Ice maker, ice-making remaining time calibration method, corresponding device, and medium

Abstract

The present application relates to an ice maker and its remaining ice-making time calibration method, as well as corresponding devices and media. The method comprises real-time monitoring of water level change data obtained by a water level sensor installed in a water tank to determine the total height of water consumed during the current ice-making process; calculating the total weight of water consumed during the current ice-making process based on the total height and the cross-sectional area of the water tank; calculating the remaining ice-making time for the current ice-making process based on a user-preset target ice-making amount, the total weight of the currently consumed water, and the corresponding consumption time; comparing the calculated remaining ice-making time with the currently displayed remaining time, and if there is a deviation, calibrating the currently displayed remaining time based on the calculated remaining ice-making time. By real-time monitoring of water level changes, calculating the total weight of consumed water, and dynamically calculating the remaining ice-making time based on the target ice-making amount and consumption time, the present application significantly improves the accuracy of the remaining ice-making time displayed by the ice maker under different environmental conditions.

Description

Technical Field

[0001] The present application relates to the field of household appliances, and in particular to an ice maker and a method for calibrating the remaining ice making time thereof, as well as corresponding devices and media. Background Art

[0002] With rising living standards and a growing demand for convenience, home ice makers have become commonplace in homes, small businesses, offices, and other places. These devices, with their ability to quickly generate ice, provide users with an instant cooling solution, significantly enhancing the convenience of daily life and business operations. Home ice makers primarily operate by using a built-in refrigeration system to cool and solidify water into ice cubes, which are then temporarily stored in the ice maker's ice basket for easy access.

[0003] Existing household ice makers usually adopt a design mode in which a fixed ice-making time corresponds to a specific ice-making amount. After the user sets the ice-making amount, the ice maker will count down based on the preset ice-making time, so that the user can know the remaining ice-making time and arrange other matters. However, this fixed-time design has certain limitations in actual use. Mechanical wear caused by long-term use of the ice maker will affect the ice-making efficiency, resulting in the time required to make the same amount of ice deviating from the factory setting. In addition, different usage environments, such as changes in ambient temperature and differences in the initial water temperature of the water used for ice making, will also affect the actual ice-making efficiency, making the countdown display inconsistent with the actual ice-making progress, thereby reducing the accuracy of the user experience. Summary of the Invention

[0004] The primary purpose of the present application is to solve at least one of the above problems and to provide an ice maker and a method for calibrating the remaining ice making time thereof, as well as corresponding devices and media.

[0005] In order to meet the various objectives of this application, this application adopts the following technical solutions:

[0006] A method for calibrating the remaining ice making time provided for one of the purposes of this application includes the following steps:

[0007] Real-time monitoring of water level change data obtained by the water level sensor in the water tank to determine the total height of water consumed in the current ice making process;

[0008] Calculating the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank;

[0009] Calculate the remaining ice making time for the current ice making process based on the user's preset target ice making volume, the total weight of the currently consumed water, and the corresponding consumption time;

[0010] The calculated remaining ice-making time is compared with the currently displayed remaining time. If there is a deviation, the currently displayed remaining time is calibrated based on the calculated remaining ice-making time.

[0011] A device for calibrating the remaining time of ice making, which is adapted to one of the purposes of this application and is provided for calibrating the remaining time of ice making, comprises:

[0012] A height value determination module is configured to monitor in real time the water level change data obtained by a water level sensor provided in the water tank to determine the total height value of water consumed in the current ice making process;

[0013] a total weight determination module configured to calculate the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank;

[0014] The remaining ice making time calculation module is configured to calculate the remaining ice making time of the current ice making process based on the target ice making amount preset by the user, the total weight of the currently consumed water, and the corresponding consumption time;

[0015] The remaining ice-making time updating module is configured to compare the calculated remaining ice-making time with the currently displayed remaining time, and if there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice-making time.

[0016] On the other hand, an ice maker provided to meet one of the purposes of the present application includes a controller and at least one ice maker, wherein the controller is used to execute the steps in the ice making remaining time calibration method to calibrate the ice making remaining time of the ice maker.

[0017] On the other hand, a computer-readable storage medium is provided to meet one of the purposes of the present application, which stores a computer program implemented according to the ice making remaining time calibration method in the form of computer-readable instructions. When the computer program is called and executed by a computer, the steps included in the method are executed.

[0018] The technical solution of this application has many advantages, including but not limited to the following:

[0019] This application monitors water level change data in real time and calculates the total weight of water consumed in the current ice-making process based on the cross-sectional area of the water tank. It then accurately calculates the remaining ice-making time for the current ice-making process based on the user's preset target ice-making volume, the total weight of the current water consumption, and the corresponding consumption time, and calibrates the displayed remaining time. This application's calibration of the remaining ice-making time based on this method can effectively solve the problems of ice-making efficiency changes and inaccurate countdown display caused by factors such as mechanical wear or different usage environments of the ice-making machine. Specifically, through accurate calibration of the remaining ice-making time, users can more accurately grasp the progress of ice-making, reasonably arrange other matters, and avoid waiting or taking ice cubes in advance due to inaccurate ice-making time estimation, thereby significantly improving the accuracy and convenience of the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 This is a flow chart of a typical embodiment of the ice making remaining time calibration method of the present application;

[0022] Figure 2 This is a flow chart of calculating the remaining ice-making time in an embodiment of the present application;

[0023] Figure 3 This is a flow chart of updating the reference ice-making time in an embodiment of the present application;

[0024] Figure 4 This is a schematic diagram of a process for updating the reference ice weight in an embodiment of the present application;

[0025] Figure 5 A schematic diagram of a process for calculating the total weight of ice cubes in an embodiment of the present application;

[0026] Figure 6 This is a flow chart of calling the model to output the remaining ice making time in an embodiment of the present application;

[0027] Figure 7 This is a flow chart of training a remaining time prediction model based on environmental parameters in an embodiment of the present application;

[0028] Figure 8 This is a functional block diagram of the ice making remaining time calibration device of the present application;

[0029] Figure 9 This is a schematic diagram of the structure of a computer device used in this application. DETAILED DESCRIPTION

[0030] The present application provides a method for calibrating the remaining time of ice making, which can be programmed as a computer program product and deployed in the control system of an ice maker to run and be implemented. For example, in the exemplary application scenario of an ice maker, the method is integrated into the intelligent control system of a household ice maker, wherein the intelligent control system realizes data acquisition and calculation through an embedded processor. The water tank of the ice maker is equipped with a high-precision water level sensor and a temperature sensor array, which can continuously monitor the water level changes, ambient temperature and water temperature parameters during the ice making process. The monitored data is transmitted to the main control unit of the intelligent control system, which implements core functions such as water level data analysis, weight conversion, time prediction and display calibration. At the same time, the main control unit interacts with the user's mobile terminal through a Wi-Fi / Bluetooth module to support remote monitoring and parameter setting. The user can set the target ice making amount through the touch screen of the ice maker panel or the corresponding APP, and the control system dynamically calibrates the remaining time display according to the various parameters collected in real time.

