Weighing zero correction method and system and computer readable medium

Abstract

The invention relates to a weighing zero point correction method and system and a computer readable medium. The method comprises the steps that S1, first original weight data are collected, and an initial zero point is calculated; s2, collecting current original weight data and judging whether the current original weight data meets a first preset condition or not, and if yes, executing the step S3; s3, collecting second original weight data and judging whether the second original weight data meets a first preset condition or not, and if yes, executing the step S4; s4, third original weight data are collected, and a pre-zero point and a first zero point fluctuation value are calculated; s5, judging whether the pre-zero point is valid or not, and if yes, executing the step S5; s5, collecting fourth original weight data, calculating a second zero point fluctuation value, judging whether a pre-zero point is effective or not, and if yes, executing the step S6; and S6, taking the pre-zero point as the current weighing zero point. According to the invention, the accuracy of weighing zero correction can be improved.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of dynamic product weighing, and particularly relates to a weighing zero-point correction method, system and computer-readable medium. Background Art

[0002] When weighing a package object during product logistics transportation and the like, the object will pass through an electronic scale (such as a belt scale) at random times. During the long-term operation of existing electronic scales, due to factors such as changes in air temperature, humidity, wind speed, adhesion of dust on the electronic scale, and the influence of the measured object (such as the grease of meat) on the electronic scale, over time, the electronic scale will have zero-point drift, resulting in a decrease in measurement accuracy and inaccurate measurement of the weight of the object.

[0003] Currently, a fixed periodic automatic zero-clearing method is usually adopted to correct the weighing zero point, so as to try to solve the zero-point drift problem caused by the long-term operation of the electronic scale. For example, a programmable logic controller (PLC) is used to periodically trigger a zero-clearing command. Some electronic scales are provided with optoelectronic sensors for detecting whether an object is on or off the scale, and some weighing zero-point correction methods achieve fixed periodic zero-clearing based on the optoelectronic signal of the object triggering the optoelectronic sensor and the weighing weight.

[0004] In the existing method of using a PLC and an optoelectronic sensor for weighing zero-point correction, since additional components such as a PLC and an optoelectronic device need to be configured on the electronic scale, the complexity of the electronic scale configuration is increased, which is not conducive to the integration of user equipment. Considering the weighing process, if an object suddenly comes onto the scale at the moment when the periodic zero-clearing operation occurs, then the zero point corrected this time will deviate from the actual zero point. If only relying on the optoelectronic signal of the object entering the scale and the optoelectronic signal of the object leaving the scale of the optoelectronic sensor to achieve fixed periodic zero-clearing, when the optoelectronic sensor is damaged, the robustness of the weighing zero-point correction will be greatly reduced or the weighing zero-point correction work cannot be carried out. There is a problem of low accuracy in weighing zero-point correction in the prior art. Summary of the Invention

[0005] The technical problem to be solved by the present application is to provide a weighing zero-point correction method, system and computer-readable medium, which can improve the accuracy of weighing zero-point correction.

[0006] The technical solution adopted by this application to solve the above technical problems is a weighing zero - point correction method, including: Step S1: Collect the first set of original weight data within the first preset time period, and calculate the initial zero point according to the first set of original weight data; Step S2: Collect the current original weight data in real - time, and determine whether the current original weight data meets the first preset condition. If the determination is no, then repeat Step S2; if the determination is yes, then proceed to Step S3; wherein, the first preset condition is set according to the initial zero point; Step S3: Collect the second set of original weight data within the second preset time period, and determine whether each second set of original weight data meets the first preset condition. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S4; Step S4: Collect a preset number of third set of original weight data, and calculate the pre - zero point and the first zero - point fluctuation value according to the third set of original weight data; Determine whether the pre - zero point is valid according to the first zero - point fluctuation value. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S5; Step S5: Collect a preset number of fourth set of original weight data, calculate the second zero - point fluctuation value according to the fourth set of original weight data, and determine whether the pre - zero point is valid according to the second zero - point fluctuation value. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S6; and Step S6: Use the pre - zero point as the current weighing zero point.

[0007] In an embodiment of the present application, in Step S5, determine whether the pre - zero point is valid according to the second zero - point fluctuation value. If the determination is yes, then repeat Step S5 at least once and then proceed to Step S6.

[0008] In an embodiment of the present application, in Steps S1 to S5, when the first set of original weight data, the current original weight data, the second set of original weight data, the third set of original weight data, and the fourth set of original weight data are collected, the following formula is used to filter and process the original weight data in each step to obtain the filtered original weight data f(n):

[0009]

[0010] wherein, N represents the frequency of collecting the original weight data, d represents the filtering depth, w[·] represents the weight array composed of the original weight data collected at a frequency of N Hertz, n represents the number of the original weight data in the weight array, and n traverses from the first original weight data in the weight array.

[0011] In an embodiment of the present application, in Step S1, the step of calculating the initial zero point according to the first set of original weight data includes: calculating the initial zero point Z0 using the following formula:

[0012]

[0013] Wherein, X represents a first preset time period, and f(i) represents the i-th first original weight data after filtering.

[0014] In an embodiment of the present application, step S1 further includes: calculating a short-period zero-point fluctuation threshold according to the first original weight data, and calculating the short-period zero-point fluctuation threshold Z1 using the following formula:

[0015]

[0016] O(n) = Max(f(n)~f(n + αN - 1)) - Min(f(n)~f(n + αN - 1))

[0017] Wherein, f(n) represents the n-th first original weight data after filtering; α is a constant greater than ; Max(f(n)~f(n + αN - 1)) represents the maximum value among the n-th first original weight data after filtering to the (n + αN - 1)-th first original weight data after filtering; Min(f(n)~f(n + αN - 1)) represents the minimum value among the n-th first original weight data after filtering to the (n + αN - 1)-th first original weight data after filtering; PrioA represents a first weight value; PrioB represents a second weight value.

[0018] In an embodiment of the present application, step S1 further includes: calculating a long-period zero-point fluctuation threshold according to the first original weight data, and calculating the long-period zero-point fluctuation threshold Z2 using the following formula:

[0019] Z2 = Max(f[·]) - Min(f[·])

[0020] Wherein, f[·] represents an array composed of all the first original weight data after filtering.

[0021] In an embodiment of the present application, the first preset condition is (K2 * Z2) + (K1 * Z1) + Z0, wherein, K1 and K2 are constants greater than or equal to 0, K1 ≠ K2 or K1 = K2; Z2 represents the long-period zero-point fluctuation threshold, Z1 represents the short-period zero-point fluctuation threshold, and Z0 represents the initial zero point; the steps of judging whether the current original weight data meets the first preset condition in step S2 and judging whether each second original weight data meets the first preset condition in step S3 include: if the original weight data after filtering is less than (K2 * Z2) + (K1 * Z1) + Z0, it is judged to meet the first preset condition; if the original weight data after filtering is greater than or equal to (K2 * Z2) + (K1 * Z1) + Z0, it is judged not to meet the first preset condition.

