A dynamic correction method and system for measuring equipment

Abstract

The present invention relates to the field of weighing technology, and specifically to a method and system for dynamic correction of measuring equipment, the method comprising: acquiring jitter data of the measuring equipment during weighing in real time; fusing the jitter data using an envelope extraction algorithm to obtain vibration attenuation trend characteristics; obtaining an attenuation curve based on the vibration attenuation trend characteristics combined with real-time weighing results; obtaining de-attenuated jitter data based on the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using the least squares method to obtain a target function; determining whether the measuring equipment currently needs to be calibrated based on a comparison result of the target function, the attenuation curve, and a standard target function and standard attenuation curve preset by the system; if so, dynamically correcting the measuring equipment; the present invention solves the problem that traditional calibration methods for measuring equipment cannot dynamically calibrate the measuring equipment in real time, resulting in measurement errors during the use of the measuring equipment, thereby improving the measurement accuracy of the measuring equipment.

Description

Technical Field

[0001] The present invention relates to the field of weighing technology, and in particular to a dynamic correction method and system for measuring equipment. Background Art

[0002] Measuring equipment is a weighing instrument commonly used for weighing, such as electronic scales. Measuring equipment is mainly divided into piezoelectric sensor type, capacitive sensor type, and electromagnetic induction sensor type according to the weighing principle. To ensure the weighing accuracy of measuring equipment, measuring equipment usually needs to test the weighing curve and perform weighing calibration before it is used to ensure accurate weighing.

[0003] However, during the use of measuring equipment, the constant weighing of heavy objects inevitably causes collisions with the measuring equipment, which may cause the measuring sensor of the measuring equipment to become inaccurate, resulting in measurement errors. Calibration of measurement errors of measuring equipment usually requires error measurement through a complete set of calibration objects to obtain a weighing curve, and then determine the specific measurement inaccuracy of the measuring equipment based on the weighing curve. However, this calibration method is cumbersome and cannot complete real-time calibration of the measuring equipment. Because traditional measuring equipment calibration methods cannot perform real-time dynamic calibration of measuring equipment, measurement errors that occur during the use of measuring equipment cannot be identified, which in turn leads to reduced measurement accuracy. Summary of the Invention

[0004] In order to solve the above technical problems, the object of the present invention is to provide a method and system for dynamic calibration of a measuring device. According to one aspect of the present invention, a method for dynamic calibration of a measuring device is provided, the method comprising:

[0005] Real-time acquisition of jitter data of measuring equipment during weighing;

[0006] Performing data fusion on the jitter data using an envelope extraction algorithm to obtain vibration attenuation trend characteristics;

[0007] Obtaining an attenuation curve based on the vibration attenuation trend characteristics and the real-time weighing results;

[0008] Obtaining de-attenuated jitter data according to the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using a least squares method to obtain a target function;

[0009] Determining whether the measuring device currently needs to be calibrated based on a comparison result of the objective function, the attenuation curve, and a standard objective function and a standard attenuation curve preset by the system;

[0010] If so, the measuring device is dynamically calibrated.

[0011] Furthermore, the real-time acquisition of jitter data of the measuring device during weighing further includes:

[0012] When the weight value measured by the measuring device is stable, obtaining the measured weight of the measuring device;

[0013] At the same time, the moment when the weight value measured by the measuring device is stable is used as the end moment, and the moment before the preset jitter duration before the end moment is used as the start moment, and a change curve of the weight measured by the measuring device within the preset jitter duration is obtained; wherein the horizontal axis of the change curve is time and the vertical axis is measured weight;

[0014] The variation curve is recorded as jitter data.

[0015] Furthermore, the step of fusing the jitter data using an envelope extraction algorithm to obtain a vibration attenuation trend feature further includes:

[0016] Taking the jitter data as input data, adopting an envelope extraction algorithm, and outputting the upper envelope and lower envelope of the jitter data;

[0017] The lower envelope is processed symmetrically along a preset straight line to obtain a symmetrical lower envelope;

[0018] The lower envelope and the upper envelope are subjected to data fusion to obtain the vibration attenuation trend characteristics; wherein, the data form of the jitter data is a vector with a length of 3000, the mth element represents the measured weight of the measuring equipment at time m, and m=0-3000.

