Differential pressure sensor precision calibration method for high-temperature environment monitoring

Abstract

The invention discloses a differential pressure sensor precision calibration method for high-temperature environment monitoring, and relates to the technical field of sensor calibration, and the method comprises the steps: carrying out the high-temperature factor extraction and simulation parameter design of the application scene information of a differential pressure sensor, and obtaining a high-temperature test parameter table of the sensor; a standard differential pressure source is arranged in the high-temperature environment controllable simulation chamber; acquiring a multi-high-temperature parameter differential pressure test data set of the standard differential pressure source; establishing a multi-high-temperature parameter differential pressure compensation model set; obtaining a high-temperature calibration coefficient differential pressure compensation model set; and performing calibration matching calibration on the application scene information of the differential pressure sensor to be calibrated to obtain a differential pressure sensor precision calibration result. The technical problem that the measurement precision and stability of the sensor are poor due to the fact that the measurement precision of the differential pressure sensor is difficult to effectively calibrate in the high-temperature environment in the existing differential pressure sensor precision calibration is solved, and the technical effects of improving the measurement precision of the differential pressure sensor and improving the measurement stability and reliability are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sensor calibration, and particularly relates to a precision calibration method for a differential pressure sensor used in high-temperature environment monitoring. BACKGROUND

[0002] With the continuous improvement of industrial automation level, the differential pressure sensor as an important measurement tool has been widely used in many fields, especially in the monitoring and control scenes in high-temperature environments such as industrial production, aerospace, energy exploration, etc. The differential pressure sensor can provide accurate differential pressure measurement data for various key equipment. However, in high-temperature environments, due to factors such as material thermal expansion, electronic component performance drift, and thermal noise interference in the signal transmission process, the performance of the differential pressure sensor is often affected by temperature fluctuations, and measurement errors and precision decline are prone to occur. How to accurately calibrate and compensate the influence of high-temperature environment on the precision of the differential pressure sensor has become a technical problem to be solved. The traditional differential pressure sensor calibration method is usually carried out at room temperature and does not consider the complex influencing factors in high-temperature environments. The material properties of the sensor, the working state of the components, and the stability will be significantly affected by temperature, resulting in deviation of the output signal of the sensor. If effective compensation and calibration cannot be performed, the accuracy of the measurement results of the differential pressure sensor cannot be guaranteed.

[0003] In the existing differential pressure sensor precision calibration technology, there is a technical problem that it is difficult to effectively calibrate the measurement precision of the differential pressure sensor in a high-temperature environment, resulting in poor sensor measurement precision and stability. SUMMARY

[0004] The present application provides a precision calibration method for a differential pressure sensor used in high-temperature environment monitoring, which solves the technical problem that the existing differential pressure sensor precision calibration cannot effectively calibrate the measurement precision of the differential pressure sensor in a high-temperature environment, resulting in poor sensor measurement precision and stability, and achieves the technical effects of improving the measurement precision of the differential pressure sensor and improving the measurement stability and reliability.

[0005] The application provides a differential pressure sensor precision calibration method for high-temperature environment monitoring, comprising the following steps: obtaining differential pressure sensor application scene information, performing high-temperature factor extraction and simulation parameter design on the differential pressure sensor application scene information, and obtaining a sensor high-temperature test parameter table; establishing a high-temperature environment controllable simulation room, setting a standard differential pressure source in the high-temperature environment controllable simulation room, and installing a target differential pressure sensor in the high-temperature environment controllable simulation room and connecting the target differential pressure sensor with the standard differential pressure source; performing high-temperature simulation control on the high-temperature environment controllable simulation room according to the sensor high-temperature test parameter table, and simultaneously collecting and obtaining a plurality of high-temperature parameter differential pressure test data sets of the standard differential pressure source through the target differential pressure sensor; performing differential pressure influence analysis on the plurality of high-temperature parameter differential pressure test data sets and the standard differential pressure source respectively, and establishing a plurality of high-temperature parameter differential pressure compensation model sets; calibrating and setting the plurality of high-temperature parameter differential pressure compensation model sets using the sensor high-temperature test parameter table, and obtaining a high-temperature calibration coefficient differential pressure compensation model set; and performing setting matching calibration on the application scene information of a differential pressure sensor to be calibrated based on the high-temperature calibration coefficient differential pressure compensation model set, and obtaining a differential pressure sensor precision calibration result.

[0006] In a possible implementation, the obtaining of the sensor high-temperature test parameter table further comprises the following processing: high-temperature factor extraction is performed on the differential pressure sensor application scene information to obtain high-temperature application scene factor information, the high-temperature application scene factor information comprises a temperature range, a temperature fluctuation, a high-temperature duration and a temperature rising rate; simulation parameter analysis is sequentially performed on the differential pressure sensor application scene information based on the high-temperature application scene factor information to obtain a plurality of scene sensor high-temperature test parameter sets; sensor precision correlation analysis is performed on the plurality of scene sensor high-temperature test parameter sets to obtain a sensor precision correlation parameter set; and simulation parameter arrangement is performed based on the plurality of scene sensor high-temperature test parameter sets and the sensor precision correlation parameter set to obtain the sensor high-temperature test parameter table.

[0007] In a possible implementation, the establishing of the plurality of high-temperature parameter differential pressure compensation model sets further comprises the following processing: noise characteristic analysis and filter algorithm matching are performed on the plurality of high-temperature parameter differential pressure test data sets to determine a differential pressure data digital filter; filter preprocessing is performed on the plurality of high-temperature parameter differential pressure test data sets based on the differential pressure data digital filter to obtain a plurality of high-temperature parameter standard differential pressure test data sets; sensor performance influence fitting is respectively performed based on the plurality of high-temperature parameter differential pressure test data sets to generate a plurality of high-temperature parameter sensor performance influence model sets; and differential pressure compensation updating is performed on the plurality of high-temperature parameter sensor performance influence model sets according to the standard differential pressure source to establish the plurality of high-temperature parameter differential pressure compensation model sets.