[0022] In an embodiment of the present application, in step S4, the steps of calculating the pre-zero point and the first zero-point fluctuation value based on the third original weight data include: calculating the pre-zero point PZ using the following formula:

[0023]

[0024] where F(i) represents the i-th third original weight data after filtering, and β is a constant greater than ; calculating the first zero-point fluctuation value M using the following formula:

[0025] M = Max(F(n)~F(n + βN)) - Min(F(n)~f(n + βN))

[0026] where F(n) represents the n-th third original weight data after filtering; Max(F(n)~F(n + βN)) represents the maximum value among the n-th third original weight data after filtering to the (n + βN)-th third original weight data after filtering; Min(F(n)~f(n + βN)) represents the minimum value among the n-th third original weight data after filtering to the (n + βN)-th third original weight data after filtering.

[0027] In an embodiment of the present application, in step S4, the steps of determining whether the pre-zero point is valid based on the first zero-point fluctuation value include: if the second preset condition is satisfied: TC - TR < X and M < Z1, or TC - TR ≥ X and M < Z2, or TC - TR > 2*X and M < 2*Z2, then it is determined that the pre-zero point is valid; if the second preset condition is not satisfied, then it is determined that the pre-zero point is invalid; where TC represents the time when the pre-zero point is obtained, TR represents the time when the initial zero point is obtained, X represents the first preset time period, M represents the first zero-point fluctuation value, Z1 represents the short-period zero-point fluctuation threshold, and Z2 represents the long-period zero-point fluctuation threshold.

[0028] In an embodiment of the present application, in step S5, the steps of determining whether the pre-zero point is valid based on the second zero-point fluctuation value include: if the third preset condition is satisfied: TC - TR < X and or TC - TR ≥ X and or TC - TR > 2*X and then it is determined that the pre-zero point is valid; if the third preset condition is not satisfied, then it is determined that the pre-zero point is invalid; where M new represents the second zero-point fluctuation value, in which C represents the number of times of executing step S5, n represents the n-th execution of step S5, and 1 ≤ n ≤ C.

[0029] In an embodiment of the present application, in step S6, after the step of taking the pre-zero point as the current weighing zero point, the following steps are further included: calculating the time interval TI = TC - TR between the time TC of obtaining the pre-zero point and the time TR of obtaining the initial zero point; storing the time interval TI into the zero-point interval array TS; taking the time TC as the time TR to refresh the time for obtaining the zero point.

[0030] In an embodiment of the present application, in step S1, during the process of calculating the short-period zero-point fluctuation threshold Z1, the following formula is used to calculate the second weight value PrioB and the first weight value PrioA:

[0031]

[0032] PrioA = 1 - PrioB

[0033] where n represents the number of data in the zero-point interval array TS, n is an integer greater than or equal to 1; γ is an integer greater than or equal to 1, n ≥ γ; X represents the first preset time period; N represents the frequency of collecting the first raw weight data; TS(i) represents the i-th data in the zero-point interval array TS.

[0034] In an embodiment of the present application, during the execution of steps S2 to S5, the object signal on the weighing device is obtained in real time. If it is determined according to the object signal that there is an object on the weighing device, then the process proceeds to execute step S2.

[0035] In an embodiment of the present application, in step S4, it is determined whether the pre-zero point is valid according to the first zero-point fluctuation value. If the determination result is yes, then before proceeding to execute step S5, the following steps are further included: saving the initial zero point to the zero-point rollback temporary storage space, and temporarily taking the pre-zero point as the current weighing zero point; and in step S5, it is determined whether the pre-zero point is valid according to the second zero-point fluctuation value. If the determination result is no, then before proceeding to execute step S2, the following step is further included: temporarily taking the latest initial zero point in the zero-point rollback temporary storage space as the current weighing zero point.

[0036] The present application also provides a weighing zero-point correction system for solving the above technical problems, including: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the weighing zero-point correction method as described above.

[0037] The present application also provides a computer-readable medium storing computer program code, and the computer program code implements the weighing zero-point correction method as described above when executed by a processor.

[0038] The technical solution of this application collects the original weight data at different time periods. By calculating the initial zero point, the short-period zero point fluctuation threshold, and the long-period zero point fluctuation threshold, it is possible to determine whether the original weight data meets the first preset condition in combination with the initial zero point, so as to detect in time whether there is an object on the electronic scale. When there is an object on the scale, no weighing zero point correction is performed; by calculating the pre-zero point, the first zero point fluctuation value, and the second zero point fluctuation value, it is possible to determine whether the pre-zero point is valid in combination with the short-period zero point fluctuation threshold, the long-period zero point fluctuation threshold, the first zero point fluctuation value, and the second zero point fluctuation value. When it is determined that the pre-zero point is invalid, it means that the pre-zero point is unreliable and needs to be discarded; when it is determined that the pre-zero point is valid, it means that the pre-zero point is reliable, so that the pre-zero point can be used for weighing zero point correction. This application adopts the concept of pre-clearing, and uses the original weight data collected at different future time periods to verify whether the pre-zero point calculated before is reliable. Such a setting can improve the accuracy of weighing zero point correction. This application can avoid the situation where there is exactly an object on the scale during the clearing operation, and improves the reliability of automatic clearing processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To make the above objects, features, and advantages of this application more obvious and understandable, the following will describe the specific embodiments of this application in detail with reference to the accompanying drawings, where:

[0040] Figure 1 is an exemplary flowchart of a weighing zero point correction method according to an embodiment of this application;

[0041] Figure 2 is an exemplary flowchart of a weighing zero point correction method according to another embodiment of this application;

[0042] Figure 3 is an exemplary flowchart of a weighing zero point correction method using zero point rollback according to this application;

[0043] Figure 4 is a system block diagram of a weighing zero point correction system according to an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the above objects, features, and advantages of this application more obvious and understandable, the following will describe the specific embodiments of this application in detail with reference to the accompanying drawings.

[0045] Many specific details are set forth in the following description in order to provide a thorough understanding of this application, but this application may be implemented in other ways different from those described herein, so this application is not limited by the specific embodiments disclosed below.