[0019] Furthermore, the data format of the vibration attenuation trend feature is the same as the data format of the jitter data;

[0020] The step of obtaining the attenuation curve based on the vibration attenuation trend characteristics and the real-time weighing results further includes:

[0021] The attenuation curve is obtained by subtracting the measured weight of the measuring device when the measured weight value is stable from each element in the vibration attenuation trend characteristic.

[0022] Furthermore, obtaining de-attenuated jitter data based on the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using the least squares method to obtain the objective function further includes:

[0023] The result of subtracting the vibration attenuation trend characteristic from the jitter data is taken as the jitter data after de-attenuation;

[0024] The de-attenuated jitter data and the sine function are curve-fitted using the least squares method, specifically: the sine function is used as the target function, the de-attenuated jitter data is used as input data, and the fitted sine function is used as output data as the target function;

[0025] The amplitude of the objective function is a physical property parameter of the elastic unit of the measuring equipment.

[0026] Furthermore, the method further comprises:

[0027] An external force interference weight is constructed according to the de-attenuated jitter data and the objective function.

[0028] Furthermore, the determining whether the measuring device currently needs to be calibrated based on the comparison result of the objective function, the attenuation curve, and the standard objective function and standard attenuation curve preset by the system further includes:

[0029] Calculating the data credibility weight based on the external force interference weight and the standard external force interference weight preset by the system;

[0030] Calculating the attenuation characteristic difference based on the attenuation curve, the data credibility weight, and a standard attenuation curve preset by the system;

[0031] Calculating an amplitude characteristic difference based on the objective function amplitude and the objective function amplitude preset by the system;

[0032] When the attenuation characteristic difference and / or the amplitude characteristic difference exceeds an error threshold preset by the system, it is determined that the measuring device currently needs to be calibrated.

[0033] Furthermore, the dynamic calibration of the measuring device further includes:

[0034] Calibration is performed based on the calibration unit and weights in the measuring device;

[0035] Among them, the calibration unit specifically comprises: forming a data pair according to the voltage size of the measuring equipment and the size of the weight, and multiple data pairs forming a weighing curve data set, and then taking the weighing curve data set as input, using the mean interpolation algorithm to calculate, outputting the weighing curve function, and using the output weighing curve function to replace the original weighing curve function to complete the calibration of the measuring equipment.

[0036] According to another aspect of the present invention, there is provided a dynamic calibration system for measuring equipment, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0037] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned method for dynamic correction of a measuring device.

[0038] The present invention has the following beneficial effects: the present invention obtains jitter data of the measuring equipment during weighing in real time; uses an envelope extraction algorithm to fuse the jitter data to obtain vibration attenuation trend characteristics; obtains an attenuation curve based on the vibration attenuation trend characteristics combined with the real-time weighing results; obtains de-attenuated jitter data based on the jitter data and the vibration attenuation trend characteristics, and uses the least squares method to fit the de-attenuated jitter data to obtain the target function; determines whether the measuring equipment currently needs to be calibrated based on the comparison results of the target function, the attenuation curve and the standard target function and standard attenuation curve preset by the system; if so, dynamically calibrates the measuring equipment; the present invention detects in real time through the jitter data of the measuring equipment whether the elastic shock absorbing module and sensor parameters of the measuring equipment have changed, so that it can dynamically determine whether there is an error in the measurement of the measuring equipment, and can timely discover the measurement error and calibrate the measuring equipment, which solves the problem that the traditional measuring equipment calibration method cannot perform real-time dynamic calibration of the measuring equipment, resulting in measurement errors during the use of the measuring equipment, and improves the measurement accuracy of the measuring equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 A flow chart of a dynamic calibration method for a measuring device provided by one embodiment of the present invention;

[0041] Figure 2 A schematic diagram of jitter data of a dynamic correction method for a measuring device provided by one embodiment of the present invention;

[0042] Figure 3 Schematic diagram of the structure of an embodiment of a dynamic correction system for computing devices according to the present invention. DETAILED DESCRIPTION

[0043] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method and system for dynamic calibration of measuring equipment according to the present invention, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0044] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0045] The specific scheme of the dynamic correction method and system for measuring equipment provided by the present invention is described in detail below with reference to the accompanying drawings.

[0046] See also Figure 1 , which shows a dynamic calibration method for a measuring device provided by an embodiment of the present invention, the method comprising:

[0047] Step S110: Acquire jitter data of the measuring equipment during weighing in real time.

