating parameters, fully considering the different effects of different water qualities on cleaning oil pollution, and improving the calculation accuracy of the operating parameters.

[0106] In one embodiment, the method further includes: obtaining the current water temperature of a temperature sensor disposed at the water inlet of the dishwasher; inputting the current water temperature and the first objective function, the oil stain detection result, and the density detection result into a cleaning parameter calculation model to obtain operating parameters.

[0107] Specifically, the role of the current water temperature in the cleaning parameter calculation model is reflected in the first objective function: when the mode selection information is energy-saving mode, if the current water temperature is not measured, the cleaning parameter calculation model will intelligently select the room temperature and the target water temperature to calculate the heating energy consumption. However, due to the different specific heat capacities of water and air, the room temperature cannot accurately reflect the water temperature of the water flow received by the dishwasher. Therefore, the present application can use a temperature sensor to measure the current water temperature of the water inlet in real time to ensure accurate calculation of the heating energy consumption and improve the accuracy of operating parameters under the energy-saving model.

[0108] See also Figure 2 In some embodiments, the method further comprises:

[0109] Step S21, after controlling the dishwasher to operate, a cleaning image inside the dishwasher is obtained during each water output pause period.

[0110] Among them, the time for acquiring the cleaning image can be selected at the middle moment corresponding to the water output suspension period. The cleaning image also includes 4 images with different phase angles to ensure accurate identification of oil residue results and prevent cleaning dead corners due to the special shape of tableware.

[0111] Step S22, inputting the cleaning image into the oil stain detection model to obtain the corresponding oil stain residue result.

[0112] Step S23, when the oil residue result is less than the preset residue threshold, the cleaning time is obtained according to the acquisition time of the cleaning image.

[0113] In actual applications, the detection standard for dishwashers is usually that the oil residue is less than 2%, so 2% can be used as the preset residue threshold.

[0114] Step S24, control the dishwasher to stop working, and set the cleaning time as the target time, and put it into the operation database together with the mode selection information, oil stain detection results, density detection results, target water temperature and target water pressure.

[0115] Furthermore, the present application can use the running database to train the cleaning parameter calculation model according to the preset period, so that the cleaning parameter training model can adapt to the current user's dishwasher usage habits and the type of detergent. The preset period is adjustable.

[0116] Specifically, due to the different degrees of condensation of oil stains on the tableware and the changes in the types of detergents added by the user, the operating parameters output by the cleaning parameter calculation model cannot guarantee 100% accuracy. Therefore, the present application further adds detection and judgment of oil residue results during the cleaning process; if the tableware is cleaned before the target time is reached, the cleaning can be ended early, and the target time can be updated based on the actual cleaning time and put into the operating database for feedback to the cleaning parameter calculation model.

[0117] In the specific implementation process, for example, the operating parameters output by the cleaning parameter calculation model are: target water temperature 40°C, target water pressure 0.45Mpa, and target duration 60 minutes; when the dishwasher performs cleaning according to the operating parameters, the water output pause period is from the 10th minute to the 12th minute, from the 30th minute to the 32nd minute, and from the 44th minute to the 46th minute after the start of cleaning; then the first cleaning image inside the dishwasher can be captured at the 11th minute, and the oil residue result of the first cleaning image can be obtained through the oil detection model. If the oil residue result of the first cleaning image is greater than or equal to the preset residue threshold, the dishwasher continues to be controlled according to the operating parameters until the second cleaning image inside the dishwasher is captured at the 31st minute. The oil stain detection model is used to obtain the oil stain residue result of the second washing image. If the oil stain residue result of the second washing image is still greater than or equal to the preset residue threshold, the dishwasher is continued to be controlled according to the operating parameters until the third washing image inside the dishwasher is captured at the 45th minute, and the oil stain residue result of the third washing image is obtained through the oil stain detection model. If the oil stain residue result of the third washing image is less than the preset residue threshold, the 60 minutes initially calculated is replaced by 45 minutes, that is, the target duration is 45 minutes, and the oil stain detection result of the reference image, the density detection result, the mode selection information corresponding to the mode selection information, the target water temperature of 40°C and the target water pressure of 0.45 MPa are put into the operation database.