[0046] As shown in this application and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0047] In this application, flowcharts are used to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the operations before or below do not necessarily need to be executed precisely in sequence. On the contrary, they can be executed in reverse order or simultaneously. At the same time, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0048] This application proposes a weighing zero - point correction method, which can be applied to electronic scales, such as logistics belt scales and product weighing scales, etc. This application is also applicable to dynamic weighing scenarios of non - belt scales, for example, the object to be measured is transported to the weighing platform by a robotic arm. The weighing zero - point correction method of this application can run in the controller of the electronic scale or in the cloud platform. When the weighing zero - point correction method runs in the cloud platform, the data of the electronic scale and the cloud platform data are interacted through a wireless network. Exemplarily, the cloud platform can include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, interconnected cloud, multi - cloud, etc. or any combination thereof. This application does not limit the operating environment of this weighing zero - point correction method.

[0049] Figure 1 is an exemplary flowchart of the weighing zero - point correction method according to an embodiment of this application. Refer to Figure 1 As shown, the weighing zero - point correction method of this embodiment includes the following steps:

[0050] Step S1: Collect the first set of original weight data within the first preset time period, and calculate the initial zero point based on the first set of original weight data.

[0051] Step S2: Continuously collect the current original weight data, and determine whether the current original weight data meets the first preset condition. If the determination is no, then repeat Step S2; if the determination is yes, then proceed to Step S3; where the first preset condition is set according to the initial zero point.

[0052] Step S3: Collect the second set of original weight data within the second preset time period, and determine whether each second set of original weight data meets the first preset condition. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S4.

[0053] Step S4: Collect a preset number of third original weight data, calculate a pre-zero point and a first zero-point fluctuation value based on the third original weight data; determine whether the pre-zero point is valid according to the first zero-point fluctuation value. If the determination result is no, then proceed to execute Step S2; if the determination result is yes, then proceed to execute Step S5.

[0054] Step S5: Collect a preset number of fourth original weight data, calculate a second zero-point fluctuation value based on the fourth original weight data, determine whether the pre-zero point is valid according to the second zero-point fluctuation value. If the determination result is no, then proceed to execute Step S2; if the determination result is yes, then proceed to execute Step S6.

[0055] Step S6: Use the pre-zero point as the current weighing zero point.

[0056] Exemplarily, the process of obtaining the pre-zero point and applying the pre-zero point as a new zero point will be introduced later. The above Steps S1 to S6 are described in detail below:

[0057] In some embodiments, exemplarily, in Steps S1 to S5 described later, when the first original weight data, the current original weight data, the second original weight data, the third original weight data, and the fourth original weight data are collected, the following formula (1) is used to filter and process the original weight data in each step to obtain the filtered original weight data f(n):

[0058]

[0059] where N represents the frequency of collecting the original weight data, d represents the filtering depth, w[·] represents the weight array composed of the original weight data collected at a frequency of N Hertz, n represents the serial number of the original weight data in the weight array, and n traverses from the first original weight data in the weight array. Exemplarily, the application does not limit the frequencies of collecting the first original weight data, the current original weight data, the second original weight data, the third original weight data, and the fourth original weight data, and these frequencies can be set to be the same or different. If it is analyzed that the low-frequency noise is concentrated around Shz (Hertz), then the filtering depth can be set

[0060] Exemplarily, in an actual application scenario, during the startup process of the electronic scale system, there may be influences such as motor vibration and unstable installation position of the weighing platform, resulting in the original weight data collected may carry noise signals. By filtering and processing the original weight data collected at different time periods, the application can improve the accuracy of subsequent data processing and can better identify the zero-point data characteristics under non-steady state. In actual applications, it is also possible to choose not to filter and process the original weight data, and the application does not make any restrictions.

[0061] In step S1, the first original weight data within the first preset time period is collected, and the initial zero point is calculated based on the first original weight data. Exemplarily, it can be considered that within a period of time (such as 1 minute to 30 minutes) after the electronic scale is powered on and turned on, it belongs to the startup stage of the electronic scale system. At this time, it is required that no object is placed on the electronic scale, and the parameters calculated based on the first original weight data within the system startup stage have good reference significance. The first preset time period can be set to any time within 1 minute to 30 minutes according to needs.

[0062] In some embodiments, in step S1, the step of calculating the initial zero point based on the first original weight data includes: calculating the initial zero point Z0 using the following formula (2):

[0063]

[0064] where X represents the first preset time period, and f(i) represents the i-th filtered first original weight data. Exemplarily, if the set collection time period is X minutes, the number of data included in the weight array w[·] composed of the first original weight data collected is X * N * 60. The moment when the calculated initial zero point Z0 is obtained can be recorded as TR at the same time.

[0065] In some embodiments, step S1 further includes: calculating the short-period zero point fluctuation threshold based on the first original weight data, and calculating the short-period zero point fluctuation threshold Z1 using the following formula (3) and formula (4):

[0066]

[0067] O(n) = Max(f(n)~f(n + αN - 1)) - Min(f(n)~f(n + αN - 1)) (4)

[0068] where f(n) represents the n-th filtered first original weight data; α is a constant greater than ; Max(f(n)~f(n + αN - 1)) represents the maximum value among the n-th filtered first original weight data to the (n + αN - 1)-th filtered first original weight data; Min(f(n)~f(n + αN - 1)) represents the minimum value among the n-th filtered first original weight data to the (n + αN - 1)-th filtered first original weight data; PrioA represents the first weight value; PrioB represents the second weight value.

[0069] Exemplarily, if the result value of αN in formula (4) contains decimal places, for example, αN = 1.4, then the result value of αN can be rounded to 1 according to the rounding method; or the result value of αN can be rounded up to 2 according to the ceiling method; or the result value of αN can be rounded down to 1 according to the floor method. This application does not limit the rounding method of the result value of αN. It can be considered that αN in formula (4) is equivalent to the first original weight data collected according to frequency N within α seconds, and (n + αN - 1) cannot exceed the index of the last value among all the first original weight data. The short-period zero-point fluctuation threshold can represent the influence brought by the inherent vibration on the electronic scale (such as motor vibration, platform vibration, etc.).

[0070] Exemplarily, the above formula (3) is equivalent to obtaining the short-period zero-point fluctuation threshold Z1 after calculating the mean value and maximum value of all O(n) and performing weighted processing. The first weight value PrioA can take a value of 0.5, and the second weight value PrioB can take a value of 0.5. This application does not limit the values of the first weight value PrioA and the second weight value PrioB. This application also specially designs an adaptive calculation method for the first weight value PrioA and the second weight value PrioB, and this adaptive calculation method will be introduced later.