[0008] In a possible implementation, the generating the multi-high-temperature-parameter sensor performance influence model set further performs the following processing: determining multi-scenario sensor high-temperature test parameter type data and corresponding sensor precision correlation parameter change data according to the multi-high-temperature-parameter differential pressure test data set; taking the multi-scenario sensor high-temperature test parameter type data as an independent variable, and taking each type of correlation parameter data in the corresponding sensor precision correlation parameter change data as a dependent variable in turn; performing influence regression fitting on the independent variable and the dependent variable respectively to obtain a multi-scenario sensor precision correlation parameter influence regression model set; and performing equal-weight fusion on the multi-scenario sensor precision correlation parameter influence regression model set according to the high-temperature test parameter type to generate the multi-high-temperature-parameter sensor performance influence model set.

[0009] In a possible implementation, the establishing the multi-high-temperature-parameter differential pressure compensation model set further performs the following processing: performing differential pressure prediction based on the multi-high-temperature-parameter sensor performance influence model set respectively to obtain a multi-high-temperature-parameter differential pressure prediction information set; calculating a difference value compared with the standard differential pressure source and the multi-high-temperature-parameter differential pressure prediction information set respectively to obtain a multi-high-temperature-parameter differential pressure deviation set; constructing a differential pressure compensation strategy and integrating the differential pressure compensation strategy into the multi-high-temperature-parameter sensor performance influence model set; performing correction and compensation update on the multi-high-temperature-parameter sensor performance influence model set based on the multi-high-temperature-parameter differential pressure deviation set according to the differential pressure compensation strategy to establish the multi-high-temperature-parameter differential pressure compensation model set.

[0010] In a possible implementation, the obtaining the differential pressure sensor precision calibration result further performs the following processing: testing scene classification is performed on application scenario information of the to-be-calibrated differential pressure sensor by using the sensor high-temperature test parameter table to determine a to-be-calibrated scene calibration coefficient; calibration matching is performed based on the to-be-calibrated scene calibration coefficient and the high-temperature calibration coefficient differential pressure compensation model set to obtain an applicable differential pressure compensation model; and precision calibration is performed based on the applicable differential pressure compensation model and differential pressure test data of the to-be-calibrated differential pressure sensor to obtain the differential pressure sensor precision calibration result.

[0011] In a possible implementation, the differential pressure sensor precision calibration method for high-temperature environment monitoring further performs the following processing: extracting model parameters of the applicable differential pressure compensation model, initializing a parameter population, and simultaneously performing performance verification evaluation on the applicable differential pressure compensation model to obtain model performance evaluation parameters; performing model optimization direction analysis on the applicable differential pressure compensation model based on the model performance evaluation parameters to determine a model parameter optimization direction; performing cross variation and population updating on the parameter population according to the model parameter optimization direction until a preset termination condition is met, and comparing and determining optimal population parameters; and performing optimization configuration on the applicable differential pressure compensation model based on the optimal population parameters to obtain an applicable differential pressure optimization compensation model.

[0012] In a possible implementation, the differential pressure sensor precision calibration method for high-temperature environment monitoring further performs the following processing: identifying uncertainty sources of the to-be-calibrated differential pressure sensor to obtain sensor test uncertainty source factors; performing precision loss analysis based on the sensor test uncertainty source factors to obtain sensor test precision loss factors; and performing supplementary correction on the differential pressure sensor precision calibration result based on the sensor test precision loss factors.

[0013] The differential pressure sensor precision calibration method for high-temperature environment monitoring provided in the present application extracts high-temperature factors from differential pressure sensor application scenario information and designs simulation parameters to obtain a sensor high-temperature test parameter table; a standard differential pressure source is arranged in a high-temperature environment controllable simulation room; a plurality of high-temperature parameter differential pressure test data sets of the standard differential pressure source are collected by a target differential pressure sensor; a plurality of high-temperature parameter differential pressure compensation model sets are established; the plurality of high-temperature parameter differential pressure compensation model sets are calibrated to obtain a high-temperature calibration coefficient differential pressure compensation model set; and the application scenario information of a to-be-calibrated differential pressure sensor is calibrated and matched to obtain a differential pressure sensor precision calibration result. The technical problem that the existing differential pressure sensor precision calibration cannot effectively calibrate the measurement precision of the differential pressure sensor in a high-temperature environment, resulting in poor sensor measurement precision and stability is solved, and the technical effects of improving the measurement precision of the differential pressure sensor, improving the measurement stability and reliability are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments of the present application will be briefly introduced below. In the present application, a flowchart is used to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in sequence. On the contrary, various steps can be processed in reverse order or simultaneously as needed. Meanwhile, other operations can be added to these processes, or a step or several steps can be removed from these processes.

[0015] Figure 1A flowchart of a precision calibration method of a differential pressure sensor for high-temperature environment monitoring is provided for the embodiments of the present application.

[0016] Figure 2 A flowchart of establishing a multi-high-temperature parameter differential pressure compensation model set in the precision calibration method of the differential pressure sensor for high-temperature environment monitoring is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0017] The above description is only a summary of the technical solutions of the present application. In order to make the technical solutions of the present application more clear, the embodiments of the present application can be implemented according to the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described as follows.

[0018] In order to make the purposes, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the accompanying drawings, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those skilled in the art without making creative labor are within the scope of protection of the present application.

[0019] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subset of all possible embodiments, and can be combined with each other without conflict. The term "first\second" is only to distinguish similar objects, and does not represent the specific order of the objects. The terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art in the technical field of the present application. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0020] The embodiments of the present application provide a precision calibration method of a differential pressure sensor for high-temperature environment monitoring, as shown in Figure 1 The method comprises the following steps:

[0021] In step S100, the application scene information of the differential pressure sensor is obtained, the high-temperature factor extraction and simulation parameter design are performed on the application scene information of the differential pressure sensor, and the sensor high-temperature test parameter table is obtained.