[0031] This application addresses the issue of mechanical wear and tear caused by long-term use of ice machines, variations in ice machine environments, and other factors that can cause ice-making efficiency to deviate from factory settings, leading to inaccurate remaining ice-making time displayed to the user and a reduced user experience. Therefore, in a typical embodiment of this application, the remaining ice-making time is determined by the user's preset target ice-making amount, the real-time acquisition of the ice-making amount (i.e., the total weight of water currently consumed), and the corresponding consumption time. The currently displayed remaining ice-making time is then calibrated based on this remaining ice-making time. The current ice-making amount of the ice-making machine is determined by the weight of water consumed in the water tank. It should be noted that since household ice-making machines are typically small in size and have a relatively small water tank capacity, multiple water additions are required to make a full batch of ice. In this case, the total weight of water currently consumed can be determined based on the water level change data after each addition.

[0032] In one embodiment, a distributed array of multiple weighing sensors is positioned at the bottom of the ice basket to prevent inaccurate data from being collected when uneven force is applied to the bottom of the basket. This embodiment uses each weighing sensor to collect ice weight data and calculates an average of the collected weight data to determine the total weight of ice produced in the basket. The arithmetic average of this total weight and a pre-stored baseline ice weight corresponding to the target ice production amount is then calculated, and the resulting value serves as the baseline ice weight corresponding to the target ice production amount. During the next ice production cycle, the calculation steps of this embodiment are repeated to calibrate and update the baseline ice weight corresponding to the target ice production amount, resulting in a more accurate estimate of the remaining ice production time.

[0033] In another embodiment, the remaining time prediction model is trained by incorporating the ambient temperature and initial water temperature into the ice-making machine to consider their impact on ice-making efficiency. This model learns the effects of these parameters on ice-making efficiency and outputs a predicted remaining time. Specifically, this embodiment integrates collected environmental parameters with the user's preset target ice production volume, the current total weight of water consumption, and the corresponding consumption time into a pre-trained remaining time prediction model. This remaining time prediction model is trained using a machine learning algorithm on historical ice-making data. When the remaining time output by the remaining time prediction model deviates from the currently displayed remaining time, the displayed remaining time is automatically calibrated based on the remaining time prediction model's output. Furthermore, after each ice-making session, the actual environmental parameters, time consumption, and other data from that session are stored as new training samples. Regular incremental training of the remaining time prediction model allows the model to continuously adapt to changes in ice-making machine performance and environmental variations, thereby ensuring accurate remaining time calibration across different seasons and geographical environments.

[0034] The ice making remaining time calibration method of the ice making machine of the present application can be realized as a computer program product and run in the main control unit of the ice making machine. Figure 1 The ice making remaining time calibration method includes the following specific steps:

[0035] Step S5100: Real-time monitoring of water level change data obtained by a water level sensor in the water tank to determine the total height of water consumed in the current ice-making process;

[0036] The water level sensor installed in the water tank is used to monitor the water level changes in the water tank in real time, obtain the corresponding water level change data, and then determine the total height of the water consumed in the current ice-making process. Water level sensors include but are not limited to float-type liquid level sensors, electronic capacitive liquid level sensors, infrared detection liquid level sensors, etc. Different sensors have different characteristics. For example, float-type liquid level sensors monitor water level changes by the up and down movement of a float. Float-type liquid level sensors have a simple structure and low cost, and are suitable for the water tank environment of most ice-making machines. However, the accuracy of float-type liquid level sensors can be affected by water fluctuations or impurities, and require regular cleaning and calibration. Electronic capacitive liquid level sensors measure water levels by detecting changes in the dielectric constant of water. Capacitive liquid level sensors have high accuracy and are not affected by water fluctuations, and can provide stable measurement results. Furthermore, capacitive level sensors are non-contact and unaffected by impurities or corrosive substances in the water, making them suitable for a wide range of water quality conditions. However, they are relatively expensive and require precise calibration to ensure accurate measurements. Infrared level sensors use the principle of infrared reflection to determine water level changes. These sensors are non-contact and do not pollute the water quality. They also have a fast response speed and can monitor water level changes in real time. However, their measurement accuracy can be affected by factors such as ambient light interference and foam on the water surface. In general, the appropriate water level sensor should be selected based on the ice maker's water tank structure, operating environment, or other considerations.

[0037] In one embodiment, when the set ice production quantity requires multiple water additions to the water tank to complete the entire ice production process, the water level sensor continuously monitors the changes in the water level in the water tank and records each water addition and consumption process. Specifically, the water level sensor begins monitoring from an initial water level. As the ice production process progresses, the water level gradually decreases, and the sensor records the water level change data in real time. When the water level drops to a preset minimum level, the water addition operation is triggered, and ice production continues, while recording the water level change data as water is consumed until the set ice production quantity is achieved. The total height of water consumed is determined based on the water level change data obtained throughout the ice production process.

[0038] Another embodiment employs multiple water level sensors to improve monitoring accuracy and reliability. For example, multiple water level sensors of the same type can be installed at different locations in the water tank. By comparing water level change data from these sensors, the final total height of water consumption can be determined, effectively reducing errors and improving water level measurement accuracy. Furthermore, a temperature compensation algorithm can be incorporated to correct for water level fluctuations caused by temperature changes, further improving monitoring accuracy.

[0039] Step S5200: Calculate the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank;

[0040] After determining the total height change of the water level in the previous step, the volume of water consumption can be calculated based on the cross-sectional area of the water tank. The cross-sectional area of the water tank is a known fixed value determined during the design phase of the ice maker and can be obtained by measuring the internal dimensions of the water tank. For example, if the water tank is a rectangular parallelepiped, its cross-sectional area can be calculated by measuring the length and width of the water tank. This cross-sectional area value is stored in the main control unit of the ice maker so that it can be directly called during the calculation process.

