Intelligent weighing data recognition method based on networked electronic scale

Abstract

The application discloses an intelligent weighing data recognition method based on a network-connected electronic scale, and belongs to the technical field of weighing data processing. The method comprises the following steps: acquiring an initial zero-point voltage signal of the network-connected electronic scale in an empty load period and an original weighing voltage sequence in a load change stage; performing sliding window sampling on the original weighing voltage sequence and extracting voltage fluctuation characteristic parameters; combining the initial zero-point voltage signal to generate a dynamic drift compensation factor, and correcting the original weighing voltage sequence point by point to obtain a smooth voltage sequence; identifying an effective weighing interval according to a voltage jump edge feature in the smooth voltage sequence, and extracting a plurality of steady-state voltage subintervals from the effective weighing interval; determining a final weighing voltage representative value according to the discrete degree of the voltage average values of the steady-state voltage subintervals, and then combining a pre-designed weight scale to calculate and output a weighing result. The method improves the accuracy and stability of the weighing data under dynamic interference.

Description

Technical Field

[0001] This invention relates to the field of weighing data processing technology, specifically to an intelligent weighing data recognition method based on a networked electronic scale. Background Technology

[0002] In fields such as commodity trading and logistics measurement, networked electronic scales need to output accurate weighing results quickly. Current weighing data identification processes typically use the single-point or short-time average voltage of the sensor after the load stabilizes as the effective signal, subtracting it from a fixed zero-point calibration value to calculate the weight. However, weighing sensors are susceptible to time-varying factors such as temperature changes, component aging, and circuit noise during operation, causing zero-point drift. This means the fixed zero-point calibration cannot reflect the true unloaded state at the time of weighing. Simultaneously, the mechanical shock and vibration generated when goods are placed introduce significant non-stationary fluctuations into the sensor output. Conventional low-pass filtering or fixed threshold truncation methods struggle to accurately separate the true steady-state load range. Including these undifferentiated fluctuations in the calculation reduces the repeatability and accuracy of the weighing results. Therefore, how to dynamically and automatically track and compensate for signal offset caused by zero-point drift during a single weighing process, and how to automatically find steady-state data segments that truly represent the object's weight from voltage sequences containing strong dynamic interference, are two key issues for improving dynamic weighing accuracy. Summary of the Invention

[0003] This paper presents an intelligent weighing data recognition method based on a network-connected electronic scale, which realizes dynamic zero-point compensation and autonomous extraction of steady-state data during the weighing process, thereby improving weighing accuracy and anti-interference capability.

[0004] To achieve the above objectives, the present invention provides the following technical solution: The present invention discloses an intelligent weighing data recognition method based on a network-connected electronic scale, comprising the following steps: acquiring the initial zero-point voltage signal generated by the network-connected electronic scale during the no-load period, and collecting the continuous original weighing voltage sequence of the network-connected electronic scale during the load change phase; performing sliding window sampling on the original weighing voltage sequence, and extracting voltage fluctuation characteristic parameters within each window; generating a dynamic drift compensation factor corresponding to the current weighing process based on the voltage fluctuation characteristic parameters and the initial zero-point voltage signal; and using the dynamic drift compensation factor to adjust the original weighing voltage... The sequence is corrected point by point to obtain a compensated steady voltage sequence; based on the voltage transition edge characteristics in the steady voltage sequence, the effective weighing range of the target object placed on the network-connected electronic scale is identified; multiple steady-state voltage sub-ranges are extracted from the steady voltage sequence within the effective weighing range; the average voltage of each steady-state voltage sub-range is calculated, and the final representative weighing voltage value of the target object is determined based on the dispersion between the average voltage values ​​of all steady-state voltage sub-ranges; based on the final representative weighing voltage value and the preset metrological scale of the network-connected electronic scale, the weighing result of the target object is calculated and output.

[0005] As a preferred embodiment of the present invention, the process of obtaining the initial zero-point voltage signal further includes: after the network-connected electronic scale is powered on and started, continuously monitoring the real-time zero-point voltage value output by the weighing sensor; when the maximum fluctuation amplitude of the real-time zero-point voltage value within a continuous first preset time period is less than a preset fluctuation threshold, the arithmetic mean of all real-time zero-point voltage values ​​within the continuous first preset time period is taken as the initial zero-point voltage signal, and the generation time of the initial zero-point voltage signal is recorded. In this way, the zero-point reference selected through the stability criterion can effectively avoid the influence of instantaneous power-on disturbances on zero-point calibration.

[0006] As another preferred technical solution of the present invention, the process of acquiring the original weighing voltage sequence further includes: real-time monitoring of the instantaneous voltage change rate output by the weighing sensor of the network-connected electronic scale; when the instantaneous voltage change rate first exceeds a preset change rate threshold, it is determined that the network-connected electronic scale has entered the load change stage, and the voltage value of each sampling point output by the weighing sensor is continuously acquired starting from this moment until the instantaneous voltage change rate is lower than the preset change rate threshold for a continuous second preset time period, at which point the acquisition stops, and the voltage values ​​of all the acquired sampling points are arranged in the order of acquisition time to form the original weighing voltage sequence. This method can completely capture the entire process from object placement to weighing stabilization, avoiding the omission of key transition information.

[0007] Preferably, the process of performing sliding window sampling and extracting voltage fluctuation feature parameters on the original weighing voltage sequence includes: sequentially sliding multiple voltage sub-windows on the original weighing voltage sequence according to a preset step size and a preset window width; for each voltage sub-window, calculating the range, variance, and number of peaks of all voltage values ​​within the sub-window, where the number of peaks is the number of sampling points where the voltage value within the sub-window is greater than the mean voltage value within the sub-window; and combining the range, variance, and number of peaks of the sub-window to form the voltage fluctuation feature parameters corresponding to the sub-window. The extracted multidimensional fluctuation features can sensitively reflect the degree of mechanical vibration and electromagnetic interference during the weighing process, providing a reliable basis for subsequent drift estimation.