[0071] In some embodiments, step S1 further includes: calculating the long-period zero-point fluctuation threshold according to the first original weight data, and using the following formula (5) to calculate the long-period zero-point fluctuation threshold Z2:

[0072] Z2 = Max(f[·]) - Min(f[·]) (5)

[0073] Where f[·] represents an array composed of all filtered first original weight data. Exemplarily, the above formula (5) is equivalent to finding the maximum value and minimum value in all the data of the array f[·] and performing a difference calculation. Exemplarily, the long-period zero-point fluctuation threshold can represent the influence brought by special circumstances, such as the influence brought by the temperature change caused by the heating of the sensor component after the electronic scale is powered on.

[0074] Exemplarily, it can be considered that after running for a period of time (such as the first preset time period), the preparation stage of the electronic scale system ends and it will enter the running stage. Steps S2 to S6 later are equivalent to the running stage of the electronic scale system.

[0075] In step S2, the current original weight data is collected in real time, and it is judged whether the current original weight data meets the first preset condition. If the judgment is negative, step S2 is repeatedly executed; if the judgment is positive, step S3 is executed; among them, the first preset condition is set according to the initial zero point. Exemplarily, by setting the first preset condition in the present application, it can be timely detected whether there is an object on the weighing scale. When there is an object on the weighing scale, it indicates that the collected data is unreliable and the data needs to be collected again. Therefore, the present application sets to repeatedly execute step S2.

[0076] In some embodiments, the first preset condition is (K2*Z2)+(K1*Z1)+Z0, where K1 and K2 are constants greater than or equal to 0, K1≠K2 or K1 = K2; Z2 represents the long-period zero-point fluctuation threshold, Z1 represents the short-period zero-point fluctuation threshold, and Z0 represents the initial zero point; the step of judging whether the current original weight data meets the first preset condition in step S2 includes:

[0077] Step S201: If the filtered current original weight data is less than (K2*Z2)+(K1*Z1)+Z0, it is judged that the first preset condition is met;

[0078] Step S202: If the filtered current original weight data is greater than or equal to (K2*Z2)+(K1*Z1)+Z0, it is judged that the first preset condition is not met.

[0079] In step S3, the second original weight data within the second preset time period is collected, and it is judged whether each second original weight data meets the first preset condition. If the judgment is negative, step S2 is executed; if the judgment is positive, step S4 is executed.

[0080] In some embodiments, the step of judging whether each second original weight data meets the first preset condition in step S3 includes:

[0081] Step S301: If the filtered each second original weight data is less than (K2*Z2)+(K1*Z1)+Z0, it is judged that the first preset condition is met;

[0082] Step S302: If the filtered each second original weight data is greater than or equal to (K2*Z2)+(K1*Z1)+Z0, it is judged that the first preset condition is not met.

[0083] Exemplarily, the second preset time period is related to the values of K1 and K2. In the first preset condition (K2*Z2)+(K1*Z1)+Z0 of the present application, K2 can take a value of 5, and K1 can take a value of 0, that is, the second preset time period can be set to 5 s (seconds). If a photoelectric sensor or other high-throughput high-speed system is provided on the electronic scale, then the values of K1 and K2 can be set to relatively small values (such as 1 or 2); if the throughput of the electronic scale is low, then the values of K1 and K2 can be set to relatively large values (such as 8 or 9). (K2*Z2) in the first preset condition is equivalent to the weight threshold, that is, K2 times the long-period zero-point fluctuation threshold Z2. In practical applications, the weight threshold (K2*Z2) can be set as a whole to 5% to 50% of the actual weight of the object to be measured, and the present application does not make any restrictions.

[0084] Exemplarily, in practical applications, since the filter may have a delay, resulting in a delay in the weight signal output by the filter, it may not be possible to accurately determine whether there is an object on the scale through the weight signal. Therefore, in the scenario of the non-photoelectric signal mode (where no photoelectric sensor is provided on the electronic scale), the duration of the second preset time period in step S3 can be appropriately increased to ensure the reliability of the empty scale state judgment. And according to the current original weight data collected in real time in step S2 and the second original weight data collected within the second preset time period in step S3, by judging the situation where these original weight data meet the first preset condition, the influence brought by the filter delay can be reduced as much as possible, and the accuracy of the overall weighing zero-point correction can be improved.

[0085] In step S4, a preset number of third original weight data are collected, and the pre-zero point and the first zero-point fluctuation value are calculated based on the third original weight data; it is judged whether the pre-zero point is valid according to the first zero-point fluctuation value. If the judgment is no, then it turns to execute step S2; if the judgment is yes, then it turns to execute step S5.

[0086] In some embodiments, in step S4, the steps of calculating the pre-zero point and the first zero-point fluctuation value based on the third original weight data include:

[0087] Step S401: Calculate the pre-zero point PZ using the following formula (6):

[0088]

[0089] where F(i) represents the i-th third original weight data after filtering, and β is a constant greater than 0, and the moment TC when the pre-zero point PZ is obtained can be recorded simultaneously;

[0090] Step S402: Calculate the first zero-point fluctuation value M using the following formula (7):

[0091] M = Max(F(n) to F(n + βN)) - Min(F(n) to f(n + βN)) (7)

[0092] Wherein, F(n) represents the nth third original weight data after filtering; Max(F(n) to F(n + βN)) represents the maximum value among the nth third original weight data after filtering to the (n + βN)th third original weight data after filtering; Min(F(n) to f(n + βN)) represents the minimum value among the nth third original weight data after filtering to the (n + βN)th third original weight data after filtering.

[0093] Exemplarily, in this application, the filtered original weight data obtained by the electronic scale system during the operation stage is represented by capital F, so as to distinguish it from the filtered original weight data f obtained by the electronic scale system during the startup stage described above. If the result value of βN in formulas (6) and (7) contains decimal places, for example, βN = 1.4, then the result value of βN can be rounded to 1 according to the rounding method; or the result value of βN can be rounded up to 2 according to the ceiling method; or the result value of βN can be rounded down to 1 according to the floor method. This application does not limit the rounding method of the result value of βN. It can be considered that βN in formula (7) is equivalent to the third original weight data collected according to the frequency N within β seconds, and (n + βN) cannot exceed the index of the last value among all the third original weight data.

[0094] In some embodiments, in step S4, the step of judging whether the pre-zero point is valid according to the first zero-point fluctuation value includes: if the second preset condition is satisfied: TC - TR < X and M < Z1, or TC - TR ≥ X and M < Z2, or TC - TR > 2 * X and M < 2 * Z2, then it is judged that the pre-zero point is valid; if the second preset condition is not satisfied, then it is judged that the pre-zero point is invalid; wherein, TC represents the moment when the pre-zero point is obtained, TR represents the moment when the initial zero point is obtained, X represents the first preset time period, M represents the first zero-point fluctuation value, Z1 represents the short-period zero-point fluctuation threshold, and Z2 represents the long-period zero-point fluctuation threshold.

