A pressure gauge calibration anomaly detection method and system

Abstract

The present application relates to the technical fields of metrological detection, and discloses a pressure gauge verification abnormality detection method and system, the method comprising: the first time the pressure gauge is connected to the pressure source, and is placed and timed in the closed cavity; the first preset time period is continuously collected, and the pressure decay curve is obtained, and the existence of the internal leakage caused by the pressure abnormal decline trend is judged according to the curve slope change; if there is leakage, the verification process is immediately interrupted and the abnormal early warning signal is sent; if there is no leakage, the connection with the pressure source is restored and the pressure is reduced; when the pressure is close to zero, the transient pressure disturbance is applied to the pressure gauge, the response curve is collected, and the damping characteristics and the abnormality of the card are evaluated according to the curve overshoot and the cycle number of the oscillation decay to the steady state, and the related verification judgment is completed; the present application can improve the efficiency of the pressure gauge verification.

Description

Technical Field

[0001] This invention relates to the field of metrology and testing technology, and in particular to a method and system for detecting abnormalities in pressure gauge calibration. Background Technology

[0002] In the existing technical system for pressure gauge calibration, the detection of calibration anomalies relies heavily on manual review and data verification after the calibration process is completed. There is no real-time anomaly identification step during the calibration process, which makes it impossible to detect problems such as internal leakage and damping abnormalities in pressure gauges in a timely manner during critical stages such as pressure holding and pressure reduction. This often leads to the execution of an invalid calibration process, which significantly reduces the efficiency of the overall calibration work. At the same time, the delayed detection of anomalies also increases the manpower and time costs of subsequent re-inspections.

[0003] Current technologies rely solely on a single pressure reading deviation threshold to determine pressure gauge calibration anomalies. They lack analysis of multi-dimensional data such as pressure decay trends and swing response characteristics, making it difficult to accurately identify hidden trends of internal leakage and non-obvious anomalies such as poor damping characteristics and jamming. This results in a high rate of missed and false detections, failing to provide accurate diagnostic results for the calibration status of pressure gauges and making it difficult to meet the high requirements for accuracy and reliability in industrial settings. Therefore, improving the accuracy of pressure gauge calibration has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for detecting abnormalities in pressure gauge calibration, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for detecting abnormalities in pressure gauge calibration, comprising:

[0006] A. After the pressure gauge under test has completed its first pressurization to the upper limit of measurement and stabilized according to the verification procedure, disconnect the connection between the pressure gauge under test and the pressure source, and keep the pressure gauge under test in a static state in the closed cavity, and start timing.

[0007] B. During the first preset time period of the static state, the reading of the pressure gauge under test is continuously collected to obtain the pressure holding attenuation curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding attenuation curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

[0008] C. If the internal leakage is determined to exist, the calibration process is interrupted, and a calibration abnormality warning signal for the pressure gauge under test is obtained;

[0009] D. If it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test;

[0010] E. After applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

[0011] In a preferred embodiment, after the pressure gauge under test has completed its initial pressurization to the upper limit of measurement according to the verification procedure and stabilized, the connection between the pressure gauge under test and the pressure source is disconnected, and the pressure gauge under test is kept in a static state within the closed cavity before timing begins, including:

[0012] After the pressure gauge under test reaches the upper limit of measurement and remains stable, the pressure reading at the stable moment is recorded as the initial holding pressure value of the pressure gauge under test.

[0013] The pressure fluctuation amplitude data of the pressure gauge under test is obtained within three consecutive calibration cycles before it reaches stability, and the statistical average value of the pressure fluctuation amplitude data is used as the stability judgment benchmark of the pressure gauge under test.

[0014] While performing the cut-off operation, a high-precision timer is started to begin timing, and the completion time of the cut-off operation is used as the timing zero point. The pressure readings within the first time window after the cut-off are continuously collected to obtain the initial transient response data sequence of the pressure gauge under test.

[0015] The trend term is extracted from the initial transient response data sequence to obtain the pressure difference of the pressure gauge under test, and the pressure difference is compared with the preset cutoff disturbance tolerance range to determine the additional disturbance of the pressure gauge under test.

[0016] Based on the additional disturbance, the timing zero point is corrected to the time corresponding to the first data point after the pressure fluctuation in the initial transient response data sequence has decayed to a stable state, thus obtaining the final timing zero point of the pressure gauge under test.

[0017] The pressure reading corresponding to the final timing zero point is used as the pressure holding starting reference value, and the pressure gauge under test is traced back from the final timing zero point to obtain the initial state reference value of the pressure gauge under test.

[0018] The starting point deviation of the pressure gauge under test is obtained by performing differential analysis between the pressure holding initial reference value and the initial state reference value, and the starting point deviation is recorded in the calibration log as the pressure state characteristic value at the beginning of the static state of the pressure gauge under test.

[0019] In a preferred embodiment, during a first preset time period of continuous static state, the readings of the pressure gauge under test are continuously collected to obtain the pressure holding decay curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding decay curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage, including:

[0020] Taking the starting time of the static state as the zero point of timing, the scale value pointed to by the pointer of the pressure gauge under test is continuously read at a fixed sampling frequency within the first preset time period. The sampling time and the corresponding pressure value are recorded as the original sampling point, and the original sampling point is subjected to coarse error elimination processing to obtain the preliminary pressure decay sequence of the pressure gauge under test.

[0021] The initial pressure decay sequence is resampled using cubic spline interpolation to obtain the pressure holding decay curve of the pressure gauge under test.

[0022] The data points on the pressure holding decay curve are numerically differentiated to obtain the local decay rate of the data points. The local decay rates are then arranged to obtain the local decay rate sequence of the pressure holding decay curve.

[0023] A variance analysis based on a sliding window is performed on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identify the window position where the dispersion changes significantly, and use the window position as the morphological inflection point of the pressure holding decay curve.

[0024] Based on the morphological inflection point, the pressure holding attenuation curve is divided into a curve segment before the inflection point and a curve segment after the inflection point. The average attenuation rate of the curve segment before the inflection point is extracted as the first rate feature value, and the average attenuation rate of the curve segment after the inflection point is extracted as the second rate feature value.

[0025] The first rate characteristic value and the second rate characteristic value are compared and analyzed with a preset steady-state threshold to determine whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

[0026] In a preferred embodiment, the step of performing a sliding window-based variance analysis on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identifying the window position where the dispersion undergoes a significant abrupt change, and using the window position as the morphological inflection point of the holding pressure decay curve includes:

[0027] Set a sliding analysis window of fixed length, and move the sliding analysis window from the starting position of the local decay rate sequence step by step backward, while capturing the local decay rate subsequence within the window at the current position.

[0028] The variance of the local decay rate subsequence is used as the local fluctuation intensity index of the sliding analysis window, and the local fluctuation intensity index is arranged according to the order of the sliding analysis window to obtain the fluctuation intensity evolution sequence of the local decay rate sequence.

[0029] Abrupt point detection is performed on the fluctuation intensity evolution sequence to obtain candidate abrupt change points of the pressure holding attenuation curve;

[0030] Gradient analysis is performed on the candidate mutation points to obtain the jump amplitude coefficients of the candidate mutation points;

[0031] The window position corresponding to the candidate abrupt change point with the largest abrupt change amplitude coefficient is determined as the final abrupt change position of the local decay rate sequence, and the time corresponding to the final abrupt change position is taken as the morphological inflection point of the pressure holding decay curve.

[0032] In a preferred embodiment, the step of interrupting the calibration process and obtaining a calibration abnormality warning signal for the pressure gauge under test if the internal leakage is determined to exist includes:

[0033] Upon determining the existence of the internal leakage, immediately terminate the currently executing verification command, lock the pressure indication data collected before the current moment, mark the pressure indication data as abnormal verification batch data, and simultaneously extract the complete data of the pressure holding attenuation curve to obtain the original evidence of the abnormality of the pressure gauge under test.