[0008] Furthermore, the process of generating the dynamic drift compensation factor includes: sorting the variance values ​​of the voltage fluctuation characteristic parameters corresponding to all the voltage sub-windows, and selecting the three voltage sub-windows with the smallest variance values ​​as candidate stable windows; calculating the window average value of all voltage values ​​within each candidate stable window, and averaging the average values ​​of the three voltage sub-windows again to obtain the average voltage of the stable window; subtracting the voltage value corresponding to the initial zero-point voltage signal from the average voltage of the stable window to obtain the zero-point drift amount of the current weighing process; and generating the dynamic drift compensation factor based on the rate of change of the zero-point drift amount over time. The dynamic drift compensation factor includes a drift direction identifier and a drift rate value. By selecting the stable window with the smallest variance to estimate the zero-point drift, the interference of load fluctuations on the drift amount calculation can be eliminated, improving the accuracy of the compensation factor.

[0009] In a preferred embodiment of the present invention, the process of point-by-point correction of the original weighing voltage sequence using the dynamic drift compensation factor includes: determining the correction polarity of the voltage value at each sampling point in the original weighing voltage sequence based on the drift direction identifier; calculating the instantaneous drift compensation amount corresponding to each sampling point based on the drift rate value and the time interval between each sampling point and the start time of the original weighing voltage sequence; superimposing the instantaneous drift compensation amount on the voltage value of each sampling point according to the corresponding correction polarity to obtain the compensated voltage value of each sampling point; and rearranging the compensated voltage values ​​of all sampling points according to the acquisition time order to form the compensated stable voltage sequence. This point-by-point compensation method can eliminate the system error introduced by the linear drift of the sensor zero point over time, making the voltage sequence more realistically reflect load changes.

[0010] Preferably, the process of identifying the effective weighing interval includes: calculating the voltage difference between two adjacent sampling points in the stationary voltage sequence to obtain a voltage difference sequence; finding the position of the first sampling point corresponding to the first positive difference value greater than a preset rising edge threshold and the position of the second sampling point corresponding to the first negative difference value less than a preset falling edge threshold from the voltage difference sequence; if the position of the first sampling point is earlier than the position of the second sampling point, then the position of the first sampling point is determined as the starting boundary of the effective weighing interval, and the position of the second sampling point is determined as the ending boundary of the effective weighing interval; extracting the voltage values ​​corresponding to all sampling points between the starting boundary and the ending boundary as the stationary voltage sequence segment within the effective weighing interval. Utilizing the automatic positioning of the effective interval using the transition edge can accurately exclude non-steady-state transition data during the object placement and removal stages, retaining only information from the actual load-bearing period.

[0011] Furthermore, the process of extracting multiple steady-state voltage sub-intervals includes: starting from the initial sampling point in the steady-state voltage sequence segment within the effective weighing interval, traversing each sampling point sequentially; whenever the absolute value of the difference between the voltage value of the current sampling point and the voltage value of the previous sampling point is less than a preset steady-state discrimination threshold, the current sampling point is marked as a candidate steady-state point; consecutive sampling points all marked as candidate steady-state points are grouped into a steady-state candidate segment; when the length of the steady-state candidate segment reaches a preset minimum length threshold, the steady-state candidate segment is extracted as a steady-state voltage sub-interval; this traversal continues until all sampling points in the steady-state voltage sequence segment within the effective weighing interval have been traversed, resulting in multiple steady-state voltage sub-intervals. Through steady-state discrimination and minimum length constraints, instantaneous spikes and short-term fluctuations can be filtered out, obtaining multiple data segments representing the true stable weighing state.

[0012] As another preferred embodiment of the present invention, the process of determining the final representative value of the weighing voltage includes: calculating the arithmetic mean of the voltage values ​​of all sampling points within each steady-state voltage sub-interval, as the sub-interval average voltage of each steady-state voltage sub-interval; calculating the total average value of all sub-interval average voltages, and calculating the relative deviation of each sub-interval average voltage relative to the total average value; removing sub-interval average voltages whose relative deviation exceeds a preset deviation threshold to obtain the remaining sub-interval average voltages after filtering; and averaging the remaining sub-interval average voltages again to obtain the final representative value of the weighing voltage. Removing sub-intervals with excessively large dispersion can eliminate local weighing deviations caused by occasional external disturbances, making the final representative value more robust.

[0013] Preferably, the process of calculating and outputting the weighing result includes: converting the final weighing voltage representative value into an initial weight value according to the scaling factor in the preset metrological scale of the network-connected electronic scale; obtaining the local gravitational acceleration value at the current location of the network-connected electronic scale; correcting the initial weight value according to the ratio of the local gravitational acceleration value to the standard gravitational acceleration value to obtain the final weight value; multiplying the final weight value by the range correction coefficient in the preset metrological scale of the network-connected electronic scale to obtain the final weighing result of the target object, and outputting the final weighing result. Through gravitational acceleration calibration and range correction, the weighing result can adapt to the weighing needs of different geographical locations and maintain high metrological accuracy across the entire range.