[0095] Exemplarily, the concept of time is introduced in the second preset condition. According to the various judgment conditions in the second preset condition of this application, it can be understood that if the time since the last successful zero clearing is short, then more strict zero clearing can be performed to ensure reliability; if the time since the last successful zero clearing is long, then the conditions can be relaxed to achieve successful zero clearing. This application can avoid the temperature drift effect caused by long-term temperature changes or the situation where zero clearing cannot be achieved due to occasional influences such as wind by setting the second preset condition. This application can have both reliability and effectiveness.

[0096] In step S5, a preset number of fourth original weight data are collected, the second zero-point fluctuation value is calculated based on the fourth original weight data, and it is determined whether the pre-zero point is valid according to the second zero-point fluctuation value. If the determination result is no, the process proceeds to step S2; if the determination result is yes, the process proceeds to step S6. Exemplarily, the second zero-point fluctuation value can be calculated using formula (7) described above. In practical applications, since the filter may introduce a delay, resulting in a delayed weight signal output by the filter, it may not be possible to accurately determine whether there is an object on the scale based on the weight signal. Therefore, in a scenario without optoelectronic signals, collecting a preset number of fourth original weight data in step S5 is equivalent to appropriately extending the acquisition time of the original weight data, thereby ensuring the reliability of the empty-scale state determination.

[0097] In some embodiments, in step S5, it is determined whether the pre-zero point is valid according to the second zero-point fluctuation value. If the determination result is yes, step S5 is repeatedly executed at least once before proceeding to step S6. Exemplarily, the number of repetitions of step S5 can be set as needed, either once or multiple times, and this application does not impose any restrictions. By setting the repeated execution of step S5 at least once when the pre-zero point is determined to be valid, the reliability of the pre-zero point can be further ensured.

[0098] In some embodiments, the step of determining whether the pre-zero point is valid according to the second zero-point fluctuation value in step S5 includes:

[0099] If the third preset condition is satisfied: TC - TR < X and or TC - TR ≥ X and or TC - TR > 2*X and then it is determined that the pre-zero point is valid; if the third preset condition is not satisfied, it is determined that the pre-zero point is invalid; where M new represents the second zero-point fluctuation value, C in represents the number of times step S5 is executed, n represents the nth execution of step S5, and 1 ≤ n ≤ C. Exemplarily, the third preset condition set in this application is equivalent to gradually relaxing some of the judgment conditions in the third preset condition as the number of executions of step S5 increases. This setting can improve the reliability of the pre-zero point and the timeliness of the weighing zero-point correction.

[0100] In step S6, the pre-zero point is used as the current weighing zero point. Exemplarily, after the judgments in the previous steps, it is shown that the pre-zero point is reliable, and the pre-zero point can be used as the current weighing zero point to correct the weighing zero point. For example, Z0 = PZ can be set, where the = sign represents an assignment operation.

[0101] In some embodiments, in step S6, after the step of using the pre-zero point as the current weighing zero point, the following steps are further included:

[0102] Step S610: Calculate the time interval TI = TC - TR between the moment TC when the pre-zero point is obtained and the moment TR when the initial zero point is obtained;

[0103] Step S620: Store the time interval TI into the zero point interval array TS;

[0104] Step S630: Use the moment TC as the moment TR to refresh the time for zero point acquisition. Exemplarily, in step S630, TR = TC can be set, where the = sign represents an assignment operation.

[0105] Exemplarily, after the aforementioned steps S2 to S6, it is equivalent to completing a round of weighing zero point calibration. Subsequently, it can be set to execute step S2 after executing step S6, indicating that the next round of weighing zero point calibration continues during the operation stage of the electronic scale system. In some embodiments, in order to enhance the adaptive ability of the electronic scale system, the short-period zero point feature model can be dynamically updated. For example, the first zero point fluctuation value M calculated according to formula (7) in step S4 above is added to the array O(n) calculated according to formula (4) in step S1 to form a new array O new (n), and the short-period zero point fluctuation threshold Z1 is recalculated according to the new array O new (n), which is equivalent to preparing for the next round of zero point calculation.

[0106] The following introduces the adaptive calculation method of the first weight value PrioA and the second weight value PrioB. In some embodiments, in step S1, during the process of calculating the short-period zero point fluctuation threshold Z1, the following formulas (8) and (9) are used to calculate the second weight value PrioB and the first weight value PrioA:

[0107]

[0108] PrioA = 1 - PrioB (9)

[0109] Where n represents the number of data in the zero point interval array TS, n is an integer greater than or equal to 1; γ is an integer greater than or equal to 1, n ≥ γ; X represents the first preset time period; N represents the frequency of collecting the first raw weight data; TS(i) represents the i-th data in the zero point interval array TS. Exemplarily, by setting formulas (8) and (9), the second weight value PrioB and the first weight value PrioA can be adaptively adjusted, thereby improving the overall accuracy of the weighing zero point calibration method.

[0110] Exemplarily, the technical content described above in this application can be applied to scenarios where no photoelectric sensor is provided on the electronic scale (no photoelectric signal mode). The electronic scale can perform weighing zero-point calibration only based on the original weight data. In the no photoelectric signal mode, since the electronic scale does not rely on externally triggered signals, the weighing zero-point calibration method of this application can be extended to non-belt scales, such as scenarios where a robotic arm is used to move the object to be measured onto the scale platform. This application is also applicable to electronic scales that cannot use photoelectric sensors due to special object characteristics (such as the object being too thin, the object being transparent, etc.).

[0111] For the scenario where a photoelectric sensor is provided on the electronic scale (with photoelectric signal mode), this application correspondingly designs a weighing zero-point calibration method, thereby expanding the application scenarios of this application and improving the flexibility of weighing zero-point calibration. In some embodiments, during the execution of steps S2 to S5, the object signals (such as the in-scale signal and out-scale signal in the photoelectric signal) on the weighing device (such as an electronic scale) are obtained in real time. If it is determined based on the object signals that there is an object on the weighing device, then the process proceeds to step S2. Most of the technical content in the weighing zero-point calibration method in the photoelectric signal mode of this application is the same as that described above and will not be elaborated here.