[0048] This embodiment uses an electronic scale as an example for dynamic calibration analysis of measuring equipment. The measurement principle of an electronic scale is typically to convert an object's mass into gravity using gravity, then use a sensor to convert gravity into an electrical signal. A mapping relationship is established between the electrical signal and the object's mass, and the object's mass is obtained based on this mapping relationship. For example, using a capacitive sensor-based measuring device, the mapping relationship between the capacitance voltage of the capacitive sensor and the object's mass is called a weighing curve. The weighing curve is a function with the capacitance voltage on the horizontal axis and the object's mass on the vertical axis. During weighing, the object's mass is determined based on the sensor voltage and the weighing curve.

[0049] When the parameters of the measuring device sensor or elastic shock-absorbing unit change due to factors such as collision, temperature and humidity changes, the actual weighing curve and the weighing curve in the measuring device storage unit will differ, which will lead to measurement errors. Therefore, it is only necessary to detect whether the parameters of the measuring device sensor have changed to find out whether the measuring device has a measurement error. When placing an object on the measuring device, the uneven placement process will cause the force applied by the placed object to the measuring device to temporarily exceed the weight of the object, which will cause the elastic shock-absorbing unit of the measuring device to vibrate. This jitter will cause the sensor data to jitter for a certain period of time, forming a sensor data change curve; the vibration of the sensor value in the sensor data change curve will gradually weaken over time. The speed of this weakening is determined by the elastic shock-absorbing unit and sensor parameters of the measuring device. Therefore, the weakening of the jitter of the sensor data curve can be used to determine whether the elastic shock-absorbing unit or sensor parameters of the measuring device have changed. Changes indicate that the measuring device may have a measurement error.

[0050] In an optional embodiment, step S110 further includes: obtaining the measured weight of the measuring device when the weight value measured by the measuring device is stable; at the same time, taking the moment when the weight value measured by the measuring device is stable as the end moment and the preset jitter duration before the end moment as the start moment, obtaining a change curve of the measured weight of the measuring device within the preset jitter duration; wherein the horizontal axis of the change curve is the moment and the vertical axis is the measured weight; the change curve is recorded as jitter data.

[0051] Figure 2 A schematic diagram of jitter data of a dynamic correction method for a measuring device provided by an embodiment of the present invention is shown as follows: Figure 2 As shown, the measured weight data obtained from the time when the object to be measured is placed on the measuring device to the time when the weight of the object is determined is called jitter data. Therefore, the measured weight of the measuring device is obtained when the measured weight value of the measuring device is stable; at the same time, the moment when the measured weight value of the measuring device is stable is taken as the end moment, and Ts seconds before the end moment is taken as the start moment, and the change curve of the measured weight of the measuring device during this period is obtained and recorded as jitter data. The sampling rate of the curve is 1 millisecond, and the jitter duration is Ts=3 seconds; finally, the change curve of the measured weight and event of the measuring device at the nth measurement of the measuring device is obtained as jitter data; the jitter data is represented in the computer as a vector with a length of 3000, in which the mth element represents the measured weight of the measuring device at the mth moment.

[0052] Step S120: performing data fusion on the jitter data using an envelope extraction algorithm to obtain vibration attenuation trend characteristics.

[0053] In an optional embodiment, step S120 further includes: taking the jitter data as input data, adopting an envelope extraction algorithm, and outputting the upper envelope and lower envelope of the jitter data; symmetrically processing the lower envelope along a preset straight line to obtain a symmetrical lower envelope; and fusing the lower envelope and the upper envelope to obtain vibration attenuation trend characteristics.

[0054] Step S130: Obtain an attenuation curve based on the vibration attenuation trend characteristics and the real-time weighing results.

[0055] In an optional embodiment, the data form of the vibration attenuation trend feature is the same as the data form of the jitter data; step S130 further includes: subtracting the measured weight when the weight value measured by the measuring device is stable from each element in the vibration attenuation trend feature and recording it as an attenuation curve.

[0056] When placing an object on an electronic scale, in the absence of external interference, its elastic shock-absorbing unit will cause the sensor measurement data to vibrate in a certain pattern. This pattern will not change when the elastic shock-absorbing unit or sensor parameters remain unchanged. However, since the measured object will be disturbed by external forces such as hand pressing on the measured object during the placement process, this jitter characteristic will become difficult to compare. Therefore, it is necessary to eliminate the influence of this external force interference on the vibration characteristics of the sensor data.