[0034] A deep analysis based on local extreme points is performed on the pressure holding attenuation curve to identify the local drop peak points of the pressure holding attenuation curve during the static time period, so as to obtain the leakage pulse characteristic sequence of the pressure gauge under test.

[0035] The leakage pulse feature sequence is compared item by item with the typical leakage mode feature library of the pressure gauge under test. Based on the comparison results, the membership mode type of the pressure gauge under test is determined, and the leakage mode code of the pressure gauge under test is obtained.

[0036] The degree of abnormality of the pressure gauge under test is determined based on the leakage mode code.

[0037] By correlating and integrating the abnormal calibration batch data of the pressure gauge under test, the pressure holding attenuation curve, the leakage mode code, and the degree of abnormality, an abnormal calibration warning signal for the pressure gauge under test is obtained.

[0038] In a preferred embodiment, if it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test, including:

[0039] After reconnecting the pressure gauge under test to the pressure source, the real-time pressure readings during the pressure reduction process are continuously collected at a fixed sampling frequency to obtain the pressure reduction sequence of the pressure gauge under test. At the same time, the timestamps of the collection are recorded to form a time axis corresponding to the pressure reduction sequence.

[0040] Real-time trend analysis is performed on the pressure drop sequence to obtain the average rate of decrease of the pressure drop sequence;

[0041] Under the condition that the average rate of decrease is within the preset stable pressure drop rate range, the absolute value of the difference between the current pressure reading and the preset zero reference value is analyzed, and the absolute value of the difference is used as the current distance from zero. At the same time, the relationship between the current distance from zero and time is recorded to obtain the distance decay curve of the pressure gauge under test.

[0042] Extrapolate the distance decay curve to obtain the distance decay trend line of the pressure gauge under test, and estimate the remaining time required for the distance value from zero to decay to a preset threshold based on the distance decay trend line. Use the remaining time as a countdown for applying disturbance to the pressure gauge under test.

[0043] When the countdown for the disturbance application decreases to zero, a disturbance trigger signal is immediately generated for the pressure gauge under test, and the trigger time is accurately recorded as the start time of the disturbance application. At the same time, the pressure reading collected at the trigger time is recorded as the steady-state value before the disturbance.

[0044] After generating the disturbance trigger signal, pressure readings are continuously collected within a short time window after the disturbance is applied, generating a transient response data sequence containing the pressure response rise and fall segments. The transient response data sequence is then associated with and stored with the steady-state value before the disturbance and the start time of the disturbance application, serving as the raw input data for evaluating the damping characteristics and jamming anomalies of the pressure gauge under test.

[0045] In a preferred embodiment, after applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles for the oscillation to decay to a steady state, including:

[0046] At the instant the micro-pressure pulse excitation is applied, the pressure reading of the pressure gauge under test is continuously acquired at a high sampling frequency to obtain the original swing response data sequence of the pressure gauge under test. The data segment before the first pressure peak appears in the original swing response data sequence is marked as the rising edge segment, and the data segment after the first pressure peak to the end of the data sequence is marked as the damped oscillation segment.

[0047] Local extreme points are detected in the damped oscillation segment to obtain the local maximum and local minimum points of the damped oscillation segment. The pressure values ​​of the local maximum points are extracted in chronological order as positive peak values, and the pressure values ​​of the local minimum points are extracted as negative valley values.

[0048] Record the times corresponding to the local maxima and local minima to obtain the peak time sequence and valley time sequence of the decaying oscillation segment;

[0049] Based on the time interval between adjacent positive peaks in the peak time sequence, the duration of the oscillation period is recorded, and the duration of the oscillation period is statistically averaged to obtain the average oscillation period value of the peak time sequence.

[0050] The final stable pressure value of the damped oscillation segment is determined based on the pressure readings of the continuous sampling points at the end of the damped oscillation segment.

[0051] The first positive peak is extracted from the positive peak as the initial overshoot peak, and the absolute value of the difference between the initial overshoot peak and the final stable pressure value is used as the overshoot characteristic value.

[0052] The first three positive peaks are extracted sequentially from the positive peaks and denoted as the first peak, the second peak, and the third peak, respectively. The ratio of the second peak to the first peak is taken as the first attenuation ratio, the ratio of the third peak to the second peak is taken as the second attenuation ratio, and the arithmetic mean of the first attenuation ratio and the second attenuation ratio is taken as the average attenuation ratio.

[0053] The damping-hysteresis comprehensive index of the pressure gauge under test is calculated based on the overshoot characteristic value, the average oscillation period value, and the average attenuation ratio.

[0054] Based on the damping-locking composite index and the average attenuation ratio, the damping characteristics and lockout anomalies of the pressure gauge under test are evaluated, and a comprehensive diagnostic conclusion for the pressure gauge under test is obtained.

[0055] In a preferred embodiment, the formula for calculating the damping-hysteresis composite index is:

[0056] ;

[0057] in, This represents the damping-hysteresis composite index. This represents the characteristic value of the overshoot. This represents the average oscillation period value. This represents the average attenuation ratio. This represents the preset overall magnitude adjustment coefficient. This represents the preset adjustment coefficient for the degree of nonlinear influence. This represents the natural logarithm function.

[0058] To address the aforementioned problems, the present invention also provides a pressure gauge calibration anomaly detection system, the system comprising:

[0059] The static state maintenance module is used to disconnect the connection between the pressure gauge under test and the pressure source after the pressure gauge under test has been pressurized to the upper limit of measurement and stabilized according to the verification procedure, and to maintain the pressure gauge under test in a static state in the closed cavity and start timing.

[0060] The anomaly detection module is used to continuously collect the reading of the pressure gauge under test during the first preset time period of the static state, obtain the pressure holding attenuation curve of the pressure gauge under test, and determine whether there is an abnormal pressure drop trend caused by internal leakage in the pressure gauge under test based on the slope change characteristics of the pressure holding attenuation curve.

[0061] The warning signal generation module is used to interrupt the verification process and obtain a verification abnormality warning signal for the pressure gauge under test if the internal leakage is determined to exist.

[0062] The pressure disturbance application module is used to restore the connection between the pressure gauge under test and the pressure source and perform a pressure reduction operation if it is determined that there is no internal leakage; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test.

[0063] The abnormal state assessment module is used to acquire the swing response curve of the pressure gauge under test after the micro-pressure pulse excitation is applied, and to assess the damping characteristics and jamming abnormality of the pressure gauge under test based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] 1. This invention performs a detailed analysis of the pressure decay curve of the pressure gauge under test during the pressure holding stage, and judges internal leakage problems by combining multi-dimensional indicators such as slope change characteristics, local decay rate and morphological inflection point. At the same time, transient pressure disturbance is applied during the pressure reduction stage, and damping characteristics and jamming anomalies are evaluated based on parameters such as overshoot and oscillation period of the swing response curve. This invention achieves accurate and comprehensive detection of pressure gauge calibration anomalies, greatly improves the accuracy of anomaly detection, and can effectively identify subtle leaks and hidden jamming problems that are easily overlooked in traditional detection methods, making the calibration results more consistent with the actual working state of the pressure gauge.

[0066] 2. This invention deeply integrates the verification process with intelligent data analysis, automatically completing data acquisition, processing, analysis, and anomaly detection during the testing process. If an internal leak is detected, the verification process will be directly interrupted and an early warning signal will be generated. This eliminates the need for cumbersome manual intervention in data analysis and judgment, significantly improving the overall efficiency of pressure gauge anomaly detection. Furthermore, by standardizing testing indicators and judgment logic, the criteria for anomaly detection are unified, reducing human error during the testing process and making pressure gauge verification work more standardized and efficient, further improving the overall quality of the verification work. Attached Figure Description

[0067] Figure 1 This is a flowchart illustrating a pressure gauge calibration anomaly detection method according to an embodiment of the present invention.