[0118] Furthermore, the method further comprises:

[0119] Step S31: If the oil residue result obtained after the target operation time is greater than or equal to the preset residue threshold, the dishwasher is controlled to continue to work according to the target water temperature and the target water pressure until the oil residue result is less than the preset residue threshold, and the delay time is recorded. Specifically, the different degrees of condensation of oil on the tableware and the changes in the type of detergent added by the user may also cause the target time to be insufficient to clean the tableware, and the delay time needs to be further increased. In this case, the target time will be updated according to the delay time, and then the operation database will be updated to ensure that the operation database can store the operation parameters of each tableware state.

[0120] Step S32, taking the sum of the target duration and the delay duration as the target duration, and putting it into the operation database together with the mode selection information, the oil pollution detection result, the density detection result, the target water temperature and the target water pressure.

[0121] Similarly, in the specific implementation process, for example, the operating parameters output by the cleaning parameter calculation model are: target water temperature 40°C, target water pressure 0.45Mpa, and target duration 60 minutes; when the dishwasher performs cleaning according to the operating parameters, if the first cleaning image is taken at the 11th minute, the second cleaning image is taken at the 31st minute, and the third cleaning image inside the dishwasher is taken at the 45th minute, and the oil residue results of the three cleaning images are all greater than or equal to the preset residue threshold, then after the 60-minute cleaning operation is completed, the fourth cleaning image is obtained.

[0122] If the oil residue result of the fourth cleaning image is less than the preset residue threshold, the target duration remains unchanged; if the oil residue result of the fourth cleaning image is greater than or equal to the preset residue threshold, the dishwasher continues to be operated at the target water temperature and target water pressure, and the water is stopped every 5 minutes to obtain the cleaning image, and the oil residue result is calculated again until the oil residue result is less than the preset residue threshold. At this time, the cleaning image corresponding to the calculated oil residue result is the one obtained in the third 5 minutes, that is, the delay time is 15 minutes, so the target duration = 60 minutes + 15 minutes = 75 minutes, and 75 minutes are put into the operation database together with the oil detection result, density detection result, mode selection information, water temperature of 40°C and water pressure of 0.45Mpa of the reference image.

[0123] The above-mentioned embodiment improves the data accuracy of the operation database by detecting the residual oil level during the cleaning process, adapts to the user's usage habits, and avoids the waste of water resources, reducing water consumption and cleaning time.

[0124] See also Figure 3 In some embodiments, the method further comprises:

[0125] Step S41, if the mode selection information is the quick wash mode, then after the dishwasher stops working, the cleaning rate corresponding to the density detection result is calculated according to the oil stain detection result and the target time.

[0126] Specifically, the oil pollution detection result is divided by the target time to obtain the cleaning rate corresponding to the density detection result.

[0127] Step S42, determining whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database.

[0128] Step S43: If yes, the cleaning rate is put into the operation database as the fastest cleaning rate of the density detection result.

[0129] Furthermore, the method also includes: after receiving the mode selection information of the quick wash mode, determining whether there is a density detection result in the operation database; if so, directly obtaining the target water temperature and target water pressure corresponding to the density detection result, and calculating the target time according to the oil detection result and the fastest cleaning rate.

[0130] Specifically, when the user selects the quick wash mode, the present application can determine whether the fastest operating parameters for washing the dishes this time are already stored in the operating database before running the cleaning parameter calculation model. If so, they can be directly selected, thereby saving the time for model calculation; further, after each direct selection of the parameters in the operating database, the number of selections is recorded. After reaching the preset selection threshold, the next time the user selects the quick wash mode, the cleaning parameter calculation model must be used to calculate the operating parameters, thereby ensuring the dynamic update of the operating parameters of the quick wash mode in the operating database.

[0131] In the specific implementation process, the preset selection threshold can be set to 5 times, that is, the parameters of the operating database are directly selected at most 5 times, and then it is necessary to continue to apply the cleaning parameter calculation model to calculate and update the operating parameters.