[0022] Preferably, the pressure difference sensor application scenario information is collected according to the environmental conditions and operation requirements of the actual use of the pressure difference sensor, and detailed information related to the scenario is collected, which usually includes the temperature range of the application environment (the minimum, maximum and average temperature in the working environment of the sensor), the temperature fluctuation characteristics, in some high-temperature scenarios, the temperature may fluctuate rapidly or periodically, for example, high-temperature furnaces in the metallurgical industry, engine compartments, etc., the pressure difference range under different temperature conditions, and the narrow space or complex equipment layout in some high-temperature scenarios may affect the installation and work of the sensor. The high-temperature factor extraction and simulation parameter design of the pressure difference sensor application scenario information is to extract the main high-temperature factors affecting the performance of the sensor according to the above collected scenario information, and design corresponding test and simulation parameters, for example, analyze which high-temperature factors will affect the accuracy of the sensor, which usually includes material expansion, component characteristic change, temperature influence on electronic signal transmission, etc. Based on the extracted high-temperature factors, a set of simulation parameters are set, which include the specific temperature value of the high-temperature test, the temperature change rate, the pressure difference range under different temperatures, and the time period required during the simulation process. Finally, the above high-temperature factors and simulation parameters are integrated to generate a parameter table for actual testing, i.e. a sensor high-temperature test parameter table, which may include temperature range and change rate, test conditions under different temperatures, corresponding pressure difference range under different temperatures, test period and frequency, and working period that the sensor needs to withstand in the simulated high-temperature environment.

[0023] In one possible implementation, step S100 further includes step S110 of extracting high-temperature factors from the pressure difference sensor application scenario information to obtain high-temperature application scenario factor information, the high-temperature application scenario factor information including temperature range, temperature fluctuation, high-temperature duration, and temperature rise rate; step S120 of sequentially analyzing simulation parameters based on the high-temperature application scenario factor information from the pressure difference sensor application scenario information to obtain a set of multi-scenario sensor high-temperature test parameters; step S130 of performing sensor accuracy correlation analysis on the set of multi-scenario sensor high-temperature test parameters to obtain a set of sensor accuracy correlation parameters; and step S140 of arranging simulation parameters based on the set of multi-scenario sensor high-temperature test parameters and the set of sensor accuracy correlation parameters to obtain the sensor high-temperature test parameter table.

[0024] Preferably, from the actual application scene of the differential pressure sensor, key information related to high temperature is extracted, including temperature range, temperature fluctuation, high temperature duration, temperature rise rate, etc. By analyzing the high temperature application scene factors one by one, the high temperature parameters in the actual working environment are simulated, the key conditions such as temperature change and time period in the application scene are analyzed, the corresponding test parameters are generated, and the analysis content may include the change of temperature from low to high, the sensor performance prediction in different temperature ranges, the response of the sensor in temperature fluctuation, etc. A set of test parameters is generated based on different high temperature application scenes, that is, a set of multi-scene sensor high temperature test parameters, which contains the simulation test data of the sensor under different high temperature conditions and reflects the performance of the sensor in different high temperature situations. By analyzing the high temperature test parameters in multiple scenes, how temperature and other factors affect the measurement accuracy of the sensor is discussed, and the change rule of the sensor accuracy under different high temperature conditions is found out. For example, within a certain temperature range, the sensor may exhibit specific error characteristics, and these errors are related to temperature range, temperature rise rate, etc. The parameter set related to the accuracy of the sensor, that is, the accuracy related parameter set, contains various factors closely related to the accuracy of the sensor, such as zero point and range offset, measurement result deviation, temperature range influence on measurement error, temperature rise rate influence on response speed, etc. By combining the multi-scene sensor high temperature test parameter set and the sensor accuracy related parameter set, different temperature ranges, temperature rise rates, high temperature durations, etc. are arranged and combined in order to cover various possible high temperature test situations, a complete set of test parameter schemes is generated to ensure that the sensor can be fully tested and calibrated under different high temperature conditions, and the final test parameter table contains all the parameters that need to be tested under different high temperature conditions.

[0025] Step S200, a high temperature environment controllable simulation room is established, a standard differential pressure source is arranged in the high temperature environment controllable simulation room, and a target differential pressure sensor is installed in the high temperature environment controllable simulation room and connected with the standard differential pressure source.

[0026] Preferably, a laboratory capable of precisely controlling and simulating high-temperature environments is established to test the performance of differential pressure sensors under controlled conditions. Specifically, the simulation chamber must have a precise temperature control system that can set and adjust the temperature range according to testing requirements, typically covering the lowest and highest temperatures in the target application scenario. The temperature control system can provide stable temperatures and simulate temperature fluctuations that may occur in the application scenario to ensure the accuracy and repeatability of test data. Due to the high temperatures required in the simulation chamber, it must have good thermal insulation design and safety measures to prevent high temperatures from causing harm to operators or the external environment; A precisely controllable standard pressure difference generating device is installed in the simulation chamber to generate precisely known pressure difference values as reference points for testing and calibration. The standard pressure difference source is a highly precise and stable device that can generate a series of known pressure difference values for sensor measurement and comparison. It not only provides precise pressure differences but also maintains stable pressure difference values at different temperatures, ensuring that temperature changes have negligible impact on the pressure difference source. It is usually equipped with a high-precision control system that can precisely adjust the pressure difference by adjusting the internal airflow or liquid flow. The standard pressure difference source provides a precise reference value for the target sensor, and the pressure difference data measured by the sensor is compared with the output of the standard pressure difference source to detect its accuracy and response changes at different temperatures; The differential pressure sensor to be calibrated is installed in the high-temperature environment simulation chamber and directly connected to the standard pressure difference source through a pipe or interface. Specifically, the target differential pressure sensor needs to be installed in the simulation chamber at an appropriate position to ensure that it is in a high-temperature environment, ensuring that the sensor is exposed to the required temperature conditions and can collect pressure difference data in real time under high-temperature conditions. The input end of the target differential pressure sensor is connected to the standard pressure difference source through a dedicated interface or pipe, which must ensure that the airflow or liquid flow is unobstructed to avoid pipe resistance or leakage affecting test results. Through this connection, the sensor can receive the precise pressure difference values generated by the standard pressure difference source in real time and compare them with the sensor's output. By comparing the sensor's output signal with the standard value, the measurement error of the sensor at different temperatures can be obtained, providing a basis for subsequent calibration.