[0041] To calculate the volume of water consumed, the total height value needs to be multiplied by the cross-sectional area of the water tank. The resulting volume value is the actual amount of water consumed during the ice-making process. Furthermore, to convert the volume of water consumed into water weight, the density of water needs to be considered. In other words, the total weight of water consumed can be calculated by multiplying the volume of water consumed by the density of water. The ice-maker's main control unit automatically completes this calculation process. Specifically, by receiving real-time water level change data from the water level sensor and combining it with pre-stored information on the cross-sectional area of the water tank and the density of water, the total weight of water consumed is quickly calculated. It is easy to understand that the total weight of water consumed is the weight of the resulting ice cubes.

[0042] It's important to note that the water level sensor and related parameters must be regularly calibrated to ensure accurate calculation results. For example, water density is affected by factors like temperature and pressure, requiring appropriate corrections in different operating environments. Implementing this step further improves calculation accuracy and reliability, providing users with a more accurate display of remaining ice making time.

[0043] In one embodiment, while determining the total weight of consumed water in this step, a built-in timer of the ice maker is started to record the ice making time of the entire ice making process, so as to subsequently calculate the remaining ice making time of the current ice making process using the total weight of the currently consumed water and the corresponding consumption time.

[0044] Step S5300: Calculate the remaining ice-making time for the current ice-making process based on the target ice-making amount preset by the user, the total weight of the currently consumed water, and the corresponding consumption time;

[0045] Users can set their target ice production volume in a variety of ways. For example, the ice maker is equipped with physical buttons for selecting the target ice production volume. Specifically, a set of physical buttons is provided on the panel of the ice maker, each corresponding to a preset ice production volume. These physical buttons allow users to set the desired ice production volume directly on the ice maker. Users can also select the target ice production volume through the ice maker's touch screen display. A slider or numeric input box is displayed on the touch screen, and users can select the desired ice production volume by sliding the slider or entering a number. In addition, users can connect to a mobile application, allowing users to set the target ice production volume remotely, that is, users enter the desired ice production volume in the mobile application.

[0046] The remaining ice-making time for the current ice-making process is calculated based on the user-preset target ice-making amount, as well as the total weight of water consumed and the corresponding consumption time recorded in the previous step. It should be noted that the total weight of water consumed in the previous step is the weight of the resulting ice cubes. In one embodiment, using the relationship that the ratio of the total weight of the currently produced ice cubes to the corresponding ice-making time is equal to the ratio of the remaining ice-making amount to the remaining ice-making time, the remaining ice-making time can be calculated as the product of the remaining ice-making amount and the corresponding ice-making time divided by the total weight of the currently produced ice cubes. The remaining ice-making amount can be calculated by subtracting the weight of the currently produced ice cubes from the user-preset target ice-making amount. The specific remaining ice-making time calculation process can be found in the subsequent detailed implementation and will not be detailed here. The ice-making machine performs this calculation in real time and dynamically updates the remaining ice-making time display based on the latest data. This dynamic adjustment mechanism provides users with a more accurate remaining ice-making time. For example, if the ice maker encounters a change in ambient temperature or a mechanical failure during operation, causing the ice making rate to drop, the ice maker automatically extends the display of the remaining ice making time to ensure that the user can accurately understand the ice making progress.

[0047] Furthermore, historical data and machine learning algorithms can be combined for optimization. For example, by recording data such as the target ice production volume, total water weight consumed, time consumed, and actual ice production time during each ice-making process, a training sample set can be constructed. This training sample set can then be trained using a machine learning algorithm (such as linear regression, decision tree, or neural network) to generate a more accurate ice-making time prediction model. This model can dynamically adjust the output of the remaining ice-making time based on current ice-making conditions and historical data, further improving prediction accuracy. For detailed model training steps, please refer to the detailed implementation method below and will not be detailed here.

[0048] Step S5400: Compare the calculated remaining ice-making time with the currently displayed remaining time. If there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice-making time.

[0049] In the previous step, the ice maker calculates the remaining ice-making time in real time. However, the ice maker's display typically displays a preset remaining time, which is calculated based on the initially set ice-making rate or historical data. Because the actual ice-making process can vary, it's necessary to compare the calculated remaining time with the currently displayed remaining time in real time to ensure consistency.

[0050] In another embodiment, the ice maker automatically performs a comparison at preset time intervals (e.g., every minute or every two minutes). This interval can be adjusted based on the ice maker's full ice time and user needs. During the comparison process, the currently calculated remaining ice making time is obtained and compared with the remaining time currently displayed on the display. If the deviation between the two is within the allowable error range (e.g., the error does not exceed 10 seconds), the currently displayed remaining time is considered accurate and no calibration is required. This error range can be set based on the ice maker's accuracy requirements and the user's demand for time accuracy. If the deviation between the calculated remaining ice making time and the currently displayed remaining time exceeds the allowable error range, a calibration process is initiated to update the calculated remaining ice making time on the display to ensure that the remaining time viewed by the user is based on the latest calculation of the current actual ice making progress.

[0051] Through the above method, the ice maker can provide users with more accurate and reliable calibration of the remaining ice making time, thereby improving the user experience and the intelligence level of the ice maker.

[0052] It can be seen from the typical embodiments of the present application that the technical solution of the present application has many advantages, including but not limited to the following aspects:

[0053] This application monitors water level change data in real time and calculates the total weight of water consumed in the current ice-making process based on the cross-sectional area of the water tank. It then accurately calculates the remaining ice-making time for the current ice-making process based on the user's preset target ice-making volume, the total weight of the current water consumption, and the corresponding consumption time, and calibrates the displayed remaining time. This application's calibration of the remaining ice-making time based on this method can effectively solve the problems of ice-making efficiency changes and inaccurate countdown display caused by factors such as mechanical wear or different usage environments of the ice-making machine. Specifically, through accurate calibration of the remaining ice-making time, users can more accurately grasp the progress of ice-making, reasonably arrange other matters, and avoid waiting or taking ice cubes in advance due to inaccurate ice-making time estimation, thereby significantly improving the accuracy and convenience of the user experience.

[0054] Based on any embodiment of the method of this application, please refer to Figure 2, based on the user's preset target ice making amount, the total weight of the current water consumption and the corresponding consumption time, calculate the remaining ice making time of the current ice making, including:

[0055] Step S5310: Calculate the difference between the target ice production amount preset by the user and the total weight of the currently consumed water to obtain the remaining ice production amount;

[0056] During the ice-making process, the target ice production volume preset by the user is the total amount of ice cubes the user expects to obtain in the end. The target ice production volume is set by the user according to his or her own needs through physical buttons, touch screen or mobile application before starting the ice maker; and the total weight of water currently consumed refers to the weight of water that has been cooled and solidified into ice through the refrigeration system of the ice maker from the start of ice making to the current moment. Since water will be gradually consumed and converted into ice during the ice-making process, the total weight of water currently consumed is actually equal to the weight of ice made.