[0057] Analyzing the vibration factors of objects on measuring equipment, the jitter data change curve is composed of three factors: First, the elastic device installed on the measuring equipment causes the object to vibrate, which can be summarized by Hooke's law as a physical model; second, the influence of the measuring equipment's shock absorption device, which gradually reduces the elastic potential energy of the object's vibration on the measuring equipment, thereby causing the vibration data to gradually decrease. Third, the vibration of the object on the measuring equipment is caused by the influence of temporary external forces.

[0058] Therefore, in order to eliminate external force interference, the attenuation factor in the jitter data is extracted in this embodiment. Since the periodic change of the jitter data affects the extraction of the attenuation factor, the attenuation factor characteristics are characterized by the numerical change of the envelope in the jitter data. Therefore, the jitter data is used as input data, and the envelope extraction algorithm is adopted. The output data is the upper envelope and lower envelope of the jitter data. The change trends of the upper and lower envelopes represent the vibration attenuation process brought to the jitter data by the shock absorber, and the numerical value of the lower envelope and the vibration attenuation trend are opposite. Therefore, the lower envelope is first symmetrically processed along a straight line to obtain a symmetrical lower envelope. The straight line is specifically: a straight line whose weight value is equal to the weighing weight of the measuring equipment and is parallel to the x-axis; then the lower envelope and the symmetrical upper envelope are data fused to obtain the vibration attenuation trend characteristics.

[0059] Since the upper envelope and the lower envelope are obtained by fitting the data, there is a fitting error. The point that fits the original data best and has the smallest error is the intersection of the envelope and the original data. The intersection points of the upper envelope and the lower envelope with the original data are poorly arranged. Therefore, when performing data fusion to obtain the vibration attenuation trend characteristics, in order to ensure the accuracy of the final calculation results and avoid calibration errors due to systematic errors, the horizontal distance between the envelope and the nearest intersection point with the original data is used as the weight for data fusion. The larger the horizontal distance, the lower the weight.

[0060] When actually calculating the vibration attenuation trend characteristics, the calculation method includes but is not limited to: for the data at the mth moment of the upper envelope line, the horizontal distance between it and the nearest intersection of the upper envelope line and the jitter data is recorded as the upper envelope line credibility, and for the data at the mth moment of the lower envelope line, the lower envelope line credibility can be obtained in the same way; the upper envelope line credibility and the lower envelope line credibility at the mth moment are normalized, and after processing, they are used as the weights of the upper envelope line function value and the symmetrical lower envelope line function value at the mth moment respectively, and the two function values are weightedly added to obtain the vibration attenuation trend characteristic function value at the mth moment, and finally the vibration attenuation trend characteristics are calculated for all moments.

[0061] Step S140: obtaining de-attenuated jitter data according to the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using the least squares method to obtain a target function.

[0062] In an optional embodiment, step S140 further includes: using the result of subtracting the vibration attenuation trend characteristic from the jitter data as the de-attenuated jitter data; and performing curve fitting on the de-attenuated jitter data and the sine function using the least squares method, specifically: using the sine function as the target function, the de-attenuated jitter data as the input data, and the fitted sine function as the output data as the target function; wherein the amplitude of the target function is a physical property parameter of the elastic unit of the measuring equipment.

[0063] In this step, the vibration attenuation trend characteristic characterizes the vibration attenuation characteristic brought by the shock-absorbing device of the measuring equipment to the jitter data, and its data form is a vector with the same length as the jitter data; finally, the vibration attenuation trend characteristic is subtracted from the jitter data to obtain the de-attenuated jitter data, thereby completing the goal of separating the attenuation factor from the jitter data; at the same time, each element in the vibration attenuation trend characteristic is subtracted from the measured weight of the measuring equipment and recorded as an attenuation curve. This step is because the measured weight will affect the numerical value of the vibration attenuation trend characteristic, and numerical correction is required to characterize the attenuation trend of the jitter characteristics of weighing objects of different weights on the measuring equipment.