[0068] Figure 2 This is a functional block diagram of a pressure gauge calibration anomaly detection system provided in an embodiment of the present invention;

[0069] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0070] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0071] This application provides a method for detecting anomalies in pressure gauge calibration. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for detecting anomalies in pressure gauge calibration can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0072] Reference Figure 1 The diagram shown is a flowchart illustrating a pressure gauge calibration anomaly detection method according to an embodiment of the present invention. In this embodiment, the pressure gauge calibration anomaly detection method includes:

[0073] A. After the pressure gauge under test has completed its first pressurization to the upper limit of measurement and stabilized according to the verification procedure, disconnect the connection between the pressure gauge under test and the pressure source, and keep the pressure gauge under test in a static state in the closed cavity, and start timing.

[0074] In this embodiment of the invention, after the pressure gauge under test completes its initial pressurization to the upper limit of measurement according to the verification procedure and stabilizes, the connection between the pressure gauge under test and the pressure source is disconnected, and the pressure gauge under test is kept in a static state within the closed cavity before timing begins, including:

[0075] After the pressure gauge under test reaches the upper limit of measurement and remains stable, the pressure reading at the stable moment is recorded as the initial holding pressure value of the pressure gauge under test.

[0076] The pressure fluctuation amplitude data of the pressure gauge under test is obtained within three consecutive calibration cycles before it reaches stability, and the statistical average value of the pressure fluctuation amplitude data is used as the stability judgment benchmark of the pressure gauge under test.

[0077] While performing the cut-off operation, a high-precision timer is started to begin timing, and the completion time of the cut-off operation is used as the timing zero point. The pressure readings within the first time window after the cut-off are continuously collected to obtain the initial transient response data sequence of the pressure gauge under test.

[0078] The trend term is extracted from the initial transient response data sequence to obtain the pressure difference of the pressure gauge under test, and the pressure difference is compared with the preset cutoff disturbance tolerance range to determine the additional disturbance of the pressure gauge under test.

[0079] Based on the additional disturbance, the timing zero point is corrected to the time corresponding to the first data point after the pressure fluctuation in the initial transient response data sequence has decayed to a stable state, thus obtaining the final timing zero point of the pressure gauge under test.

[0080] The pressure reading corresponding to the final timing zero point is used as the pressure holding starting reference value, and the pressure gauge under test is traced back from the final timing zero point to obtain the initial state reference value of the pressure gauge under test.

[0081] The starting point deviation of the pressure gauge under test is obtained by performing differential analysis between the pressure holding initial reference value and the initial state reference value, and the starting point deviation is recorded in the calibration log as the pressure state characteristic value at the beginning of the static state of the pressure gauge under test.

[0082] Once the pressure gauge reading reaches the upper limit of measurement and remains constant, the pressure reading corresponding to this stable moment is directly recorded, and this pressure reading is determined as the initial holding pressure value of the pressure gauge.

[0083] Retrieve the difference between the maximum and minimum values ​​of the pressure reading deviation from the average value in each of the three consecutive calibration cycles before the pressure gauge reaches the above-mentioned stable state. Sum these three sets of pressure fluctuation amplitude data and divide by three. The result is used as the stability judgment benchmark for the pressure gauge under test.

[0084] At the same time as the connection between the pressure gauge under test and the pressure source is disconnected, a high-precision timer is started to start timing. The moment the disconnection operation is completed is set as the timing zero point. Immediately after the disconnection operation is completed, the first time window of fixed duration is selected. Within this time window, the pressure reading of the pressure gauge under test is continuously and uninterruptedly collected. All the collected pressure readings are arranged in chronological order to form the initial transient response data sequence of the pressure gauge under test.

[0085] The continuous trend of change presented in the initial transient response data sequence is extracted, and the overall trend of pressure value change with time in the data sequence is sorted out. The difference between the pressure value at different time points in the data sequence and the pressure value corresponding to the initial timing zero point is calculated. These differences are integrated to obtain the pressure difference value of the pressure gauge under test. The pressure difference value is compared with the pre-set cut-off disturbance tolerance range one by one. Based on the comparison results, the additional disturbance generated by the pressure gauge under test during the cut-off operation is identified.

[0086] Based on the identified additional disturbance, the first data point in the initial transient response data sequence where the pressure reading no longer fluctuates with time and remains stable is found. The time corresponding to this data point is used to replace the original timing zero point, and the replaced time is determined as the final timing zero point of the pressure gauge under test.

[0087] Find the pressure reading of the pressure gauge under test corresponding to the final zero point of timing, set this pressure reading as the pressure holding start reference value of the pressure gauge under test, take the final zero point of timing as the time node, trace back the pressure reading data of the pressure gauge under test before this node, select the value that can reflect the initial state of the pressure gauge from the traced pressure reading data, and determine this value as the initial state reference value of the pressure gauge under test.

[0088] The difference between the initial pressure holding reference value and the initial state reference value is calculated by subtracting the two values. This difference is the starting point deviation of the pressure gauge under test. This starting point deviation is used as a characteristic value that represents the pressure state of the pressure gauge at the beginning of the static state and is fully recorded in the calibration log of the pressure gauge under test.

[0089] The beneficial effects of this implementation process are as follows: First, by accurately recording the initial holding pressure value, and combining it with pressure fluctuation data from three consecutive calibration cycles, a stability judgment benchmark is calculated, establishing an accurate initial reference system that closely matches the actual state of the pressure gauge for subsequent pressure testing under static conditions. After the cut-off operation, the initial transient response data sequence is promptly collected. The pressure difference is extracted through trend term analysis and compared to identify additional disturbances, which are then used to correct the final timing zero point. This effectively eliminates the interference of disturbances caused by the cut-off operation on subsequent holding pressure testing, ensuring that the timing benchmark perfectly matches the actual stable static state of the pressure gauge. Then, by backtracking to obtain the initial state reference value, differential analysis is performed with the initial holding pressure benchmark value to obtain the starting point deviation, which is recorded in the calibration log. This accurately captures the pressure characteristics at the beginning of the static state and achieves full traceability of pressure data during this stage. This provides an accurate and reliable time and pressure benchmark for subsequent internal leakage judgment based on the holding pressure decay curve, ensuring the accuracy of subsequent anomaly judgment results from the initial stage of detection. Furthermore, the standardized operation and data processing procedures make the testing work during the static stage more standardized.

[0090] B. During the first preset time period of the static state, the reading of the pressure gauge under test is continuously collected to obtain the pressure holding attenuation curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding attenuation curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

[0091] In this embodiment of the invention, during the first preset time period of the static state, the readings of the pressure gauge under test are continuously collected to obtain the pressure holding decay curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding decay curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage, including:

[0092] Taking the starting time of the static state as the zero point of timing, the scale value pointed to by the pointer of the pressure gauge under test is continuously read at a fixed sampling frequency within the first preset time period. The sampling time and the corresponding pressure value are recorded as the original sampling point, and the original sampling point is subjected to coarse error elimination processing to obtain the preliminary pressure decay sequence of the pressure gauge under test.

[0093] The initial pressure decay sequence is resampled using cubic spline interpolation to obtain the pressure holding decay curve of the pressure gauge under test.

[0094] The data points on the pressure holding decay curve are numerically differentiated to obtain the local decay rate of the data points. The local decay rates are then arranged to obtain the local decay rate sequence of the pressure holding decay curve.

[0095] A variance analysis based on a sliding window is performed on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identify the window position where the dispersion changes significantly, and use the window position as the morphological inflection point of the pressure holding decay curve.