[0057] The remaining ice capacity is calculated by subtracting the total weight of water currently consumed from the user's preset target ice capacity. This remaining ice capacity reflects how much ice the ice maker needs to produce at the current moment to reach the user's preset target ice capacity. For example, if the user's preset target ice capacity is 1 kg, and the total weight of water currently consumed (i.e., the weight of ice produced) is 0.3 kg, the remaining ice capacity is 0.7 kg.

[0058] Step S5320: multiply the remaining ice making amount by the consumed time to obtain a first intermediate value;

[0059] Elapsed time is the time elapsed from the start of ice making to the current moment. By multiplying the remaining ice making capacity by the elapsed time, we obtain a first intermediate value, which is used in subsequent calculations to calculate the remaining ice making time. Simply put, assuming that the ice maker has completed a portion of its ice making work at a certain efficiency during the elapsed elapsed time, and that there is a certain proportional relationship between the remaining ice making capacity (i.e., the remaining ice making capacity) and the elapsed time (i.e., the elapsed time), multiplying the remaining ice making capacity by the elapsed time yields a value related to the remaining ice making time, i.e., the first intermediate value. This first intermediate value provides the basis for subsequent calculations of the remaining ice making time.

[0060] Step S5330: Divide the first intermediate value by the total weight of the currently consumed water to obtain the remaining ice-making time.

[0061] Divide the first intermediate value calculated in the previous step by the total weight of water currently consumed to obtain the remaining ice-making time for the current ice-making process. The total weight of water currently consumed refers to the total weight of water consumed from the start of ice-making to the current moment. This weight is calculated using the water level sensor to monitor the water level in the water tank. The remaining ice-making time is calculated by dividing the first intermediate value (which factors in both the remaining ice-making volume and the elapsed time) by the total weight of water currently consumed. This remaining ice-making time is calculated based on the current ice-making progress and the elapsed ice-making time, more accurately reflecting the time required for the ice-maker to achieve the user's preset target ice-making volume under current conditions.

[0062] In this embodiment, the calculation relationship that the ratio of the total weight of the ice cubes currently produced and the corresponding ice-making time is equal to the ratio of the remaining ice-making amount and the remaining ice-making time is used to derive the calculation process of the remaining ice-making time. Based on this calculation process, the remaining ice-making time of the current ice making can be determined.

[0063] Based on any embodiment of the method of this application, please refer to Figure 3 , compare the calculated remaining ice making time with the currently displayed remaining time. If there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice making time, including:

[0064] Step S6100: monitor and determine the actual ice-making time consumed for the current ice-making process to be completed;

[0065] In one embodiment, after the ice maker starts making ice, a built-in timer is started to record the time taken from the start of ice making to the completion of ice making. The timer continues to run until the ice maker completes the current ice making task. The judgment standard for ice making completion can be that the ice cubes in the ice basket reaches the target ice making amount preset by the user, or the ice basket reaches a full load state.

[0066] The timer is tightly integrated with the ice maker's main control unit, which determines whether ice making is complete based on the real-time monitoring of the ice basket weight, water level changes, and other relevant parameters. For example, if a high-precision weighing sensor is installed at the bottom of the ice basket, when the weight of the ice cubes in the ice basket reaches the user's preset target ice making amount, the timer will stop immediately and the current time will be recorded as the actual ice making time. Specifically, assuming the user's preset target ice making amount is 500 grams, the timer will start after the ice maker starts making ice. During the ice making process, the weight changes of the ice basket will be continuously monitored. When the weight of the ice cubes in the ice basket reaches 500 grams, the timer will stop, and the time recorded at this time is the actual ice making time.

[0067] In another embodiment, data from other sensors can be combined to improve the accuracy of the actual ice-making time. For example, in addition to the weighing sensor, an infrared sensor can be installed at the opening of the ice basket to detect whether the basket is full. When the infrared sensor detects that the basket is full, the timer stops and the actual ice-making time is recorded. This multi-sensor fusion method can effectively reduce the error that may occur from a single sensor and improve the measurement accuracy of the actual ice-making time.

[0068] Step S6200: Calculate the arithmetic mean of the actual ice-making time and the pre-stored reference ice-making time corresponding to the target ice-making amount;

[0069] The benchmark ice-making time is pre-set based on the ice-making time required for the ice-maker to complete a specific target ice-making volume under specific environmental conditions (such as a specific ambient temperature and initial water temperature). This benchmark ice-making time is obtained through multiple experiments and data analysis and can reflect the ice-making efficiency of the ice-maker under ideal conditions.

[0070] After completing an ice-making task, the actual ice-making time is obtained and compared with the pre-stored benchmark ice-making time. The arithmetic mean of the two times is calculated. This arithmetic mean more accurately reflects the ice-making efficiency of the ice-making machine under the current environmental conditions. By implementing this step, the benchmark ice-making time can be dynamically adjusted to more closely match actual operating conditions, thereby improving the accuracy of subsequent ice-making time predictions.

[0071] Step S6300: The calculated arithmetic mean value is used as a new reference ice-making time for displaying the subsequent remaining time.

[0072] The benchmark ice-making time is an average value derived from multiple tests of the ice maker under specific environmental conditions. However, due to variations in environmental conditions (such as ambient temperature and initial water temperature) and mechanical wear from long-term operation, the actual ice-making time may deviate from the benchmark time. To improve the accuracy of the remaining ice-making time display, after each ice-making cycle, an arithmetic mean is calculated based on the actual ice-making time and the stored benchmark time. This mean value is used as the new benchmark time. Specifically, suppose the actual ice-making time during a particular ice-making cycle is 30 minutes, while the stored benchmark time is 25 minutes. Based on the calculation in the previous step, the arithmetic mean value is 27.5 minutes. This new benchmark time is stored in the ice-making machine's main control unit and used to display the remaining time for the next ice-making cycle. That is, when the user restarts the ice-making machine and sets the target ice-making amount, the remaining ice-making time countdown will be displayed on the display based on the new benchmark time (27.5 minutes).

[0073] The ice maker continuously updates its baseline ice-making time. After each ice-making cycle, it recalculates the arithmetic average of the actual ice-making time and the current baseline ice-making time, and uses this average as the baseline ice-making time. For example, suppose the actual ice-making time during several ice-making cycles is 32 minutes, 28 minutes, and 31 minutes, respectively. After each ice-making cycle, the arithmetic average is recalculated and the baseline ice-making time is updated. After repeated updates, the baseline ice-making time gradually stabilizes at a value closer to the actual operating conditions, such as 29 minutes.