[0027] Step S300, according to the sensor high-temperature test parameter table, the high-temperature environment controllable simulation chamber is respectively controlled under high-temperature simulation, and the target differential pressure sensor is used to collect and obtain a plurality of high-temperature parameter pressure difference test data sets of the standard pressure difference source.

[0028] Preferably, the high-temperature environment controllable simulation chamber is set and adjusted according to the high-temperature test parameter table, for example, the parameter table may require the simulation chamber to reach 300°C at a certain stage and maintain for a period of time, then gradually increase to 400°C, or simulate temperature fluctuations, which need to be accurately executed by the temperature control system of the simulation chamber. The control system gradually adjusts the temperature in the high-temperature environment according to the instructions of the sensor high-temperature test parameter table, to ensure that the temperature change process meets the test requirements, such as step-by-step temperature rise or fall at different temperature stages, maintaining at each set temperature point for a long enough time, simulating temperature fluctuation characteristics (such as periodic temperature rise and fall); at the same time, the target differential pressure sensor collects and obtains a plurality of high-temperature parameter differential pressure test data sets of the standard differential pressure source. At each temperature point, the differential pressure sensor measures the differential pressure corresponding to the temperature, for example, at 200°C, 300°C and 400°C, etc. The differential pressure sensor measures the differential pressure provided by the standard differential pressure source and records these data. When the temperature changes, the differential pressure sensor collects differential pressure data at multiple different temperatures to form a test data set with multiple temperatures and multiple differential pressures. This process will be repeated multiple times to cover all high-temperature conditions specified in the parameter table. Specifically, at each temperature stage, the sensor records the output differential pressure value from the standard differential pressure source. The performance of the sensor at each high-temperature condition is recorded and compared with the actual output of the standard differential pressure source. Through multiple temperature adjustments and data collection, a set of differential pressure measurement data at multiple temperatures is obtained, i.e. a plurality of high-temperature parameter differential pressure test data sets, including the differential pressure sensor output data at each specific temperature and the differential pressure value of the standard differential pressure source at the same temperature.

[0029] Step S400, based on the plurality of high-temperature parameter differential pressure test data sets respectively, differential pressure influence analysis is performed with the standard differential pressure source to establish a plurality of high-temperature parameter differential pressure compensation models.

[0030] Preferably, under high-temperature conditions, a detailed comparative analysis is conducted between the actual measured values ​​of the differential pressure sensor and the reference values ​​of the standard differential pressure source to identify the impact of high temperature on sensor accuracy. A corresponding set of compensation models is then established to improve the sensor's measurement accuracy under different high-temperature environments. Specifically, the differential pressure test data of multiple high-temperature parameters collected by the sensor is compared with the reference differential pressure values ​​provided by the standard differential pressure source. By comparing the differences between the sensor's output data and the standard differential pressure at different temperatures, the degree of temperature influence on the sensor's measurement results is identified. For example, at 300℃, the differential pressure value provided by the standard differential pressure source is 100 Pa, while the sensor's measured value may be 95 Pa. The effect of temperature on the sensor output is determined to be -5 Pa. Based on the comparison results, the error trend of temperature on the sensor's measurement results is analyzed, which may show that as the temperature rises... The temperature may increase or decrease, or exhibit nonlinear changes. By analyzing the relationship between the sensor output value and the standard differential pressure value at various temperature points, the specific influence of temperature on differential pressure measurement is determined. Based on the above influence analysis, a compensation model is established to correct the error of the differential pressure sensor under different high-temperature conditions. The compensation model is used to adjust the sensor output value so that it is closer to the actual value provided by the standard differential pressure source under high-temperature conditions. Since the error of the sensor may be different at different temperatures, multiple compensation models need to be established for different temperature ranges. Finally, a multi-high-temperature parameter differential pressure compensation model is obtained. Each model is designed for different high-temperature parameters (such as temperature, pressure range, etc.) to help the differential pressure sensor automatically adjust the output results in high-temperature environments to compensate for the influence of high temperature on sensor performance, thereby ensuring the accuracy of the sensor under various temperature conditions.

[0031] In one possible implementation, such as Figure 2 As shown, step S400 further includes step S410, performing noise characteristic analysis and filter algorithm matching on the multi-high temperature parameter differential pressure test data set to determine the differential pressure data digital filter; step S420, performing filtering preprocessing on the multi-high temperature parameter differential pressure test data set based on the differential pressure data digital filter to obtain a multi-high temperature parameter standard differential pressure test data set; step S430, performing sensor performance influence fitting on the multi-high temperature parameter differential pressure test data set to generate a multi-high temperature parameter sensor performance influence model set; step S440, updating the multi-high temperature parameter sensor performance influence model set with differential pressure compensation based on the standard differential pressure source to establish the multi-high temperature parameter differential pressure compensation model set.

[0032] Preferably, the differential pressure test data set collected in a high temperature environment can be disturbed by various noises (e.g. electromagnetic interference from the environment, equipment vibration, etc.), and the purpose of noise characteristic analysis is to identify the type, frequency distribution, amplitude, etc. of these noises, for example by spectrum analysis or statistical method, to analyze the distribution of high frequency noise, low frequency drift or random noise in the test data, to determine the main source of the noise and its characteristics, based on the results of noise characteristic analysis, to select or design a suitable digital filter algorithm (such as low pass filter, band pass filter, Kalman filter, etc.) to eliminate the interference of noise on the differential pressure test data, for example, if the noise is mainly high frequency component, a low pass filter can be selected to suppress high frequency noise, if the noise is random drift, a Kalman filter can be considered for dynamic adjustment, according to the above analysis results, to determine the digital filter suitable for the specific differential pressure data, including the type, order and parameter setting of the filter; filter the collected multi-temperature parameter differential pressure test data set to eliminate noise interference in the data, extract more real and accurate differential pressure signals, process each set of differential pressure data to remove high frequency noise, drift and other interference components, make the data more smooth and stable, generate a multi-temperature parameter standard differential pressure test data set, which better reflects the real differential pressure response of the sensor in a high temperature environment.