[0014] This invention effectively suppresses the impact of sensor zero drift, dynamic impact and random interference on weighing accuracy by performing dynamic drift compensation, edge positioning, steady-state interval screening and dispersion optimization on the original weighing voltage signal, and significantly improves the reliability of weighing data and intelligent recognition capability of networked electronic scales under complex working conditions.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: The process involves acquiring the initial zero-point voltage signal generated during the no-load period of the network-connected electronic scale and collecting continuous raw weighing voltage sequences during load changes. A sliding window sampling method is applied to the raw weighing voltage sequences, extracting voltage fluctuation characteristic parameters within each window. Based on the voltage fluctuation characteristic parameters and the initial zero-point voltage signal, a dynamic drift compensation factor corresponding to the current weighing process is generated. This dynamic drift compensation factor is then used to correct the raw weighing voltage sequence point by point, resulting in a compensated stable voltage sequence. This processing method eliminates the dependence on external fixed zero-point calibration values. By analyzing the fluctuation characteristics of the sensor signal during the weighing process, it automatically determines and reconstructs the zero-point drift trend adapted to the dynamic load of that weighing. The corrected voltage sequence effectively eliminates signal baseline offset caused by time-varying factors such as temperature and circuit status, ensuring that subsequent weighing calculations are always based on the corrected signal level. This avoids the cumulative error of fixed zero-point deviation over time and improves the consistency of data in multiple consecutive weighings. Based on the voltage transition edge characteristics in the stationary voltage sequence, the effective weighing interval for placing the target object is identified. Multiple steady-state voltage sub-intervals are extracted from the stationary voltage sequence within the effective weighing interval. The average voltage value of each steady-state voltage sub-interval is calculated, and the final representative weighing voltage value is determined based on the dispersion among the average voltage values ​​of all steady-state voltage sub-intervals. This method no longer relies on a single sampling point voltage or directly averaging all data from the loaded segment. Instead, it locates the core period of load application based on the transition edge and further filters out multiple signal segments that are actually in a stable state within this period. By analyzing the consistency of the average voltage values ​​of these steady-state segments, abnormal segments that deviate from the overall central tendency due to brief disturbances are eliminated. This ensures that the final representative weighing voltage value accurately reflects the stable load signal characteristics of the measured object, effectively eliminating the interference of instantaneous impact and residual oscillations on the measurement results and enhancing the stability of the weighing output value. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a flowchart of an intelligent weighing data recognition method based on a network-connected electronic scale; Figure 2 This is a flowchart of the zero-point calibration and load change detection process for network-connected electronic scales; Figure 3 This is a flowchart of the sliding window voltage fluctuation feature extraction and zero-point drift compensation process; Figure 4 This is a flowchart of dynamic drift compensation for weighing voltage sequence; Figure 5 This is a flowchart of weighing signal processing based on steady-state voltage sub-interval deviation screening. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] See Figure 1 This invention provides an intelligent weighing data recognition method based on a network-connected electronic scale. The method acquires the initial zero-point voltage signal generated by the network-connected electronic scale during the no-load period and collects continuous raw weighing voltage sequences during load changes. It performs sliding window sampling on the raw weighing voltage sequences, extracting voltage fluctuation characteristic parameters within each window. Based on the voltage fluctuation characteristic parameters and the initial zero-point voltage signal, it generates a dynamic drift compensation factor corresponding to the current weighing process. The dynamic drift compensation factor is used to correct the raw weighing voltage sequence point by point, obtaining a compensated stable voltage sequence. Based on the voltage transition edge characteristics in the stable voltage sequence, the effective weighing range of the target object placed on the network-connected electronic scale is identified. Multiple steady-state voltage sub-ranges are extracted from the stable voltage sequence within the effective weighing range. The average voltage value of each steady-state voltage sub-range is calculated, and the final representative weighing voltage value of the target object is determined based on the dispersion between the average voltage values ​​of all steady-state voltage sub-ranges. Based on the final representative weighing voltage value and the preset metrological scale of the network-connected electronic scale, the weighing result of the target object is calculated and output.

[0020] Example 1:

[0021] In specific implementation, please refer to Figure 2After the connected electronic scale is powered on, it continuously monitors the real-time zero-point voltage value output by the weighing sensor. The real-time zero-point voltage value output by the weighing sensor is an analog voltage signal, which is converted into a digital quantity by an analog-to-digital converter. This digital quantity is then read by the microcontroller of the connected electronic scale at a fixed sampling period and temporarily stored in a buffer. During monitoring, the microcontroller continuously updates the currently read real-time zero-point voltage value and maintains a sliding window data queue that records all real-time zero-point voltage values ​​within the most recent first preset time period. The first preset time period is a pre-configured time length, determined based on the sensor stability characteristics of the connected electronic scale, for example, set to 30 seconds. When the time span covered by the data points in the sliding window data queue reaches the first preset time period, the microcontroller calculates the maximum fluctuation amplitude of the real-time zero-point voltage value within that first preset time period. The maximum fluctuation amplitude is the difference between the maximum and minimum values ​​among all real-time zero-point voltage values ​​within the sliding window. The microcontroller compares the maximum fluctuation amplitude with a preset fluctuation threshold. The preset fluctuation threshold is a voltage value pre-calibrated based on the system noise level and allowable zero-point drift tolerance of the networked electronic scale. For example, the preset fluctuation threshold is 0.05% of the full-scale output voltage of the weighing sensor.

[0022] When the maximum fluctuation amplitude of the real-time zero-point voltage value within a continuous first preset time period is less than a preset fluctuation threshold, it is determined that the current no-load state has reached stability. At this time, the microcontroller extracts all real-time zero-point voltage values ​​within the first preset time period from the current sliding window data queue, calculates the arithmetic mean of these real-time zero-point voltage values, and uses the calculated arithmetic mean as the initial zero-point voltage signal. Simultaneously, the microcontroller records the moment when the arithmetic mean calculation is completed as the generation time of the initial zero-point voltage signal, and stores the initial zero-point voltage signal and the generation time together in non-volatile memory.

[0023] In some embodiments, if the maximum fluctuation amplitude is greater than or equal to a preset fluctuation threshold, the sliding window data queue is updated, and the calculation of the maximum and minimum values ​​and the comparison of fluctuation amplitude are repeated until the stability condition is met.

[0024] After acquiring the initial zero-point voltage signal, the networked electronic scale enters the load monitoring state. The microcontroller monitors the instantaneous voltage change rate output by the weighing sensor of the networked electronic scale in real time. The instantaneous voltage change rate is calculated by the microcontroller based on the voltage values ​​of two consecutive samples. Specifically, let the weighing sensor output voltage value acquired at the current sampling moment be... The voltage value collected at the previous sampling time is The time interval between the two samplings is Then the instantaneous voltage change rate The calculation method is as follows:

[0025] in, This indicates the voltage value output by the weighing sensor at the current sampling time, in millivolts. This indicates the voltage value output by the weighing sensor at the previous sampling time, in millivolts. This represents the time interval between two consecutive samples, in seconds. It is the reciprocal of the sampling period, which is determined by the sampling rate of the analog-to-digital converter of the network-connected electronic scale; This represents the instantaneous voltage change rate calculated at the current sampling moment, in millivolts per second.