[0096] Based on the morphological inflection point, the pressure holding attenuation curve is divided into a curve segment before the inflection point and a curve segment after the inflection point. The average attenuation rate of the curve segment before the inflection point is extracted as the first rate feature value, and the average attenuation rate of the curve segment after the inflection point is extracted as the second rate feature value.

[0097] The first rate characteristic value and the second rate characteristic value are compared and analyzed with a preset steady-state threshold to determine whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

[0098] The step of performing a sliding window-based variance analysis on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identifying the window position where the dispersion undergoes a significant abrupt change, and using the window position as the morphological inflection point of the holding pressure decay curve, includes:

[0099] Set a sliding analysis window of fixed length, and move the sliding analysis window from the starting position of the local decay rate sequence step by step backward, while capturing the local decay rate subsequence within the window at the current position.

[0100] The variance of the local decay rate subsequence is used as the local fluctuation intensity index of the sliding analysis window, and the local fluctuation intensity index is arranged according to the order of the sliding analysis window to obtain the fluctuation intensity evolution sequence of the local decay rate sequence.

[0101] Abrupt point detection is performed on the fluctuation intensity evolution sequence to obtain candidate abrupt change points of the pressure holding attenuation curve;

[0102] Gradient analysis is performed on the candidate mutation points to obtain the jump amplitude coefficients of the candidate mutation points;

[0103] The window position corresponding to the candidate abrupt change point with the largest abrupt change amplitude coefficient is determined as the final abrupt change position of the local decay rate sequence, and the time corresponding to the final abrupt change position is taken as the morphological inflection point of the pressure holding decay curve.

[0104] Using the initial moment of the static state as the zero point of timing, the scale value indicated by the pointer of the pressure gauge under test is continuously read at a fixed sampling frequency within the first preset time period. The specific time of each sampling and the corresponding pressure value at that time are recorded as the original sampling points. The original sampling points are subjected to coarse error elimination processing. After eliminating the sampling points that are obviously deviated from the normal data range, the remaining sampling points are arranged in chronological order to obtain the preliminary pressure decay sequence of the pressure gauge under test.

[0105] The initial pressure decay sequence is resampled using cubic spline interpolation. Based on the distribution pattern of existing data points in the initial pressure decay sequence, interpolation points that conform to the variation law of cubic spline function are inserted between adjacent data points to supplement and form a continuous and smooth dataset. The pressure decay curve of the pressure gauge under test is plotted based on this dataset.

[0106] Numerical differentiation is performed on each data point on the pressure holding decay curve. The local decay rate corresponding to each data point is obtained by calculating the rate of change at each data point. The local decay rates of all data points are arranged in order on the curve to obtain the local decay rate sequence of the pressure holding decay curve.

[0107] Set a sliding analysis window of fixed length. Start the sliding analysis window from the beginning of the local decay rate sequence and move it forward step by step. At each step, extract the local decay rate subsequence within the current window range, ensuring that the length of each subsequence is consistent with the length of the sliding analysis window.

[0108] The variance of each captured local decay rate subsequence is used as the local fluctuation intensity index of the corresponding sliding analysis window. The local fluctuation intensity indices of all sliding analysis windows are arranged in the order of window movement to form the fluctuation intensity evolution sequence of the local decay rate sequence.

[0109] Abrupt change point detection is performed on the fluctuation intensity evolution sequence to identify points in the sequence where the values ​​suddenly change. These points are then identified as candidate abrupt change points for the pressure holding decay curve, and all detected candidate abrupt change points and their corresponding location information are fully preserved.

[0110] Gradient analysis is performed on each candidate mutation point to calculate the gradient of the change in value at each candidate mutation point. The jump amplitude coefficient corresponding to each candidate mutation point is determined based on the gradient magnitude, so as to accurately quantify the jump degree of each candidate mutation point.

[0111] The sliding analysis window position corresponding to the candidate mutation point with the largest jump amplitude coefficient is determined as the final jump position of the local decay rate sequence. The time information corresponding to the final jump position is queried, and this time is used as the morphological inflection point of the pressure holding decay curve.

[0112] Based on the determined morphological inflection point, the pressure holding attenuation curve is divided into a curve segment before the inflection point and a curve segment after the inflection point. The average value of the local attenuation rate of all data points in the curve segment before the inflection point is calculated and extracted as the first rate characteristic value. The average value of the local attenuation rate of all data points in the curve segment after the inflection point is calculated and extracted as the second rate characteristic value.

[0113] The extracted first and second rate feature values ​​are compared with preset steady-state thresholds one by one. Based on the comparison results of the two rate feature values ​​and the steady-state thresholds, it is comprehensively judged whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

[0114] The beneficial effects of this implementation process are that by collecting data at a fixed sampling frequency and eliminating gross errors, the accuracy and validity of the original pressure data are ensured. A smooth pressure decay curve is obtained through cubic spline interpolation and resampling, making the pressure decay trend more continuous and analyzable. A local decay rate sequence is obtained through numerical differentiation, and variance analysis is performed using a fixed-length sliding window to accurately capture changes in the sequence's dispersion. Then, abrupt change point detection and gradient analysis determine the morphological inflection points, achieving precise location of nodes in the pressure decay trend. Based on the morphological inflection points, curve segments are divided and rate feature values ​​are extracted. These are compared with steady-state thresholds to determine the leakage trend. The entire process replaces subjective judgment with quantitative data analysis, and the progressive processing method makes the determination of internal leakage more scientific and accurate, effectively identifying abnormal pressure decline trends and improving the reliability of anomaly detection during the pressure gauge's holding phase.

[0115] C. If the internal leakage is determined to exist, the calibration process is interrupted, and a calibration abnormality warning signal for the pressure gauge under test is obtained;

[0116] In this embodiment of the invention, the step of interrupting the calibration process and obtaining a calibration abnormality warning signal for the pressure gauge under test if the internal leakage is determined to exist includes:

[0117] Upon determining the existence of the internal leakage, immediately terminate the currently executing verification command, lock the pressure indication data collected before the current moment, mark the pressure indication data as abnormal verification batch data, and simultaneously extract the complete data of the pressure holding attenuation curve to obtain the original evidence of the abnormality of the pressure gauge under test.

[0118] A deep analysis based on local extreme points is performed on the pressure holding attenuation curve to identify the local drop peak points of the pressure holding attenuation curve during the static time period, so as to obtain the leakage pulse characteristic sequence of the pressure gauge under test.

[0119] The leakage pulse feature sequence is compared item by item with the typical leakage mode feature library of the pressure gauge under test. Based on the comparison results, the membership mode type of the pressure gauge under test is determined, and the leakage mode code of the pressure gauge under test is obtained.

[0120] The degree of abnormality of the pressure gauge under test is determined based on the leakage mode code.

[0121] By correlating and integrating the abnormal calibration batch data of the pressure gauge under test, the pressure holding attenuation curve, the leakage mode code, and the degree of abnormality, an abnormal calibration warning signal for the pressure gauge under test is obtained.

[0122] When it is determined that the pressure gauge under test has an internal leak, all currently executing verification commands are immediately terminated, and all pressure readings collected before that moment are locked to prevent data from being tampered with or overwritten. This portion of pressure readings is uniformly marked as abnormal verification batch data. At the same time, all data information corresponding to the pressure holding decay curve is completely extracted, and this portion of data is determined as the original basis for the abnormality of the pressure gauge under test.

[0123] A deep analysis based on local extreme points is conducted on the pressure decay curve during the holding pressure period. The numerical changes of the curve are checked point by point during the resting period. The local drop peak points where the pressure value drops sharply are accurately identified. All local drop peak points are sorted in chronological order, and the pressure change and time characteristics corresponding to each peak point are extracted to form the leakage pulse characteristic sequence of the pressure gauge under test.