[0033] Preferably, sensor performance influence fitting is performed according to a plurality of high-temperature parameter pressure difference test data sets respectively to evaluate the specific influence of high-temperature environment on the performance of the pressure difference sensor, including measurement error, sensitivity change, etc. Specifically, based on the plurality of high-temperature data, curve fitting is performed on the output of the sensor and the reference data of the standard pressure difference source to generate a mathematical model (e.g., linear fitting, polynomial fitting, etc.) for describing the performance change of the sensor, reflecting the output change trend of the sensor under different high-temperature conditions, and can describe the error characteristics of the sensor. A corresponding performance influence model is generated for each high-temperature condition, and each model describes the performance change (e.g., sensitivity decrease, response time slow down, etc.) of the sensor at a specific temperature, forming a plurality of high-temperature parameter sensor performance influence model sets. After establishing the sensor performance influence model set, further combined with the data of the standard pressure difference source, the models are updated for compensation, and the error characteristics of the sensor are corrected to make the output of the sensor closer to the true value of the standard pressure difference source. Specifically, based on the reference pressure difference value of the standard pressure difference source, the performance influence model is updated one by one so that the sensor error under different high-temperature conditions can be effectively compensated, for example, adjusting the parameters in the model, or introducing a compensation function to correct the output of the sensor. After pressure difference compensation update, a plurality of high-temperature parameter pressure difference compensation model sets are finally generated for automatically adjusting the output of the sensor during actual work, ensuring that the sensor can still maintain high measurement accuracy even under different high-temperature conditions. For example, for a certain high-temperature segment, the compensation model may automatically add or subtract a correction value according to the output of the sensor, so that the final measurement result is closer to the true value, that is, dynamically compensating the error of the sensor under different high-temperature conditions, ensuring the measurement accuracy of the sensor in high-temperature environment.

[0034] In a possible implementation, step S430 further includes step S431 of determining, according to the plurality of high-temperature parameter pressure difference test data sets, a plurality of scene sensor high-temperature test parameter type data and corresponding sensor accuracy associated parameter change data; step S432 of taking the plurality of scene sensor high-temperature test parameter type data as independent variables and each type of associated parameter data in the corresponding sensor accuracy associated parameter change data as dependent variables in turn; step S433 of performing influence regression fitting on the independent variables and the dependent variables respectively to obtain a plurality of scene sensor accuracy associated parameter influence regression model sets; and step S434 of performing equal-weight fusion on the plurality of scene sensor accuracy associated parameter influence regression model sets according to high-temperature test parameter types to generate the plurality of high-temperature parameter sensor performance influence model sets.

[0035] Preferably, according to the multi-high-temperature parameter differential pressure test data set, the multi-scene sensor high-temperature test parameter type data and the sensor precision correlation parameter change data are determined. Specifically, under different high-temperature scenes, the collected sensor test parameter data covers the running conditions of the sensor under different temperature and pressure difference conditions, such as temperature range, measured pressure difference value, sensor running period, and environmental variables (such as humidity, pressure fluctuation, etc.). The sensor precision correlation parameter change data refers to the change of the sensor precision under different high-temperature scenes, that is, how the high-temperature environment affects the measurement precision of the sensor, including the measurement error of the sensor, the change of the response speed, the decrease of the sensitivity, and the drift of the output signal. The multi-scene sensor high-temperature test parameter type data, such as temperature, pressure, and working time, which affect the precision of the sensor, are used as the independent variables for regression analysis, and each type of parameter in the sensor precision correlation parameter change data, including measurement error, response speed, and sensitivity change, is used as the dependent variable. For each type of sensor precision correlation parameter change data, regression fitting is performed respectively to find the relationship between each type of precision parameter and the test condition (independent variable), such as the influence of temperature on measurement error, the influence of pressure difference on sensitivity, and the influence of working time on response speed.

[0036] Preferably, through regression analysis, the mathematical relationship between the independent variables (such as temperature, pressure difference, etc.) and the dependent variables (such as measurement error, sensitivity, etc.) is found, that is, the change trend of the dependent variable is predicted by the known independent variable. Since different precision correlation parameters (dependent variables) may be affected by different types of high-temperature test parameters (independent variables), each independent variable-dependent variable pair will generate a regression model. The collection of multiple regression models is the multi-scene sensor precision correlation parameter influence regression model set, which includes the influence regression model of each sensor precision correlation parameter corresponding to each high-temperature test parameter type. Each model can describe the influence of a certain independent variable on the performance parameter of a specific sensor under different high-temperature conditions. The output results of multiple regression models are processed by weighted average, and each model is given equal weight (i.e. uniform weight), to generate a comprehensive performance influence model that comprehensively considers the influence of each test parameter on the performance of the sensor, making the model more representative. Finally, a comprehensive model set containing the performance changes of the sensor under multiple high-temperature conditions is obtained, each model corresponds to a specific high-temperature test parameter type and can describe the performance change of the sensor under different conditions. This model set can be used to predict the performance of the sensor in different high-temperature environments.

[0037] In a possible implementation, step S440 further includes the following steps: S441, respectively performing pressure difference prediction based on the set of multi-high-temperature parameter sensor performance influence models to obtain a set of multi-high-temperature parameter pressure difference prediction information; S442, respectively calculating the difference between the standard pressure difference source and the set of multi-high-temperature parameter pressure difference prediction information to obtain a set of multi-high-temperature parameter pressure difference deviations; S443, constructing a pressure difference compensation strategy and integrating the pressure difference compensation strategy into the set of multi-high-temperature parameter sensor performance influence models; and S444, performing correction and compensation update on the set of multi-high-temperature parameter sensor performance influence models based on the set of multi-high-temperature parameter pressure difference deviations according to the pressure difference compensation strategy, to establish a set of multi-high-temperature parameter pressure difference compensation models.

