Self-service weighing and settlement system and method for cafeteria

Abstract

The invention provides a self-service weighing settlement system and method for a cafeteria, and relates to the technical field of self-service weighing, and the method comprises the steps: determining the zero drift characteristics actually measured by a weighing platform according to the no-load state of the weighing platform, carrying out the mapping correlation of the zero drift characteristics and environment temperature information, and obtaining the zero temperature coefficient of a weighing instrument; extracting temperature deviation characteristics of the weighing platform in each temperature interval in the on-load state, and determining a sensitivity temperature coefficient of the weighing instrument through all the temperature deviation characteristics; determining a temperature drift error caused by the environment temperature to the weighing instrument based on the zero temperature coefficient and the sensitivity temperature coefficient, and determining a compensation characteristic of the weighing platform through the temperature drift error and the current environment temperature; and carrying out temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight, and carrying out weighing settlement according to the actual weight, so that the drift compensation of the actual measurement in self-service weighing can be realized, and the accuracy of self-service weighing settlement is improved.

Description

Technical Field

[0001] This application relates to the technical field of self-service weighing, and more specifically, to a self-service weighing and settlement system and method for a cafeteria. Background Art

[0002] In a cafeteria, customers can independently select and weigh food and settle accounts based on the weighing results. This self-service weighing and settlement mode not only improves the restaurant operation efficiency but also reduces human intervention and enhances the customer experience. However, traditional self-service weighing systems may be affected by various factors, resulting in deviation of the weighing results, especially in the case of environmental temperature changes. Temperature changes can cause zero drift and sensitivity changes of the weighing instrument, thus affecting the accuracy of the weighing results. Therefore, how to accurately compensate for the errors caused by temperature and ensure the accuracy of self-service weighing and settlement is a key issue in improving the operation efficiency of the cafeteria and customer satisfaction.

[0003] Existing self-service weighing and settlement technologies usually rely on traditional sensor technologies and simple hardware designs when facing environmental temperature fluctuations. These solutions have significant limitations. First, when the temperature changes, the zero drift and sensitivity changes of the weighing instrument are often not effectively compensated, resulting in large errors in the weighing results and unable to meet the requirements of accurate settlement. Second, traditional technologies lack an effective dynamic temperature compensation mechanism and cannot adjust the deviation of the weighing system in real time, especially when the temperature fluctuates greatly in the restaurant environment. In addition, most existing technologies fail to comprehensively control the impact of temperature on weighing accuracy through the effective association of temperature and weighing data. These problems affect the stability of the weighing instrument and the fairness of settlement, and further affect the operation efficiency of the restaurant and the customer experience. Therefore, how to solve the impact brought by temperature changes through an intelligent compensation mechanism has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] This application provides a self-service weighing and settlement system and method for a cafeteria, which can realize the drift compensation of the actual measurement in self-service weighing, thereby improving the accuracy of self-service weighing and settlement.

[0005] In a first aspect, this application provides a self-service weighing and settlement method for a cafeteria. The self-service weighing and settlement method includes the following steps: In the weighing instrument, when there is no weight change on the weighing platform within a continuous fixed time window, record the environmental temperature information and the no-load state of the weighing platform; Determine the zero drift characteristics of the actual measurement of the weighing platform according to the no-load state, map and associate the zero drift characteristics and the environmental temperature information to obtain the zero temperature coefficient of the weighing instrument; Extract the temperature offset characteristics of the weighing platform in each temperature range under the load state, and determine the sensitivity temperature coefficient of the weighing instrument based on all the temperature offset characteristics; Determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero-point temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristics of the weighing platform based on the temperature drift error and the current ambient temperature; When the user conducts self-service weighing of selected items in the cafeteria, perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight of the selected items by the user, and then perform weighing settlement based on the actual weight.

[0006] In this embodiment, the weighing instrument is an electronic platform scale.

[0007] In this embodiment, the continuous fixed time window is set to 10 seconds.

[0008] In this embodiment, the ambient temperature information is recorded by a temperature sensor.

[0009] In this embodiment, determining the zero-point drift characteristics of the actual measurement of the weighing platform according to the no-load state specifically includes: When the weighing platform is in the no-load state, record its weight reading as the current zero-point reference value; Determine the zero-point drift characteristics of the actual measurement of the weighing platform by comparing the zero-point reference value with the initial zero-point value calibrated by the device.