[0124] The obtained leakage pulse feature sequence is compared item by item with the preset feature library of typical leakage modes of the pressure gauge under test. The feature sequence is matched with the feature parameters of each typical mode in the feature library one by one. Based on the matching result of the feature parameters, the membership mode type of the pressure gauge under test is determined. At the same time, the leakage mode code corresponding to the pressure gauge under test is generated and obtained according to the coding rules of the feature library.

[0125] Based on the leakage mode code of the pressure gauge under test, and by comparing it with the preset correspondence between the code and the degree of abnormality, the leakage level represented by the code is accurately matched from the correspondence, thereby determining the degree of abnormality of the pressure gauge under test and clarifying the severity of the internal leakage.

[0126] The abnormal calibration batch data, complete data of the pressure holding attenuation curve, leakage mode code, and the determined degree of abnormality of the pressure gauge under test are comprehensively correlated and integrated. The data information of each part is combined and arranged according to the preset format to form an abnormality warning signal of the pressure gauge under test containing complete abnormality detection information.

[0127] The beneficial effects of this implementation process are that it immediately interrupts the verification process and locks relevant data upon determining an internal leak, effectively preventing the continuation of invalid verification operations and improving the overall efficiency of the verification work. Simultaneously, the locked abnormal verification batch data and extracted original evidence of the anomalies provide a complete and authentic data source for subsequent anomaly analysis. By deeply analyzing the pressure attenuation curve during pressure holding, leakage pulse characteristic sequences are obtained. Combined with a typical leakage mode feature library, pattern matching is completed and codes are generated, making the determination of internal leak types more standardized and accurate. Determining the severity of the anomaly based on the codes also provides a clear quantitative standard for judging the severity of the leak. Finally, various anomaly-related data are correlated and integrated to form a verification anomaly early warning signal. This ensures that the early warning signal contains complete and comprehensive information, providing accurate and detailed reference data for subsequent pressure gauge maintenance and re-inspection work, thus improving the practicality and guidance of the anomaly early warning.

[0128] D. If it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test;

[0129] In this embodiment of the invention, if it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test, including:

[0130] After reconnecting the pressure gauge under test to the pressure source, the real-time pressure readings during the pressure reduction process are continuously collected at a fixed sampling frequency to obtain the pressure reduction sequence of the pressure gauge under test. At the same time, the timestamps of the collection are recorded to form a time axis corresponding to the pressure reduction sequence.

[0131] Real-time trend analysis is performed on the pressure drop sequence to obtain the average rate of decrease of the pressure drop sequence;

[0132] Under the condition that the average rate of decrease is within the preset stable pressure drop rate range, the absolute value of the difference between the current pressure reading and the preset zero reference value is analyzed, and the absolute value of the difference is used as the current distance from zero. At the same time, the relationship between the current distance from zero and time is recorded to obtain the distance decay curve of the pressure gauge under test.

[0133] Extrapolate the distance decay curve to obtain the distance decay trend line of the pressure gauge under test, and estimate the remaining time required for the distance value from zero to decay to a preset threshold based on the distance decay trend line. Use the remaining time as a countdown for applying disturbance to the pressure gauge under test.

[0134] When the countdown for the disturbance application decreases to zero, a disturbance trigger signal is immediately generated for the pressure gauge under test, and the trigger time is accurately recorded as the start time of the disturbance application. At the same time, the pressure reading collected at the trigger time is recorded as the steady-state value before the disturbance.

[0135] After generating the disturbance trigger signal, pressure readings are continuously collected within a short time window after the disturbance is applied, generating a transient response data sequence containing the pressure response rise and fall segments. The transient response data sequence is then associated with and stored with the steady-state value before the disturbance and the start time of the disturbance application, serving as the raw input data for evaluating the damping characteristics and jamming anomalies of the pressure gauge under test.

[0136] After restoring the connection between the pressure gauge under test and the pressure source, the real-time pressure readings at each sampling moment during the pressure reduction process are continuously collected at a fixed sampling frequency. All real-time pressure readings are arranged in chronological order of collection time to obtain the pressure reduction sequence of the pressure gauge under test. At the same time, a corresponding collection timestamp is matched for each collected pressure reading. All timestamps are arranged in the same order to form a time axis that corresponds one-to-one with the pressure reduction sequence.

[0137] Real-time trend analysis is performed on the pressure reduction sequence. The ratio of the difference between adjacent pressure values ​​in the pressure reduction sequence to the corresponding time interval is calculated. All calculated ratios are summed and divided by the number of data sets to obtain the average rate of decrease of the pressure reduction sequence, which fully reflects the overall pressure reduction speed during the pressure reduction process.

[0138] Once it is confirmed that the average rate of pressure drop is within the preset range of stable pressure drop rate, the absolute value of the difference between the currently collected pressure reading and the preset zero-point reference value is calculated. This absolute value is defined as the current distance from zero. At the same time, the current distance from zero is continuously recorded at each moment. Based on the recorded values ​​and the corresponding moments, a curve is plotted to obtain the distance decay curve of the pressure gauge under test.

[0139] Extrapolate and predict the distance decay curve. Based on the existing numerical trend and direction of the curve, extend and draw the subsequent curve trend to obtain the distance decay trend line of the pressure gauge under test. Find the corresponding time when the distance value from zero reaches the preset threshold according to the trend line, calculate the time difference between the time and the current time, and set the time difference as the countdown for the disturbance of the pressure gauge under test.

[0140] When the countdown to the disturbance application reaches zero, a disturbance trigger signal is immediately generated for the pressure gauge under test. The moment of signal generation is accurately recorded as the start time of the disturbance application. At the same time, the pressure reading of the pressure gauge under test collected at the trigger moment is extracted and formally recorded as the steady-state value before the disturbance.

[0141] After generating the disturbance trigger signal, a short time window of fixed duration is selected after the disturbance is applied. Within this window, the pressure readings of the pressure gauge under test are continuously collected. The collected pressure readings are organized in chronological order to form a transient response data sequence containing the pressure response rise and fall segments. This transient response data sequence is associated and bound with the previously recorded steady-state value before the disturbance and the start time of the disturbance application, and then stored. This set of associated and stored data is used as the original input data for subsequent evaluation of the damping characteristics and jamming anomalies of the pressure gauge under test.

[0142] The beneficial effects of this implementation process are that after reconnection, pressure reduction data is collected at a fixed sampling frequency and matched with a time axis, forming a complete and orderly record of pressure change data during the pressure reduction process, providing a standardized data source for subsequent analysis. Real-time trend analysis yields the average rate of pressure drop, which serves as the criterion for determining pressure reduction stability, ensuring that subsequent disturbances are applied only when the pressure reduction process is stable, thus avoiding interference from pressure fluctuations in disturbance detection results. By calculating the distance from zero and plotting the distance decay curve, combined with extrapolation prediction to obtain a disturbance application countdown, the timing of transient pressure disturbance application can be precisely controlled, ensuring that the disturbance is applied at the optimal point when the pressure drops close to zero. After the disturbance is triggered, transient response data sequences are collected promptly and associated with relevant parameters for storage, preserving complete and accurate raw data for subsequent assessment of damping characteristics and jamming anomalies. The entire process is interconnected, achieving precision and standardization in pressure disturbance application, and ensuring the effectiveness and accuracy of subsequent anomaly assessment.

[0143] E. After applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

[0144] In this embodiment of the invention, after applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles for the oscillation to decay to a steady state. This includes:

[0145] At the instant the micro-pressure pulse excitation is applied, the pressure reading of the pressure gauge under test is continuously acquired at a high sampling frequency to obtain the original swing response data sequence of the pressure gauge under test. The data segment before the first pressure peak appears in the original swing response data sequence is marked as the rising edge segment, and the data segment after the first pressure peak to the end of the data sequence is marked as the damped oscillation segment.

