Cleaning method, cleaning identification system, and electronic device

Abstract

The application relates to a cleaning method, a cleaning identification system and electronic equipment. The cleaning method comprises the following steps: in response to a cleaning instruction, for a plurality of set cleaning stages, collecting electrical parameters of a plurality of to-be-tested liquids at different time nodes in each cleaning stage to represent liquid types; generating an actual electrical parameter change graph corresponding to each cleaning stage according to a plurality of electrical parameters in each cleaning stage and corresponding time nodes; obtaining a target electrical parameter change graph corresponding to each cleaning stage based on a preset mapping model; and obtaining fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage; and judging whether a cleaning process is incorrect based on fitting parameters corresponding to the plurality of cleaning stages. The cleaning method can realize integrity monitoring of a cleaning process and is beneficial to improving the accuracy of cleaning detection.

Description

Technical Field

[0001] This application relates to the field of beverage equipment cleaning technology, and in particular to cleaning methods, cleaning identification systems and electronic equipment. Background Technology

[0002] To improve the beverage production quality of beverage equipment, manufacturers equip it with cleaning modules and programs. Specifically, after each beverage production cycle, the beverage circuit can be repeatedly cleaned with water, and a deep cleaning can be performed daily or after a certain period of use. This ensures the cleanliness of the beverage circuit and prevents flavor contamination.

[0003] In related technologies, to improve the beverage-making effect of beverage equipment, many beverage equipment systems use tablets to clean the brewing unit, pipes, and other components. Specifically, this may involve multiple cleaning steps such as quick wash, medicated wash, and water wash. However, in actual cleaning processes, issues such as tablets not being added, insufficient dosage, or no cleaning solution being output can arise, leading to incomplete cleaning or even no cleaning at all, affecting the cleaning effect and making it difficult to guarantee cleaning quality in practice. Summary of the Invention

[0004] Therefore, it is necessary to provide a cleaning method, a cleaning identification system, and electronic equipment to address the issue of how to improve the integrity of the cleaning process.

[0005] A first aspect of this application provides a cleaning method, comprising: In response to a cleaning command, for multiple set cleaning stages, electrical parameters of multiple test liquids are collected at different time points within each cleaning stage to characterize the liquid type. Based on the multiple electrical parameters and their corresponding time points in each cleaning stage, a graph of actual electrical parameter changes corresponding to each cleaning stage is generated. Based on a preset mapping model, obtain the target electrical parameter change graphs corresponding to each cleaning stage; The fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage are obtained; based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is erroneous.

[0006] In one embodiment, the step of obtaining a fitting parameter between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, and determining whether the cleaning process is erroneous based on the fitting parameters corresponding to each of the multiple cleaning stages, includes: The electrical parameters corresponding to multiple time points in the actual electrical parameter change graph and the target electrical parameter change graph are subtracted to obtain multiple parameter difference values ​​corresponding to multiple time points; The number of parameter differences that are not within a preset difference range within the same cleaning stage is used as the fitting parameter; If the fitting parameter for any one of the multiple cleaning stages exceeds the preset range, the cleaning process is determined to be erroneous.

[0007] In one embodiment, the step of generating an actual electrical parameter change graph for each cleaning stage based on the plurality of electrical parameters and their corresponding time points includes: All electrical parameters within the same cleaning stage are fitted to obtain corresponding baselines or reference bars, such that different cleaning stages correspond to different baselines or reference bars; wherein, within the same cleaning stage, all electrical parameters and the values ​​of the baseline at the corresponding time nodes are within a preset first fluctuation range; any electrical parameter within the same cleaning stage and the threshold value corresponding to the reference bar are within a preset second fluctuation range. Multiple baselines form a line graph or multiple baseline bars form a bar graph, which serves as a graphical representation of the actual electrical parameter changes.

[0008] In one embodiment, all electrical parameters within the same cleaning stage are fitted to obtain corresponding baselines or reference bars, such that different cleaning stages correspond to different baselines or reference bars, including: In each cleaning stage, all electrical parameters that conform to a preset change pattern are obtained and recorded as selected parameters, and the selected parameters and their corresponding time nodes are recorded. The corresponding baseline or baseline bar is obtained by fitting multiple selected parameters and corresponding time nodes.

[0009] In one embodiment, a fitting parameter is obtained between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage; and based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is erroneous, including: Obtain the number of baselines or baseline bars in the actual electrical parameter change graph corresponding to the cleaning stage, and record it as the first number; Obtain the number of calibration lines or calibration bars in the target electrical parameter change graph corresponding to the first cleaning stage, and record it as the second number; The first quantity and the second quantity are recorded as a comparison group. If the first quantity is not equal to the second quantity in any of the comparison groups corresponding to the multiple cleaning stages, it is determined that the cleaning process is incorrect. Wherein, the calibration line is a line segment or polyline graph in the target electrical parameter change graph that corresponds to the cleaning stage of the baseline; the calibration bar is a bar graph in the target electrical parameter change graph that corresponds to the cleaning stage of the baseline bar.

[0010] In one embodiment, the fitting parameters include slope similarity; the slope similarity is negatively correlated with the slope difference between the baseline and the calibration line. Based on the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, a fitting parameter between the two is obtained; and based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is erroneous, including: According to the cleaning instruction, the corresponding cleaning stage of the cleaning solution is obtained from the pre-stored instruction database; Obtain the baseline in the actual electrical parameter change graph corresponding to the drug cleaning stage; Obtain the calibration line in the target electrical parameter change graph corresponding to the drug cleaning stage; wherein, the calibration line is a line segment or polyline graph formed by multiple target parameters in the target electrical parameter change graph corresponding to the cleaning stage of the drug cleaning stage; When the slope similarity is within the first error range, the cleaning process is judged to be correct; When the slope similarity is not within the first error range, it is determined that the cleaning process is incorrect, and a judgment result is generated indicating that the valves and / or pumps involved in executing the cleaning command are faulty.

[0011] In one embodiment, the fitting parameters include shape similarity between images; Based on the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, a fitting parameter between the two is obtained; and based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is erroneous, including: The shape similarity between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage is obtained; multiple cleaning stages correspond one-to-one with multiple shape similarities; If the difference between the shape similarity corresponding to any of the cleaning stages and the preset similarity is not within the second error range, the cleaning process is judged to be erroneous.

[0012] In one embodiment, the cleaning method further includes: According to the cleaning instructions, multiple cleaning steps corresponding to the cleaning instructions are obtained from the pre-stored instruction database and performed in sequence; each cleaning step has a start time node and an end time node when it is executed. Within each cleaning step, the start time node, the end time node, and all time nodes in between are divided into the same cleaning stage, so that multiple cleaning steps correspond one-to-one to form multiple cleaning stages; wherein, the order of the multiple cleaning stages is consistent with the execution order of the multiple cleaning steps.

[0013] In one embodiment, the fitting parameters include electrical parameter similarity; the electrical parameter similarity is negatively correlated with the absolute value of the difference between the electrical parameter and the target parameter at the corresponding time node; The cleaning method further includes: Before the end of each cleaning step, the electrical parameters corresponding to the end time node are obtained; the target parameter is the electrical parameter corresponding to the end time node in the target electrical parameter change graph. When the similarity of the electrical parameters is within the third error range, the cleaning step ends. If the electrical parameter similarity is not within the third error range, the cleaning step is repeated until the electrical parameter similarity is within the third error range.