[0010] In this embodiment, mapping and correlating the zero-point drift characteristics and the ambient temperature information to obtain the zero-point temperature coefficient of the weighing instrument specifically includes: Extract the zero-point drift characteristics and the corresponding ambient temperature information recorded at different time points from the database; Adopt the regression analysis method to establish a mathematical model of the mapping relationship between temperature and zero-point drift amount based on all the zero-point drift characteristics and ambient temperature information; Determine the influence rate of temperature on zero-point drift based on the mathematical model, and determine the zero-point temperature coefficient of the weighing instrument through the influence rate.

[0011] In this embodiment, determining the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics specifically includes: Determine the weighing sensitivity of the weighing instrument in different temperature ranges based on all the temperature offset characteristics; Determine the sensitivity temperature coefficient of the weighing instrument through all the weighing sensitivities.

[0012] In this embodiment, determining the compensation characteristics of the weighing platform based on the temperature drift error and the current ambient temperature specifically includes: Read the current ambient temperature and call the temperature drift error corresponding to the current ambient temperature; Determine the compensation characteristics of the weighing platform at the current ambient temperature based on the temperature drift error corresponding to the current ambient temperature.

[0013] In this embodiment, performing temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight of the user-selected commodity means adjusting the measured weight through the compensation characteristics to eliminate the error caused by temperature and obtaining the accurate actual weight of the commodity.

[0014] In a second aspect, the present application provides a self-service weighing and settlement system for a cafeteria, which is used to execute a self-service weighing and settlement method for a cafeteria. The self-service weighing and settlement system includes: A recording module, configured to record the ambient temperature information and the no-load state of the weighing platform in the weighing instrument when there is no weight change in the weighing platform within a continuous fixed time window; A zero-point temperature coefficient determination module, configured to determine the zero-point drift characteristics of the actual measurement of the weighing platform according to the no-load state, map and associate the zero-point drift characteristics with the ambient temperature information to obtain the zero-point temperature coefficient of the weighing instrument; A sensitivity temperature coefficient determination module, configured to extract the temperature offset characteristics in each temperature range of the weighing platform in the loaded state, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; A compensation characteristic extraction module, configured to determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero-point temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristics of the weighing platform through the temperature drift error and the current ambient temperature; A settlement module, configured to, when the user performs self-service weighing of the selected commodity in the cafeteria, perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight of the user-selected commodity, and then perform weighing settlement based on the actual weight.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: First, in a weighing instrument, when there is no weight change on the weighing platform within a continuous fixed time window, record the ambient temperature information and the no-load state of the weighing platform; determine the zero-drift characteristic actually measured by the weighing platform according to the no-load state, map and associate the zero-drift characteristic and the ambient temperature information to obtain the zero temperature coefficient of the weighing instrument; extract the temperature offset characteristics in each temperature range under the loaded state of the weighing platform, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristic of the weighing platform through the temperature drift error and the current ambient temperature; when a user conducts self-service weighing of selected items in a cafeteria, perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristic to obtain the actual weight of the items selected by the user, and then conduct weighing settlement based on the actual weight.

[0016] It can be seen that in this application, temperature drift compensation is performed on the actual measurement of the weighing platform through the compensation characteristic to obtain the actual weight of the items selected by the user; First, by recording the ambient temperature information under the no-load state in the weighing instrument and determining the zero-drift characteristic through this information, the influence of temperature change on the zero point of the weighing device can be accurately identified and quantified, so as to provide an accurate compensation basis for zero drift in practical applications; Second, by extracting the temperature offset characteristics of the weighing platform in different temperature ranges and determining the sensitivity temperature coefficient, the dynamic influence of temperature on weighing accuracy can be clearly understood, which helps to automatically adjust the sensitivity of the device in different temperature environments to ensure that the sensitivity of the weighing instrument remains consistent regardless of how the temperature fluctuates, further reducing the error caused by temperature change; Then, by combining the zero temperature coefficient and the sensitivity temperature coefficient, calculate the temperature drift error, and based on this, accurately formulate the temperature compensation characteristic. The compensation characteristic will provide real-time and intelligent calibration for error correction in each weighing process to ensure that the weighing result is still accurate and reliable even in an environment with large temperature changes; Finally, when the user selects and weighs items in the cafeteria, the system automatically corrects the weighing data based on the compensation characteristic to obtain the accurate weight of the items, ensuring the accuracy and fairness of the settlement process.