[0132] The above-mentioned embodiment realizes the rapid determination of the operating parameters of the quick wash mode by recording the cleaning rate in the quick wash mode, reduces the model calculation time required for the quick wash mode, and further shortens the cleaning time of the dishwasher.

[0133] In some embodiments, the cleaning parameter calculation model is a MOPSO algorithm model; the first objective function, the oil pollution detection result and the density detection result are input into the cleaning parameter calculation model to obtain the operating parameters, including:

[0134] Step S151, constructing a second objective function of washing water temperature, washing water pressure, washing time, density and oil pollution degree.

[0135] Specifically, the degree of oil pollution is the left value, and the cleaning water temperature, cleaning water pressure, cleaning time and density are the right values:

[0136]

[0137] Where N is the number of tableware, is the degree of oil pollution; T is the cleaning time, W is the cleaning temperature, and P is the cleaning water pressure; D is the density, which is the density detection result during model calculation; is the oil adhesion parameter corresponding to the nth tableware material, which is the known data measured previously. , and is the weight coefficient, It is the water quality solubility parameter, which is determined by the water quality test results. When the water quality test result is hard water, the water quality solubility parameter =1.239, when the water quality test result is soft water, the water quality solubility parameter =1.562; Here, only two water quality solubility parameters are given based on the two water quality test results. In fact, the water quality test results can be more detailed, and the particle size of the corresponding water quality solubility parameters can also change accordingly.

[0138] Step S152, determine the model parameters of the MOPSO algorithm model and initialize the number of iterations; the model parameters include the maximum number of population iterations, the acceleration factor, the iteration weight factor and the mapping iteration number.

[0139] The initial number of iterations is 0, and it increases by 1 for each subsequent iteration.

[0140] Specifically, since there is more than one objective function when calculating the operating parameters in the present application, the MOPSO multi-objective particle swarm algorithm is used to calculate the optimal particles that can simultaneously satisfy each objective function.

[0141] Step S153, constructing an initial population and an initial position of each particle in the initial population based on chaos theory.

[0142] Specifically, the above construction of the initial population and the initial position of each particle in the initial population based on chaos theory includes:

[0143] Step S1531, generating a preset number of random numbers within a preset random range, wherein the preset random range may be 0-1.

[0144] Step S1532, iterating each random number based on the Logistic mapping equation and the number of mapping iterations to obtain a preset number of particles.

[0145] Among them, the Logistic mapping equation is: , m is the number of mapping iterations, is a random number, is a fixed chaotic parameter. When it iterates to the mapping iteration number, a chaotic sequence corresponding to the random number is generated. 1 , a 2 , …, a m}, and take the chaotic sequence as the particle corresponding to the random number.

[0146] Furthermore, the number of mapping iterations depends on the number of variables required by the model. For example, in the present application, the variables required are operating parameters, including water temperature, water pressure and duration, so the number of mapping iterations here is m=3.

[0147] Step S1533, mapping each particle to a value range corresponding to the calibration parameter of the dishwasher to obtain the initial position of each particle.

[0148] Among them, the dishwasher calibration parameters are the maximum and minimum values ​​that each operating parameter of the dishwasher can reach.

[0149] Specifically, the mapping process is: , where [s, t] is the value interval, X is the particle, and Y is the initial position. The position of the particle is the running parameter, so the mapping here needs to be executed the number of times the number of parameters in the running parameter.

[0150] Step S154, using the second objective function to calculate the second fitness of each particle.

[0151] Step S155: taking particles whose second fitness is smaller than the oil pollution detection result as target particles.

[0152] Specifically, step S154 is to substitute the position of each particle, that is, the operating parameter, into the second objective function, and the obtained value is used as the second fitness of the particle; if the second fitness is greater than or equal to the oil pollution detection result, it is used as the target particle.

[0153] Step S156, randomly generating an initial velocity of each target particle within a preset velocity range.

[0154] Step S157, optimization step: optimizing each target particle based on the acceleration factor and the iteration weight factor.

[0155]

[0156] in, , , and is the acceleration factor, which takes a random value between 0 and 1; w is the iteration weight factor, q is the number of iterations, pbest is the optimal solution for each particle, and gbest is the optimal solution in the entire population. is the velocity of the ith particle, is the position of the ith particle. The MOPSO algorithm used in this application has the advantages of fewer parameter settings and faster convergence speed.