[0014] In one embodiment, the cleaning method further includes: When the cleaning process is determined to be erroneous, the result of the determination is output and recorded in the cleaning log. And / or, the cleaning method further includes: If an error is detected in the cleaning process, a control command is output to re-execute the cleaning instruction.

[0015] A second aspect of this application provides a cleaning identification system applied to a control component within a beverage equipment; the cleaning identification system includes: A liquid type detection module is used to collect electrical parameters of multiple liquids to be tested at different time points in response to the cleaning command issued by the control component to characterize the liquid type; the liquid type detection module is connected to the pipeline for flowing the liquids to be tested; The main control module is used to receive multiple electrical parameters corresponding to different cleaning stages, and generate actual electrical parameter change graphs based on the multiple electrical parameters and their corresponding time nodes; and obtain target electrical parameter change graphs corresponding to the cleaning instructions based on a locally stored preset mapping model; and obtain fitting parameters between the actual electrical parameter change graphs and the target electrical parameter change graphs, and generate corresponding control instructions based on the fitting parameters.

[0016] According to a third aspect of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the cleaning method described in the above embodiments.

[0017] The aforementioned cleaning method, cleaning identification system, and electronic equipment achieve full-cycle, continuous monitoring of the cleaning process by collecting electrical parameters of multiple liquids at different time points during the cleaning process. This overcomes the problem of missing data at different stages caused by single-point or offline sampling methods, thereby eliminating monitoring blind spots caused by sampling intervals or time lags.

[0018] Furthermore, by using multiple electrical parameters and their corresponding time points to generate actual electrical parameter change graphs, the evolution of liquid type during the cleaning process is transformed into a visualized actual electrical parameter change graph, which preserves the fluctuation, transition and stable state information of the cleaning medium at each stage, which is beneficial for assessing the integrity of the cleaning process.

[0019] Furthermore, by comparing the actual electrical parameter change graphs with the target electrical parameter change graphs corresponding to the cleaning commands, the integrity of the entire cleaning path, rather than a single moment's state, is verified. This enables the identification of defects such as local parameter anomalies, timing deviations, or discontinuous transitions during the cleaning process, thus improving the accuracy of cleaning detection. Simultaneously, control commands are generated based on the fitting parameters between the actual and target electrical parameter change graphs, allowing for timely intervention or feedback when the cleaning process fails to meet standards. This prevents subsequent contamination caused by incomplete cleaning or media residue, ensuring the integrity of the cleaning command execution. Attached Figure Description

[0020] Figure 1 This is a schematic diagram illustrating the interaction between the cleaning identification module and the control component in one embodiment.

[0021] Figure 2 This is a schematic flowchart of a cleaning method shown in one embodiment.

[0022] Figure 3 for Figure 2 The diagram shows a detailed process flow for step S200.

[0023] Figure 4 This is a schematic flowchart of a cleaning method shown in another embodiment.

[0024] Figure 5 for Figure 3 The diagram shows a detailed process flow for step S210.

[0025] Figure 6 for Figure 1 The diagram shows a detailed process flow of step S400 in one example shown.

[0026] Figure 7 for Figure 1 A detailed flowchart of step S400 is shown in another example.

[0027] Figure 8 for Figure 1 A detailed flowchart of step S400 is shown in another example.

[0028] Figure 9 for Figure 1 A detailed flowchart of step S400 is shown in the other examples.

[0029] Figure 10 This is a graph showing the change in target electrical parameters during a cleaning command, as illustrated in one embodiment.

[0030] Figure 11 This is a graph showing the change in target electrical parameters during another cleaning command as illustrated in one embodiment.

[0031] Figure 12 for Figure 1 The following is a detailed flowchart of step S400 in another example shown.

[0032] Explanation of reference numerals in the attached figures: 100. Liquid type detection module; 200. Main control module; 300. Control components. Detailed Implementation

[0033] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0034] One aspect of this application, such as Figure 1As shown, a cleaning identification system is provided, applied to a control component 300 within a beverage equipment. The cleaning identification system includes a liquid type detection module 100 and a main control module 200.

[0035] The liquid type detection module 100 is used to collect electrical parameters of multiple liquids to be tested at different time points in response to the cleaning command issued by the control component 300 to characterize the liquid type; the liquid type detection module 100 is connected to the pipeline for the flow of the liquid to be tested.

[0036] The main control module 200 is used to receive multiple electrical parameters corresponding to different cleaning stages, and generate actual electrical parameter change graphs based on the multiple electrical parameters and their corresponding time nodes; and obtain target electrical parameter change graphs corresponding to cleaning instructions based on a locally stored preset mapping model; and obtain fitting parameters between the actual electrical parameter change graphs and target electrical parameter change graphs, and generate corresponding control instructions based on the fitting parameters.

[0037] To facilitate understanding of how to use the cleaning identification system, such as Figure 2 As shown, another aspect of this application provides a cleaning method.

[0038] Specifically, the cleaning methods include: S100, In response to a cleaning command. For multiple set cleaning stages, electrical parameters of multiple test liquids are collected at different time points within each cleaning stage to characterize the liquid type.

[0039] The cleaning command includes multiple cleaning stages. When a cleaning command is received, the probe on the liquid type detection module 100 receives an excitation signal, and the voltage or current value of the excitation signal remains consistent at different time points. Because the liquid flowing in the pipeline changes as the cleaning stages progress, the electrical signal at different time points will exhibit range-bound fluctuations. These fluctuations are converted by components such as an analog-to-digital converter to obtain current or voltage values. According to Ohm's law, the resistance value of the flowing liquid can be calculated from the aforementioned voltage or current values, and this resistance value serves as an electrical parameter characterizing the liquid type.

[0040] The detection of cleaning commands can be achieved in several ways: for example, the beverage equipment issues a prompt signal while executing the cleaning command, and the liquid type detection module 100 performs electrical parameter acquisition upon receiving the signal; another example is that when the pipeline changes from a liquid-free state to a liquid-containing state, the probe of the liquid type detection module 100 switches from an open circuit to a closed circuit, and the electrical signal changes significantly. If the electrical signal changes from infinity to a finite value, it can be determined that there is liquid in the pipeline, thereby triggering the liquid type detection module 100 to start electrical parameter acquisition.

[0041] S200. Based on the multiple electrical parameters and their corresponding time points in each cleaning stage, generate a graph showing the actual electrical parameter changes corresponding to each cleaning stage.

[0042] In this process, multiple time points and their corresponding electrical parameters can be packaged and sent to the corresponding processing unit, which will then process the data to generate a graph of actual electrical parameter changes with the time points as the horizontal axis and the electrical parameters as the vertical axis; alternatively, a graph of actual electrical parameter changes with the electrical parameters as the horizontal axis and the time points as the vertical axis can also be generated.

[0043] S300: Based on a preset mapping model, obtain the target electrical parameter change graph corresponding to the cleaning stage.

[0044] Understandably, the preset mapping model stores multiple time points and corresponding electrical parameter values ​​for multiple cleaning stages, reflecting the level of change in electrical parameters at different cleaning stages. The actual test time point is the same as the time point in the preset model. However, due to the differences in cleaning stages and cleaning solutions in different cleaning processes, the corresponding electrical parameter change patterns also differ.