[0074] In this embodiment, by continuously updating the benchmark ice-making time, the ice-making machine can more accurately reflect the ice-making efficiency under the current environmental conditions and equipment status, thereby providing users with a more reliable estimate of the remaining ice-making time. This embodiment not only improves the user experience, but also reduces the prediction error caused by environmental changes or equipment aging, ensuring that the ice-making machine always maintains a high time prediction accuracy under different conditions, reflecting a higher level of intelligence.

[0075] Based on any embodiment of the method of this application, please refer to Figure 4 , compare the calculated remaining ice making time with the currently displayed remaining time. If there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice making time, including:

[0076] Step S7100: Obtain the total weight of ice cubes actually produced in the ice basket after the current ice making is completed;

[0077] After the ice maker completes its current cycle of ice making, it's necessary to accurately determine the total weight of the ice cubes produced in the basket. This is accomplished by installing a high-precision load cell at the bottom of the basket. The load cell monitors the basket's weight changes in real time and transmits this data to the ice maker's main control unit. After ice making is complete, the final reading from the load cell is read to determine the total weight of the ice cubes produced. Specifically, assume the ice maker's basket is empty before ice making begins. The empty basket weighs 500 grams. After ice making is complete, the total weight measured by the load cell is 1500 grams. This means the total weight of the ice cubes produced in the basket is 1500 grams - 500 grams = 1000 grams. This means that under the current ice making conditions, the total weight of the ice cubes produced by the ice maker is 1000 grams.

[0078] In one embodiment, the ice maker samples and averages the weight data received multiple times to ensure accurate weighing data. For example, after ice making is complete, a sample is taken every 1 second for 10 consecutive times. The average of these 10 samples is then calculated as the final total ice weight. This effectively reduces measurement errors caused by factors such as sensor noise and ice sway.

[0079] In another embodiment, the ice maker installs multiple high-precision weighing sensors at the bottom of the ice basket to further improve the accuracy and reliability of measuring the total weight of ice cubes. These weighing sensors are distributed at different locations on the bottom of the ice basket, and can monitor the weight changes of the ice basket from multiple angles. Specifically, multiple weighing sensors can provide redundant data, effectively reducing measurement errors caused by single sensor failure or uneven accumulation of ice cubes in a certain area. For example, suppose four weighing sensors are installed at the bottom of the ice basket, one at each of the four corners of the ice basket. After ice making is completed, each sensor will independently measure the weight of the ice basket, and the data from multiple weighing sensors will be averaged. For example, if the total weight of the ice basket measured by the four sensors is 1490 grams, 1500 grams, 1510 grams, and 1505 grams respectively, the average of these four data is calculated, and then the total weight of ice cubes actually produced in the ice basket can be obtained by subtracting the weight of the empty ice basket.

[0080] Step S7200: Calculate the arithmetic mean of the total weight of the ice cubes and the pre-stored reference ice weight corresponding to the target ice production amount;

[0081] The reference ice weight is the target ice yield set by the user via the physical button, touchscreen display, or mobile app before making ice. The arithmetic mean is calculated between this reference ice weight and the actual weight of the ice produced (hereinafter referred to as the total ice weight). This mean is used to calibrate the ice maker's target ice yield, ensuring it accurately produces the desired amount of ice under varying environmental conditions (such as temperature fluctuations). During the ice-making process, ice may partially melt due to high ambient temperatures or other factors, resulting in a discrepancy between the actual ice yield and the target yield. By calculating the mean, the reference ice weight can be dynamically adjusted, improving the accuracy of subsequent ice-making cycles. This dynamic adjustment mechanism allows the ice maker to adapt to varying environmental conditions and mitigate inaccurate ice yields caused by ice melting or other factors. For example, in high ambient temperatures, ice may partially melt, resulting in the actual ice yield being lower than the target yield. By calculating the mean and updating the reference ice weight, the ice maker can appropriately increase ice yield during subsequent ice-making cycles to compensate for the partial ice melt.

[0082] Step S7300: Update the reference ice weight corresponding to the target ice production amount based on the calculated arithmetic mean.

[0083] In this step, the ice maker stores the arithmetic mean value calculated in the previous step as the new baseline ice weight in the ice maker's main control unit. This new baseline ice weight will be used in subsequent ice-making processes to ensure that the ice maker can more accurately produce the user's desired ice quantity. For example, if the user restarts the ice maker and sets the same target ice production quantity, the ice maker will adjust the ice-making process based on the new baseline ice weight (1100 grams) to more accurately meet the user's desired ice production quantity. After multiple updates, the baseline ice weight will gradually stabilize at a value that is closer to the actual operating conditions. Through this method, the ice maker can provide users with more accurate and reliable ice production calibration, thereby improving the user experience and the ice maker's intelligence level. This dynamic update mechanism enables the ice maker to adapt to different usage scenarios and environmental conditions, ensuring that the ice maker maintains efficient ice-making performance throughout long-term operation.

[0084] In this embodiment, by accurately measuring and dynamically updating the reference ice weight, the ice maker can effectively deal with the melting of ice cubes that may occur during the ice-making process, especially under high ambient temperature or other unfavorable conditions. This adaptive mechanism not only improves the ice-making accuracy of the ice maker under different environmental conditions, but also reduces the problem of inconsistent ice production caused by ice melting, significantly improving the user experience.

[0085] Based on any embodiment of the method of this application, please refer to Figure 5 , get the total weight of ice cubes actually produced in the ice basket after the current ice making is completed, including:

[0086] Step S7110: obtaining weight data collected by an array of weighing sensors distributed at the bottom of the ice basket;

[0087] A sensor array consisting of multiple high-precision load cells is installed at the bottom of the ice basket to accurately measure the total weight of the ice in the basket. Evenly distributed across the basket, the high-precision load cells monitor the basket's weight changes in real time and transmit the collected data to the ice maker's main control unit. After ice making is complete, weight data collected by each load cell is retrieved. This weight data reflects the weight variations at different locations within the basket. Because the ice in the basket can be unevenly distributed, the data from a single sensor can be affected by localized weight variations. Therefore, the weight data collected by multiple load cells must be comprehensively analyzed to determine the total weight of the ice in the basket.

[0088] Step S7120: Calculate the average value of the collected weight data as the total weight of the ice cubes actually produced.