[0026] The microcontroller will calculate the instantaneous voltage change rate. The value is compared with a preset rate of change threshold. The preset rate of change threshold is a pre-set positive value used to distinguish between minor fluctuations caused by environmental noise and significant load changes caused by the placement of objects. The preset rate of change threshold is determined based on the sensitivity of the weighing sensor of the networked electronic scale and the voltage change rate corresponding to the minimum identifiable load weight in the actual application scenario. For example, the preset rate of change threshold is the rate of change corresponding to a 1% change in the full-scale output voltage of the weighing sensor within 0.1 seconds.

[0027] When the instantaneous voltage change rate When the preset rate of change threshold is exceeded for the first time, the microcontroller determines that the networked electronic scale has entered the load change phase, and takes this moment as the starting point of the load change phase, and begins to continuously collect the voltage value of each sampling point output by the weighing sensor. During the continuous collection process, the voltage value of each sampling point is accompanied by a collection timestamp, and is temporarily stored in the dynamic storage area in the order of collection.

[0028] The microcontroller continuously calculates the instantaneous voltage change rate at each subsequent sampling point and simultaneously monitors whether the instantaneous voltage change rate remains below a preset change rate threshold for a continuous second preset time period. The second preset time period is a pre-set duration used to confirm that the load signal has returned to stability after the object placement action is completed. The value of the second preset time period is determined based on the damping characteristics of the networked electronic scale's mechanical structure and the response time of the weighing sensor; for example, the second preset time period is set to 5 seconds.

[0029] At each sampling moment after the start of the load change phase, the microcontroller compares the latest calculated instantaneous voltage change rate with a preset change rate threshold and records the duration for which the instantaneous voltage change rate is continuously lower than the preset change rate threshold. When it is detected that the instantaneous voltage change rate calculated at each sampling point within a consecutive second preset time period is less than the preset change rate threshold, the microcontroller determines that the load change process has ended and stops collecting the voltage value output by the weighing sensor.

[0030] At this point, the microcontroller arranges the voltage values ​​of all sampling points collected from the start of the load change phase to the stop of data acquisition according to the chronological order of their respective acquisition timestamps, forming a voltage-time sequence, which is the original weighing voltage sequence. The original weighing voltage sequence contains complete voltage change information before the object is placed, at the instant of placement, and after the signal tends to stabilize, and is stored in the memory of the networked electronic scale for subsequent processing.

[0031] Example 2:

[0032] In specific implementation, please refer to Figure 3 After obtaining the original weighing voltage sequence, sliding window sampling is performed. Multiple voltage sub-windows are sequentially slid across the original weighing voltage sequence according to a preset step size and preset window width. The preset window width determines the number of sampling points contained in each voltage sub-window. The preset window width is set based on the response time of the weighing sensor of the networked electronic scale and the duration of the load change phase; for example, the preset window width is set to 50 sampling points. The preset step size represents the interval sampling points between the starting sampling points of two adjacent voltage sub-windows. The preset step size is smaller than the preset window width to ensure partial overlap between adjacent voltage sub-windows; for example, the preset step size is set to 10 sampling points.

[0033] Starting from the first sampling point of the original weighing voltage sequence, the first voltage sub-window is captured with a preset window width. Then, the window moves backward by a preset number of sampling points to capture the second voltage sub-window, and so on, until the end boundary of the sliding window exceeds the end sampling point of the original weighing voltage sequence, thus obtaining multiple voltage sub-windows.

[0034] For each voltage sub-window that is slid in, the following calculations are performed within that voltage sub-window: calculate the range of all voltage values ​​within the voltage sub-window, where the range is the difference between the maximum and minimum voltage values ​​within the voltage sub-window; calculate the variance of all voltage values ​​within the voltage sub-window; calculate the number of sampling points where the voltage value within the voltage sub-window is greater than the mean voltage value within the voltage sub-window, and use this number as the peak value count.

[0035] Among them, the variance of all voltage values ​​within the voltage sub-window The calculation formula is as follows:

[0036] in, This indicates the total number of sampling points contained within the current voltage sub-window, which is determined by the preset window width; Indicates the current voltage sub-window's... Voltage values ​​at each sampling point The value ranges from 1 to Integer index; This indicates all values ​​within the current voltage sub-window. The arithmetic mean of the voltage values ​​at each sampling point; This represents the variance of the voltage value corresponding to the current voltage sub-window, expressed in millivolts squared. Each parameter in the formula is calculated independently based on the data within the current voltage sub-window.

[0037] The average voltage value within a voltage sub-window is calculated by taking all the voltage values ​​within that sub-window. Summing and dividing by The number of peak values ​​is counted by iterating through the voltage values ​​of each sampling point within the voltage sub-window. , and In comparison, if If the number of peaks increases by one, then the number of peaks will increase by one.

[0038] After calculating the range, variance, and number of peaks for a voltage sub-window, these three values ​​are combined into a voltage fluctuation characteristic parameter, and each voltage fluctuation characteristic parameter is stored in a one-to-one correspondence with the corresponding voltage sub-window.

[0039] The variance values ​​of the voltage fluctuation characteristic parameters corresponding to all voltage sub-windows are sorted in ascending order. The three smallest variance values ​​are selected from the sorted variance values, and the three voltage sub-windows corresponding to these three smallest variance values ​​are chosen as candidate stable windows. The candidate stable windows are the interval segments in the original weighing voltage sequence with the smallest voltage fluctuation amplitude and the most stable signal.

[0040] For each candidate stabilization window, the window average of the voltage values ​​at all sampling points within that window is calculated. This window average is the arithmetic mean of all voltage values ​​within the candidate stabilization window. After obtaining the window averages for each of the three candidate stabilization windows, the arithmetic mean of these three window averages is calculated again, and the resulting value is taken as the average voltage of the stabilization window.

[0041] The difference between the average voltage of the stable window and the voltage value corresponding to the initial zero-point voltage signal is used as the zero-point drift in the current weighing process. The voltage value corresponding to the initial zero-point voltage signal is the value of the initial zero-point voltage signal obtained during the no-load stable phase.