[0045] Based on this, the target electrical parameter change graphs obtained at the corresponding cleaning stages can clearly reflect the electrical parameter change patterns at different time points during the ideal cleaning process, thus providing a reliable reference for judging whether the actual cleaning process is erroneous.

[0046] S400. Based on the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, obtain the fitting parameters between the two, and based on the fitting parameters corresponding to each of the multiple cleaning stages, determine whether there is an error in the cleaning process.

[0047] Fitting parameters may include, but are not limited to, the consistency between the number of polylines within the image, image shape similarity, and image numerical similarity. Based on the fitting parameters corresponding to each of the multiple cleaning stages, it is possible to determine whether there are errors in the cleaning process. This not only helps to determine whether there are errors in the entire cleaning process, but also helps to determine whether there are errors in each cleaning stage, ensuring the accuracy of cleaning detection, providing a reliable reference for cleaning decisions, and thus helping to improve the subsequent cleaning effect.

[0048] Optionally, in one example, after determining whether the cleaning process is erroneous, a control command can be generated based on the determination result. The control command can take various forms, including judgment commands such as "cleaning without error" or "cleaning error," as well as action commands such as "repeat cleaning" or "stop cleaning." After responding to the action command, the beverage equipment will execute the corresponding cleaning action.

[0049] The above embodiments achieve continuous monitoring of the cleaning process by collecting electrical parameters of multiple test liquids at different time points during the cleaning phase. This overcomes the problem of missing data at certain stages caused by single-point or offline sampling methods, thereby minimizing monitoring blind spots caused by sampling time lags. Furthermore, by generating actual electrical parameter change graphs using multiple electrical parameters and their corresponding time points, the evolution of liquid type during cleaning is transformed into a visualized graph of actual electrical parameter changes. This preserves the fluctuation, transition, and stable state information of the cleaning medium at each stage, facilitating the assessment of cleaning integrity. In addition, based on the fitted parameters corresponding to each of the multiple cleaning stages, errors in the cleaning process can be determined. This not only helps determine whether there are errors throughout the entire cleaning process but also at each stage, ensuring the accuracy of cleaning detection and providing a reliable reference for cleaning decisions, thus contributing to improved subsequent cleaning results.

[0050] To facilitate understanding of the above cleaning method, some example scenarios will be used for illustration below.

[0051] Electrical parameters can be converted into electrical signal values ​​(i.e., AD values) by an analog-to-digital converter. The electrical signal values ​​can indirectly reflect the conductivity of the liquid. Different types and dilution ratios of liquids have different conductivity, and the TDS values ​​of the liquids measured by a TDS meter are also different. Therefore, the liquid type can be identified by detecting the electrical signal values ​​of the liquid, such as voltage or current changes or TDS values ​​measured by a TDS meter, at least one of the electrical signal values.

[0052] In this example scenario, referring to the changes in electrical parameters of different solution formulations in Table 1 below, five experimental subjects were used. Four of these subjects—milk cleaning tablets, milk, coffee cleaning tablets, and espresso—were diluted with purified water from a water purifier at certain ratios to obtain corresponding solutions. Since the amount of cleaning solution used in the milk circuit system and the coffee brewing system of the beverage equipment is different, the dilution ratios for the two systems were different in the experiment. For the milk circuit system, the diluent volumes were 0.5L, 1L, and 2L, respectively; for the coffee brewing system, the diluent volumes were 0.4L, 0.8L, and 1.6L, respectively. The electrical parameters of the diluted solutions and the control purified water were tested, and the test results are shown in Table 1 below.

[0053] Table 1. Variation of electrical parameters in different solution formulations

[0054] As can be observed from Table 1, there are significant differences in the electrical TDS and AD values ​​of the cleaning agent (tablets used in the experiment), purified water, or aqueous solutions containing residual milk or coffee, and purified water. Furthermore, the electrical parameters also differ for different dilution ratios of the same solute. Therefore, the TDS or AD values ​​of the known experimental objects can be used as target electrical parameters and as indicators to determine whether a corresponding target cleaning agent exists. By comparing the actual electrical parameters of each cleaning stage with the target electrical parameters, and by analyzing the comparison results (such as the number of parameters that meet the conditions or the trend of change), the fitted parameters can be characterized, and it can be determined whether there are any errors in the cleaning process.

[0055] For example, taking milk cleaning tablets as the target cleaning agent and the milk system's liquid cleaning phase as an example, the target electrical parameter values ​​at multiple different time points during this liquid cleaning phase can be determined in advance through experiments. This serves as a preset mapping model, and the changes in these multiple target electrical parameters can be generated based on the corresponding acquisition times. Figure 11 In the middle (2-2) section, based on the actual electrical parameters collected at the corresponding cleaning stage and time node in the actual cleaning process, a graph of actual electrical parameter changes is generated. The two are then fitted to obtain the fitting parameters in order to determine whether there is an error in the cleaning process of the cleaning stage of the drug solution.

[0056] In some embodiments, such as Figure 3 As shown, step S200 above includes: S210. Fit all electrical parameters within the same cleaning stage to obtain the corresponding baseline or reference bar, so that different cleaning stages correspond to different baselines or reference bars.

[0057] Within the same cleaning phase, all electrical parameters and the values ​​of the baseline at the corresponding time nodes are within a preset first fluctuation range, while any electrical parameter within the same cleaning phase is within a preset second fluctuation range, corresponding to the threshold value of the baseline column.

[0058] It is understandable that in the actual cleaning process, the same liquid is used to clean the beverage circuit during the cleaning stage, and the electrical parameters detected in the pipeline will be similar or even the same. Multiple electrical parameters in the same cleaning stage will show a specific trend (such as rising or falling, stable fluctuations that are close to a straight line, or fluctuations concentrated around a certain value). Therefore, the electrical parameters in the same cleaning stage that conform to the same specific trend can be fitted into a baseline or reference bar.

[0059] Taking water cleaning as an example, the electrical parameters detected during the cleaning process are similar to or consistent with the resistance value of water. Therefore, they can be fitted into a straight line as a baseline or a fixed value as a reference column.

[0060] Taking chemical cleaning as an example: In one chemical cleaning scenario, the diluted solution is injected into a container holding the cleaning agent, and then the cleaning solution is quantitatively delivered into the pipeline in batches through the connection between the pipeline inlet and the container. At this time, the electrical parameters detected in the pipeline are similar to or consistent with the resistance value of the cleaning solution, so they can be fitted as a straight line as a baseline or a fixed value as a reference column.

[0061] In another medicated cleaning scenario, a container is pre-filled with liquid cleaning agent, and then a measured amount of diluent is injected into the container sequentially, through which the cleaning solution is fed into the pipeline. In this case, because the degree of dilution changes with each injection of diluent, the electrical parameters detected at different time points will show a specific trend (the resistance value gradually approaches the resistance value of the diluent). Therefore, within the same cleaning stage, a sloping line can be fitted as a baseline.

[0062] In this way, fitting all electrical parameters within the same cleaning stage to obtain corresponding baselines or reference bars can effectively suppress local random errors caused by liquid turbulence, bubbles, instantaneous fluctuations in sensors, or sampling noise of electrical parameters. Compared with directly using the original discrete points, the fitted baselines or reference bars can reflect the stable characteristics of the liquid type within the cleaning stage, avoiding interference from single-point anomalies in determining the integrity of the cleaning process, thereby improving the reliability of monitoring results.