[0017] To sum up, through the dynamic temperature compensation mechanism, the solution of this application can achieve drift compensation of the actual measurement in self-service weighing, effectively eliminate the influence of ambient temperature change on the self-service weighing settlement system, and thus improve the accuracy and stability of the weighing result. Brief Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 is a flowchart of a self-service weighing and settlement method for a cafeteria provided according to the present application; Figure 2 is an exemplary flowchart for determining the zero-point temperature coefficient provided according to the present application; Figure 3 is an exemplary flowchart for determining the sensitivity temperature coefficient provided according to the present application; Figure 4 is a module structure diagram of a self-service weighing and settlement system for a cafeteria provided according to the present application. Detailed implementation manners

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0021] The embodiments of the present application provide a self-service weighing and settlement system and method for a cafeteria. The core is to determine the zero-point drift characteristics of the actual measurement of the weighing platform according to the no-load state of the weighing platform, map and associate the zero-point drift characteristics with the ambient temperature information to obtain the zero-point temperature coefficient of the weighing instrument; extract the temperature offset characteristics in each temperature range under the loaded state of the weighing platform, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero-point temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristics of the weighing platform through the temperature drift error and the current ambient temperature; perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight, and perform weighing settlement based on the actual weight. In summary, this solution can achieve drift compensation for the actual measurement in self-service weighing, thereby improving the accuracy of self-service weighing and settlement.

[0022] In Embodiment 1, to better understand the above technical solution, the following will detail the above technical solution in combination with the drawings in the specification and specific implementation manners. Refer to Figure 1As shown, the figure is an exemplary flowchart of a self-service weighing and settlement method for a cafeteria according to this embodiment of the present application. The self-service weighing and settlement method for a cafeteria includes the following steps: In step S1, in the weighing instrument, when there is no weight change on the weighing platform within a continuous fixed time window, record the ambient temperature information and the no-load state of the weighing platform.

[0023] It should be noted that in the present application, when there is no weight change on the weighing platform within a continuous fixed time window means that when the weighing platform within the set fixed time window (for example, 10 seconds), its weight reading remains constant and the change value is lower than the set error threshold (such as ±0.1 g), then it is considered that the weighing platform is in a state of no weight change, that is, the no-load state. At this time, it can be used to record the zero-point drift characteristics and perform temperature compensation analysis.

[0024] It should also be noted that in the present application, the ambient temperature of the weighing instrument can be collected using a temperature sensor; the no-load state of the weighing platform in the present application means that there is no any additional load on it, and the weight measured by the weighing sensor is stable at zero or only has a slight drift.

[0025] Specifically, in the weighing instrument, set a fixed time window (such as 10 seconds) and monitor the weight change of the weighing platform. If the change value is lower than the set threshold (such as ±0.1 g), then it is determined that the weighing platform is in the no-load state, record the current weight as the no-load reference value, and at the same time obtain the ambient temperature information through the temperature sensor and match and store it with the no-load state data for subsequent zero-point drift analysis and temperature compensation calculation.

[0026] In step S2, determine the zero-point drift characteristics actually measured by the weighing platform according to the no-load state, map and associate the zero-point drift characteristics and the ambient temperature information to obtain the zero-point temperature coefficient of the weighing instrument.

[0027] In this embodiment, determining the zero-point drift characteristics actually measured by the weighing platform according to the no-load state can be implemented by the following steps: When the weighing platform is in the no-load state, record its weight reading as the current zero-point reference value; Determine the zero-point drift characteristics actually measured by the weighing platform by comparing the zero-point reference value with the initial zero value calibrated by the device.

[0028] It should be noted that the zero-point reference value refers to the current weight reading measured by the weighing platform in the no-load state, which is used to judge whether the zero point drifts; the zero-point drift characteristic refers to the difference between the current zero-point reference value of the weighing platform and the calibrated initial zero value, which is used to measure the offset degree of the zero point with the change of the environment.