[0146] Local extreme points are detected in the damped oscillation segment to obtain the local maximum and local minimum points of the damped oscillation segment. The pressure values ​​of the local maximum points are extracted in chronological order as positive peak values, and the pressure values ​​of the local minimum points are extracted as negative valley values.

[0147] Record the times corresponding to the local maxima and local minima to obtain the peak time sequence and valley time sequence of the decaying oscillation segment;

[0148] Based on the time interval between adjacent positive peaks in the peak time sequence, the duration of the oscillation period is recorded, and the duration of the oscillation period is statistically averaged to obtain the average oscillation period value of the peak time sequence.

[0149] The final stable pressure value of the damped oscillation segment is determined based on the pressure readings of the continuous sampling points at the end of the damped oscillation segment.

[0150] The first positive peak is extracted from the positive peak as the initial overshoot peak, and the absolute value of the difference between the initial overshoot peak and the final stable pressure value is used as the overshoot characteristic value.

[0151] The first three positive peaks are extracted sequentially from the positive peaks and denoted as the first peak, the second peak, and the third peak, respectively. The ratio of the second peak to the first peak is taken as the first attenuation ratio, the ratio of the third peak to the second peak is taken as the second attenuation ratio, and the arithmetic mean of the first attenuation ratio and the second attenuation ratio is taken as the average attenuation ratio.

[0152] The damping-hysteresis comprehensive index of the pressure gauge under test is calculated based on the overshoot characteristic value, the average oscillation period value, and the average attenuation ratio.

[0153] Based on the damping-locking composite index and the average attenuation ratio, the damping characteristics and lockout anomalies of the pressure gauge under test are evaluated, and a comprehensive diagnostic conclusion for the pressure gauge under test is obtained.

[0154] The formula for calculating the damping-hysteresis composite index is as follows:

[0155] ;

[0156] in, This represents the damping-hysteresis composite index. This represents the characteristic value of the overshoot. This represents the average oscillation period value. This represents the average attenuation ratio. This represents the preset overall magnitude adjustment coefficient. This represents the preset adjustment coefficient for the degree of nonlinear influence. This represents the natural logarithm function.

[0157] At the instant the micro-pressure pulse excitation is applied, the pressure reading of the pressure gauge under test is continuously collected at a high sampling frequency. All the collected pressure readings are sorted in chronological order to obtain the original swing response data sequence of the pressure gauge under test. The position corresponding to the first pressure peak is found in the data sequence. All data segments before this position are marked as rising edge segments, and all data segments after the first pressure peak until the end of the data sequence are marked as damped oscillation segments.

[0158] Local extreme points are detected in the decaying oscillation segment. The changes in pressure values ​​within the data segment are analyzed point by point. Local maximum points where the value changes from rising to falling and local minimum points where the value changes from falling to rising are accurately identified. The pressure value corresponding to each local maximum point is extracted in chronological order and defined as a positive peak value. The pressure value corresponding to each local minimum point is extracted in chronological order and defined as a negative valley value.

[0159] Accurately record the acquisition time corresponding to each local maximum and local minimum point, arrange the times of all local maximum points in order to obtain the peak time sequence of the decaying oscillation segment, and arrange the times of all local minimum points in order to obtain the valley time sequence of the decaying oscillation segment.

[0160] Extract the time corresponding to two adjacent positive peaks from the peak time sequence, calculate the time interval between the two times and take this interval as the duration of a single oscillation period, calculate the sum of the durations of all single oscillation periods, and then divide the sum by the total number of oscillation periods to obtain the average oscillation period value of the peak time sequence.

[0161] Select continuous sampling points at the end of the damped oscillation segment, calculate the average pressure reading corresponding to these sampling points, and determine the average value as the final stable pressure value of the damped oscillation segment, thereby characterizing the steady-state pressure state after the pressure gauge oscillates and decays.

[0162] Extract the first positive peak that appears from all positive peaks and define it as the initial overshoot peak. Calculate the absolute value of the difference between the initial overshoot peak and the final stable pressure value, and use this absolute value as the overshoot characteristic value to quantify the degree of overshoot of the pressure gauge after disturbance.

[0163] Extract the first three positive peaks in chronological order of their appearance from all positive peaks. Label the first peak as the first peak, the second peak as the second peak, and the third peak as the third peak. Calculate the ratio of the second peak to the first peak and use this ratio as the first attenuation ratio. Calculate the ratio of the third peak to the second peak and use this ratio as the second attenuation ratio. Sum the first attenuation ratio and the second attenuation ratio and divide by two to obtain the arithmetic mean of the two ratios, which is defined as the average attenuation ratio.

[0164] Substituting the overshoot characteristic value, average oscillation period value, and average attenuation ratio into the preset calculation logic, the damping-hysteresis comprehensive index of the pressure gauge under test is obtained after numerical calculation, thereby comprehensively quantifying the damping and hysteresis related states of the pressure gauge.

[0165] The overshoot characteristic value is derived from the raw swing response data sequence acquired after applying a micro-pressure pulse excitation to the pressure gauge under test. This data sequence is first divided into a rising edge segment and a damped oscillation segment. Local extreme points are detected in the damped oscillation segment to obtain local maxima and local minima. The pressure value at the local maxima is extracted as the positive peak value. The absolute value of the difference between the first positive peak value and the final stable pressure value of the damped oscillation segment is determined as the overshoot characteristic value. The average oscillation period value is derived from the peak time sequence formed by recording the times corresponding to the local maxima in the damped oscillation segment. The time interval between adjacent positive peaks in this sequence is calculated and statistically averaged; the result is the average. The oscillation period value; the average attenuation ratio is derived from the first three positive peaks extracted from the positive peaks, which are denoted as the first peak, the second peak, and the third peak, respectively. The ratio of the second peak to the first peak is calculated to obtain the first attenuation ratio, and the ratio of the third peak to the second peak is calculated to obtain the second attenuation ratio. The arithmetic mean of the first attenuation ratio and the second attenuation ratio is the average attenuation ratio. The overall magnitude adjustment coefficient is a pre-set coefficient used to adjust the overall magnitude of the damping-hysteresis composite index. The nonlinear influence degree adjustment coefficient is a pre-set coefficient used to adjust the degree of nonlinear influence of the ratio of the overshoot characteristic value to the average oscillation period value on the damping-hysteresis composite index.

[0166] This calculation method integrates three core characteristic indicators—overshoot, average oscillation period, and average attenuation ratio—during the swing response of the pressure gauge under test, along with two pre-set adjustment coefficients, to achieve a quantitative assessment of the damping characteristics and jamming anomalies of the pressure gauge under test. The quantitative results directly reflect the comprehensive abnormality of damping and jamming in the pressure gauge under test, providing a precise quantitative basis for subsequent assessment of the damping characteristics and jamming anomalies of the pressure gauge under test.

[0167] When the value of the overshoot characteristic increases, the ratio of the overshoot characteristic to the mean oscillation period also increases, and the damping-caecil index increases as other values ​​remain constant. Conversely, when the value of the mean oscillation period increases, the ratio of the overshoot characteristic to the mean oscillation period decreases, and the damping-caecil index decreases as other values ​​remain constant. Similarly, when the value of the mean attenuation ratio increases, the ratio of 1 to the mean attenuation ratio decreases, and its natural logarithm also decreases, and the damping-caecil index decreases as other values ​​remain constant. When the value of the overall magnitude adjustment coefficient increases, the damping-caecil index increases as other values ​​remain constant. When the value of the nonlinearity effect adjustment coefficient increases, the power of the ratio of the overshoot characteristic to the mean oscillation period increases, and the damping-caecil index increases as other values ​​remain constant.

[0168] By combining the calculated damping-locking comprehensive index with the average attenuation ratio, and comparing it with the preset damping characteristics and lockout anomaly judgment criteria, the damping strength and the presence and degree of lockout of the pressure gauge under test are comprehensively evaluated, and finally a comprehensive diagnostic conclusion of the pressure gauge under test is obtained.