[0063] Furthermore, this helps reduce the amount of parameter calculation required for fitting the target electrical parameter change graph and the actual electrical parameter change graph. It eliminates the need to compare the electrical parameters corresponding to multiple time points one by one, and only requires comparison through baselines or baseline bars, which helps improve the efficiency of cleaning and detection.

[0064] Furthermore, fitting the electrical parameters corresponding to multiple time points into baselines or reference bars can eliminate redundant time differences between time points, ensure the integrity of the actual electrical parameter change graph, and thus obtain the complete change trend of the cleaning process. This facilitates the overall analysis and evaluation of whether the cleaning is thorough, and improves the comprehensiveness of cleaning detection.

[0065] S220, multiple baselines form a line graph or multiple baseline bars form a bar graph, which serves as a graph of actual electrical parameter changes.

[0066] Thus, a line graph composed of multiple baselines or a bar chart composed of baseline bars can uniformly map the changes in electrical parameters during different cleaning stages into a graphical structure with clear amplitude and order. This actual electrical parameter change graph is easy to fit and compare with the target electrical parameter change graph segment by segment and trend by trend, and can clearly identify the overall deviation within a certain cleaning stage (rather than isolated point deviations). Therefore, it is possible to determine whether there are any errors in the cleaning process throughout the entire cleaning process, thereby improving the accuracy of the cleaning process assessment.

[0067] Furthermore, in one example, by independently fitting a baseline or benchmark bar in each cleaning stage, and using different numbers of time nodes or sampling frequencies in different cleaning stages, it is possible to increase the number of electrical parameter samples and reasonably participate in the fitting during critical cleaning stages (such as the chemical cleaning agent injection stage), and to appropriately sparsely sample during stable stages. Ultimately, a complete actual electrical parameter change graph covering the entire cleaning process can still be formed, avoiding process data loss or distortion caused by differences in sampling strategies, thereby improving the accuracy of judgment throughout the cleaning process.

[0068] Optionally, in one embodiment, as Figure 4 As shown, the above cleaning method includes: S001. According to the cleaning instruction, obtain the multiple cleaning steps corresponding to the cleaning instruction in sequence from the pre-stored instruction database.

[0069] Each cleaning step has a corresponding start time node and end time node.

[0070] S002. Within each cleaning step, the start time node, the end time node, and all time nodes in between are divided into the same cleaning stage, so that multiple cleaning steps correspond one-to-one to form multiple cleaning stages.

[0071] The order in which the multiple cleaning stages are arranged is consistent with the execution order of the multiple cleaning steps.

[0072] Specifically, the instruction database stores multiple cleaning steps corresponding to each cleaning instruction, as well as the execution stage required for each cleaning step, which serves as the corresponding cleaning stage. This helps determine whether each cleaning step is erroneous and confirms whether each cleaning step has been executed. It also allows for a clear determination of the integrity of a specific cleaning step (e.g., electrical parameters not meeting expectations in the alkaline washing stage), rather than a general judgment that the entire cleaning process is abnormal. Ultimately, this achieves refined integrity monitoring of each cleaning step and the relationships between them.

[0073] In one example, this division method allows for the fitting of a baseline or benchmark bar for each cleaning step, and independent comparison with the target benchmark electrical parameters of the corresponding step in the target electrical parameter change graph, thereby improving the reference value of the cleaning process detection.

[0074] In some embodiments, such as Figure 5 As shown, step S210 above includes: S211. In each cleaning stage, all electrical parameters that conform to the preset change law in that cleaning stage are obtained and recorded as selected parameters, and the selected parameters and their corresponding time nodes are recorded.

[0075] In actual cleaning processes, outlier electrical parameters may be generated due to factors such as momentary sensor failure, brief liquid turbulence, bubble interference, or electromagnetic noise. At the same time, the fluctuation range of electrical parameters and noise levels of different cleaning steps (such as alkaline washing, acid washing, and water washing) within the same cleaning stage may also lead to the occurrence of a small number of outlier electrical parameters.

[0076] By selecting electrical parameters that conform to a preset variation pattern as input parameters, the parameters involved in the fitting can more realistically reflect the typical electrical characteristics of the liquid under test during the cleaning stage, avoiding the traction and distortion of the baseline or reference column by abnormal electrical parameters, thereby reducing the detection error caused by inaccurate data acquisition.

[0077] Among them, all electrical parameters that conform to the preset change law can have multiple judgment conditions.

[0078] In one judgment condition, the mode, median or mean of all electrical parameters within the same cleaning stage are taken as the standard value. Electrical parameters that conform to the preset change pattern refer to electrical parameters whose difference from the standard value is within the preset range.

[0079] It is understandable that most, if not all, time points within the same cleaning stage correspond to the execution process of the same cleaning step. Therefore, the levels of most electrical parameters acquired by the liquid type detection module 100 will tend to be similar. If discrete parameters appear, they can be considered to belong to other cleaning steps or cleaning errors and should be discarded. Thus, this standard value can be regarded as the electrical parameter corresponding to the current cleaning step, which can truly reflect the electrical parameter level during the execution of this step. In addition, using the mode, median, or mean as the standard value can not only ensure the reference value of electrical parameters within the same cleaning stage, but also reduce the calculation difficulty—eliminating the need for complex calculations and improving the efficiency of cleaning detection.

[0080] In another criterion, all electrical parameters conforming to a preset change pattern refer to all electrical parameters within the same cleaning stage exhibiting an upward or downward trend, or all electrical parameters in that section can be fitted to the same broken line, and the numerical deviation of each electrical parameter from the corresponding point on that broken line is within a preset range. Furthermore, for electrical parameters with different change patterns, those with the same change pattern can be grouped together. Thus, electrical parameters conforming to different change patterns within the same cleaning stage can be divided into multiple groups, each group of electrical parameters can be fitted to form a broken line, resulting in multiple broken line segments within the same cleaning stage.

[0081] In one example, the preset variation pattern refers to a variation pattern that conforms to at least one or more combinations of linear function and constant function graphs. Thus, in the actual cleaning process, especially during the drug injection, mixing, or reaction stages, the electrical parameters may not follow a single variation pattern. For example, the electrical parameters during the drug concentration increase or decrease stage may exhibit a linear function increase, while during the stable injection stage, they may exhibit a constant function level. This embodiment allows, within the same cleaning stage, electrical parameters conforming to different preset variation patterns to be divided into independent groups and fitted into multiple segmented line graphs. The actual electrical parameter variation graph formed by these line graphs can reflect the multiple variation characteristics of different stages within a single cleaning step, avoiding information loss or morphological distortion caused by forcibly fitting a complex process to a single trend, thereby improving the completeness of cleaning monitoring.

[0082] S212. Based on multiple selected parameters and corresponding time points, the corresponding baseline or reference bar is obtained by fitting.

[0083] This improves the reference value of the baseline or benchmark column, thereby enhancing the accuracy of subsequent judgments on the integrity of the cleaning process.

[0084] It should be noted that there are multiple methods for determining whether the cleaning process is erroneous in step S300 above, based on the fitting parameters corresponding to each of the multiple cleaning stages. For example, the value of the fitting parameter can be used to determine whether the cleaning process is erroneous: when the fitting parameter is less than a preset range, it indicates that the cleaning process under this cleaning command is relatively complete and no further cleaning is needed, so the cleaning process is judged to be erroneous; when the fitting parameter is greater than or equal to the preset range, it indicates that the cleaning process after this cleaning command is executed is incomplete or has an error, so the cleaning process is judged to be erroneous.