[0038] Preferably, the models in the set of multi-high-temperature parameter sensor performance influence models are used to predict the pressure difference under different high-temperature scenarios, to calculate the pressure difference values that the sensor may measure under different temperature and pressure difference conditions, to form a set of multi-high-temperature parameter pressure difference prediction information, that is, a series of predicted pressure difference values of the sensor based on its current performance under various high-temperature scenarios; the predicted pressure difference values of the sensor are compared with the actual values of the standard pressure difference source to obtain the pressure difference errors or deviations of the sensor, to form a set of multi-high-temperature parameter pressure difference deviations, which reflect the deviation degrees of the pressure difference measured by the sensor from the standard values under different high-temperature conditions; based on the set of pressure difference deviations, a compensation strategy is formulated to correct the errors of the sensor in measuring the pressure difference under high-temperature conditions, that is, a pressure difference compensation strategy, to adjust the predicted values of the sensor to be close to the standard values, thereby improving the measurement accuracy, and the pressure difference compensation strategy is integrated into the existing set of multi-high-temperature parameter sensor performance influence models, so that the compensation strategy is automatically applied to the predicted results each time the models output pressure difference prediction, thereby improving the accuracy of the models, for example, adding or subtracting a compensation value to the predicted values of the models to reduce the deviation from the standard values; according to the formulated pressure difference compensation strategy, the deviation data in the set of multi-high-temperature parameter pressure difference deviations are used to adjust and correct the sensor performance influence models, the predicted pressure difference errors are automatically adjusted, the original error values are considered by the models through application of the compensation strategy, and the output of the models is adjusted in real time according to the deviation data, to improve the prediction accuracy of the models, so that the measurement of the sensor under high-temperature conditions is more accurate, and the set of models after correction and compensation is the final set of pressure difference compensation models, which can accurately predict the pressure difference under different high-temperature conditions and automatically compensate according to the actual deviation, to ensure the accuracy of the measurement results.

[0039] S500, calibrating and demarcating the set of multi-high-temperature parameter pressure difference compensation models using the sensor high-temperature test parameter table to obtain a set of high-temperature demarcated coefficient pressure difference compensation models.

[0040] Preferably, the generated multi-high-temperature parameter differential pressure compensation model is further calibrated and accurately adjusted using the sensor high-temperature test parameter table to ensure that the model can accurately reflect the differential pressure measurement of the sensor under various high-temperature environments. Specifically, the calibration refers to comparing and adjusting the differential pressure compensation model with the actual test data to make the output of the model more accurately reflect the real measurement value of the sensor under high-temperature environment. The parameters in the sensor high-temperature test parameter table (such as temperature, differential pressure, etc.) are brought into the compensation model, and the output result (i.e. the predicted value of the differential pressure) of the model is adjusted by adjusting the model parameters (such as compensation coefficient, correction value, etc.) to make it as close as possible to the value of the actual standard differential pressure source. The key coefficients in the model are continuously adjusted during the calibration process to ensure that the model's response to high-temperature environment is more accurate, reducing the measurement error of the sensor under different temperature conditions. The high-temperature calibration coefficient is a correction coefficient generated during the calibration process, which reflects the error and performance deviation of the sensor under different high-temperature scenarios. By introducing the calibration coefficient to adjust the compensation model, the output of the model is more accurate. That is, by introducing the high-temperature calibration coefficient, the original multi-high-temperature parameter differential pressure compensation model is optimized in precision to obtain a high-temperature calibration coefficient differential pressure compensation model set, which can better reflect the actual performance of the sensor in a high-temperature environment, further reduce measurement error, and ensure its measurement accuracy under different high-temperature conditions.

[0041] In step S600, the application scene information of the differential pressure sensor to be calibrated is calibrated and matched based on the high-temperature calibration coefficient differential pressure compensation model set to obtain a differential pressure sensor precision calibration result.

[0042] Preferably, the established high-temperature calibration coefficient differential pressure compensation model is used to calibrate and match the operating conditions of the differential pressure sensor to be calibrated in the specific application scenario to ensure the measurement accuracy of the sensor under these conditions. Specifically, according to the application scenario information of the sensor to be calibrated, the most suitable model is selected from the set of high-temperature calibration coefficient differential pressure compensation models for application, including finding the corresponding compensation model from the model set according to the application temperature, differential pressure range and other conditions of the sensor, bringing the operating data of the sensor into the model, and correcting the output of the sensor through the calibration coefficient and compensation mechanism in the model. In the actual calibration process, the measurement data of the sensor will be compared with the output of the compensation model to confirm whether the sensor can accurately reflect the true differential pressure value under high-temperature conditions. If there is a deviation, the model will automatically apply compensation to adjust the sensor output until the accuracy requirement is met. If the application scenario information (such as temperature, pressure, etc.) of the sensor changes during actual work, the compensation model will be adjusted in real time according to these dynamic changes to ensure the output of the sensor under different conditions is still accurate. Finally, the differential pressure sensor precision calibration result is obtained, which reflects the calibration effect of the sensor under specific application scenarios. Through multiple calibration and adjustment of the sensor output, the error of the sensor in the entire high-temperature range is minimized to ensure its reliability and accuracy in actual application.

[0043] In one possible implementation, step S600 further includes step S610 of using the sensor high-temperature test parameter table to test the application scenario information of the differential pressure sensor to be calibrated, and determining the calibration coefficient of the to-be-calibrated scenario; step S620 of performing calibration matching based on the calibration coefficient of the to-be-calibrated scenario and the set of high-temperature calibration coefficient differential pressure compensation models, and obtaining an applicable differential pressure compensation model; and step S630 of performing precision calibration based on the differential pressure test data of the differential pressure sensor to be calibrated and the applicable differential pressure compensation model, and obtaining the precision calibration result of the differential pressure sensor.