[0169] The beneficial effects of this implementation process are that it acquires data at a high sampling frequency after applying micro-pressure pulse excitation, accurately capturing the details of the pressure gauge's swing response. By dividing the response data into rising edge and decaying oscillation segments, the analysis becomes more targeted. Extreme point detection and related sequence extraction in the decaying oscillation segment enable precise quantification of oscillation characteristics. The calculation of the average oscillation period, overshoot characteristic value, and average decay ratio provides multi-dimensional quantitative indicators for assessing damping and jamming states. A comprehensive damping-jamming index is obtained through multi-indicator calculation, and combined with the average decay ratio for comprehensive evaluation. This allows the determination of damping characteristics and jamming anomalies to move beyond subjective experience, relying on quantitative data for more accurate and objective diagnostic results. Simultaneously, the complete data analysis process can effectively identify subtle damping anomalies and hidden jamming problems, improving the comprehensiveness and reliability of pressure gauge anomaly detection.

[0170] like Figure 2 The diagram shown is a functional block diagram of a pressure gauge calibration anomaly detection system provided in an embodiment of the present invention.

[0171] The pressure gauge calibration anomaly detection system of the present invention can be installed in an electronic device. Depending on the functions implemented, the pressure gauge calibration anomaly detection system 100 may include a static state maintenance module 101, an anomaly determination module 102, an early warning signal generation module 103, a pressure disturbance application module 104, and an anomaly state evaluation module 105. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0172] In this embodiment, the functions of each module / unit are as follows:

[0173] The static state maintenance module 101 is used to disconnect the connection between the pressure gauge under test and the pressure source after the pressure gauge under test has completed the first pressure increase to the upper limit of measurement and stabilized according to the verification procedure, and to maintain the static state of the pressure gauge under test in the closed cavity and start timing.

[0174] The anomaly determination module 102 is used to continuously collect the reading of the pressure gauge under test during the first preset time period of the static state, obtain the pressure holding attenuation curve of the pressure gauge under test, and determine whether there is an abnormal pressure drop trend caused by internal leakage in the pressure gauge under test based on the slope change characteristics of the pressure holding attenuation curve.

[0175] The warning signal generation module 103 is used to interrupt the verification process and obtain a verification abnormality warning signal for the pressure gauge under test if it is determined that there is internal leakage.

[0176] The pressure disturbance application module 104 is used to restore the connection between the pressure gauge under test and the pressure source and perform a pressure reduction operation if it is determined that there is no internal leakage; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test.

[0177] The abnormal state assessment module 105 is used to acquire the swing response curve of the pressure gauge under test after the micro-pressure pulse excitation is applied, and to assess the damping characteristics and jamming abnormality of the pressure gauge under test based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

[0178] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0179] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0181] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0182] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for detecting abnormalities in pressure gauge calibration, characterized in that, The method includes: A. After the pressure gauge under test has completed its first pressurization to the upper limit of measurement and stabilized according to the verification procedure, disconnect the connection between the pressure gauge under test and the pressure source, and keep the pressure gauge under test in a static state in the closed cavity, and start timing. B. During the first preset time period of the static state, the reading of the pressure gauge under test is continuously collected to obtain the pressure holding attenuation curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding attenuation curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage. C. If the internal leakage is determined to exist, the calibration process is interrupted, and a calibration abnormality warning signal for the pressure gauge under test is obtained; D. If it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test; E. After applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

2. The method for detecting abnormalities in pressure gauge calibration as described in claim 1, characterized in that, After the pressure gauge under test has completed its initial pressurization to the upper limit of measurement according to the verification procedure and stabilized, the connection between the pressure gauge under test and the pressure source is disconnected, and the pressure gauge under test is kept in a static state within the closed cavity before timing begins, including: After the pressure gauge under test reaches the upper limit of measurement and remains stable, the pressure reading at the stable moment is recorded as the initial holding pressure value of the pressure gauge under test. The pressure fluctuation amplitude data of the pressure gauge under test is obtained within three consecutive calibration cycles before it reaches stability, and the statistical average value of the pressure fluctuation amplitude data is used as the stability judgment benchmark of the pressure gauge under test. While performing the cut-off operation, a high-precision timer is started to begin timing, and the completion time of the cut-off operation is used as the timing zero point. The pressure readings within the first time window after the cut-off are continuously collected to obtain the initial transient response data sequence of the pressure gauge under test. The trend term is extracted from the initial transient response data sequence to obtain the pressure difference of the pressure gauge under test, and the pressure difference is compared with the preset cutoff disturbance tolerance range to determine the additional disturbance of the pressure gauge under test. Based on the additional disturbance, the timing zero point is corrected to the time corresponding to the first data point after the pressure fluctuation in the initial transient response data sequence has decayed to a stable state, thus obtaining the final timing zero point of the pressure gauge under test. The pressure reading corresponding to the final timing zero point is used as the pressure holding starting reference value, and the pressure gauge under test is traced back from the final timing zero point to obtain the initial state reference value of the pressure gauge under test. The starting point deviation of the pressure gauge under test is obtained by performing differential analysis between the pressure holding initial reference value and the initial state reference value, and the starting point deviation is recorded in the calibration log as the pressure state characteristic value at the beginning of the static state of the pressure gauge under test.

3. The method for detecting abnormalities in pressure gauge calibration as described in claim 1, characterized in that, During the first preset time period of the static state, the readings of the pressure gauge under test are continuously collected to obtain the pressure holding decay curve of the pressure gauge under test. Based on the slope change characteristics of the pressure holding decay curve, it is determined whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage, including: Taking the starting time of the static state as the zero point of timing, the scale value pointed to by the pointer of the pressure gauge under test is continuously read at a fixed sampling frequency within the first preset time period. The sampling time and the corresponding pressure value are recorded as the original sampling point, and the original sampling point is subjected to coarse error elimination processing to obtain the preliminary pressure decay sequence of the pressure gauge under test. The initial pressure decay sequence is resampled using cubic spline interpolation to obtain the pressure holding decay curve of the pressure gauge under test. The data points on the pressure holding decay curve are numerically differentiated to obtain the local decay rate of the data points. The local decay rates are then arranged to obtain the local decay rate sequence of the pressure holding decay curve. A variance analysis based on a sliding window is performed on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identify the window position where the dispersion changes significantly, and use the window position as the morphological inflection point of the pressure holding decay curve. Based on the morphological inflection point, the pressure holding attenuation curve is divided into a curve segment before the inflection point and a curve segment after the inflection point. The average attenuation rate of the curve segment before the inflection point is extracted as the first rate feature value, and the average attenuation rate of the curve segment after the inflection point is extracted as the second rate feature value. The first rate characteristic value and the second rate characteristic value are compared and analyzed with a preset steady-state threshold to determine whether the pressure gauge under test has an abnormal pressure drop trend caused by internal leakage.

4. The method for detecting abnormalities in pressure gauge calibration as described in claim 3, characterized in that, The step of performing a sliding window-based variance analysis on the local decay rate sequence to obtain the dispersion of the local decay rate sequence, identifying the window position where the dispersion undergoes a significant abrupt change, and using the window position as the morphological inflection point of the holding pressure decay curve, includes: Set a sliding analysis window of fixed length, and move the sliding analysis window from the starting position of the local decay rate sequence step by step backward, while capturing the local decay rate subsequence within the window at the current position. The variance of the local decay rate subsequence is used as the local fluctuation intensity index of the sliding analysis window, and the local fluctuation intensity index is arranged according to the order of the sliding analysis window to obtain the fluctuation intensity evolution sequence of the local decay rate sequence. Abrupt point detection is performed on the fluctuation intensity evolution sequence to obtain candidate abrupt change points of the pressure holding attenuation curve; Gradient analysis is performed on the candidate mutation points to obtain the jump amplitude coefficients of the candidate mutation points; The window position corresponding to the candidate abrupt change point with the largest abrupt change amplitude coefficient is determined as the final abrupt change position of the local decay rate sequence, and the time corresponding to the final abrupt change position is taken as the morphological inflection point of the pressure holding decay curve.