[0112] This application determines whether there is an object on the electronic scale (such as a belt scale) currently through the logical judgment of the photoelectric signal and the weight threshold. If no object passes through the electronic scale for a period of time, it can be considered that the electronic scale is currently in a stable near-zero state, and thus the original weight data can be collected for a period of time and the pre-zero point can be calculated. Subsequently, continue to observe for a period of time. If within the preset observation time, the photoelectric signal is not triggered and the weight remains stable and does not exceed the threshold, it can be considered that the previously calculated pre-zero point is a valid and reliable zero point, and the pre-zero point can be set as the new zero point subsequently. If the photoelectric signal is triggered within the observation time, it means that the calculated pre-zero point is obtained when an object is about to be placed on the scale, then this pre-zero point is unreliable and can be discarded. By introducing the dual judgment of the photoelectric signal and the original weight data, as well as the pre-clearing operation, this application can avoid the situation where an object enters the scale exactly during the automatic zero-clearing operation, thereby improving the accuracy of weighing zero-point calibration.

[0113] The present application also designs a zero-point rollback method for weighing zero-point calibration. In some embodiments, in step S4, it is determined whether the pre-zero point is valid according to the first zero-point fluctuation value. If the determination is yes, before transitioning to execute step S5, it further includes: saving the initial zero point Z0 to the zero-point rollback temporary storage space ZP, and temporarily using the pre-zero point PZ as the current weighing zero point; and in step S5, it is determined whether the pre-zero point is valid according to the second zero-point fluctuation value. If the determination is no, before transitioning to execute step S2, it further includes: temporarily using the latest initial zero point in the zero-point rollback temporary storage space ZP as the current weighing zero point. In the weighing zero-point calibration method with the zero-point rollback concept in the present application, most of the technical content is the same as that in the previous text and will not be elaborated here.

[0114] Exemplarily, the zero-point rollback concept is described in combination with a specific scenario. For example, when it is determined that there is no object on the scale through optoelectronic signals and a weight threshold, it is continuously detected for a period of time. If the weight fluctuation during this period is not greater than a certain proportion of the preset weight threshold (for example, 5% - 80% of the weight threshold), then a new zero point is calculated using the original weight data collected during this period. While making this zero point effective, the previous zero point is saved. It is possible to continue waiting for a preset period of time Time or collect a preset number of original weight data from the time point when the new zero point becomes effective. If the weight fluctuation amplitude during this period of time Time or the collected original weight data exceeds the weight threshold, or the weight fluctuation amplitude exceeds a certain multiple of the weight threshold (for example, 0.8 times to 5 times), or the optoelectronic sensor detects that an object has been placed on the scale, then it is considered that this new zero point is unreliable, and the previously saved old zero point is immediately rolled back to maintain the previous zero point state.

[0115] The technical solution of the present application collects the original weight data in different time periods. By calculating the initial zero point, short-period zero-point fluctuation threshold, and long-period zero-point fluctuation threshold, it is possible to determine whether the original weight data meets the first preset condition in combination with the initial zero point, so as to timely detect whether an object has been placed on the electronic scale. When an object is placed on the scale, no weighing zero-point calibration is performed; by calculating the pre-zero point, the first zero-point fluctuation value, and the second zero-point fluctuation value, it is possible to determine whether the pre-zero point is valid in combination with the short-period zero-point fluctuation threshold, long-period zero-point fluctuation threshold, first zero-point fluctuation value, and second zero-point fluctuation value. When it is determined that the pre-zero point is invalid, it means that the pre-zero point is unreliable and needs to be discarded; when it is determined that the pre-zero point is valid, it means that the pre-zero point is reliable, and thus this pre-zero point can be used for weighing zero-point calibration. The present application adopts the concept of pre-clearing and uses the original weight data collected in different future time periods to verify whether the previously calculated pre-zero point is reliable. Such a setting can improve the accuracy of weighing zero-point calibration. The present application can avoid the situation where an object is placed on the scale exactly during the clearing operation, improving the reliability of the automatic clearing process.

[0116] The following will introduce the weighing zero - point calibration method of the present application with two embodiments.

[0117] Embodiment 1

[0118] Figure 2 is an exemplary flowchart of the weighing zero - point calibration method of another embodiment of the present application. Refer to Figure 2 As shown, at step S210, the electronic scale system starts; at step S220, the original weight data within a period of time is collected; at step S230, the original weight data is filtered and the initial zero point is calculated; at step S240, the short - period zero - point fluctuation threshold and the long - period zero - point fluctuation threshold are calculated; at step S250, the electronic scale system enters the operation stage; at step S260, the current original weight data is collected in real - time and filtered; at step S270, it is determined in real - time whether the current original weight data meets the first preset condition. If the determination is no, then step S270 is repeatedly executed; if the determination is yes, then step S280 is executed; at step S280, the original weight data within the next period of time is collected, and it is determined whether each original weight data meets the first preset condition. If the determination is no, then it turns to execute step S270; if the determination is yes, then step S290 is executed.

[0119] Continue to refer to Figure 2 As shown, at step S290, a preset number of original weight data is collected, the pre - zero point and the zero - point fluctuation value are calculated, and it is determined whether the pre - zero point is valid. If the determination is no, then it turns to execute step S270; if the determination is yes, then step S2100 is executed; at step S2100, a preset number of original weight data is continuously collected, and it is determined whether the pre - zero point is valid. If the determination is no, then it turns to execute step S270; if the determination is yes, then step S2110 is executed; step S2100 can be repeatedly executed multiple times; at step S2110, the pre - zero point is set as the current weighing zero point, and the zero - point acquisition time is updated; reaching step S2120 indicates that this zero - clearing is successful, and enters the next round of periodic zero - clearing, or ends the weighing zero - point calibration method; if it is necessary to enter the next round of periodic zero - clearing, then it turns to execute step S250. Optionally, the short - period zero - point fluctuation model in step S240 can be updated after step S2120 to prepare for the next round of periodic zero - clearing.

[0120] Embodiment 2

[0121] Figure 3 is an exemplary flowchart of the weighing zero - point calibration method using zero - point rollback of the present application. Refer to Figure 3As shown, in step S310, the electronic scale system enters the startup phase; in step S320, the original weight data is collected for a period of time; in step S330, the original weight data is filtered and the initial zero point is calculated; in step S340, the short-period zero-point fluctuation threshold and the long-period zero-point fluctuation threshold are calculated; in step S350, the electronic scale system enters the operation phase; in step S360, the current original weight data is collected in real time and filtered; in step S370, it is determined in real time whether the current original weight data meets the first preset condition. If the determination is no, step S370 is repeatedly executed; if the determination is yes, step S380 is executed; in step S380, the original weight data for the next period of time is collected, and it is determined whether each original weight data meets the first preset condition. If the determination is no, it is changed to execute step S370; if the determination is yes, step S390 is executed.