[0085] In some embodiments, such as Figure 6 As shown, the fitting parameters may include the consistency of the number of baselines or baseline bars.

[0086] Step S400 includes: S410. Obtain the number of baselines or baseline bars in the actual electrical parameter change graph corresponding to a cleaning stage, and record it as the first quantity.

[0087] The first number of the baseline or baseline bar in the actual electrical parameter change graph corresponds to the number of cleaning stages actually performed during the cleaning process, that is, the number of cleaning steps actually completed.

[0088] S420. Obtain the number of calibration lines or calibration bars in the target electrical parameter change graph corresponding to the cleaning stage, and record it as the second quantity.

[0089] The calibration line is a line segment or polygonal line in the target electrical parameter change graph that corresponds to the cleaning stage of the baseline; the calibration bar is a bar graph in the target electrical parameter change graph that corresponds to the cleaning stage of the reference bar. If the cleaning process is complete, the number of baselines or reference bars in the actual electrical parameter change graph should be consistent with the number of calibration lines or calibration bars in the target electrical parameter change graph.

[0090] S430. Record the first quantity and the second quantity as a comparison group. If the first quantity is not equal to the second quantity in any of the comparison groups corresponding to multiple cleaning stages, then the cleaning process is judged to be incorrect.

[0091] Thus, by comparing whether the first quantity and the second quantity are equal, it is possible to directly determine whether there are missing steps (such as a step not being executed) or redundant steps (such as the insertion of unexpected steps) in the cleaning process. When the first quantity is not equal to the second quantity, it is not necessary to rely on the specific amplitude or shape of each baseline to directly generate a judgment result indicating that the cleaning process is erroneous. This reduces the computational difficulty of electrical parameter comparison and improves the efficiency of judging the integrity of the cleaning process. At the same time, it can also accurately identify errors such as electrical parameter amplitudes being within the normal range, but cleaning steps being skipped or repeated due to valve malfunctions, thereby reducing the risk of misjudgment and improving the accuracy of judging the integrity of the cleaning process.

[0092] In one embodiment, the cleaning method further includes: when the first quantity is not equal to the second quantity, generating a judgment result indicating an error in the cleaning process and recording it in the cleaning log. Currently, when the first quantity is not equal to the second quantity, a judgment result indicating an error in the cleaning process can be obtained and recorded in the cleaning log, providing a clear basis for subsequent quality traceability, equipment maintenance, or process optimization.

[0093] In another embodiment, when the first quantity equals the second quantity, the cleaning process is deemed error-free. When the first quantity equals the second quantity, a judgment result indicating that the cleaning process is error-free can be generated. This step can determine whether there are any errors in the process structure within the cleaning steps. However, it should be noted that the result obtained in this step only indicates that the quantity completeness of the cleaning steps is satisfied, but it does not guarantee that the amplitude or trend of electrical parameters in each step meets the target requirements. To determine whether the parameter quality is error-free, further refined comparisons of other fitted parameters (such as slope, amplitude difference, area difference, or threshold comparison, etc.) can be carried out subsequently, which will be illustrated with examples later.

[0094] In one example, when the first quantity is not equal to the second quantity, a judgment result indicating an error in the cleaning process is generated and recorded in the cleaning log, which provides a clear basis for subsequent quality traceability, equipment maintenance or process optimization.

[0095] Optionally, in one embodiment, the fitting parameters include slope similarity. Slope similarity is negatively correlated with the slope difference between the baseline and the calibration line.

[0096] like Figure 7 As shown, step S400 above includes: S440. According to the cleaning instruction, obtain the corresponding chemical cleaning stage from the pre-stored instruction database.

[0097] S450, Obtain the baseline in the graph of actual electrical parameter changes corresponding to the cleaning stage of the medicine solution.

[0098] Understandably, in the actual cleaning process, the step that has the greatest impact on the cleaning effect is the chemical washing step. If the chemical washing concentration is insufficient, residues (such as grease) from the previous beverage preparation process will still remain in the pipeline. Based on this, by obtaining data for the chemical washing stage and the corresponding baseline, we can reflect the level of change in the resistance value (i.e., the level of change in concentration) of the cleaning solution during the chemical washing stage, which can provide a reference for detecting the cleaning effect.

[0099] Specifically, when valves and / or pumps connected to the pipeline in the beverage equipment malfunction, the amount of cleaning solution used in each batch may vary. Consequently, the residual cleaning solution concentration detected by the liquid type detection module 100 after cleaning the beverage preparation circuit will also differ, resulting in fluctuations in the baseline. In an ideal cleaning process, the amount of cleaning solution used in each batch is consistent. Consequently, the residual cleaning solution concentration detected by the liquid type detection module 100 after cleaning the beverage preparation circuit will tend to be consistent, and the corresponding baseline in an ideal cleaning process without hardware malfunctions will approach a straight line.

[0100] S460. Obtain the calibration line in the graph of the target electrical parameter change corresponding to the drug cleaning stage.

[0101] Based on the above analysis, the slope similarity between the baseline and the calibration line reflects the abnormal rate of change in the concentration of the medicine. This abnormal rate of change is generally not due to inconsistent amounts of cleaning reagents loaded in the container, but rather to valve and / or pump malfunctions that lead to unstable output flow rates, resulting in inconsistent dilution. Therefore, slope similarity can reflect whether there are any abnormalities in the hardware of the beverage preparation equipment.

[0102] S470. Determine whether the slope similarity is within the first error range.

[0103] If the slope similarity is within the first error range, the cleaning process is considered to be correct.

[0104] Specifically, when the slope similarity is within the first error range, it indicates that the output flow of the valves and / or pumps is stable during each batch of cleaning, thus confirming that the cleaning process is correct. In one example, the result of confirming the cleaning process is correct can be recorded in the cleaning log so that maintenance personnel can monitor the cleaning status throughout the entire process.

[0105] If the slope similarity is not within the first error range, the cleaning process is judged to be erroneous, and a judgment result is generated indicating that the valves and / or pumps involved in executing the cleaning command are erroneous.

[0106] Errors in valves and / or pumps can include, but are not limited to, abnormal valve opening speed or unstable pump output flow during the chemical cleaning process. In one example, when a valve and / or pump malfunctions, the relevant information is recorded in the cleaning log, facilitating fault analysis and repair by maintenance personnel, improving maintenance response speed, and thus ensuring the quality of subsequent cleaning.

[0107] In other embodiments, the fitting parameters include shape similarity between images. For example... Figure 8 As shown, step S400 above includes: S401. Obtain the shape similarity between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage.

[0108] The multiple cleaning stages correspond to multiple shape similarity scores. The more similar the shapes of two graphics, the higher their shape similarity score.

[0109] S402. If the difference between the shape similarity corresponding to any cleaning stage and the preset similarity is not within the second error range, it is determined that the cleaning process is incorrect.

[0110] Understandably, when the difference between the shape similarity and the preset similarity is within the second error range, in addition to ensuring that the slopes of the baselines and calibration lines corresponding to each cleaning stage are consistent, it is also necessary to ensure that the number of multiple baselines or baseline columns formed by multiple cleaning steps corresponding to multiple cleaning stages is consistent. At the same time, when comparing the shape similarity of the actual electrical parameter change graph composed of all electrical parameters with the target electrical parameter change graph, the two must also maintain similarity in global morphological features such as rising / falling trends, peak positions, curvature changes, and shape lengths.