[0042] A dynamic drift compensation factor is generated based on the rate of change of zero-point drift over time. The specific process is as follows: The time information corresponding to the candidate stabilization windows is determined; the starting time of the candidate stabilization window whose time position is in the middle among the three candidate stabilization windows is selected as the reference time; the time offset of this reference time relative to the starting time of the original weighing voltage sequence is denoted as... The zero-point drift is The rate of change of the zero-point drift over time is... This rate of change is the drift rate value. Based on the zero-point drift... The positive and negative values ​​determine the drift direction indicator, if A positive value indicates a positive drift direction; if... A negative value indicates a negative drift direction. The dynamic drift compensation factor includes both the drift direction indicator and the drift rate value.

[0043] Example 3:

[0044] In specific implementation, please refer to Figure 4 The system retrieves the generated dynamic drift compensation factor and the original weighing voltage sequence from memory. The dynamic drift compensation factor includes a drift direction indicator and a drift rate value. The drift direction indicator indicates the polarity of the zero-point drift; different values ​​correspond to positive or negative drift, respectively. The drift rate value is a scalar value representing the rate of change of the zero-point drift per unit time; the unit of the drift rate value is the voltage change per unit time.

[0045] The correction polarity of the voltage value at each sampling point in the original weighing voltage sequence is determined based on the drift direction indicator. The correction polarity is defined as the direction of calculation when compensating for the voltage value at the sampling point. When the drift direction indicator indicates a positive drift, the correction polarity is determined to be negative, indicating that the drift compensation amount is subtracted from the original voltage value. When the drift direction indicator indicates a negative drift, the correction polarity is determined to be positive, indicating that the drift compensation amount is added to the original voltage value.

[0046] For each sampling point in the original weighing voltage sequence, calculate the instantaneous drift compensation amount corresponding to that sampling point. The instantaneous drift compensation amount is related to the time interval between the sampling point and the start time of the original weighing voltage sequence. Specifically, the calculation method is as follows: obtain the timestamp corresponding to the start time of the original weighing voltage sequence, obtain the acquisition timestamp carried by the current sampling point, calculate the difference between the acquisition timestamp of the current sampling point and the start timestamp, and obtain the time interval between the current sampling point and the start time of the original weighing voltage sequence. The formula for calculating the instantaneous drift compensation amount is as follows:

[0047] in, This indicates the index number of the sampling point in the original weighing voltage sequence. From 1 to integers, This represents the total number of sampling points in the original weighing voltage sequence. Indicates the first The time interval between each sampling point relative to the start time of the original weighing voltage sequence The unit is seconds. The value is obtained through the first The timestamps of each sampling point are obtained by subtracting the timestamp of the start time of the original weighing voltage sequence. This represents the drift rate value extracted from the dynamic drift compensation factor. The unit is millivolts per second. The value is calculated from the rate of change of the zero-point drift over time. Indicates the first The instantaneous drift compensation amount corresponding to each sampling point The unit is millivolt.

[0048] The instantaneous drift compensation amount corresponding to each sampling point in the original weighing voltage sequence was calculated. Then, the voltage value of each sampling point is superimposed with the instantaneous drift compensation amount according to the correction polarity corresponding to that sampling point to obtain the compensated voltage value of each sampling point. The specific method of superposition operation is as follows: when the correction polarity is positive, the compensated voltage value is equal to the original sampling point voltage value plus... When the correction polarity is negative, the compensated voltage value is equal to the original sampling point voltage value minus... .

[0049] In some embodiments, the mapping relationship between the corrected polarity and the drift direction identifier is fixedly stored in the configuration parameter area of ​​the networked electronic scale, and is read by the microcontroller during the correction process and the corresponding addition and subtraction operations are executed.

[0050] After calculating the compensated voltage values ​​for all sampling points in the original weighing voltage sequence, the compensated voltage values ​​are rearranged according to the original timestamps of each sampling point. The order of the timestamps corresponds to the sampling time order of the sampling points in the original weighing voltage sequence. The elements in the rearranged voltage value sequence are the compensated voltage values, and the element arrangement order is consistent with the arrangement order of the corresponding sampling points in the original weighing voltage sequence. The rearranged voltage value sequence is the compensated stable voltage sequence. The compensated stable voltage sequence is stored in the memory of the networked electronic scale. This compensated stable voltage sequence eliminates the zero-point drift caused by long-term operation or temperature changes.

[0051] Example 4:

[0052] In practice, a compensated stationary voltage sequence is obtained, which consists of the compensated voltage values ​​from multiple sampling points arranged in chronological order of acquisition time. The voltage difference between each pair of adjacent sampling points in the stationary voltage sequence is calculated; adjacent sampling points refer to the preceding and following sampling points in the stationary voltage sequence that are acquired at adjacent times. All voltage differences between adjacent sampling point pairs in the stationary voltage sequence are then arranged in chronological order according to the position of the corresponding preceding sampling point within the stationary voltage sequence, forming a voltage difference sequence.

[0053] The formula for calculating each voltage difference in the voltage difference sequence is:

[0054] in, This represents the index of the sampling point in the stationary voltage sequence. From 1 to integers, This represents the total number of sampling points contained in a stationary voltage sequence. Indicating the first [unit] in a stationary voltage sequence The compensated voltage value at each sampling point is expressed in millivolts. Indicating the first [unit] in a stationary voltage sequence The compensated voltage value at each sampling point is expressed in millivolts. Indicates the first The voltage difference, i.e., the th voltage difference in the stationary voltage sequence. The sampling point and the first The difference in the compensated voltage values ​​at each sampling point The unit is millivolt.

[0055] After obtaining the voltage difference sequence, a forward search is performed within the sequence to find the first positive voltage difference value greater than a preset rising edge threshold. The preset rising edge threshold is a pre-defined positive voltage difference value, determined based on the lower limit of the voltage step amplitude generated by the networked electronic scale at the instant the target object is placed. For example, the preset rising edge threshold is set to 2% of the full-scale output voltage of the weighing sensor. The search process starts from the first element of the voltage difference sequence and compares each voltage difference value sequentially. The value of the preset rising edge threshold, when it first appears Greater than the preset rising edge threshold and When the sampling point location is positive, the voltage difference is... The corresponding next sampling point (i.e., the first sampling point in the stationary voltage sequence) The position of the first sampling point (one sampling point) in the stationary voltage sequence is recorded as the first sampling point position. The first sampling point position marks the starting point where the voltage signal shows a significant upward jump when the load is first applied.