[0089] In one embodiment, after obtaining the weight data uploaded in real time by each weighing sensor in the previous step, the data is first preprocessed to eliminate possible instantaneous interference or sensor noise, and then the readings of all valid weighing sensors at the same timestamp are algebraically summed, and the sum is divided by the number of weighing sensors involved in the calculation to obtain the average weight of the ice cubes in the ice basket. The implementation of this step eliminates local outliers caused by uneven distribution of ice cubes, ensuring that the final output average value accurately reflects the overall load of the ice basket. At the same time, the average value sequence of multiple consecutive sampling periods is recorded, and the data fluctuations are further smoothed through sliding window filtering technology. Finally, the stable converged value is used as the total weight of the ice cubes actually produced.

[0090] In another embodiment, more advanced data fusion technology, such as a Kalman filter, can be used to process the data of multiple weighing sensors to improve the measurement accuracy. The Kalman filter can dynamically adjust the weight of each weighing sensor data based on the measurement error of the weighing sensor and the correlation of the data, thereby obtaining a more accurate total weight of the ice cubes.

[0091] In this embodiment, through the combination of a multi-sensor array and data processing technology, the ice maker can effectively address the problem of uneven ice distribution and reduce the impact of local outliers on measurement results.

[0092] Based on any embodiment of the method of this application, please refer to Figure 6 ,include:

[0093] Step S8100: Obtain the ambient temperature and initial water temperature corresponding to the current ice-making environment;

[0094] In one embodiment, a temperature sensor is installed on the outside of the ice maker to measure the ambient temperature. The temperature sensor is installed in a location away from the heat source (such as the power supply component) and the cold source (such as the refrigeration system) of the ice maker to ensure that the measured temperature can accurately reflect the actual temperature of the environment in which the ice maker is located; a temperature sensor is installed at the water inlet of the water tank to measure the initial water temperature. The temperature sensor is in direct contact with the water entering the water tank and can monitor the temperature changes of the water in real time.

[0095] In another embodiment, the collected temperature data is sampled multiple times and averaged to ensure data accuracy and reliability. For example, a temperature sensor monitoring the ambient temperature samples the data five times every one second. The average of these five samples is then calculated as the final ambient temperature. This multiple sampling and averaging method can effectively reduce measurement errors caused by sensor noise or ambient temperature fluctuations. By obtaining the ambient temperature and initial water temperature of the current ice-making environment, the ice-maker can dynamically adjust the ice-making time prediction model, thereby providing users with a more accurate remaining ice-making time.

[0096] Step S8200: Input the ambient temperature, the initial water temperature, the target ice making amount preset by the user, the total weight of the currently consumed water, and the corresponding consumption time into the trained remaining time prediction model to obtain the remaining ice making time of the current ice making process;

[0097] The ambient temperature and initial water temperature data obtained in the previous step, as well as the target ice production volume set by the user through physical buttons, touch screen display, or mobile application, and the total weight of water currently consumed and the corresponding consumption time calculated by the water level sensor are input as input features into a pre-trained remaining time prediction model. Based on these input features, the remaining time prediction model calculates the remaining ice production time for the current ice production using its internal algorithm and parameters. The remaining time prediction model is trained based on a large amount of historical ice production data and can learn the changing patterns of ice production time under different environmental conditions.

[0098] In one embodiment, the remaining time prediction model utilizes a machine learning algorithm, such as linear regression, decision trees, or neural networks, that can dynamically adjust model parameters based on the complex relationships between input features, thereby more accurately predicting the remaining ice-making time. For example, if the remaining time prediction model detects a high ambient temperature, the predicted remaining ice-making time may be relatively long, as ice-making efficiency generally decreases in high-temperature environments.

[0099] Through this remaining time prediction model based on multiple input features, the ice maker can provide users with more accurate and reliable remaining ice making time estimation.

[0100] Step S8300: Compare the remaining ice-making time output by the remaining time prediction model with the currently displayed remaining time. If there is a deviation, calibrate the currently displayed remaining time based on the remaining ice-making time.

[0101] The ice maker's main control unit receives the remaining ice-making time output by the remaining time prediction model and simultaneously reads the remaining time displayed on the current display screen. The two time values are compared to check for any deviation between them. The magnitude of the deviation can be determined by calculating the difference between the two time values. In one embodiment, a threshold is set. If the deviation exceeds the threshold, the currently displayed remaining time is determined to be inaccurate and requires calibration. The calibration program is initiated to update the remaining ice-making time output by the remaining time prediction model to the display screen, thereby ensuring that the remaining time seen by the user is the latest calculated result based on the current actual ice-making progress. This dynamic update mechanism can effectively reduce prediction errors caused by environmental changes, equipment aging, or other factors, ensuring that the ice maker can accurately display the remaining ice-making time under different conditions.

[0102] Through this dynamic calibration mechanism based on the remaining time prediction model, the ice maker can provide users with a more accurate and reliable estimate of the remaining ice making time.

[0103] In this embodiment, the ice maker's ambient temperature and initial water temperature, combined with the remaining ice-making time output by the remaining time prediction model, are used to calibrate the currently displayed remaining time. The remaining ice-making time output by the model is compared with the current remaining time on the display. If the deviation exceeds a set threshold, a calibration process is initiated, updating the remaining ice-making time output by the model to the display. This dynamic calibration mechanism not only considers the impact of environmental conditions on ice-making efficiency but also incorporates actual ice-making data to ensure that the ice maker accurately displays the remaining ice-making time under different conditions.

[0104] Based on any embodiment of the method of this application, please refer to Figure 7 Before obtaining the ambient temperature and initial water temperature corresponding to the current ice-making environment, the following steps are performed:

[0105] Step S9100: When there is a deviation between the calculated remaining ice-making time and the currently displayed remaining time, the ambient temperature and initial water temperature corresponding to the current ice-making environment are recorded;

[0106] The system continuously monitors the remaining ice-making time calculated from real-time data collected during the ice-making process and the remaining time currently displayed on the display. If a deviation is detected between these two time values, it triggers the recording of environmental parameters, obtaining the current ambient temperature and initial water temperature data from the temperature sensor. This data is stored in the ice-making machine's main control unit and, along with the corresponding ice-making process data (such as target ice production, total weight of water consumed, and elapsed time), forms a complete data record for subsequent analysis and model training, enabling the ice-making machine to better adapt to different environmental conditions.