[0111] In other words, this solution enables full-process detection during the cleaning stage, effectively avoiding false detections caused by differences in image shape or inconsistent image length even when the number, slope, and amplitude parameters of the baselines or reference pillars corresponding to each cleaning step are normal. This improves the comprehensiveness of cleaning detection and thus enhances its accuracy.

[0112] In one example, shape similarity is related to whether the trends of the baseline and calibration line are consistent. Taking the water washing stage as an example, this stage refers to cleaning the beverage equipment with clean water. If the trend of both the baseline and calibration line is detected to be flat, then the current shape similarity can be considered high (within the second error range of the preset similarity). Taking the residual liquid cleaning stage as another example, this stage refers to cleaning the beverage equipment with clean water to remove residual liquid. If the trend of both the baseline and calibration line is detected to be gradually rising, then the current shape similarity can be considered high (within the second error range of the preset similarity).

[0113] It should be noted that the execution order of steps S401, S402 and S410, S420, S430, S440, S450, S460 and S470 can be adjusted according to actual usage requirements.

[0114] In one example, steps S401 and S402 have a higher execution priority than steps S410, S420, S430, S440, S450, S460, and S470. Specifically, if a judgment result indicating an error in the cleaning process is obtained after steps S401 and S402, steps S410, S420, and S430, and / or steps S440, S450, S460, and S470 can be executed sequentially. This allows for further analysis of the cleaning process error to determine whether the problem stems from incomplete cleaning steps or hardware issues such as valve and / or pump malfunctions, thereby improving the accuracy of the cleaning process. Furthermore, compared to comparing the electrical parameters in the target electrical parameter change graph with the actual electrical parameter change graph one by one at the same time point, this embodiment is beneficial for improving detection efficiency.

[0115] In another example, steps S410, S420, and S430 are executed sequentially, and / or steps S440, S450, S460, and S470 are executed sequentially, with a higher execution priority than steps S401 and S402. Specifically, when a judgment result indicating that the cleaning process is error-free is obtained through steps S410, S420, and S430, and / or when a judgment result indicating that the cleaning process is error-free is obtained through steps S440, S450, S460, and S470, steps S401 and S402 can be executed sequentially to further confirm whether the entire cleaning process is complete and consistent. Only when the difference between the shape similarity and the preset similarity is within the second error range is a final judgment result indicating that the cleaning process is error-free generated. This improves the reliability of cleaning detection and simplifies the calculation steps in case of errors in the cleaning process, thereby improving detection efficiency.

[0116] In some embodiments, the fitting parameters include electrical parameter similarity. Combined with step S002 above, such as... Figure 9 As shown, the cleaning method also includes: S500: Before the end of each cleaning step, obtain the electrical parameters corresponding to the end time node.

[0117] The electrical parameter similarity is negatively correlated with the absolute value of the difference between the electrical parameter and the target parameter at the corresponding time node. The target parameter is the electrical parameter corresponding to the end time node in the graph of the change of the target electrical parameter.

[0118] Thus, the electrical parameters corresponding to the end time point reflect the liquid resistance value in the pipeline before the current cleaning step ends, and can be used to determine whether the cleaning step is complete. The more thorough the cleaning, the fewer contaminants can be carried away by the cleaning liquid in the beverage preparation circuit, and the closer the liquid resistance value in the pipeline is to the resistance value of the cleaning liquid itself. For example, the more thorough the cleaning, the more consistent the AD value (i.e., electrical parameter) obtained by the digital-to-analog converter after the electrical signal detected by the liquid type detection module 100 is with the AD value (i.e., target parameter) of the cleaning solution (such as water or special cleaning solution) used in this step.

[0119] Based on this principle, the similarity of electrical parameters can be used to determine whether the cleaning step is complete, thereby ensuring the quality of each cleaning step.

[0120] S600. Determine whether the similarity of electrical parameters is within the third error range.

[0121] When the electrical parameter similarity is within the third error range, the cleaning step ends.

[0122] If the electrical parameter similarity is not within the third error range, the cleaning step is repeated until the electrical parameter similarity is within the third error range.

[0123] Therefore, when the electrical parameter similarity is outside the third error range, it is usually because contaminants in the pipeline have not been completely cleaned and have mixed with the cleaning fluid in the pipeline, indicating that the current cleaning step has not been thoroughly completed. In this case, repeating the cleaning step can ensure the cleaning quality of the step.

[0124] To improve the efficiency of cleaning and inspection, optionally, in one embodiment, steps S400 and S500 can be performed only during the last cleaning step. It is understood that the last cleaning step is mostly a water rinsing process, the purpose of which is to remove residual cleaning solution from the pipeline to avoid affecting subsequent beverage preparation. Therefore, inspection can be specifically performed during the last cleaning step: if the electrical parameter similarity is not within the third error range, it indicates that cleaning solution still remains in the pipeline. Repeating this cleaning step ensures that the cleaning solution is thoroughly rinsed away, thereby improving the reliability of beverage preparation; at the same time, eliminating the need for multiple inspections also helps improve the efficiency of cleaning and inspection.

[0125] To better understand the principle behind using one or more of the following parameters—the number of baselines or reference pillars, the slope similarity of baselines, the shape similarity of image components, and the electrical parameter similarity—as fitting parameters in the above embodiments, this embodiment provides various cleaning processes as examples.

[0126] Figure 10 The image shows the ideal target electrical parameter changes when a cleaning command is issued for cleaning the rinsing module.

[0127] Specifically, such as Figure 10 As shown, the cleaning command from control component 300 for the brewing module includes three main steps: Step A, Step B, and Step C. First, Step A: a first rinse with clean water, which removes any remaining beverage residue from the brewing circuit. Second, Step B: a cleaning solution rinse, which uses a cleaning solution to break down and remove residual contaminants from the brewing circuit, dissolving them and flushing them out with the solution. Finally, Step C: a second rinse with clean water, which removes any remaining contaminants and cleaning solution from the brewing circuit to prevent interference with subsequent beverage preparation.

[0128] from Figure 10As can be seen, under ideal conditions, the curves showing the change of electrical parameters over time can be divided into corresponding cleaning stages based on the number of cleaning steps. This example includes three cleaning steps, thus corresponding to three cleaning stages: the cleaning stage corresponding to step A is denoted as a, which is the water rinsing stage. In this stage, the baselines for multiple electrical parameters are horizontal straight lines, indicating that the change trend of electrical parameters in step A is relatively gentle. Similarly, the cleaning stage corresponding to step B is denoted as b. Since the concentration of the medicine solution remains constant, its electrical parameter baseline is also a horizontal straight line. The cleaning stage corresponding to step C is denoted as c, and the electrical parameter baseline in this stage is also a horizontal straight line. This is because, during the medicine solution cleaning stage, due to the reset action of the brewing module during multiple cleaning cycles, the cleaned medicine solution is basically not left in the brewer, and the cleaning medicine solution has been discharged from the brewing circuit with the impact of the brewer within the brewing module, so there is not much residue left in the circuit. Therefore, the electrical parameters in cleaning stage c are mostly close to the electrical parameters of water.