[0056] After determining the location of the first sampling point, the system continues searching the voltage difference sequence for the first negative voltage difference value less than a preset falling edge threshold value, starting from the location of the first sampling point. The preset falling edge threshold is a pre-defined negative voltage difference value. The absolute value of the preset falling edge threshold can be the same as or different from the absolute value of the preset rising edge threshold. The value of the preset falling edge threshold is determined based on the lower limit of the voltage drop when the target object is removed. For example, the preset falling edge threshold is set to 2% of the negative full-scale output voltage of the load cell. The search process begins with the element in the voltage difference sequence corresponding to the location of the first sampling point and compares each voltage difference value sequentially. The value of the preset falling edge threshold, when it first appears Less than the preset falling edge threshold (i.e. When the sampling point is negative and its absolute value is greater than the absolute value of the preset falling edge threshold, the voltage difference is... The corresponding next sampling point (i.e., the first sampling point in the stationary voltage sequence) The position of the second sampling point (the first sampling point) in the stationary voltage sequence is recorded as the second sampling point position. The second sampling point position marks the end point where the voltage signal shows a significant drop when the load is removed.

[0057] In some embodiments, if no positive or negative difference value that meets the conditions is found in the voltage difference sequence, the network-connected electronic scale determines that no effective load change was detected in this weighing process and ends the identification process.

[0058] After locating the first and second sampling points, their order within the stationary voltage sequence is compared. If the index of the first sampling point in the stationary voltage sequence is less than the index of the second sampling point, meaning the first sampling point occurred earlier than the second, then the first sampling point is defined as the starting boundary of the effective weighing interval, and the second sampling point is defined as the ending boundary. The starting and ending boundaries define the time interval during which the voltage signal carries effective weighing information from the placement to the removal of the target object.

[0059] Extract the voltage values ​​corresponding to all sampling points in the stationary voltage sequence, starting from the sampling point corresponding to the starting boundary and ending at the sampling point corresponding to the ending boundary, including the sampling points at the starting and ending boundaries. Arrange these voltage values ​​in their original order to form a subsequence, which is the stationary voltage sequence segment within the effective weighing range.

[0060] After obtaining a stable voltage sequence segment within the effective weighing range, starting from the initial sampling point of the stable voltage sequence segment, each sampling point in the segment is traversed sequentially. During the traversal, for each current sampling point, the voltage value of the current sampling point and the voltage value of the preceding sampling point are obtained. The absolute value of the difference between the voltage value of the current sampling point and the voltage value of the preceding sampling point is calculated. The absolute value of the calculated difference is compared with a preset steady-state discrimination threshold. The preset steady-state discrimination threshold is a pre-set small voltage fluctuation value, and its value is determined based on the peak-to-peak noise level of the weighing sensor in steady state. For example, the preset steady-state discrimination threshold is set to 0.1% of the full-scale output voltage of the weighing sensor. Whenever the absolute value of the difference between the voltage value of the current sampling point and the voltage value of the preceding sampling point is less than the preset steady-state discrimination threshold, the current sampling point is marked as a candidate steady-state point. If the absolute value is greater than or equal to the preset steady-state discrimination threshold, the current sampling point is not marked as a candidate steady-state point.

[0061] During the traversal, one or more consecutive sampling points that are all marked as candidate steady-state points are grouped into a steady-state candidate segment. A steady-state candidate segment ends when a sampling point not marked as a candidate steady-state point is detected or when the traversal reaches the end of the sequence. It is then determined whether the length of the steady-state candidate segment reaches a preset minimum length threshold. The preset minimum length threshold represents the minimum number of consecutive sampling points that an effective steady-state interval should contain. The preset minimum length threshold is determined based on the data output rate of the networked electronic scale and the required steady-state duration. For example, the preset minimum length threshold is set to 100 sampling points, corresponding to a steady-state duration of approximately 0.5 seconds at a specific sampling rate. When the length of a steady-state candidate segment is greater than or equal to the preset minimum length threshold, the steady-state candidate segment is extracted as a steady-state voltage sub-interval. If the length is insufficient, the steady-state candidate segment is discarded.

[0062] The process of marking, segmenting, and determining length continues until all sampling points in the steady-state voltage sequence segment within the effective weighing range have been traversed, ultimately yielding multiple steady-state voltage sub-intervals within the effective weighing range. Each steady-state voltage sub-interval corresponds to the steady-state voltage signal during a period when the target object remains relatively stationary on the weighing platform.

[0063] Example 5:

[0064] In specific implementation, please refer to Figure 5After obtaining multiple steady-state voltage sub-intervals within the effective weighing range, each steady-state voltage sub-interval is processed separately. Each steady-state voltage sub-interval consists of compensated voltage values ​​from several consecutive sampling points. The arithmetic mean of the voltage values ​​at all sampling points within each steady-state voltage sub-interval is calculated by summing the voltage values ​​at all sampling points within the sub-interval and dividing by the number of sampling points within that sub-interval. The resulting value is taken as the sub-interval average voltage of that steady-state voltage sub-interval.

[0065] After obtaining the average voltage of each sub-interval corresponding to all steady-state voltage sub-intervals, the overall average value of all sub-interval average voltages is calculated. The overall average value is calculated by summing the average voltages of all sub-intervals and then dividing by the total number of steady-state voltage sub-intervals. Let the first sub-interval be... The average voltage of each steady-state voltage sub-interval is , This refers to the numbering of the steady-state voltage sub-intervals. The value range is from 1 to integers, The total number of steady-state voltage sub-intervals extracted from the effective weighing interval is represented by the total average value. The calculation formula is:

[0066] in, Indicates the first The average voltage of each steady-state voltage sub-interval, in millivolts, is calculated from the voltage value of the corresponding steady-state voltage sub-interval. The total number of steady-state voltage sub-intervals is an integer value determined by the aforementioned steady-state voltage sub-interval extraction process; This represents the total average voltage across all sub-intervals, expressed in millivolts.