[0107] Step S9200: Construct a training sample set based on the recorded ambient temperature, initial water temperature, corresponding user-preset target ice making amount, total weight of currently consumed water and corresponding consumption time, and remaining ice making time of the current ice making process;

[0108] In one embodiment, a sample quantity threshold is pre-set, which is determined based on the ice maker's operating experience and data volume requirements. When the number of samples recorded in the previous step accumulates to exceed the preset threshold, these accumulated samples are constructed into a complete training sample set. The constructed sample training set contains rich information for subsequent training of the remaining time prediction model. Specifically, each sample records in detail the key parameters of the ice-making process, including ambient temperature, initial water temperature, user-preset target ice production volume, total weight of current water consumption, corresponding consumption time, and the remaining ice-making time of the current ice-making process recorded when a time deviation is detected. Together, these parameters constitute a comprehensive data set that can reflect the operating status of the ice maker under different environmental conditions and operating settings. By setting the sample quantity threshold, the ice maker can ensure that a sufficient number of data samples have been accumulated before model training, improving the accuracy and reliability of the training model. A large number of samples can better cover various possible operating conditions and environmental changes.

[0109] Step S9300: Input the training sample set into the remaining time prediction model for training, so that it can learn the ability to obtain the remaining ice-making time of the current ice-making based on the ambient temperature and initial water temperature corresponding to the current ice-making environment, the user's preset target ice-making amount, the total weight of the current water consumption, and the corresponding consumption time.

[0110] The constructed training sample set is input into the remaining time prediction model. The remaining time prediction model can utilize various machine learning algorithms, such as linear regression, decision trees, or neural networks. Based on the relationship between input features (ambient temperature, initial water temperature, etc.) and output labels (remaining ice-making time), the remaining time prediction model parameters are dynamically adjusted to more accurately predict the remaining ice-making time. During training, the performance of the remaining time prediction model is continuously monitored to ensure that it accurately learns the complex relationship between input features and remaining ice-making time. In one embodiment, techniques such as cross-validation can be used to divide the training sample set into multiple subsets, which are used for training and validating the model, respectively. This improves the generalization ability of the remaining time prediction model, avoids model overfitting, and enhances its prediction performance on unseen data.

[0111] The trained remaining time prediction model can accurately predict the remaining ice-making time based on the current environmental conditions (such as ambient temperature and initial water temperature), the user's preset target ice production volume, the total weight of water currently consumed, and the corresponding consumption time. This intelligent training mechanism significantly improves the intelligence level of the ice maker, providing users with a more efficient and reliable ice-making experience.

[0112] In this embodiment, by recording environmental parameters and incorporating them into the remaining time prediction model training, the ice maker can learn the changing patterns of ice-making time under different environmental conditions, thereby more accurately reflecting the remaining ice-making time in actual operation. This embodiment not only improves the accuracy of the prediction, but also enhances the adaptability of the ice maker to environmental changes, enabling the ice maker to operate efficiently under different environmental conditions and provide users with a more reliable ice-making experience.

[0113] See also Figure 8 Another embodiment of the present application further provides an ice-making remaining time calibration device, which includes a height value determination module 5100, a total weight determination module 5200, a remaining ice-making time calculation module 5300, and a remaining ice-making time update module 5400, wherein the height value determination module 5100 is configured to monitor water level change data obtained by a water level sensor installed in a water tank in real time to determine the total height value of water consumed in the current ice-making process; the total weight determination module 5200 is configured to calculate the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank; the remaining ice-making time calculation module 5300 is configured to calculate the remaining ice-making time of the current ice-making process based on a user-preset target ice-making amount, the total weight of the currently consumed water, and the corresponding consumption time; the remaining ice-making time update module 5400 is configured to compare the calculated remaining ice-making time with the currently displayed remaining time, and if there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice-making time.

[0114] Based on any embodiment of the device of the present application, the total weight determination module 5200 includes: a remaining ice making amount calculation submodule, configured to calculate the difference between the target ice making amount preset by the user and the total weight of the currently consumed water to obtain the remaining ice making amount; a first intermediate value determination submodule, configured to multiply the remaining ice making amount by the consumption time to obtain a first intermediate value; and a remaining time determination submodule, configured to divide the first intermediate value by the total weight of the currently consumed water to obtain the remaining ice making time.

[0115] Based on any embodiment of the device of the present application, the remaining ice-making time update module 5400 includes: an actual ice-making time determination submodule, which is configured to monitor and determine the actual ice-making time consumed for the current ice-making process; an average value calculation submodule, which is configured to calculate the arithmetic mean of the actual ice-making time and the benchmark ice-making time corresponding to the pre-stored target ice-making amount; and a benchmark ice-making time update submodule, which is configured to use the calculated arithmetic mean as a new benchmark ice-making time for displaying the subsequent remaining time.

[0116] Based on any embodiment of the device of the present application, the remaining ice-making time updating module 5400 includes: a total ice weight obtaining submodule, which is configured to obtain the total weight of ice cubes actually made in the ice basket after the current ice making is completed; a weight average value calculating submodule, which is configured to calculate the arithmetic average of the total ice weight and the pre-stored reference ice weight corresponding to the target ice making amount; and a reference ice weight updating submodule, which is configured to update the reference ice weight corresponding to the target ice making amount based on the calculated arithmetic average.

[0117] Based on any embodiment of the device of the present application, the total weight acquisition submodule of ice cubes includes: a weight data acquisition submodule, configured to obtain weight data collected by the weighing sensor array distributed at the bottom of the ice basket; an actual total weight update submodule, configured to calculate the average value of the collected weight data as the actual total weight of ice cubes produced.

[0118] Based on any embodiment of the device of the present application, it also includes: an environmental parameter acquisition submodule, which is configured to obtain the ambient temperature and initial water temperature corresponding to the current ice-making environment; a model determination time submodule, which is configured to input the ambient temperature, the initial water temperature, the user-preset target ice-making amount, the total weight of the current water consumption and the corresponding consumption time into the trained remaining time prediction model to obtain the remaining ice-making time of the current ice-making; a time calibration submodule, which is configured to compare the remaining ice-making time output by the remaining time prediction model with the currently displayed remaining time. If there is a deviation, the currently displayed remaining time is calibrated based on the remaining ice-making time.

[0119] On the basis of any embodiment of the device of the present application, the environmental parameter acquisition submodule includes: an environmental parameter recording submodule, which is configured to record the ambient temperature and initial water temperature corresponding to the current ice-making environment when there is a deviation between the calculated remaining ice-making time and the currently displayed remaining time; a training sample set construction submodule, which is configured to construct a training sample set based on the recorded ambient temperature, initial water temperature, the corresponding user-preset target ice-making amount, the total weight of the current water consumption and the corresponding consumption time, and the remaining ice-making time of the current ice-making; a model training submodule, which is configured to input the training sample set into the remaining time prediction model for training, so that it can learn the ability to obtain the remaining ice-making time of the current ice-making based on the ambient temperature and initial water temperature corresponding to the current ice-making environment, the user-preset target ice-making amount, the total weight of the current water consumption and the corresponding consumption time.