[0129] Figure 11 The image shows the ideal target electrical parameter changes when a cleaning command is issued for cleaning dairy beverage pipelines.

[0130] Specifically, such as Figure 11 As shown, the cleaning instructions of the control component 300 for cleaning dairy beverages include four steps, namely steps (1), (2), (3), and (4). First, step (1): the first water rinsing step, which is to rinse the beverage residue in the beverage making circuit with clean water; second, step (2): the cleaning solution cleaning step, which is to decompose and clean the residual contaminants in the beverage making circuit with cleaning solution, so that the contaminants are dissolved into the solution and carried out of the beverage making circuit; then, step (3): the second water rinsing step, which is to clean the residual contaminants and cleaning solution in the beverage making circuit with clean water to avoid interfering with the subsequent beverage making; finally, step (4): the third cleaning and rinsing step, which is to rinse the beverage making circuit of the beverage equipment with the final cleaning to ensure the reliability of the cleaning.

[0131] from Figure 11As can be seen, under ideal conditions, the curves of electrical parameters changing with time can be divided into corresponding cleaning stages according to the number of cleaning steps. Referring to Table 1 above, different liquids can exhibit different electrical parameters. This example contains four cleaning steps, and therefore corresponds to four cleaning stages: the cleaning stage corresponding to step (1) is denoted as (1-1), which is the stage of emptying residual milk from the pipeline. The baseline formed by multiple electrical parameters in this stage is a straight line, indicating that the change of electrical parameters in step (1) tends to be gradual; similarly, the cleaning stage corresponding to step (2) is denoted as (2-2), which is the stage of cleaning with chemical solution. The baseline formed by its electrical parameters is also a straight line; the cleaning stage corresponding to step (3) is denoted as (3-3), which is the stage of cleaning with residual chemical solution. The baseline formed by its electrical parameters first shows an upward sloping segment and then turns into a straight line or is set as an upward sloping segment. This is because the residual cleaning solution in the dairy beverage cleaning pipeline will be continuously diluted by clean water, causing the baseline to show a gradually rising trend; when the cleaning solution is completely diluted, only clean water remains in the pipeline, and the baseline turns into a straight segment. The cleaning stage corresponding to step (4) is denoted as (4-4). This cleaning stage is the water rinsing stage, and the baseline formed by its electrical parameters is also a straight line.

[0132] From the above analysis, it can be seen that, combined with Figure 10 as well as Figure 11 As shown, based on the aforementioned two cleaning instructions, if the number of detected baselines is not equal to the number of calibration lines in the cleaning stage, it indicates that there is a program error in the cleaning process, resulting in redundant or missing cleaning steps. This indicates that the cleaning is incomplete and outputs a result indicating an error in the cleaning process.

[0133] Meanwhile, if the slope similarity of the detected baseline exceeds the first error range (e.g., exceeding 0~0.3), it indicates that the baseline fluctuates in the actual test. When the amount of cleaning agent is fixed, the fluctuation of the baseline can reflect the fluctuation of the dilution level, which in turn indicates that the corresponding pump and / or valve is abnormal. At this time, the result that the cleaning process is wrong should also be output.

[0134] like Figure 11 As shown, taking the (3-3) cleaning stage as an example, if the corresponding baseline does not show the expected "rising-flat" or "rising" shape change characteristics, it indicates that the cleaning process is wrong. There may be situations where the cleaning solution cannot clean or there is no cleaning solution. It can be judged that the cleaning process is wrong.

[0135] Combination Figure 10 Step C in the text corresponds to the cleaning stage c and Figure 11As can be seen from the cleaning stage (3-3) corresponding to step (3) in the text, the electrical parameters detected at the end time points of both are close to the target parameters (i.e., the AD value of water). Therefore, by verifying whether the deviation between the electrical parameter value at the end time point and the target parameter is within the second error range (e.g., ±5%), it can be determined whether the cleaning step has been thoroughly performed, thereby ensuring the cleaning effect.

[0136] In another aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the cleaning method as described in any of the above embodiments.

[0137] This facilitates accurate detection of the cleaning integrity. Simultaneously, control commands are generated based on the fitting parameters between the actual and target electrical parameter change graphs, enabling timely intervention or feedback when the cleaning process fails to meet standards, thus ensuring the effectiveness of subsequent beverage preparation.

[0138] In other embodiments, such as Figure 12 As shown, step S400 above further includes: S403. Perform subtraction processing on the electrical parameters corresponding to the actual electrical parameter change graph and the target electrical parameter change graph at multiple time points to obtain the parameter difference values ​​corresponding to multiple time points.

[0139] In the above embodiments, the actual electrical parameter change graph and the target electrical parameter change graph can be graphs composed of multiple discrete points. Based on this, the parameter difference value can be obtained by subtracting the corresponding electrical parameters in the actual electrical parameter change graph and the target electrical parameter change graph.

[0140] S404. Use the number of parameter differences that are not within the preset difference range among all parameter differences in the same cleaning stage as the fitting parameter.

[0141] S405. If the fitting parameter for any one of the multiple cleaning stages exceeds the preset range, the cleaning process is judged to be incorrect.

[0142] Understandably, if the difference between the electrical parameters and the target parameters is significant, it indicates that the concentration of the cleaning solution is insufficient to meet the expected cleaning effect, suggesting an error in the cleaning process. Furthermore, the number of parameter differences outside the preset range within the same cleaning stage can be used as a fitting parameter. This allows for the detection of whether the cleaning solution concentration meets the cleaning level, and by comparing the number with the preset range, it reduces the impact of detection errors on the judgment, thereby improving the accuracy of determining whether the cleaning process is flawed.

[0143] In one embodiment, the cleaning method further includes: When an error is detected in the cleaning process, the system outputs the error result and records it in the cleaning log. This facilitates regular inspection and maintenance by maintenance personnel.

[0144] Optionally, in one embodiment, when it is determined that the cleaning process is correct, the judgment result that the cleaning process is correct is output and also recorded in the cleaning log, so as to facilitate maintenance personnel to check and maintain it regularly.

[0145] In another embodiment, the cleaning method further includes: If an error is detected in the cleaning process, a control command is output to re-execute the cleaning instruction. This allows for repeated cleaning by re-executing the instruction, ensuring the reliability of the cleaning process.

[0146] Optionally, in one embodiment, when it is determined that the cleaning process is correct, a control command to stop the cleaning is output. This ensures the smooth operation of the subsequent beverage preparation process.