[0067] To obtain the overall average Then, calculate the average voltage of each sub-interval. relative to the overall average The relative deviation is calculated as follows: subtract the total average value from the average voltage of the sub-interval to obtain the absolute deviation, take the absolute value of the absolute deviation, and then divide it by the total average value. The relative deviation of the average voltage of each sub-interval is compared with a preset deviation threshold. The preset deviation threshold is a pre-set upper limit for relative deviation, and its value is determined based on the degree of swaying of the target object on the weighing platform and the requirements for weighing repeatability. For example, the preset deviation threshold is set to 0.5%. Sub-interval average voltages with relative deviations exceeding the preset deviation threshold are removed from the set of sub-interval average voltages. These removed sub-interval average voltages are considered to be non-representative steady-state values ​​caused by instantaneous movement of the target object or external disturbances. Sub-interval average voltages with relative deviations less than or equal to the preset deviation threshold are retained, and these retained sub-interval average voltages constitute the remaining sub-interval average voltages after screening.

[0068] The arithmetic mean of the average voltages of the remaining sub-intervals after screening is calculated again. This is done by summing the average voltages of all remaining sub-intervals and dividing by the number of remaining sub-intervals. The resulting value is used as the final representative weighing voltage value. This final representative weighing voltage value represents the compensated voltage level corresponding to when the target object is stable during this weighing process.

[0069] After obtaining the final representative weighing voltage value, the final representative weighing voltage value is converted into the initial weight value according to the scaling factor in the preset metrological scale of the networked electronic scale. The preset metrological scale is stored in the memory of the networked electronic scale and includes the scaling factor, the range correction coefficient, and the standard gravitational acceleration value. The scaling factor reflects the linear conversion relationship between the output voltage of the weighing sensor and the weight under standard gravitational acceleration conditions. The unit of the scaling factor is the weight corresponding to a unit voltage, such as millivolts per kilogram. The initial weight value is converted by multiplying the final representative weighing voltage value by the scaling factor. If the scaling factor is expressed in the form of a linear equation and includes an intercept term, the corresponding intercept value also needs to be added during conversion.

[0070] Obtain the local gravitational acceleration value of the current location of the network-connected electronic scale. The local gravitational acceleration value is obtained in two ways: the network-connected electronic scale has a built-in or external positioning module. The positioning module outputs the current geographical location information, and the microcontroller queries a pre-stored geographical distribution table of gravitational acceleration based on this information to obtain the local gravitational acceleration value; alternatively, the network-connected electronic scale obtains the local gravitational acceleration value based on the current network or satellite positioning from a cloud server via a wireless communication module. The standard gravitational acceleration value is the gravitational acceleration value calibrated in the preset measurement scale, typically taken as 9.8 or 9.80665 meters per square second.

[0071] The initial weight value is corrected based on the ratio of the local gravitational acceleration value to the standard gravitational acceleration value. The correction method involves multiplying the initial weight value by the ratio of the standard gravitational acceleration value to the local gravitational acceleration value. Because the load cell measures gravity, and the scaling factor is typically calibrated based on the standard gravitational acceleration, the same mass object will experience different gravitational forces at different locations with varying gravitational accelerations. Therefore, the corrected final weight value reflects the weight of the object under standard gravity, corresponding to its true mass. The calculation process is: the final weight value equals the initial weight value multiplied by the standard gravitational acceleration value, then divided by the local gravitational acceleration value.

[0072] The final weight value is multiplied by the range correction factor in the preset measurement scale of the network-connected electronic scale to obtain the final weighing result of the target object. The range correction factor is a dimensionless multiplier factor in the preset measurement scale. The value of the range correction factor is determined through multi-point calibration and linearity testing before the network-connected electronic scale leaves the factory, and is used to compensate for the nonlinear error of the weighing sensor within its full-scale range. The value of the range correction factor is usually stored as a constant close to 1.0, for example, between 0.990 and 1.010. The final weighing result is expressed in weight units and output by the display module of the network-connected electronic scale or through the communication interface.

[0073] Optionally, the final weighing result output includes a timestamp and an identification code for this weighing process, which is then uploaded to the server via a wireless communication module or interacted with a handheld terminal.

[0074] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for intelligent weighing data recognition based on a network-connected electronic scale, characterized in that, Includes the following steps: Acquire the initial zero-point voltage signal generated by the network-connected electronic scale during the no-load period, and collect the continuous original weighing voltage sequence of the network-connected electronic scale during the load change phase; The original weighing voltage sequence is sampled using a sliding window to extract voltage fluctuation characteristic parameters within each window; Based on the voltage fluctuation characteristic parameters and the initial zero-point voltage signal, a dynamic drift compensation factor corresponding to the current weighing process is generated. The original weighing voltage sequence is corrected point by point using the dynamic drift compensation factor to obtain a compensated stable voltage sequence. Based on the voltage transition edge characteristics in the stable voltage sequence, the effective weighing range of the target object placed on the network-connected electronic scale is identified; Extract multiple steady-state voltage sub-intervals from the stationary voltage sequence within the effective weighing interval; Calculate the average voltage value of each of the steady-state voltage sub-intervals, and determine the final representative value of the weighing voltage of the target object based on the dispersion between the average voltage values ​​of all the steady-state voltage sub-intervals; The weighing result of the target object is calculated and output based on the final weighing voltage representative value and the preset measurement scale of the network-connected electronic scale; Based on the voltage fluctuation characteristic parameters and the initial zero-point voltage signal, a dynamic drift compensation factor corresponding to the current weighing process is generated, further including: The variance values ​​of the voltage fluctuation characteristic parameters corresponding to all the voltage sub-windows are sorted, and the three voltage sub-windows with the smallest variance values ​​are selected as candidate stable windows. Calculate the window average of all voltage values ​​within each candidate stable window, and then average the average values ​​of the three voltage sub-windows again to obtain the stable window average voltage; Subtract the voltage value corresponding to the initial zero-point voltage signal from the average voltage of the stable window to obtain the zero-point drift of the current weighing process; The dynamic drift compensation factor is generated based on the rate of change of the zero-point drift over time. The dynamic drift compensation factor includes a drift direction identifier and a drift rate value. Based on the voltage transition edge characteristics in the stable voltage sequence, the effective weighing range of the target object placed on the network-connected electronic scale is identified, further including: Calculate the voltage difference between two adjacent sampling points in the stationary voltage sequence to obtain the voltage difference sequence; Find the position of the first sampling point corresponding to the first positive difference value that is greater than the preset rising edge threshold from the voltage difference sequence, and find the position of the second sampling point corresponding to the first negative difference value that is less than the preset falling edge threshold. If the position of the first sampling point is earlier than the position of the second sampling point, then the position of the first sampling point is determined as the starting boundary of the effective weighing interval, and the position of the second sampling point is determined as the ending boundary of the effective weighing interval. Extract the voltage values ​​corresponding to all sampling points between the starting boundary and the ending boundary, and use them as a stationary voltage sequence segment within the effective weighing interval; Calculating the average voltage value for each of the steady-state voltage sub-intervals, and determining the final representative weighing voltage value of the target object based on the dispersion among the average voltage values ​​of all the steady-state voltage sub-intervals, further including: Calculate the arithmetic mean of the voltage values ​​of all sampling points in each of the steady-state voltage sub-intervals, and use it as the sub-interval average voltage of each of the steady-state voltage sub-intervals; Calculate the total average value of the average voltage of all said sub-intervals, and calculate the relative deviation of the average voltage of each said sub-interval relative to the total average value; The average voltage of the sub-intervals whose relative deviation exceeds the preset deviation threshold is removed to obtain the average voltage of the remaining sub-intervals after filtering. The average voltage of the remaining sub-intervals after screening is averaged again to obtain the final representative value of the weighing voltage.