[0157] Step S158, using the first objective function to calculate the first fitness of each target particle.

[0158] Step S159, determining whether the minimum first fitness is less than the first fitness of the optimal particle in the previous iteration; if so, taking the target particle corresponding to the minimum first fitness as the optimal particle.

[0159] Specifically, after optimization, the performance of the operating parameters corresponding to each particle in the first objective function is determined, and the target particle with the smallest first fitness, that is, the target particle that best meets the mode selection information, is selected for comparison and iteration with the last optimal particle.

[0160] Step S160, add 1 to the number of iterations to determine whether the number of iterations is greater than the maximum number of iterations of the population; if so, use the position of the optimal particle as the operating parameter; otherwise, return to the optimization step, i.e., step S157.

[0161] Among them, the maximum number of population iterations can be adjusted; the larger the maximum number of population iterations, the better the calculation result, but the more calculation time and required computing resources, the smaller the maximum number of population iterations, the less calculation time and required computing resources, but the calculation result is not as good as the calculation result corresponding to the larger maximum number of population iterations.

[0162] The above embodiment can simultaneously satisfy multiple objective functions based on the MOPSO algorithm model, thereby ensuring that the output operating parameters can take into account both the cleaning effect and the mode selection information, while also improving the accuracy and speed of the operating parameter calculation.

[0163] In some embodiments, the method further includes: after obtaining the initial parameters, inputting them into an image recognition model to determine whether there are items that do not belong to the preset dishwashing dishes; if so, generating foreign object prompt information.

[0164] The input image recognition model is specifically images of 4 different phase angles in the initial parameters.

[0165] Specifically, the preset dishwashing dishes are the types of dishwashing that can be washed by the dishwasher. If the user puts in items that cannot be washed by the dishwasher, not only will the items be damaged, but the dishwasher may also be damaged. Therefore, after obtaining the reference image, the present application further uses an image recognition model to identify the type of items in the image to avoid accidents.

[0166] See also Figure 4 In some embodiments, the method further comprises:

[0167] Step S51, when the oil residue result is less than the preset residue threshold, the target duration is added to the accumulated cleaning duration.

[0168] The target duration here refers to the target duration updated according to the cleaning duration or the delay duration.

[0169] Step S52, determining whether the accumulated cleaning time exceeds a preset maintenance threshold.

[0170] Step S53: if exceeded, a maintenance reminder message is generated, and after receiving the maintenance instruction, the accumulated cleaning time is cleared.

[0171] Among them, the preset maintenance threshold of the cumulative cleaning time can be 100 hours.

[0172] Specifically, when a dishwasher is operated for a long time, its internal mechanical components will inevitably produce some wear and tear. Therefore, this application accumulates the target time after each cleaning of the dishwasher, and prompts the user to maintain it after exceeding a certain threshold. After the user reports that the maintenance has been completed, the cleaning time is accumulated again.

[0173] In the specific implementation process, it is assumed that the target duration in the operating parameters output by the cleaning parameter calculation model is 60 minutes; when the dishwasher performs cleaning according to the operating parameters, the water output pause period is from the 10th minute to the 12th minute, from the 30th minute to the 32nd minute, and from the 44th minute to the 46th minute after the start of cleaning; if the first cleaning image taken at the 11th minute, the second cleaning image taken at the 31st minute, the third cleaning image inside the dishwasher taken at the 45th minute, and the fourth cleaning image taken after the 60-minute cleaning operation, the oil residue results of the four cleaning images are greater than or equal to the preset residue threshold, then continue to operate according to the target water temperature and target The dishwasher is operated by water pressure, and the water is stopped every 5 minutes to obtain the cleaning image. The oil residue result is calculated again until the oil residue result is less than the preset residue threshold. At this time, the calculation delay time is 15 minutes, so the target time = 60 minutes + 15 minutes = 75 minutes. 75 minutes is converted to 1.25 hours and added to the cumulative cleaning time, and the cumulative cleaning time is 100.25 hours. If it is greater than 100 hours, the electronic screen on the dishwasher will display "The cumulative use time is too long and maintenance is required as soon as possible". After the user maintains the dishwasher, click the corresponding button on the dishwasher, it is judged that the dishwasher maintenance has been completed, and the cumulative cleaning time is cleared from 100.25 hours to 0 hours, and accumulated again.