[0064] In the de-attenuated jitter data, the data can be decomposed into a data model based on Hooke's law and a data model under external force interference; when the data satisfies Hooke's law, the vibration of the object on the measuring equipment should be a simple harmonic vibration. At the same time, since the elastic force acting on the object should be proportional to the distance the object moves, in the absence of external force interference, the jitter data will take the shape of a sine function. Therefore, the de-attenuated jitter data is curve fitted with the sine function. The part with the best fitting effect in the fitting result is the data part that is not interfered with by external force. Using the data of this part to judge whether the elastic shock absorbing unit and sensor parameters of the measuring equipment have changed can obtain more accurate judgment results.

[0065] In the process of fitting the sine function with the de-attenuated jitter data, a higher weight should be given to the position with a larger index number of the de-attenuated jitter data. This is because during the use of the measuring equipment, the impact of external forces on the measuring equipment is concentrated in the early stage of the stabilization of the measuring equipment data. The closer to the moment of data stabilization, the less likely the object on the measuring equipment is to be affected by external forces. In actual operation, this manifests as the weighing object having left the user's palm when the user weighs the object. The data index signal is used as a weight to eliminate systematic errors and improve the accuracy of the final calculation results, avoid misjudgment caused by excessive errors in the fitting results, and thus make it impossible to correct the weighing results of the measuring equipment.

[0066] Methods for fitting a sine function to the de-attenuated jitter data include, but are not limited to, fitting using the least squares method. When this method is used for fitting, the sine function is used as the objective function, the fitting parameters are the amplitude A and phase φ of the sine function, and the input is the de-attenuated jitter data. When calculating the residuals in the set, the time m of the data can be selected as the weight. The data position with a larger time m has a higher weight when calculating the residual. The final output is the fitted sine function, i.e., the objective function. The amplitude A of the objective function is a physical property parameter of the elastic unit of the measuring equipment. When the physical properties of the unit change, the amplitude A usually changes accordingly.

[0067] Step S150: Determine whether the measuring device currently needs to be calibrated based on the comparison result of the objective function, the attenuation curve, and the standard objective function and standard attenuation curve preset by the system.

[0068] In an optional implementation, the method further includes: constructing an external force interference weight based on the de-attenuated jitter data and the objective function.

[0069] In this step, the de-attenuated jitter data and the objective function are compared to construct an external force interference weight. The greater the difference, the more severely affected the location is by the external force. The jitter data at that location should be used less frequently to determine whether the elastic damping unit or sensor parameters have changed. The greater the external force interference weight at the corresponding time m, the greater the difference. Methods for calculating the external force interference weight include, but are not limited to, using the absolute value of the difference between the de-attenuated jitter data and the fitted sine function as the external force interference weight.

[0070] Since the amplitude of the attenuation curve and the objective function characterize the changing characteristics of the elastic shock absorbing unit or sensor parameters of the measuring equipment, the jitter data is obtained during the last calibration measurement of the measuring equipment during the last calibration, and the amplitude and attenuation curve of the jitter data are calculated according to the method described in this embodiment, which are respectively recorded as the standard amplitude and standard attenuation curve. At the same time, the external force interference weight of the standard attenuation curve is obtained and recorded as the standard external force interference weight.

[0071] In an optional embodiment, step S150 further includes: calculating the data credibility weight based on the external force interference weight and the standard external force interference weight preset by the system; calculating the attenuation characteristic difference based on the attenuation curve, the data credibility weight, and the standard attenuation curve preset by the system; calculating the amplitude characteristic difference based on the target function amplitude and the target function amplitude preset by the system; when the attenuation characteristic difference and / or the amplitude characteristic difference exceeds the error threshold preset by the system, determining that the measuring equipment currently needs to be calibrated.

[0072] Finally, the attenuation curve and the amplitude of the target function during this weighing are compared with the standard attenuation curve and the standard amplitude. When comparing the attenuation curves, the external force interference weight and the standard external force interference weight are first summed and then the inverse is obtained. All inverses are normalized to obtain the data credibility weight. The larger the data credibility weight, the less the data at the mth moment is subject to external force interference. The comparison result at this time can accurately characterize whether the elastic shock absorbing unit and the sensor parameters of the measuring equipment have changed; and the greater the difference in the final comparison result, the more likely it is that a measurement error will occur in the nth weighing and needs to be corrected.

[0073] The comparison method includes but is not limited to: calculating the absolute value of the difference between the standard attenuation curve function value and the attenuation curve function value at time m, then comparing the difference with the sum of the two function values, and then summing the sum with the data credibility weight as the weight to obtain the attenuation characteristic difference; calculating the absolute value of the difference between the target function amplitude and the standard amplitude, and then dividing it by the sum of the two to obtain the amplitude characteristic difference.