[0029] In specific implementation, first, when the weighing platform is in an unloaded state (i.e., without any external load) and remains stable for a period of time, the system will automatically collect the current weight reading, store it as the current zero reference value, and call the initial zero value recorded when the weighing instrument left the factory or during the most recent calibration. This value is usually stored in the internal storage unit of the device as the reference zero data under standard environmental conditions. Then, the system compares the difference between the current zero reference value and the initial zero value to determine whether the zero point of the weighing platform has drifted. To reduce accidental errors and improve the stability of measurement, the system can continuously collect zero data multiple times and use data smoothing algorithms such as moving average filtering to optimize the data, making the zero reference value more stable. Finally, the calculated zero drift characteristics are stored in the database for subsequent temperature compensation or device calibration, and real-time monitoring is performed during subsequent weighing. If the drift amount exceeds the set threshold, the system can trigger automatic zero calibration or alarm prompts to ensure the accuracy and stability of the weighing data.

[0030] In this embodiment, with reference to Figure 2 as shown, this figure is an exemplary flowchart for determining the zero temperature coefficient in the embodiment of the present application. In this embodiment, mapping and associating the zero drift characteristics and the ambient temperature information to obtain the zero temperature coefficient of the weighing instrument can be implemented by the following steps: In step S21, extract the zero drift characteristics and the corresponding ambient temperature information recorded at different time points from the database; In step S22, use the regression analysis method to establish a mathematical model of the mapping relationship between temperature and zero drift amount based on all the zero drift characteristics and ambient temperature information; In step S23, based on the mathematical model, determine the influence rate of temperature on zero drift, and determine the zero temperature coefficient of the weighing instrument through the influence rate.

[0031] It should be noted that the mathematical model in the present application refers to the mathematical expression used to describe the relationship between the ambient temperature and the zero drift characteristics of the weighing platform. Its core function is to establish the influence law of temperature change on zero drift to achieve subsequent compensation calculations. Its technical principle is: based on regression analysis, by fitting a large amount of historical data, the functional relationship between temperature change and zero drift is determined. For example, the linear regression model assumes a linear relationship between the two and can be represented by a straight-line equation, which is suitable for situations where the drift is relatively stable; polynomial regression is suitable for situations where the non-linear drift is more obvious to improve the fitting accuracy.

[0032] It should also be noted that the zero temperature coefficient refers to the influence rate of temperature change on the zero drift of the weighing platform, which is used to compensate for the weighing error caused by ambient temperature change.

[0033] In specific implementation, first, extract the zero-drift characteristics of historical records and their corresponding ambient temperature information from the database, ensuring that the data cover different temperature ranges to guarantee the applicability and accuracy of the model. After data extraction, perform data cleaning, such as removing outliers and filling in missing data, and normalize the data to improve computational stability. Second, adopt the regression analysis method to construct a mapping relationship model between temperature and zero-drift characteristics in a statistical software or computing system (such as Scikit-learn in Python, MATLAB). Commonly used methods include linear regression, quadratic regression, or multiple regression. Select the optimal model according to the distribution characteristics of the data. For example, if the data shows a linear relationship, the least squares linear regression can be used; if the temperature influence shows a non-linear trend, polynomial regression or machine learning methods (such as random forest regression) can be adopted to improve the fitting accuracy. Then, based on the fitted mathematical model, calculate the influence rate of temperature change on zero drift, that is, the change amount of the zero-drift characteristic when the temperature changes by one unit (such as 1°C). This influence rate is the zero temperature coefficient, which is used to quantify the influence of temperature on the zero stability of the weighing instrument.

[0034] In step S3, extract the temperature offset characteristics in each temperature range when the weighing platform is in the loaded state, and determine the sensitivity temperature coefficient of the weighing instrument based on all the temperature offset characteristics.

[0035] It should be noted that the extraction of the temperature offset characteristics in each temperature range when the weighing platform is in the loaded state in this application refers to measuring the weighing platform with a known load under different temperature conditions and calculating the deviation between the actual measured weight and the standard weight to determine the influence of temperature on the weighing accuracy. In specific implementation, first, select multiple temperature ranges (such as 10°C, 20°C, 30°C, etc.) and conduct loaded experiments within each range, placing weights with known masses on the weighing platform. Second, record the actual measured weights displayed by the weighing platform within each temperature range and compare them with the standard weight of the weights to calculate the weighing error caused by temperature. Then, adopt the regression analysis or interpolation method to analyze and establish a relationship model between temperature and weighing error, and extract the temperature offset characteristics at different temperatures. The temperature offset characteristic refers to the influence performance of temperature change on the weighing result, usually manifested as the deviation between the actual measured weight and the standard weight of the weighing platform under different temperature conditions. This deviation reveals the influence of temperature on the weighing accuracy.