[0174] In some embodiments, the method further comprises:

[0175] Step S61, during the operation of the dishwasher, the water level value of the water level monitor inside the dishwasher is obtained in real time.

[0176] Step S62, determining whether the water level value exceeds a preset drainage threshold; if so, generating drainage fault prompt information.

[0177] Furthermore, after the drainage fault prompt information is generated, the operation of the dishwasher is stopped.

[0178] Specifically, when the dishwasher is actually used, due to the user's negligence in operation, it is very easy for food residues to remain on the dishes placed in the dishwasher, which will lead to blockage of the water outlet pipe. The sewage after cleaning cannot be discharged in time, and further overflows from the dishwasher to wet the ground, causing trouble to the user; therefore, the present application adds a drainage fault monitoring function, which monitors the internal water level value in real time during the operation of the dishwasher, and closes the water outlet pipe in time when a drainage fault occurs and reminds the user to handle it.

[0179] In the specific implementation process, some larger volumes of condensed grease or wet garbage may cause a temporary blockage in the drain. However, as the water level inside the dishwasher increases, the water pressure at the drain increases and the wet garbage will be flushed down. Therefore, the timing can be started when it is detected that the water level exceeds the preset drainage threshold. When the timing reaches the preset alarm duration, it means that the increase in water pressure cannot clear the drain, and an alarm prompt for drainage failure will be issued at this time.

[0180] It is worth noting that the preset residual threshold, preset maintenance threshold, preset drainage threshold and preset cycle in the above embodiments are all adjustable; but they cannot exceed the corresponding safe adjustment range.

[0181] See also Figure 5 Another embodiment of the present application provides an operation control device for a dishwasher, comprising:

[0182] The image acquisition module 101 is used to receive a start instruction and acquire initial parameters of the dishwasher.

[0183] The initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image and pressure data of a pressure sensor disposed at the bottom of the dishwasher.

[0184] The first detection module 102 is used to input the initial parameters into the oil stain detection model to obtain the oil stain detection result of the tableware.

[0185] The second detection module 103 is used to input the initial parameters into the density detection model to obtain the density detection result of the tableware.

[0186] The selection module 104 is configured to receive mode selection information from a user and determine a first objective function corresponding to the mode selection information.

[0187] The calculation module 105 is used to input the first objective function, the oil pollution detection result and the density detection result into the cleaning parameter calculation model to obtain the operation parameters; wherein the operation parameters include the target duration, the target water temperature and the target water pressure.

[0188] The control module 106 is used to control the operation of the dishwasher according to the operating parameters.

[0189] In some embodiments, the apparatus further comprises:

[0190] The real-time acquisition module is used to control the operation of the dishwasher and obtain the cleaning images inside the dishwasher during each water output pause period.

[0191] The residue detection module is used to input the cleaning image into the oil stain detection model to obtain the corresponding oil stain residue result.

[0192] The duration update module is used to obtain the cleaning duration according to the acquisition time of the cleaning image when the oil residue result is less than the preset residue threshold; control the dishwasher to stop working, and use the cleaning duration as the target duration, and put it into the operation database together with the mode selection information, oil residue detection results, density detection results, target water temperature and target water pressure.

[0193] In some embodiments, the apparatus further comprises:

[0194] The delay module is used to control the dishwasher to continue working according to the target water temperature and target water pressure after running for the target time, if the oil residue result is greater than or equal to the preset residue threshold, until the oil residue result is less than the preset residue threshold, and record the delay time.

[0195] The storage module is used to take the sum of the target duration and the delay duration as the target duration, and put it into the operation database together with the mode selection information, the oil pollution detection result, the density detection result, the target water temperature and the target water pressure.

[0196] In some embodiments, the apparatus further comprises:

[0197] The rate calculation module is used to calculate the cleaning rate corresponding to the density detection result according to the oil stain detection result and the target time when the mode selection information is the quick wash mode and after the dishwasher stops working.