[0044] Preferably, based on the sensor-based application scene information, it is assigned to a predefined high-temperature test scene, for example, a certain application scene may be classified as 300-400℃, a high-pressure difference interval category, according to the classification result, determine the calibration coefficient matched with the scene, used to correct the sensor error under different high temperature and pressure difference conditions; according to the calibration coefficient of the scene to be calibrated, match the generated high-temperature calibration coefficient pressure difference compensation model set, that is, select the most suitable compensation model for the current application scene in the model set, according to the temperature and pressure difference conditions of the scene to be calibrated, adjust the specific calibration coefficient, ensure that the compensation result is the most accurate; use the applicable pressure difference compensation model to calibrate the pressure difference test data of the sensor, specifically, the actual measurement data in the scene to be calibrated is taken as the input, the compensation model will correct the measurement error of the sensor according to the actual output value of the sensor and the corresponding temperature and pressure difference conditions, ensure that the pressure difference value output by the sensor is closer to the actual standard value, finally, the sensor output corrected by the compensation model is the precision calibration result of the pressure difference sensor, the calibration result reflects the measurement precision of the sensor under actual working conditions, and confirms whether the sensor meets the precision requirement.

[0045] In a possible implementation, step S620 further includes step S621 of extracting model parameters of the applicable pressure difference compensation model, initializing a parameter population, and simultaneously performing performance verification evaluation on the applicable pressure difference compensation model to obtain model performance evaluation parameters; step S622 of performing model optimization direction analysis on the applicable pressure difference compensation model based on the model performance evaluation parameters to determine a model parameter optimization direction; step S623 of performing cross variation and population updating on the parameter population according to the model parameter optimization direction until a preset termination condition is met, and comparing and determining optimal population parameters; and step S624 of performing optimized configuration on the applicable pressure difference compensation model based on the optimal population parameters to obtain an applicable pressure difference optimized compensation model.

[0046] Preferably, the model parameters of the differential pressure compensation model are extracted, which can include differential pressure correction coefficients, temperature compensation coefficients, non-linear correction parameters, etc. A certain number of population individuals are randomly generated according to the model parameters, each population individual represents a set of model parameters, and the parameter population is a collection of several sets of possible parameter values. The performance of the differential pressure compensation model is evaluated using the current extracted model parameters to determine the effectiveness and accuracy of the model in compensating for the error of the differential pressure sensor. The evaluation criteria can include the error correction accuracy of the model, the calculation efficiency, the stability of the model, etc. The evaluation parameters obtained through performance verification evaluation are used to quantify the performance of the current differential pressure compensation model. By analyzing the model performance evaluation parameters, the optimization direction of the model is determined, and it is found out which model parameters have a greater impact on the overall performance, and it is decided how to adjust these parameters. On the basis of analyzing the current performance of the model, it is decided how to adjust each parameter to optimize the performance of the model. According to the performance indicators, the priority is sorted, and the direction that can most improve the performance of the model is selected. The optimization direction can include improving the accuracy of the model (such as reducing the differential pressure error), reducing the calculation complexity, improving the stability of the model, etc. Crossover is to combine two or more parameter populations to generate new parameter groups. Mutation is to randomly make small adjustments to some parameters to explore new parameter combinations. Through the recombination and random disturbance of parameters, a new and better parameter population is generated to find a better combination of model parameters. Population updating refers to constantly eliminating poor-performing parameter groups and retaining good-performing parameter groups. Iterative generation of better model parameters, i.e. evaluating the performance of new parameter combinations, selecting the best-performing parameter combination for the next round of optimization, until the preset termination condition is met. By constantly comparing the performance of different parameter groups, the optimal parameter combination, i.e. the optimal population parameter, is ultimately found, which can maximize the performance of the differential pressure compensation model and ensure its accuracy and stability in compensating for sensor errors in high-temperature environments. Finally, the optimal population parameter is used to optimize the configuration of the differential pressure compensation model, i.e. the optimal parameters found are applied to the compensation model to adjust the structure and parameter settings of the model so that the model can achieve the best compensation effect and obtain the optimized differential pressure compensation model. Not only can the sensor error be corrected, but also a high measurement accuracy and compensation effect can be maintained in high-temperature and complex environments.

[0047] In a possible implementation, step S600 further includes step S640 of identifying the uncertainty source of the differential pressure sensor to be calibrated to obtain a sensor test uncertainty source factor; step S650 of performing precision loss analysis based on the sensor test uncertainty source factor to obtain a sensor test precision loss factor; and step S660 of supplementarily correcting the differential pressure sensor precision calibration result based on the sensor test precision loss factor.

[0048] Preferably, the uncertainty source identification is performed on the pressure difference sensor to be calibrated, all possible self-state factors that may affect the test accuracy of the pressure difference sensor are identified, i.e. sensor test uncertainty source factors, such as sensor shell damage, service life, interface loosening, electrical connection performance, etc., each factor will have different degrees of influence on the final measurement result; for each uncertainty source factor, the specific influence of each factor on the sensor measurement accuracy is evaluated, and the influence coefficient of each factor on the overall test accuracy is calculated according to the analysis of each uncertainty source factor, the sensor test accuracy loss factor reflects the accuracy loss of the sensor in the measurement process due to the uncertainty; finally, the pressure difference sensor accuracy calibration result is supplemented and corrected according to the sensor test accuracy loss factor, and the accuracy loss caused by the uncertainty is considered, so that the final pressure difference sensor accuracy is higher, the error is smaller, and the accuracy and reliability of the pressure difference sensor calibration result are higher.

[0049] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application. In some cases, the actions or steps described in the present application can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or may be advantageous.

Claims

1. A method for precision calibration of differential pressure sensors for high temperature environment monitoring, characterized in that, The method comprises: obtaining pressure difference sensor application scene information, performing high-temperature factor extraction and simulation parameter design on the pressure difference sensor application scene information, and obtaining a sensor high-temperature test parameter table; establishing a high-temperature environment controllable simulation room, setting a standard pressure difference source in the high-temperature environment controllable simulation room, and installing a target pressure difference sensor in the high-temperature environment controllable simulation room and connecting the target pressure difference sensor with the standard pressure difference source; controlling the high-temperature environment controllable simulation room according to the sensor high-temperature test parameter table, and simultaneously collecting and obtaining a plurality of high-temperature parameter pressure difference test data sets of the standard pressure difference source through the target pressure difference sensor; performing pressure difference influence analysis on the plurality of high-temperature parameter pressure difference test data sets and the standard pressure difference source respectively, and establishing a plurality of high-temperature parameter pressure difference compensation model sets; calibrating and setting the plurality of high-temperature parameter pressure difference compensation model sets using the sensor high-temperature test parameter table, and obtaining a high-temperature calibration coefficient pressure difference compensation model set; based on the high-temperature calibration coefficient pressure difference compensation model set, performing calibration and matching calibration on the application scene information of a to-be-calibrated pressure difference sensor, and obtaining a pressure difference sensor precision calibration result.