[0122] Continue to refer to Figure 3 As shown, in step S390, a preset number of original weight data are collected, the pre-zero point and the zero-point fluctuation value are calculated, and it is determined whether the pre-zero point is valid. If the determination is no, it is changed to execute step S370; if the determination is yes, step S3100 is executed; in step S3100, the pre-zero point is set as the current weighing zero point, and the previous old zero point is saved; in step S3110, a preset number of original weight data are continuously collected, and it is determined whether the pre-zero point is valid. If the determination is no, it comes to step S3122 indicating that the pre-zero point is unreliable, and the current weighing zero point is rolled back to the previous state using the previously saved old zero point, and it is changed to execute step S370; if the determination is yes, it comes to step S3121 indicating that the pre-zero point is reliable and there is no need to roll back the zero point, the zero-point array is updated, and the zero-point acquisition time is refreshed; it comes to step S3130 indicating that the current zero clearing is successful, and the next round of periodic zero clearing is entered, or the weighing zero-point calibration method is ended; if it is necessary to enter the next round of periodic zero clearing, it is changed to execute step S350. Optionally, the short-period zero-point fluctuation model in step S340 can be updated after step S3130 to prepare for the next round of periodic zero clearing.

[0123] This application also includes a weighing zero-point calibration system, including a memory and a processor. Among them, the memory is used to store instructions executable by the processor; the processor is used to execute the instructions to implement the weighing zero-point calibration method described above.

[0124] Figure 4 It is the system block diagram of the weighing zero-point calibration system according to an embodiment of this application. Refer to Figure 4As shown, the weighing zero - point correction system 400 may include an internal communication bus 401, a processor 402, a read - only memory (ROM) 403, a random - access memory (RAM) 404, and a communication port 405. The weighing zero - point correction system 400 may also include a hard disk 406. The internal communication bus 401 can enable data communication among the components of the weighing zero - point correction system 400. The processor 402 can make judgments and issue prompts. In some embodiments, the processor 402 may consist of one or more processors. The communication port 405 can enable data communication between the weighing zero - point correction system 400 and the outside. In some embodiments, the weighing zero - point correction system 400 can send and receive information and data from a network through the communication port 405. The weighing zero - point correction system 400 may also include different forms of program storage units and data storage units, such as the hard disk 406, the read - only memory (ROM) 403, and the random - access memory (RAM) 404, which can store various data files used for computer processing and / or communication, as well as possible program instructions executed by the processor 402. The processor executes these instructions to implement the main part of the method. The results processed by the processor are transmitted to the user device through the communication port and displayed on the user interface.

[0125] The above - mentioned weighing zero - point correction method can be implemented as a computer program, stored in the hard disk 406, and loaded into the processor 402 for execution to implement the weighing zero - point correction method of the present application.

[0126] The present application also includes a computer - readable medium storing computer program code, which implements the weighing zero - point correction method described above when executed by a processor.

[0127] When the weighing zero - point correction method is implemented as a computer program, it can also be stored in a computer - readable storage medium as an article of manufacture. For example, the computer - readable storage medium may include, but is not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips), optical disks (e.g., compact discs (CDs), digital versatile discs (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read - only memories (EPROMs), cards, sticks, key drives). In addition, the various storage media described herein can represent one or more devices and / or other machine - readable media for storing information. The term "machine - readable medium" may include, but is not limited to, wireless channels and various other media (and / or storage media) that can store, contain, and / or carry code and / or instructions and / or data.

[0128] It should be understood that the embodiments described above are merely illustrative. The embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processor can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, and / or other electronic units designed to perform the functions described herein, or a combination thereof.

[0129] Some aspects of the present application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software can be referred to as a "block", "module", "engine", "unit", "component", or "system". The processor can be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or a combination thereof. In addition, aspects of the present application may be embodied as a computer product located on one or more computer readable media, the product including computer readable program code. For example, the computer readable media may include, but is not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes,...), optical disks (e.g., compact disk CD, digital versatile disk DVD,...), smart cards, and flash memory devices (e.g., cards, sticks, key drives,...).

[0130] The computer readable media may contain a propagated data signal having computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take various forms, including electromagnetic forms, optical forms, etc., or a suitable combination thereof. The computer readable media can be any computer readable media other than a computer readable storage media, which can communicate, propagate, or transport a program for use by being connected to an instruction execution system, apparatus, or device. The program code located on the computer readable media can be propagated through any suitable media, including radio, cable, fiber optic cable, radio frequency signal, or similar media, or any combination of the above media.

[0131] The basic concepts have been described above. Obviously, for those skilled in the art, the above application disclosure is merely an example and does not constitute a limitation to the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to the present application. Such modifications, improvements, and corrections are proposed in the present application, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of the present application.

[0132] Meanwhile, this application uses specific terms to describe the embodiments of this application. For example, "an embodiment", "one embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0133] In some embodiments, numbers are used to describe the components and the quantity of attributes. It should be understood that such numbers used to describe the embodiments are, in some examples, modified by the modifiers "about", "approximately", or "substantially". Unless otherwise stated, "about", "approximately", or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and such approximate values can change according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of this application to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are made as precise as possible within the feasible range.

Claims

1. A weighing zero-point correction method, characterized in that, Including: Step S1: Collect the first original weight data within the first preset time period, and calculate the initial zero point according to the first original weight data; Step S2: Collect the current original weight data in real time, and determine whether the current original weight data meets the first preset condition. If the determination is no, then repeat Step S2; if the determination is yes, then proceed to Step S3; wherein, the first preset condition is set according to the initial zero point; Step S3: Collect the second original weight data within the second preset time period, and determine whether each second original weight data meets the first preset condition. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S4; Step S4: Collect a preset number of third original weight data, and calculate the preliminary zero point and the first zero point fluctuation value according to the third original weight data; determine whether the preliminary zero point is valid according to the first zero point fluctuation value. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S5; Step S5: Collect a preset number of fourth original weight data, calculate the second zero point fluctuation value according to the fourth original weight data, and determine whether the preliminary zero point is valid according to the second zero point fluctuation value. If the determination is no, then proceed to Step S2; if the determination is yes, then proceed to Step S6; and Step S6: Use the preliminary zero point as the current weighing zero point.

2. The weighing zero-point correction method according to claim 1, characterized in that, In Step S5, determine whether the preliminary zero point is valid according to the second zero point fluctuation value. If the determination is yes, then repeat Step S5 at least once and then proceed to Step S6.

3. The weighing zero-point correction method according to claim 1, characterized in that, In Steps S1 to S5, when the first original weight data, the current original weight data, the second original weight data, the third original weight data, and the fourth original weight data are collected, the following formula is used to filter and process the original weight data in each step to obtain the filtered original weight data f(n): Wherein, N represents the frequency of collecting the original weight data, d represents the filtering depth, w[·] represents the weight array composed of the original weight data collected at the frequency of N Hertz, n represents the number of the original weight data in the weight array, and n traverses from the first original weight data in the weight array.