[0198] The rate update module is used to determine whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database; and when the cleaning rate is greater than the fastest cleaning rate, the cleaning rate is put into the operation database as the fastest cleaning rate of the density detection result.

[0199] In some embodiments, the apparatus further comprises:

[0200] The parameter query module is used to determine whether there are density detection results in the operation database after receiving the mode selection information of the quick wash mode; if so, directly obtain the target water temperature and target water pressure corresponding to the density detection result, and calculate the target time according to the oil detection result and the fastest cleaning rate.

[0201] In some embodiments, the apparatus further comprises:

[0202] The periodic training module is used to train the cleaning parameter calculation model using the running database according to a preset period.

[0203] In some embodiments, the apparatus further comprises:

[0204] The image recognition module is used to input the initial parameters into the image recognition model after obtaining them, and determine whether there are any items that do not belong to the preset dishwashing dishes; if so, generate foreign body prompt information.

[0205] In some embodiments, the apparatus further comprises:

[0206] The duration accumulation module is used to add the target duration to the cumulative cleaning duration when the oil residue result is less than the preset residue threshold.

[0207] The maintenance judgment module is used to judge whether the cumulative cleaning time exceeds the preset maintenance threshold.

[0208] The maintenance reminder module is used to generate maintenance reminder information and clear the accumulated cleaning time after receiving the maintenance instruction.

[0209] In some embodiments, the apparatus further comprises:

[0210] The monitoring module is used to obtain the water level value of the water level monitor inside the dishwasher in real time during the operation of the dishwasher.

[0211] The fault prompt module is used to generate drainage fault prompt information when it is determined that the water level height value exceeds a preset drainage threshold.

[0212] The specific definition of the operation control device of a dishwasher provided in this embodiment can be found in the embodiment of the operation control method of a dishwasher described above, and will not be repeated here. Each module in the operation control device of the dishwasher described above can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0213] The embodiment of the present application provides a computer device, which may include a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the processor executes the steps of a method for controlling the operation of a dishwasher as in any of the above embodiments.

[0214] The working process, working details and technical effects of the computer device provided in this embodiment can be found in the above embodiment of a dishwasher operation control method, which will not be described in detail here.

[0215] The embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for controlling the operation of a dishwasher as in any of the above embodiments are implemented. The computer-readable storage medium refers to a carrier for storing data, which may include but is not limited to a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive and / or a memory stick, etc. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The working process, working details and technical effects of the computer-readable storage medium provided in this embodiment can be found in the above embodiment of a method for controlling the operation of a dishwasher, and will not be repeated here.

[0216] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0217] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0218] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for controlling the operation of a dishwasher, characterized in that: include: receiving a start instruction and acquiring initial parameters of the dishwasher; the initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image and pressure data of a pressure sensor disposed at the bottom of the dishwasher; Inputting the initial parameters into the oil stain detection model to obtain the oil stain detection result of the tableware; Inputting the initial parameters into a density detection model to obtain a density detection result of tableware; Receiving mode selection information from a user, and determining a first objective function corresponding to the mode selection information; Inputting the first objective function, the oil stain detection result and the density detection result into a cleaning parameter calculation model to obtain operating parameters; wherein the operating parameters include target duration, target water temperature and target water pressure; wherein the cleaning parameter calculation model is a MOPSO algorithm model; the inputting the first objective function, the oil stain detection result and the density detection result into the cleaning parameter calculation model to obtain operating parameters includes: Construct a second objective function of washing water temperature, washing water pressure, washing time, density and oil pollution degree; determine the model parameters of the MOPSO algorithm model and initialize the number of iterations; the model parameters include the maximum number of iterations of the population, acceleration factor, iteration weight factor and mapping iteration number; construct an initial population and the initial position of each particle in the initial population based on chaos theory; use the second objective function to calculate the second fitness of each particle; take the particles whose second fitness is less than the oil pollution detection result as target particles; randomly generate the initial speed of each target particle within a preset speed range; optimization step: optimize each target particle based on the acceleration factor and the iteration weight factor; use the first objective function to calculate the first fitness of each target particle; determine whether the minimum first fitness is less than the first fitness of the optimal particle of the previous iteration; if so, take the target particle corresponding to the minimum first fitness as the optimal particle; let the number of iterations increase by 1, and determine whether the number of iterations is greater than the maximum number of iterations of the population; if so, take the position of the optimal particle as the operating parameter; otherwise return to the optimization step; The dishwasher is controlled to operate according to the operating parameters.