2. The differential pressure sensor accuracy calibration method for high temperature environment monitoring of claim 1, wherein, The sensor high-temperature test parameter table is obtained by: extracting high-temperature factors from the pressure difference sensor application scene information to obtain high-temperature application scene factor information, wherein the high-temperature application scene factor information includes temperature range, temperature fluctuation, high-temperature duration, and temperature rising rate; sequentially performing simulation parameter analysis on the pressure difference sensor application scene information based on the high-temperature application scene factor information, and obtaining a plurality of scene sensor high-temperature test parameter sets; performing sensor precision correlation analysis on the plurality of scene sensor high-temperature test parameter sets, and mapping to obtain a sensor precision correlation parameter set; based on the plurality of scene sensor high-temperature test parameter sets and the sensor precision correlation parameter set, performing simulation parameter arrangement, and obtaining the sensor high-temperature test parameter table.

3. The method for precision calibration of differential pressure sensors for high temperature environment monitoring as claimed in claim 1, wherein, The plurality of high-temperature parameter pressure difference compensation model sets are established by: performing noise characteristic analysis and filter algorithm matching on the plurality of high-temperature parameter pressure difference test data sets to determine a pressure difference data digital filter; based on the pressure difference data digital filter, performing filter preprocessing on the plurality of high-temperature parameter pressure difference test data sets to obtain a plurality of high-temperature parameter standard pressure difference test data sets; based on the plurality of high-temperature parameter pressure difference test data sets, performing sensor performance influence fitting respectively to generate a plurality of high-temperature parameter sensor performance influence model sets; based on the standard pressure difference source, performing pressure difference compensation update on the plurality of high-temperature parameter sensor performance influence model sets to establish the plurality of high-temperature parameter pressure difference compensation model sets.

4. The method for precision calibration of a differential pressure sensor for high temperature environment monitoring of claim 3, wherein, The plurality of high-temperature parameter sensor performance influence model sets are generated by: determining a plurality of scene sensor high-temperature test parameter type data and corresponding sensor precision correlation parameter change data according to the plurality of high-temperature parameter pressure difference test data sets; taking the plurality of scene sensor high-temperature test parameter type data as independent variables, and taking each type of correlation parameter data in the corresponding sensor precision correlation parameter change data as dependent variables in turn; Perform influence regression fitting on the independent variables and the dependent variables respectively to obtain a set of multi-scenario sensor accuracy correlation parameter influence regression models; Fuse the set of multi-scenario sensor accuracy correlation parameter influence regression models according to high-temperature test parameter types to generate a set of multi-high-temperature parameter sensor performance influence models.

5. The method for precision calibration of a differential pressure sensor for high temperature environment monitoring of claim 3, wherein, The establishment of the set of multi-high-temperature parameter differential pressure compensation models comprises: Perform differential pressure prediction based on the set of multi-high-temperature parameter sensor performance influence models respectively to obtain a set of multi-high-temperature parameter differential pressure prediction information; Calculate the difference between the standard differential pressure source and the set of multi-high-temperature parameter differential pressure prediction information respectively to obtain a set of multi-high-temperature parameter differential pressure deviation sets; Construct a differential pressure compensation strategy and integrate the differential pressure compensation strategy into the set of multi-high-temperature parameter sensor performance influence models; Perform correction and compensation update on the set of multi-high-temperature parameter sensor performance influence models based on the set of multi-high-temperature parameter differential pressure deviation sets according to the differential pressure compensation strategy to establish the set of multi-high-temperature parameter differential pressure compensation models.

6. The method for precision calibration of differential pressure sensors for high temperature environment monitoring as claimed in claim 1, wherein, The obtaining of the differential pressure sensor accuracy calibration result comprises: Test scene classification is performed on the application scenario information of the to-be-calibrated differential pressure sensor using the sensor high-temperature test parameter table to determine a to-be-calibrated scene calibration coefficient; Calibration matching is performed based on the to-be-calibrated scene calibration coefficient and the set of high-temperature calibration coefficient differential pressure compensation models to obtain an applicable differential pressure compensation model; Accuracy calibration is performed on the differential pressure test data of the to-be-calibrated differential pressure sensor based on the applicable differential pressure compensation model to obtain the differential pressure sensor accuracy calibration result.

7. The method for precision calibration of a differential pressure sensor for high temperature environment monitoring of claim 6, wherein, The method comprises: Model parameters of the applicable differential pressure compensation model are extracted, a parameter population is initialized, and performance verification and evaluation are performed on the applicable differential pressure compensation model to obtain model performance evaluation parameters; Model optimization direction analysis is performed on the applicable differential pressure compensation model based on the model performance evaluation parameters to determine a model parameter optimization direction; The parameter population is subjected to cross variation and population update according to the model parameter optimization direction until a preset termination condition is met, and optimal population parameters are determined by comparison and optimization; The applicable differential pressure compensation model is optimized and configured based on the optimal population parameters to obtain an applicable differential pressure optimization compensation model.

8. The method for precision calibration of differential pressure sensors for high temperature environment monitoring as claimed in claim 1, wherein, The method comprises: Uncertainty source identification is performed on the to-be-calibrated differential pressure sensor to obtain sensor test uncertainty source factors; Accuracy loss analysis is performed based on the sensor test uncertainty source factors to obtain sensor test accuracy loss factors; The differential pressure sensor accuracy calibration result is supplemented and corrected based on the sensor test accuracy loss factors.

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