4. The weighing zero-point correction method according to claim 3, characterized in that, In Step S1, the step of calculating the initial zero point according to the first original weight data includes: calculating the initial zero point Z0 using the following formula: Wherein, X represents the first preset time period, and f(i) represents the i-th first original weight data after filtering.

5. The weighing zero-point correction method according to claim 3, characterized in that, In Step S1, it also includes: calculating the short-period zero point fluctuation threshold according to the first original weight data, and calculating the short-period zero point fluctuation threshold Z1 using the following formula: O(n) = Max(f(n)~f(n + αN - 1)) - Min(f(n)~f(n + αN - 1)) Among them, f(n) represents the nth first original weight data after filtering; α is a constant greater than ; Max(f(n)~f(n+αN-1)) represents the maximum value among the nth first original weight data after filtering to the (n+αN-1)th first original weight data after filtering; Min(f(n)~f(n+αN-1)) represents the minimum value among the nth first original weight data after filtering to the (n+αN-1)th first original weight data after filtering; PrioA represents the first weight value; PrioB represents the second weight value.

6. The weighing zero-point correction method according to claim 5, characterized in that, In Step S1, it also includes: calculating the long-period zero point fluctuation threshold according to the first original weight data, and calculating the long-period zero point fluctuation threshold Z2 using the following formula: Z2 = Max(f[·]) - Min(f[·]) where f[·] represents an array composed of all filtered first original weight data.

7. The weighing zero-point correction method according to claim 6, characterized in that, The first preset condition is (K2 * Z2) + (K1 * Z1) + Z0, where K1 and K2 are constants greater than or equal to 0, and K1 ≠ K2 or K1 = K2; Z2 represents the long - period zero - point fluctuation threshold, Z1 represents the short - period zero - point fluctuation threshold, and Z0 represents the initial zero point; the steps of determining whether the current original weight data satisfies the first preset condition in step S2 and determining whether each second original weight data satisfies the first preset condition in step S3 include: If the filtered original weight data is less than (K2 * Z2) + (K1 * Z1) + Z0, it is determined that the first preset condition is satisfied; If the filtered original weight data is greater than or equal to (K2 * Z2) + (K1 * Z1) + Z0, it is determined that the first preset condition is not satisfied.

8. The weighing zero-point correction method according to claim 6, characterized in that, In step S4, the steps of calculating the pre - zero point and the first zero - point fluctuation value according to the third original weight data include: The pre - zero point PZ is calculated using the following formula: Among them, F(i) represents the i-th third original weight data after filtering, and β is a constant greater than ; The first zero - point fluctuation value M is calculated using the following formula: M = Max(F(n)~F(n + βN)) - Min(F(n)~f(n + βN)) where F(n) represents the nth filtered third original weight data; Max(F(n)~F(n + βN)) represents the maximum value among the nth filtered third original weight data to the (n + βN)th filtered third original weight data; Min(F(n)~f(n + βN)) represents the minimum value among the nth filtered third original weight data to the (n + βN)th filtered third original weight data.

9. The weighing zero - point correction method according to claim 8, characterized in that, In step S4, the steps of determining whether the pre - zero point is valid according to the first zero - point fluctuation value include: If the second preset condition is satisfied: TC - TR < X and M < Z1, or TC - TR ≥ X and M < Z2, or TC - TR > 2 * X and M < 2 * Z2, it is determined that the pre - zero point is valid; if the second preset condition is not satisfied, it is determined that the pre - zero point is invalid; where TC represents the time when the pre - zero point is obtained, TR represents the time when the initial zero point is obtained, X represents the first preset time period, M represents the first zero - point fluctuation value, Z1 represents the short - period zero - point fluctuation threshold, and Z2 represents the long - period zero - point fluctuation threshold.

10. The weighing zero - point correction method according to claim 9, characterized in that, In step S5, the steps of determining whether the pre - zero point is valid according to the second zero - point fluctuation value include: If the third preset condition is satisfied: TC - TR < X and or TC - TR ≥ X and or TC - TR > 2*X and then it is determined that the pre-zero point is valid; if the third preset condition is not satisfied, it is determined that the pre-zero point is invalid; Among them, M new represents the second zero-point fluctuation value, C in represents the number of times of executing the step S5, n represents the nth execution of the step S5, and 1 ≤ n ≤ C.

11. The weighing zero - point correction method according to claim 5, characterized in that, In step S6, after the step of using the pre - zero point as the current weighing zero point, it further includes: Calculating the time interval TI = TC - TR between the time TC when the pre - zero point is obtained and the time TR when the initial zero point is obtained; Storing the time interval TI into the zero - point interval array TS; Taking the time TC as the time TR to refresh the zero - point acquisition time.

12. The weighing zero - point correction method according to claim 11, characterized in that, In the step S1, in the process of calculating the short-period zero-point fluctuation threshold Z1, the following formula is used to calculate the second weight value PrioB and the first weight value PrioA: PrioA = 1 - PrioB Where n represents the number of data in the zero-point interval array TS, n is an integer greater than or equal to 1; γ is an integer greater than or equal to 1, n ≥ γ; X represents the first preset time period; N represents the frequency of collecting the first original weight data; TS(i) represents the i-th data in the zero-point interval array TS.

13. The weighing zero - point correction method according to any one of claims 1 - 12, characterized in that, In the process of executing the step S2 to the step S5, the object signal on the weighing device is obtained in real time. If it is determined according to the object signal that there is an object on the weighing device, then the execution is switched to the step S2.

14. The weighing zero - point correction method according to claim 13, characterized in that, In the step S4, it is determined whether the pre-zero point is valid according to the first zero-point fluctuation value. If it is determined to be yes, before switching to execute the step S5, it further includes: saving the initial zero point to the zero-point rollback temporary storage space, and temporarily using the pre-zero point as the current weighing zero point; and In the step S5, it is determined whether the pre-zero point is valid according to the second zero-point fluctuation value. If it is determined to be no, before switching to execute the step S2, it further includes: temporarily using the latest initial zero point in the zero-point rollback temporary storage space as the current weighing zero point.

15. A weighing zero - point correction system, characterized in that, Including: A memory for storing instructions executable by a processor; A processor for executing the instructions to implement the weighing zero-point correction method according to any one of claims 1-14.

16. A computer - readable medium storing computer program code, characterized in that, The computer program code, when executed by a processor, implements the weighing zero-point correction method according to any one of claims 1-14.

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