[0036] In this embodiment, refer to Figure 3 As shown, this figure is an exemplary flowchart for determining the sensitivity temperature coefficient in the embodiment of this application. The determination of the sensitivity temperature coefficient of the weighing instrument based on all the temperature offset characteristics in this embodiment can be achieved by the following steps: In step S31, determine the weighing sensitivity of the weighing instrument in different temperature ranges based on all temperature offset characteristics; In step S32, determine the temperature coefficient of sensitivity of the weighing instrument based on all the weighing sensitivities.

[0037] It should be noted that the temperature coefficient of sensitivity in this application refers to the influence rate of temperature change on the change of the weighing sensitivity of the weighing instrument, which is used to compensate for the weighing sensitivity error caused by temperature.

[0038] In specific implementation, first, analyze all temperature offset characteristics to determine the weighing sensitivity of the weighing instrument in different temperature ranges. Sensitivity is usually defined as the output change of the weighing instrument under a unit load. That is, a series of weighing experiments with known loads can be carried out under different temperature conditions, record the actual readings of the weighing instrument, calculate their relative deviations, and use existing regression analysis techniques (such as polynomial regression) to model the relationship between the temperature range and sensitivity, and find the functional relationship between temperature and sensitivity change. This process can be implemented with the help of tools such as the Scikit-learn library in Python. By fitting the data, find the influence law of temperature change on sensitivity; then, based on the weighing sensitivity data at different temperatures, use regression analysis to further construct a temperature coefficient of sensitivity model, usually using linear regression or non-linear regression (such as polynomial regression). Through the model, analyze the quantitative relationship between temperature and sensitivity change, and then obtain the temperature coefficient of sensitivity of the weighing instrument. The temperature coefficient of sensitivity is used to describe the influence rate of temperature change on sensitivity. This coefficient can reflect the influence of temperature change on weighing accuracy and help to perform precise compensation at different temperatures to improve the stability and accuracy of the weighing instrument.

[0039] In step S4, determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero-point temperature coefficient and the temperature coefficient of sensitivity, and determine the compensation characteristics of the weighing platform through the temperature drift error and the current ambient temperature.

[0040] It should be noted that in this application, the temperature drift error caused by the environmental temperature on the weighing instrument determined based on the zero temperature coefficient and the sensitivity temperature coefficient refers to calculating the comprehensive influence of the temperature change on the zero drift and the sensitivity change of the weighing instrument, so as to obtain the total temperature error. In specific implementation, first, the current environmental temperature is read, and the influence of the current temperature change on the weighing instrument is predicted through these two coefficients. Then, through mathematical modeling, by using the weighted summation or regression analysis method, the zero temperature coefficient and the sensitivity temperature coefficient are combined with the difference in the current environmental temperature to calculate the error contribution brought by each coefficient. For example, the influence of the zero temperature coefficient can be obtained by multiplying the current temperature difference to get the zero drift error, and the sensitivity temperature coefficient determines the sensitivity error by calculating the relationship between the current temperature change and the sensitivity. Then, these two parts of errors are combined to obtain the total error caused by the temperature to the weighing instrument, that is, the temperature drift error. A common implementation method is to use an addition model to combine the zero error and the sensitivity error into a total temperature drift error.

[0041] In this embodiment, the compensation characteristics of the weighing platform can be determined based on the temperature drift error and the current environmental temperature by the following steps: Read the current environmental temperature and call the temperature drift error corresponding to the current environmental temperature; Determine the compensation characteristics of the weighing platform at the current environmental temperature based on the temperature drift error corresponding to the current environmental temperature.

[0042] In specific implementation, first, the current environmental temperature can be read through the temperature sensor built in the weighing platform or an external environmental temperature sensor to ensure accurate environmental temperature data is obtained in real time. Secondly, the system matches this temperature with the previously established temperature drift error model to find the temperature drift error corresponding to the current environmental temperature. Then, based on the temperature drift error corresponding to the current temperature, the system can apply it to the measured value of the weighing platform. Through simple error compensation calculations, such as deducting the corresponding error from the measured weight, the compensation characteristics are determined. In this embodiment, the temperature drift error corresponding to the current environmental temperature can be used as the compensation characteristics of the weighing platform at the current environmental temperature.