[0120] Based on any embodiment of this application, please refer to Figure 9 Another embodiment of the present application further provides a computer device that can serve as a controller in an ice maker. Figure 9As shown, a schematic diagram of the internal structure of a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium of the computer device stores an operating system, a database, and a computer program that encapsulates computer-readable instructions. The database may store a control information sequence. When the computer-readable instructions are executed by the processor, the processor may implement a method for calibrating the remaining time of ice making. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor may execute the method for calibrating the remaining time of ice making of the present application. The network interface of the computer device is used to connect and communicate with a terminal. Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0121] In this embodiment, the processor is used to execute Figure 8 The memory stores the program code and various data required to execute the modules and submodules in the device. The network interface is used to transmit data between user terminals and servers. The memory in this embodiment stores the program code and data required to execute all modules and submodules in the ice making remaining time calibration device of this application. The server can call the server's program code and data to execute the functions of all submodules.

[0122] The present application also provides a non-volatile computer-readable storage medium storing computer-readable instructions, which, when executed by one or more processors, causes the one or more processors to perform the steps of the ice making remaining time calibration method described in any embodiment of the present application.

[0123] Those skilled in the art will appreciate that all or part of the processes in the above-described embodiments of the present application can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes in the above-described embodiments of the method. The aforementioned storage medium can be a computer-readable storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0124] The above description is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for calibrating the remaining time of ice making, characterized in that: include: Real-time monitoring of water level change data obtained by the water level sensor in the water tank to determine the total height of water consumed in the current ice making process; Calculating the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank; Calculate the remaining ice making time for the current ice making process based on the user's preset target ice making volume, the total weight of the currently consumed water, and the corresponding consumption time; Compare the calculated remaining ice-making time with the currently displayed remaining time. If there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice-making time. Monitor and determine the actual ice-making time taken to complete the current ice-making process; Calculating the arithmetic mean of the actual ice-making time and the pre-stored reference ice-making time corresponding to the target ice-making amount; The calculated arithmetic mean value is used as the new benchmark ice-making time for subsequent display of the remaining time.

2. The ice making remaining time calibration method according to claim 1, characterized in that: Based on the user's preset target ice making volume, the total weight of the current water consumption, and the corresponding consumption time, the remaining ice making time of the current ice making is calculated, including: Calculate the difference between the target ice production amount preset by the user and the total weight of the currently consumed water to obtain the remaining ice production amount; multiplying the remaining ice making amount by the consumption time to obtain a first intermediate value; The remaining ice-making time is obtained by dividing the first intermediate value by the total weight of the currently consumed water.

3. The ice making remaining time calibration method according to claim 1, characterized in that: The calculated remaining ice-making time is compared with the currently displayed remaining time. If there is a deviation, the currently displayed remaining time is calibrated based on the calculated remaining ice-making time, including: Get the total weight of ice cubes actually produced in the ice basket after the current ice making is completed; Calculating an arithmetic mean of the total weight of the ice cubes and a pre-stored reference ice weight corresponding to the target ice production amount; The reference ice weight corresponding to the target ice production amount is updated based on the calculated arithmetic mean value.

4. The ice making remaining time calibration method according to claim 3, characterized in that: Get the total weight of ice cubes actually produced in the ice basket after the current ice making is completed, including: Obtaining weight data collected by an array of weighing sensors distributed at the bottom of the ice basket; The average value of the collected weight data is calculated as the total weight of the ice cubes actually produced.

5. The ice making remaining time calibration method according to any one of claims 1, 3-4, characterized in that: include: Get the ambient temperature and initial water temperature corresponding to the current ice-making environment; Input the ambient temperature, the initial water temperature, the target ice making amount preset by the user, the total weight of the currently consumed water, and the corresponding consumption time into the trained remaining time prediction model to obtain the remaining ice making time of the current ice making; The remaining ice-making time output by the remaining time prediction model is compared with the currently displayed remaining time. If there is a deviation, the currently displayed remaining time is calibrated based on the remaining ice-making time.

6. The ice making remaining time calibration method according to claim 5, characterized in that: Before obtaining the ambient temperature and initial water temperature corresponding to the current ice-making environment, the following steps are included: When the calculated remaining ice-making time deviates from the currently displayed remaining time, the ambient temperature and initial water temperature corresponding to the current ice-making environment are recorded; The recorded ambient temperature, initial water temperature, corresponding user-preset target ice making amount, total weight of current water consumption and corresponding consumption time, and the remaining ice making time of the current ice making are used to construct a training sample set; The training sample set is input into the remaining time prediction model for training, so that it can learn the ability to obtain the remaining ice-making time of the current ice-making based on the ambient temperature and initial water temperature corresponding to the current ice-making environment, the user's preset target ice-making amount, the total weight of the current water consumption, and the corresponding consumption time.

7. A device for calibrating the remaining time of ice making, characterized in that: include: A height value determination module is configured to monitor in real time the water level change data obtained by a water level sensor provided in the water tank to determine the total height value of water consumed in the current ice making process; a total weight determination module configured to calculate the total weight of water consumed in the current ice-making process based on the total height value and the cross-sectional area of the water tank; The remaining ice making time calculation module is configured to calculate the remaining ice making time of the current ice making process based on the target ice making amount preset by the user, the total weight of the currently consumed water, and the corresponding consumption time; a remaining ice-making time updating module configured to compare the calculated remaining ice-making time with the currently displayed remaining time, and if there is a deviation, calibrate the currently displayed remaining time based on the calculated remaining ice-making time; The actual ice making time determination submodule is configured to monitor and determine the actual ice making time consumed by the current ice making process; an average value calculation submodule, configured to calculate the arithmetic average of the actual ice-making time and the pre-stored reference ice-making time corresponding to the target ice-making amount; The reference ice-making time updating submodule is configured to use the calculated arithmetic mean as the new reference ice-making time for displaying the subsequent remaining time.

8. An ice making machine, characterized in that: The invention comprises a controller and at least one ice maker, wherein the controller is used to execute the steps of the method according to any one of claims 1 to 6 to calibrate the remaining time for ice making of the ice maker.

9. A computer-readable storage medium, characterized in that It stores a computer program implemented according to the method described in any one of claims 1 to 6 in the form of computer-readable instructions, and when the computer program is called and executed by a computer, the steps included in the corresponding method are executed.

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