5. The method for detecting abnormalities in pressure gauge calibration as described in claim 1, characterized in that, If the internal leakage is determined to exist, the calibration process is interrupted, and a calibration abnormality warning signal for the pressure gauge under test is obtained, including: Upon determining the existence of the internal leakage, immediately terminate the currently executing verification command, lock the pressure indication data collected before the current moment, mark the pressure indication data as abnormal verification batch data, and simultaneously extract the complete data of the pressure holding attenuation curve to obtain the original evidence of the abnormality of the pressure gauge under test. A deep analysis based on local extreme points is performed on the pressure holding attenuation curve to identify the local drop peak points of the pressure holding attenuation curve during the static time period, so as to obtain the leakage pulse characteristic sequence of the pressure gauge under test. The leakage pulse feature sequence is compared item by item with the typical leakage mode feature library of the pressure gauge under test. Based on the comparison results, the membership mode type of the pressure gauge under test is determined, and the leakage mode code of the pressure gauge under test is obtained. The degree of abnormality of the pressure gauge under test is determined based on the leakage mode code. By correlating and integrating the abnormal calibration batch data of the pressure gauge under test, the pressure holding attenuation curve, the leakage mode code, and the degree of abnormality, an abnormal calibration warning signal for the pressure gauge under test is obtained.

6. The method for detecting abnormalities in pressure gauge calibration as described in claim 1, characterized in that, If it is determined that there is no internal leakage, the connection between the pressure gauge under test and the pressure source is restored, and a pressure reduction operation is performed. When the pressure drops to near zero, a transient pressure disturbance is applied to the pressure gauge under test, including: After reconnecting the pressure gauge under test to the pressure source, the real-time pressure readings during the pressure reduction process are continuously collected at a fixed sampling frequency to obtain the pressure reduction sequence of the pressure gauge under test. At the same time, the timestamps of the collection are recorded to form a time axis corresponding to the pressure reduction sequence. Real-time trend analysis is performed on the pressure drop sequence to obtain the average rate of decrease of the pressure drop sequence; Under the condition that the average rate of decrease is within the preset stable pressure drop rate range, the absolute value of the difference between the current pressure reading and the preset zero reference value is analyzed, and the absolute value of the difference is used as the current distance from zero. At the same time, the relationship between the current distance from zero and time is recorded to obtain the distance decay curve of the pressure gauge under test. Extrapolate the distance decay curve to obtain the distance decay trend line of the pressure gauge under test, and estimate the remaining time required for the distance value from zero to decay to a preset threshold based on the distance decay trend line. Use the remaining time as a countdown for applying disturbance to the pressure gauge under test. When the countdown for the disturbance application decreases to zero, a disturbance trigger signal is immediately generated for the pressure gauge under test, and the trigger time is accurately recorded as the start time of the disturbance application. At the same time, the pressure reading collected at the trigger time is recorded as the steady-state value before the disturbance. After generating the disturbance trigger signal, pressure readings are continuously collected within a short time window after the disturbance is applied, generating a transient response data sequence containing the pressure response rise and fall segments. The transient response data sequence is then associated with and stored with the steady-state value before the disturbance and the start time of the disturbance application, serving as the raw input data for evaluating the damping characteristics and jamming anomalies of the pressure gauge under test.

7. The method for detecting abnormalities in pressure gauge calibration as described in claim 1, characterized in that, After applying the micro-pressure pulse excitation, the swing response curve of the pressure gauge under test is acquired, and the damping characteristics and jamming anomalies of the pressure gauge under test are evaluated based on the overshoot of the swing response curve and the number of cycles for the oscillation to decay to a steady state, including: At the instant the micro-pressure pulse excitation is applied, the pressure reading of the pressure gauge under test is continuously acquired at a high sampling frequency to obtain the original swing response data sequence of the pressure gauge under test. The data segment before the first pressure peak appears in the original swing response data sequence is marked as the rising edge segment, and the data segment after the first pressure peak to the end of the data sequence is marked as the damped oscillation segment. Local extreme points are detected in the damped oscillation segment to obtain the local maximum and local minimum points of the damped oscillation segment. The pressure values ​​of the local maximum points are extracted in chronological order as positive peak values, and the pressure values ​​of the local minimum points are extracted as negative valley values. Record the times corresponding to the local maxima and local minima to obtain the peak time sequence and valley time sequence of the decaying oscillation segment; Based on the time interval between adjacent positive peaks in the peak time sequence, the duration of the oscillation period is recorded, and the duration of the oscillation period is statistically averaged to obtain the average oscillation period value of the peak time sequence. The final stable pressure value of the damped oscillation segment is determined based on the pressure readings of the continuous sampling points at the end of the damped oscillation segment. The first positive peak is extracted from the positive peak as the initial overshoot peak, and the absolute value of the difference between the initial overshoot peak and the final stable pressure value is used as the overshoot characteristic value. The first three positive peaks are extracted sequentially from the positive peaks and denoted as the first peak, the second peak, and the third peak, respectively. The ratio of the second peak to the first peak is taken as the first attenuation ratio, the ratio of the third peak to the second peak is taken as the second attenuation ratio, and the arithmetic mean of the first attenuation ratio and the second attenuation ratio is taken as the average attenuation ratio. The damping-hysteresis comprehensive index of the pressure gauge under test is calculated based on the overshoot characteristic value, the average oscillation period value, and the average attenuation ratio. Based on the damping-locking composite index and the average attenuation ratio, the damping characteristics and lockout anomalies of the pressure gauge under test are evaluated, and a comprehensive diagnostic conclusion for the pressure gauge under test is obtained.

8. The method for detecting abnormalities in pressure gauge calibration as described in claim 7, characterized in that, The formula for calculating the damping-hysteresis composite index is as follows: ； in, This represents the damping-hysteresis composite index. This represents the characteristic value of the overshoot. This represents the average oscillation period value. This represents the average attenuation ratio. This represents the preset overall magnitude adjustment coefficient. This represents the preset adjustment coefficient for the degree of nonlinear influence. This represents the natural logarithm function.

9. A pressure gauge calibration anomaly detection system, characterized in that, The system for implementing the pressure gauge calibration anomaly detection method according to claim 1, the system comprising: The static state maintenance module is used to disconnect the connection between the pressure gauge under test and the pressure source after the pressure gauge under test has been pressurized to the upper limit of measurement and stabilized according to the verification procedure, and to maintain the pressure gauge under test in a static state in the closed cavity and start timing. The anomaly detection module is used to continuously collect the reading of the pressure gauge under test during the first preset time period of the static state, obtain the pressure holding attenuation curve of the pressure gauge under test, and determine whether there is an abnormal pressure drop trend caused by internal leakage in the pressure gauge under test based on the slope change characteristics of the pressure holding attenuation curve. The warning signal generation module is used to interrupt the verification process and obtain a verification abnormality warning signal for the pressure gauge under test if the internal leakage is determined to exist. The pressure disturbance application module is used to restore the connection between the pressure gauge under test and the pressure source and perform a pressure reduction operation if it is determined that there is no internal leakage; when the pressure is reduced to near zero, a transient pressure disturbance is applied to the pressure gauge under test. The abnormal state assessment module is used to acquire the swing response curve of the pressure gauge under test after the micro-pressure pulse excitation is applied, and to assess the damping characteristics and jamming abnormality of the pressure gauge under test based on the overshoot of the swing response curve and the number of cycles of oscillation decay to steady state.

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