[0043] In step S5, when the user conducts self-service weighing of selected items in the cafeteria, temperature drift compensation is performed on the measured value of the weighing platform based on the compensation characteristics to obtain the actual weight of the selected items by the user, and then weighing settlement is performed based on the actual weight.

[0044] It should be noted that in this application, temperature drift compensation is performed on the actual measurement of the weighing platform based on the compensation feature, and obtaining the actual weight of the selected commodity by the user means adjusting the measured weight through the compensation feature to eliminate the error caused by temperature, so as to obtain the accurate actual weight of the commodity. Specifically, in implementation, first, the system applies the compensation feature to the actual measurement of the current weighing platform, usually using a simple addition or subtraction model for compensation. By deducting the error from the measured value, the weighing deviation caused by temperature is corrected. Finally, after temperature drift compensation, the weight output by the system is the actual weight of the selected commodity by the user, ensuring that under the condition of ambient temperature change, the weighing result can accurately reflect the true weight of the commodity.

[0045] It should also be noted that the weighing settlement based on the actual weight in this application means calculating the amount that the user should pay according to the accurate weight after temperature drift compensation.

[0046] Thus, in this application, temperature drift compensation is performed on the actual measurement of the weighing platform through the compensation feature to obtain the actual weight of the selected commodity by the user. First, by recording the ambient temperature information in the no-load state in the weighing instrument and determining the zero-point drift feature through this information, the influence of temperature change on the zero point of the weighing device can be accurately identified and quantified, so as to provide a precise compensation basis for the zero-point drift in actual applications. Secondly, by extracting the temperature offset features of the weighing platform in different temperature ranges and determining the sensitivity temperature coefficient, the dynamic influence of temperature on the weighing accuracy can be clearly understood, helping to automatically adjust the sensitivity of the device in different temperature environments to ensure that the sensitivity of the weighing instrument remains consistent regardless of how the temperature fluctuates, further reducing the error caused by temperature change. Then, by combining the zero-point temperature coefficient and the sensitivity temperature coefficient, the temperature drift error is calculated, and based on this, the temperature compensation feature is accurately formulated. Through the compensation feature, real-time and intelligent calibration will be provided for error correction in each weighing process to ensure that the weighing result is still accurate and reliable even in an environment with large temperature changes. Finally, when the user selects and weighs the commodity in the cafeteria, the system automatically corrects the weighing data based on the compensation feature to obtain the accurate weight of the commodity, ensuring the accuracy and fairness of the settlement process.

[0047] In summary, the solution of this application can realize the drift compensation of the actual measurement in self-service weighing through the dynamic temperature compensation mechanism, effectively eliminating the influence of ambient temperature change on the self-service weighing settlement system, thereby improving the accuracy and stability of the weighing result.

[0048] Embodiment 2. This application provides a self-service weighing settlement system for a cafeteria. Refer to Figure 4 As shown in the figure, which is a schematic diagram of the self-service weighing settlement system for a cafeteria according to this embodiment of this application. The self-service weighing settlement system for a cafeteria includes: A recording module 100, configured to record ambient temperature information and the no-load state of a weighing platform when there is no weight change in the weighing platform within a continuous fixed time window in a weighing instrument; A zero-point temperature coefficient determination module 200, configured to determine the zero-point drift characteristic actually measured by the weighing platform according to the no-load state, map and associate the zero-point drift characteristic and the ambient temperature information to obtain the zero-point temperature coefficient of the weighing instrument; A sensitivity temperature coefficient determination module 300, configured to extract the temperature offset characteristics in each temperature range of the weighing platform in a loaded state, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; A compensation characteristic extraction module 400, configured to determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero-point temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristic of the weighing platform through the temperature drift error and the current ambient temperature; A settlement module 500, configured to, when a user performs self-service weighing of selected commodities in a cafeteria, perform temperature drift compensation on the actually measured value of the weighing platform based on the compensation characteristic to obtain the actual weight of the selected commodities by the user, and then perform weighing settlement according to the actual weight.