2. The operation control method of the dishwasher according to claim 1, characterized in that: If the mode selection information is the energy-saving mode, the first objective function is a summation formula of pressurizing energy consumption and heating energy consumption; If the mode selection information is the quick wash mode, the first objective function is a washing time calculation formula.

3. The operation control method of the dishwasher according to claim 1, characterized in that: Also includes: Obtain the current water temperature of the temperature sensor located at the water inlet of the dishwasher; The current water temperature, the first objective function, the oil pollution detection result, and the density detection result are input into a cleaning parameter calculation model to obtain the operating parameters.

4. The operation control method of the dishwasher according to claim 2, characterized in that: Also includes: After controlling the dishwasher to operate, obtaining a cleaning image inside the dishwasher during each water output pause period; Inputting the cleaning image into the oil stain detection model to obtain the corresponding oil stain residue result; When the oil residue result is less than a preset residue threshold, the cleaning time is obtained according to the acquisition time of the cleaning image; The dishwasher is controlled to stop working, and the cleaning time is taken as the target time, and is put into an operation database together with the mode selection information, the oil stain detection result, the density detection result, the target water temperature and the target water pressure.

5. The operation control method of the dishwasher according to claim 4, characterized in that: Also includes: If, after running for the target time, the oil residue result obtained is greater than or equal to the preset residue threshold, the dishwasher is controlled to continue to work according to the target water temperature and the target water pressure until the oil residue result is less than the preset residue threshold, and the delay time is recorded; The sum of the target duration and the delay duration is taken as the target duration, and is put into the operation database together with the mode selection information, the oil pollution detection result, the density detection result, the target water temperature and the target water pressure.

6. The operation control method of the dishwasher according to claim 5, characterized in that: Also includes: If the mode selection information is the quick wash mode, after the dishwasher stops working, the cleaning rate corresponding to the density detection result is calculated according to the oil stain detection result and the target time length; Determine whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database; If so, the cleaning rate is put into the operation database as the fastest cleaning rate of the density detection result.

7. The operation control method of the dishwasher according to claim 6, characterized in that: Also includes: After receiving the mode selection information of the quick wash mode, determining whether there is the density detection result in the operation database; If yes, the target water temperature and the target water pressure corresponding to the density detection result are directly obtained, and the target duration is calculated according to the oil pollution detection result and the fastest cleaning rate.

8. The operation control method of the dishwasher according to claim 7, characterized in that: Also includes: The cleaning parameter calculation model is trained using the operation database according to a preset period.

9. The operation control method of a dishwasher according to claim 1, characterized in that: The constructing of the initial population and the initial position of each particle in the initial population based on chaos theory includes: Generate a preset number of random numbers within a preset random range; Iterate each of the random numbers based on the Logistic mapping equation and the number of mapping iterations to obtain a preset number of particles; Each of the particles is mapped to a value range corresponding to a calibration parameter of the dishwasher to obtain an initial position of each of the particles.

10. The operation control method of a dishwasher according to claim 1, characterized in that: Also includes: After obtaining the initial parameters, input them into the image recognition model to determine whether there are items that do not belong to the preset dishwashing items; If so, a foreign object prompt message is generated.

11. The operation control method of a dishwasher according to claim 8, characterized in that: Also includes: When the oil residue result is less than the preset residue threshold, the target duration is added to the cumulative cleaning duration; Determining whether the accumulated cleaning time exceeds a preset maintenance threshold; If it exceeds, a maintenance reminder message is generated, and after receiving the maintenance instruction, the accumulated cleaning time is cleared.