2. The intelligent weighing data recognition method based on a networked electronic scale according to claim 1, characterized in that, The acquisition of the initial zero-point voltage signal generated by the network-connected electronic scale during the no-load period further includes: After the connected electronic scale is powered on and started, the real-time zero-point voltage value output by the weighing sensor of the connected electronic scale is continuously monitored; When the maximum fluctuation amplitude of the real-time zero-point voltage value within a continuous first preset time period is less than a preset fluctuation threshold, the arithmetic mean of all real-time zero-point voltage values ​​within the continuous first preset time period is taken as the initial zero-point voltage signal, and the generation time of the initial zero-point voltage signal is recorded.

3. The intelligent weighing data recognition method based on a networked electronic scale according to claim 1, characterized in that, Collecting the continuous raw weighing voltage sequence of the network-connected electronic scale during the load change phase further includes: Real-time monitoring of the instantaneous voltage change rate output by the weighing sensor of the network-connected electronic scale; When the instantaneous voltage change rate first exceeds the preset change rate threshold, it is determined that the network-connected electronic scale has entered the load change stage. Starting from this moment, the voltage value of each sampling point output by the weighing sensor is continuously collected until the instantaneous voltage change rate is lower than the preset change rate threshold for a continuous second preset time period. The collection stops when the voltage value of all the sampling points is arranged in the order of collection time to form the original weighing voltage sequence.

4. The intelligent weighing data recognition method based on a networked electronic scale according to claim 3, characterized in that, Sliding window sampling is performed on the original weighing voltage sequence to extract voltage fluctuation characteristic parameters within each window, further including: According to the preset step size and preset window width, multiple voltage sub-windows are sequentially slid across the original weighing voltage sequence; For each voltage sub-window that is slid in, calculate the range, variance and number of peaks of all voltage values ​​in the voltage sub-window, where the number of peaks is the number of sampling points in the voltage sub-window where the voltage value is greater than the average voltage value in the voltage sub-window. The range, variance, and number of peak values ​​of the voltage sub-window are combined to form the voltage fluctuation characteristic parameters corresponding to the voltage sub-window.

5. The intelligent weighing data recognition method based on a networked electronic scale according to claim 1, characterized in that, The original weighing voltage sequence is corrected point by point using the dynamic drift compensation factor to obtain a compensated stable voltage sequence, which further includes: The corrected polarity of the voltage value at each sampling point in the original weighing voltage sequence is determined based on the drift direction identifier; Based on the drift rate value and the time interval between each sampling point and the start time of the original weighing voltage sequence, calculate the instantaneous drift compensation amount corresponding to each sampling point; The voltage value of each sampling point is superimposed with the instantaneous drift compensation amount according to the corresponding correction polarity to obtain the compensated voltage value of each sampling point; The compensated voltage values ​​of all the sampling points are rearranged according to the acquisition time sequence to form the compensated stable voltage sequence.

6. The intelligent weighing data recognition method based on a networked electronic scale according to claim 1, characterized in that, Extracting multiple steady-state voltage sub-intervals from the stationary voltage sequence within the effective weighing interval further includes: Starting from the initial sampling point in the steady voltage sequence segment within the effective weighing range, each sampling point is traversed sequentially. Whenever the absolute value of the difference between the voltage value of the current sampling point and the voltage value of the previous sampling point is less than the preset steady-state discrimination threshold, the current sampling point is marked as a candidate steady-state point; A steady-state candidate segment is formed by combining consecutive sampling points that are all marked as candidate steady-state points. When the length of the steady-state candidate segment reaches a preset minimum length threshold, the steady-state candidate segment is extracted as a steady-state voltage sub-interval; Continue traversing backwards until all sampling points in the steady-state voltage sequence segment within the effective weighing interval have been traversed, resulting in multiple steady-state voltage sub-intervals.

7. The intelligent weighing data recognition method based on a networked electronic scale according to claim 1, characterized in that, Based on the final weighing voltage representative value and the preset metrological scale of the network-connected electronic scale, the weighing result of the target object is calculated and output, further including: Based on the scaling factor in the preset metrological scale of the network-connected electronic scale, the final weighing voltage representative value is converted into the initial weight value; Obtain the local gravitational acceleration value of the current location of the network-connected electronic scale; The initial weight value is corrected based on the ratio of the local gravitational acceleration value to the standard gravitational acceleration value to obtain the final weight value; The final weight value is multiplied by the range correction coefficient in the preset measurement scale of the network-connected electronic scale to obtain the final weighing result of the target object, and the final weighing result is output.

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