[0147] Those skilled in the art will understand that implementing all or part of the processes in the cleaning methods of the above embodiments can be accomplished by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, image processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0148] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A cleaning method, characterized in that, include: In response to a cleaning command, for multiple set cleaning stages, electrical parameters of multiple test liquids are collected at different time points within each cleaning stage to characterize the liquid type. Based on the multiple electrical parameters and their corresponding time points in each cleaning stage, a graph of actual electrical parameter changes corresponding to each cleaning stage is generated. Based on a preset mapping model, obtain the target electrical parameter change graphs corresponding to each cleaning stage; Based on the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, a fitting parameter between the two is obtained; based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is incorrect; The step of generating an actual electrical parameter change graph corresponding to each cleaning stage based on multiple electrical parameters and their corresponding time points within each cleaning stage includes: All electrical parameters within the same cleaning stage are fitted to obtain corresponding baselines or reference bars, such that different cleaning stages correspond to different baselines or reference bars; wherein, within the same cleaning stage, all electrical parameters and the values ​​of the baseline at the corresponding time nodes are within a preset first fluctuation range; any electrical parameter within the same cleaning stage and the threshold value corresponding to the reference bar are within a preset second fluctuation range. Multiple baselines are used to form a line graph or multiple baseline bars are used to form a bar graph, which serves as a graph of the actual electrical parameter changes. The step of obtaining fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage; and determining whether the cleaning process is erroneous based on the fitting parameters corresponding to each of the multiple cleaning stages, includes: Obtain the number of baselines or baseline bars in the actual electrical parameter change graph corresponding to the cleaning stage, and record it as the first number; Obtain the number of calibration lines or calibration bars in the target electrical parameter change graph corresponding to the first cleaning stage, and record it as the second number; The first quantity and the second quantity are recorded as a comparison group. If the first quantity is not equal to the second quantity in any of the comparison groups corresponding to the multiple cleaning stages, it is determined that the cleaning process is incorrect. Wherein, the calibration line is a line segment or polyline graph in the target electrical parameter change graph that corresponds to the cleaning stage of the baseline; the calibration bar is a bar graph in the target electrical parameter change graph that corresponds to the cleaning stage of the baseline bar.

2. The cleaning method according to claim 1, characterized in that, The step of obtaining fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, and determining whether the cleaning process is erroneous based on the fitting parameters corresponding to each of the multiple cleaning stages, includes: The electrical parameters corresponding to multiple time points in the actual electrical parameter change graph and the target electrical parameter change graph are subtracted to obtain multiple parameter difference values ​​corresponding to multiple time points; The number of parameter differences that are not within the preset difference range within the same cleaning stage is used as the fitting parameter; If the fitting parameter for any one of the multiple cleaning stages exceeds the preset range, the cleaning process is determined to be erroneous.

3. The cleaning method according to claim 1, characterized in that, Fitting all electrical parameters within the same cleaning stage to obtain corresponding baselines or reference bars, such that different cleaning stages correspond to different baselines or reference bars, including: In each cleaning stage, all electrical parameters that conform to a preset change pattern are obtained and recorded as selected parameters, and the selected parameters and their corresponding time nodes are recorded. The corresponding baseline or baseline bar is obtained by fitting multiple selected parameters and corresponding time nodes.

4. The cleaning method according to claim 3, characterized in that, The fitting parameters include slope similarity; the slope similarity is negatively correlated with the slope difference between the baseline and the calibration line; The fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage are obtained. Furthermore, based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether there are any errors in the cleaning process, including: According to the cleaning instruction, the corresponding cleaning stage of the cleaning solution is obtained from the pre-stored instruction database; Obtain the baseline in the actual electrical parameter change graph corresponding to the drug cleaning stage; Obtain the calibration line in the target electrical parameter change graph corresponding to the drug cleaning stage; wherein, the calibration line is a line segment or polyline graph formed by multiple target parameters in the target electrical parameter change graph corresponding to the cleaning stage of the drug cleaning stage; When the slope similarity is within the first error range, the cleaning process is judged to be correct; When the slope similarity is not within the first error range, it is determined that the cleaning process is incorrect, and a judgment result is generated indicating that the valves and / or pumps involved in executing the cleaning command are faulty.

5. The cleaning method according to claim 1, characterized in that, The fitting parameters include the shape similarity between images; Based on the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage, a fitting parameter between the two is obtained; and based on the fitting parameters corresponding to each of the multiple cleaning stages, it is determined whether the cleaning process is erroneous, including: The shape similarity between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage is obtained; multiple cleaning stages correspond one-to-one with multiple shape similarities; If the difference between the shape similarity corresponding to any of the cleaning stages and the preset similarity is not within the second error range, the cleaning process is judged to be erroneous.

6. The cleaning method according to claim 1, characterized in that, The cleaning method further includes: According to the cleaning instructions, multiple cleaning steps corresponding to the cleaning instructions are obtained from the pre-stored instruction database and performed in sequence; each cleaning step has a start time node and an end time node when it is executed. Within each cleaning step, the start time node, the end time node, and all time nodes in between are divided into the same cleaning stage, so that multiple cleaning steps correspond one-to-one to form multiple cleaning stages; wherein, the order of the multiple cleaning stages is consistent with the execution order of the multiple cleaning steps.

7. The cleaning method according to claim 6, characterized in that, The fitting parameters include electrical parameter similarity; the electrical parameter similarity is negatively correlated with the absolute value of the difference between the electrical parameter and the target parameter at the corresponding time node; The cleaning method further includes: Before the end of each cleaning step, the electrical parameters corresponding to the end time node are obtained; the target parameter is the electrical parameter corresponding to the end time node in the target electrical parameter change graph. When the similarity of the electrical parameters is within the third error range, the cleaning step ends. If the electrical parameter similarity is not within the third error range, the cleaning step is repeated until the electrical parameter similarity is within the third error range.

8. The cleaning method according to claim 1, characterized in that, The cleaning method further includes: When the cleaning process is determined to be erroneous, the result of the determination is output and recorded in the cleaning log. And / or, the cleaning method further includes: If an error is detected in the cleaning process, a control command is output to re-execute the cleaning instruction.

9. A cleaning identification system, characterized in that, For implementing the cleaning method as described in any one of claims 1 to 8, the cleaning identification system is applied to a control component within a beverage device; the cleaning identification system includes: A liquid type detection module is used to respond to the cleaning command issued by the control component, and to collect electrical parameters of multiple liquids to be tested at different time points in each set cleaning stage to characterize the liquid type; the liquid type detection module is connected to a pipeline for flowing the liquids to be tested. The main control module is used to generate a graph of actual electrical parameter changes corresponding to each cleaning stage based on multiple electrical parameters and their corresponding time points within each cleaning stage; wherein, all electrical parameters within the same cleaning stage are fitted to obtain corresponding baselines or baseline bars, so that different cleaning stages correspond to different baselines or baseline bars; within the same cleaning stage, within the time interval covered by the baseline, the values ​​of all electrical parameters and the baseline at the corresponding time points are within a preset first fluctuation range; and the values ​​of any electrical parameter within the same cleaning stage and the threshold corresponding to the baseline bar are within a preset second fluctuation range. The main control module is used to obtain the target electrical parameter change graph corresponding to each cleaning stage based on a preset mapping model; The main control module is further configured to obtain fitting parameters between the actual electrical parameter change graph and the target electrical parameter change graph corresponding to each cleaning stage; and to determine whether the cleaning process is erroneous based on the fitting parameters corresponding to each of the multiple cleaning stages. Specifically, it acquires the number of baselines or baseline bars in the actual electrical parameter change graph corresponding to a cleaning stage and records them as a first number; acquires the number of calibration lines or calibration bars in the target electrical parameter change graph corresponding to that cleaning stage and records them as a second number; and sets the first number and the second number as a comparison group. If any one of the comparison groups corresponding to the multiple cleaning stages contains a first number that is not equal to the second number, then it is determined that the cleaning process is erroneous. The calibration line is a line segment or polygonal line graph in the target electrical parameter change graph corresponding to the cleaning stage where the baseline is located; the calibration bar is a bar graph in the target electrical parameter change graph corresponding to the cleaning stage where the baseline is located.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the cleaning method as described in any one of claims 1 to 8.

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