[0074] Among them, the amplitude characteristic difference mainly indicates whether the physical parameters including the spring coefficient of the elastic shock-absorbing unit of the measuring equipment have changed, resulting in a change in the amplitude of its fitting function. If there is a change, it means that the measuring equipment needs to be calibrated; the attenuation characteristic difference mainly indicates whether the weighing curve function of the sensor varies when measuring weight. When the degree of variation is large, it means that the measuring equipment needs to be calibrated.

[0075] If the difference in attenuation or amplitude characteristics exceeds the system's preset error threshold, it is determined that a measurement error has occurred and needs to be corrected. The alarm module will then operate. Otherwise, the weight will be displayed normally. The error threshold is empirically set to 0.05.

[0076] Step S160: If it is determined that the measuring device currently needs to be calibrated, the measuring device is dynamically calibrated.

[0077] In an optional embodiment, step S160 further includes: completing calibration based on the calibration unit and the equipped weights in the measuring device; wherein, the calibration unit specifically comprises: forming a data pair according to the voltage size of the measuring device and the weight size, and multiple data pairs forming a weighing curve data set, and then using the weighing curve data set as input, using the mean interpolation algorithm to calculate, outputting a weighing curve function, and replacing the original weighing curve function with the output weighing curve function to complete the calibration of the measuring device.

[0078] Specifically, if it is determined that the measuring device currently needs to be calibrated, a reminder message is sent to the user of the measuring device through the indicator light, reminding the user that a measurement error occurred in the measurement and the measurement result is unreliable. At the same time, the user is reminded to calibrate the weighing curve of the measuring device.

[0079] The weighing curve can be calibrated using the calibration unit and weights in the measuring device. The user is required to place the weights in the measuring device in sequence according to the prompts of the measuring device, and the measuring device records the voltage information of the capacitive sensor at this time.

[0080] The mean interpolation algorithm is a commonly used technique in the field of computer data processing. Optionally, to improve accuracy, the mean interpolation algorithm can be replaced by a polynomial interpolation algorithm, a cubic spline interpolation algorithm, or the like.

[0081] Optionally, the calibration of the measuring equipment can also be performed by the customer sending the measuring equipment to the manufacturer, and the manufacturer will calibrate the measuring equipment and then send it back to the user.

[0082] By adopting the method of this embodiment, the jitter data of the measuring equipment is used to detect in real time whether the elastic shock-absorbing module and sensor parameters of the measuring equipment have changed. Therefore, it is possible to dynamically determine whether there is an error in the measurement of the measuring equipment, and to promptly discover the measurement error and calibrate the measuring equipment. This solves the problem that traditional measuring equipment calibration methods cannot perform real-time dynamic calibration of the measuring equipment, resulting in measurement errors during the use of the measuring equipment, and improves the measurement accuracy of the measuring equipment.

[0083] Figure 3 A schematic structural diagram of an embodiment of a dynamic correction system for measuring equipment according to the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the correction system.

[0084] like Figure 3 As shown, the correction system may include:

[0085] Processor, Communications Interface, Memory, and Communication Bus.

[0086] The processor, communication interface, and memory communicate with each other via a communication bus. The communication interface is used to communicate with other devices, such as client devices or other server network elements. The processor is used to execute a program, specifically, the steps described in the aforementioned embodiment of a dynamic calibration method for a metering device.

[0087] Specifically, the program may include program codes including computer operation instructions.

[0088] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the server may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0089] Memory, used to store programs. Memory may include high-speed RAM (RAM) or non-volatile memory, such as at least one disk drive.

[0090] The program can be specifically used to cause the processor to perform the following operations:

[0091] Real-time acquisition of jitter data of measuring equipment during weighing;

[0092] The envelope extraction algorithm is used to fuse the jitter data to obtain the vibration attenuation trend characteristics;

[0093] The attenuation curve is obtained based on the vibration attenuation trend characteristics and the real-time weighing results;

[0094] De-attenuated jitter data is obtained based on the jitter data and vibration attenuation trend characteristics, and the de-attenuated jitter data is fitted using the least squares method to obtain the target function;

[0095] Determine whether the measuring equipment currently needs to be calibrated based on the comparison results of the objective function, the attenuation curve and the standard objective function and the standard attenuation curve preset by the system;

[0096] If so, perform dynamic calibration on the measuring equipment.