[0049] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0050] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disc memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0051] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent in such a process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, commodity or device including the element.

Claims

1. A self-service weighing and settlement method for a cafeteria, characterized in that, The self-service weighing and settlement method includes the following steps: In the weighing instrument, when there is no weight change on the weighing platform within a continuous fixed time window, record the ambient temperature information and the no-load state of the weighing platform; Determine the zero-drift characteristic of the actual measurement of the weighing platform according to the no-load state, map and correlate the zero-drift characteristic and the ambient temperature information to obtain the zero temperature coefficient of the weighing instrument; Extract the temperature offset characteristics in each temperature range when the weighing platform is in the loaded state, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; Determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristic of the weighing platform through the temperature drift error and the current ambient temperature; When the user performs self-service weighing of selected commodities in the cafeteria, perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristic to obtain the actual weight of the user-selected commodities, and then perform weighing settlement based on the actual weight.

2. The self-service weighing and settlement method for a cafeteria according to claim 1, wherein The weighing instrument is an electronic platform scale.

3. The self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, The continuous fixed time window is set to 10 seconds.

4. The self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, Record the ambient temperature information through a temperature sensor.

5. The self-service weighing and settlement method for a cafeteria according to claim 4, wherein, Determining the zero-drift characteristic of the actual measurement of the weighing platform according to the no-load state specifically includes: When the weighing platform is in the no-load state, record its weight reading as the current zero reference value; Determine the zero-drift characteristic of the actual measurement of the weighing platform by comparing the zero reference value with the initial zero value calibrated by the device.

6. The self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, Mapping and correlating the zero-drift characteristic and the ambient temperature information to obtain the zero temperature coefficient of the weighing instrument specifically includes: Extract the zero-drift characteristics and the corresponding ambient temperature information recorded at different time points from the database; Adopt the regression analysis method to establish a mathematical model of the mapping relationship between temperature and zero-drift amount according to all the zero-drift characteristics and ambient temperature information; Determine the influence rate of temperature on zero drift based on the mathematical model, and determine the zero temperature coefficient of the weighing instrument through the influence rate.

7. A self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, Determining the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics specifically includes: Determine the weighing sensitivity of the weighing instrument in different temperature ranges according to all the temperature offset characteristics; Determine the sensitivity temperature coefficient of the weighing instrument through all the weighing sensitivities.

8. The self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, Determining the compensation characteristic of the weighing platform through the temperature drift error and the current ambient temperature specifically includes: Read the current ambient temperature and call the temperature drift error corresponding to the current ambient temperature; Determine the compensation characteristic of the weighing platform at the current ambient temperature according to the temperature drift error corresponding to the current ambient temperature.

9. The self-service weighing and settlement method for a cafeteria according to claim 1, characterized in that, Performing temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristic to obtain the actual weight of the user-selected commodities means adjusting the measured weight through the compensation characteristic to eliminate the error caused by temperature and obtaining the accurate actual weight of the commodities.

10. A self-service weighing and settlement system for a cafeteria, which is used to execute a self-service weighing and settlement method for a cafeteria according to any one of claims 1 to 9, characterized in that, The self-service weighing and settlement system includes: A recording module, used to record the ambient temperature information and the no-load state of the weighing platform in the weighing instrument when there is no weight change on the weighing platform within a continuous fixed time window; The zero temperature coefficient determination module is used to determine the zero drift characteristics of the actual measurement of the weighing platform according to the no-load state, map and correlate the zero drift characteristics with the ambient temperature information, and obtain the zero temperature coefficient of the weighing instrument; The sensitivity temperature coefficient determination module is used to extract the temperature offset characteristics in each temperature range of the weighing platform under the loaded state, and determine the sensitivity temperature coefficient of the weighing instrument through all the temperature offset characteristics; The compensation characteristic extraction module is used to determine the temperature drift error caused by the ambient temperature to the weighing instrument based on the zero temperature coefficient and the sensitivity temperature coefficient, and determine the compensation characteristic of the weighing platform through the temperature drift error and the current ambient temperature; The settlement module is used to, when the user conducts self-service weighing of selected commodities in the cafeteria, perform temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristic to obtain the actual weight of the user-selected commodities, and then perform weighing settlement based on the actual weight.

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