12. The operation control method of a dishwasher according to claim 11, characterized in that: Also includes: During the operation of the dishwasher, a water level value of a water level monitor inside the dishwasher is obtained in real time; Determine whether the water level value exceeds a preset drainage threshold; If so, a drainage fault prompt message is generated.

13. The operation control method of a dishwasher according to claim 12, characterized in that: The preset residual threshold, the preset maintenance threshold, the preset drainage threshold and the preset period are all adjustable.

14. An operation control device for a dishwasher, characterized in that: include: An image acquisition module, used to receive a start instruction and obtain initial parameters of the dishwasher; The initial parameters include a first phase angle image, a second phase angle image, a third phase angle image, a fourth phase angle image and pressure data of a pressure sensor disposed at the bottom of the dishwasher; A first detection module, used to input the initial parameters into an oil stain detection model to obtain an oil stain detection result of tableware; A second detection module, used for inputting the initial parameters into a density detection model to obtain a density detection result of tableware; A selection module, configured to receive mode selection information from a user and determine a first objective function corresponding to the mode selection information; A calculation module is used to input the first objective function, the oil pollution detection result and the density detection result into a cleaning parameter calculation model to obtain operation parameters; wherein the operation parameters include target duration, target water temperature and target water pressure; wherein the cleaning parameter calculation model is a MOPSO algorithm model; the calculation module is specifically used to: Construct a second objective function of washing water temperature, washing water pressure, washing time, density and oil pollution degree; determine the model parameters of the MOPSO algorithm model and initialize the number of iterations; the model parameters include the maximum number of iterations of the population, acceleration factor, iteration weight factor and mapping iteration number; construct an initial population and the initial position of each particle in the initial population based on chaos theory; use the second objective function to calculate the second fitness of each particle; take the particles whose second fitness is less than the oil pollution detection result as target particles; randomly generate the initial speed of each target particle within a preset speed range; optimization step: optimize each target particle based on the acceleration factor and the iteration weight factor; use the first objective function to calculate the first fitness of each target particle; determine whether the minimum first fitness is less than the first fitness of the optimal particle of the previous iteration; if so, take the target particle corresponding to the minimum first fitness as the optimal particle; let the number of iterations increase by 1, and determine whether the number of iterations is greater than the maximum number of iterations of the population; if so, take the position of the optimal particle as the operating parameter; otherwise return to the optimization step; A control module is used to control the dishwasher to operate according to the operating parameters.

15. The operation control device of the dishwasher according to claim 14, characterized in that: Also includes: A real-time acquisition module, used to obtain cleaning images inside the dishwasher during each water output pause period; A residue detection module, used for inputting the cleaning image into the oil stain detection model to obtain a corresponding oil stain residue result; A duration updating module, used for obtaining the cleaning duration according to the acquisition time of the cleaning image when the oil residue result is less than a preset residue threshold; The dishwasher is controlled to stop working, and the cleaning time is taken as the target time, and is put into an operation database together with the mode selection information, the oil stain detection result, the density detection result, the target water temperature and the target water pressure.

16. The operation control device of the dishwasher according to claim 15, characterized in that: Also includes: A delay module, configured to control the dishwasher to continue to operate according to the target water temperature and the target water pressure, if the oil residue result is greater than or equal to the preset residue threshold after the target duration of operation, until the oil residue result is less than the preset residue threshold, and record the delay duration; A storage module is used to take the sum of the target duration and the delay duration as the target duration, and put it into an operation database together with the mode selection information, the oil pollution detection result, the density detection result, the target water temperature and the target water pressure.

17. The operation control device of the dishwasher according to claim 16, characterized in that: Also includes: a rate calculation module, configured to calculate a cleaning rate corresponding to the density detection result according to the oil stain detection result and the target duration when the mode selection information is a quick wash mode and after the dishwasher stops working; The rate update module is used to determine whether the cleaning rate is greater than the fastest cleaning rate corresponding to the density detection result in the operation database; and when the cleaning rate is greater than the fastest cleaning rate, the cleaning rate is placed in the operation database as the fastest cleaning rate of the density detection result.

18. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the operation control method of the dishwasher according to any one of claims 1 to 13 are implemented.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the operation control method of the dishwasher according to any one of claims 1 to 13 are implemented.

Images