[0097] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0098] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A dynamic calibration method for measuring equipment, characterized in that: The method comprises: Real-time acquisition of jitter data of measuring equipment during weighing; Performing data fusion on the jitter data using an envelope extraction algorithm to obtain vibration attenuation trend characteristics; Obtaining an attenuation curve based on the vibration attenuation trend characteristics and the real-time weighing results; Obtaining de-attenuated jitter data according to the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using a least squares method to obtain a target function; Determining whether the measuring device currently needs to be calibrated based on a comparison result of the objective function, the attenuation curve, and a standard objective function and a standard attenuation curve preset by the system; If so, dynamically calibrate the measuring device; The step of fusing the jitter data using an envelope extraction algorithm to obtain a vibration attenuation trend feature further includes: Taking the jitter data as input data, adopting an envelope extraction algorithm, and outputting the upper envelope and lower envelope of the jitter data; The lower envelope is processed symmetrically along a preset straight line to obtain a symmetrical lower envelope; The lower envelope and the upper envelope are subjected to data fusion to obtain a vibration attenuation trend characteristic; wherein the jitter data is in the form of a vector with a length of 3000, the mth element represents the measured weight of the measuring device at time m, and m = 0-3000; The data format of the vibration attenuation trend feature is the same as the data format of the jitter data; The step of obtaining the attenuation curve based on the vibration attenuation trend characteristics and the real-time weighing results further includes: Subtracting the measured weight of the measuring device when the measured weight value is stable from each element in the vibration attenuation trend characteristic to record it as an attenuation curve; Obtaining de-attenuated jitter data based on the jitter data and the vibration attenuation trend characteristics, and fitting the de-attenuated jitter data using the least squares method to obtain the objective function further includes: The result of subtracting the vibration attenuation trend characteristic from the jitter data is taken as the jitter data after de-attenuation; The de-attenuated jitter data and the sine function are curve-fitted using the least squares method, specifically: the sine function is used as the target function, the de-attenuated jitter data is used as input data, and the fitted sine function is used as output data as the target function; The amplitude of the objective function is a physical property parameter of the elastic unit of the measuring equipment.

2. A dynamic calibration method for measuring equipment according to claim 1, characterized in that: The real-time acquisition of jitter data of the measuring device during weighing further includes: When the weight value measured by the measuring device is stable, obtaining the measured weight of the measuring device; At the same time, the moment when the weight value measured by the measuring device is stable is used as the end moment, and the moment before the preset jitter duration before the end moment is used as the start moment, and a change curve of the weight measured by the measuring device within the preset jitter duration is obtained; wherein the horizontal axis of the change curve is time and the vertical axis is measured weight; The variation curve is recorded as jitter data.

3. A dynamic calibration method for measuring equipment according to claim 1, characterized in that: The method further comprises: An external force interference weight is constructed according to the de-attenuated jitter data and the objective function.

4. A dynamic calibration method for measuring equipment according to claim 3, characterized in that: The determining whether the measuring device currently needs to be calibrated based on the comparison result of the objective function, the attenuation curve, and the standard objective function and standard attenuation curve preset by the system further includes: Calculating the data credibility weight based on the external force interference weight and the standard external force interference weight preset by the system; Calculating the attenuation characteristic difference based on the attenuation curve, the data credibility weight, and a standard attenuation curve preset by the system; Calculating an amplitude characteristic difference based on the objective function amplitude and the objective function amplitude preset by the system; When the attenuation characteristic difference and / or the amplitude characteristic difference exceeds an error threshold preset by the system, it is determined that the measuring device currently needs to be calibrated.

5. A dynamic calibration method for measuring equipment according to claim 4, characterized in that: The dynamic calibration of the measuring device further comprises: Calibration is performed based on the calibration unit and weights in the measuring device; Among them, the calibration unit specifically comprises: forming a data pair according to the voltage size of the measuring equipment and the size of the weight, and multiple data pairs forming a weighing curve data set, and then taking the weighing curve data set as input, using the mean interpolation algorithm to calculate, outputting the weighing curve function, and using the output weighing curve function to replace the original weighing curve function to complete the calibration of the measuring equipment.

6. A dynamic calibration system for measuring equipment, characterized in that: include: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the dynamic correction method for measuring equipment according to any one of claims 1 to 5.

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