Verification method and apparatus for gas analysis system, device, and storage medium

Abstract

A verification method and apparatus (20) for a gas analysis system, an electronic device (30), and a computer-readable storage medium, relating to the technical field of gas testing. The method comprises: on the basis of a first confidence interval obtained by testing a gas analysis system under standard working conditions (S101), a second confidence interval obtained by testing the gas analysis system under simulated working conditions (S102), a third confidence interval obtained by testing the gas analysis system under ideal working conditions (S103), and a fourth confidence interval obtained by testing the gas analysis system under actual working conditions (S104), verifying the gas analysis system (S105). According to the verification method for a gas analysis system, the effectiveness of data measured by the gas analysis system can be determined.

Description

Verification method, device, equipment and storage medium of gas analysis system Technical Field

[0001] The present application relates to the field of gas detection technology. Specifically, the present application relates to a verification method, device, equipment and computer-readable storage medium for a gas analysis system. Background Art

[0002] In some industries that require continuous and accurate determination of data validity, the analysis system itself has a significant impact on data accuracy. How to determine the accuracy of data measured by the analysis system is an urgent problem that needs to be solved.

[0003] Summary of the Invention

[0004] The embodiments of the present application provide a gas analysis system verification method, apparatus, device, computer-readable storage medium, and computer program product for solving the technical problem of being unable to determine the effectiveness of the gas analysis system.

[0005] According to one aspect of an embodiment of the present application, a method for verifying a gas analysis system is provided, the method comprising:

[0006] The gas analysis system is tested using cylinder gases under multiple standard working conditions to determine multiple baseline linearity curves and corresponding first confidence intervals of the gas analysis system;

[0007] Testing the gas analysis system using simulated operating condition data to determine second confidence intervals for the multiple reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system;

[0008] Testing the gas analysis system using ideal operating condition data of the object to be measured to determine a third confidence interval of the plurality of baseline linearity curves;

[0009] Testing the gas analysis system using first actual operating condition data of the object to be measured to determine fourth confidence intervals of the multiple reference linearity curves;

[0010] The gas analysis system is validated based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

[0011] In one possible implementation, verifying the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval includes:

[0012] If the fourth confidence interval is completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, the gas analysis system passes the verification;

[0013] A union range of the first confidence interval, the second confidence interval, and the third confidence interval is determined as a linearity confidence interval.

[0014] In another possible implementation, the verifying the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval further includes:

[0015] If the fourth confidence interval is not completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, measuring the gas analysis system using the first operating condition data to determine a fifth confidence interval of the multiple baseline linearity curves;

[0016] The first operating condition data includes the simulated operating condition data and second actual operating condition data, and the second actual operating condition data is the first actual operating condition data corresponding to a portion of the fourth confidence interval that is not covered by the union range of the first confidence interval, the second confidence interval, and the third confidence interval;

[0017] A union of the first confidence interval, the second confidence interval, the third confidence interval, the fourth confidence interval, and the fifth confidence interval is determined as the linearity confidence interval.

[0018] In yet another possible implementation, the method further includes:

[0019] Measuring third actual working condition data of the object to be measured using the gas analysis system to obtain measurement data;

[0020] determining a confidence interval from the linearity confidence intervals based on the measurement data;

[0021] Invalid data and valid data in the measurement data are determined based on the determined confidence interval.

[0022] In yet another possible implementation, determining invalid data and valid data in the measurement data based on the determined confidence interval includes:

[0023] Determining first data in the measurement data that does not exceed the determined confidence interval as the valid data;

[0024] Second data in the measurement data that exceeds the determined confidence interval within a first moment or a first time period is determined as the invalid data.

[0025] In yet another possible implementation, determining a confidence interval from the linearity confidence interval includes:

[0026] According to the measurement parameter in the measurement data, a confidence interval corresponding to the measurement parameter is determined from the linearity confidence interval.

[0027] In yet another possible implementation, the method further includes:

[0028] Periodically updating the linearity confidence interval; or,

[0029] The linearity confidence interval is updated in any of the following cases:

[0030] The measured data contains data that exceeds the linearity confidence interval;

[0031] Adjustment of process parameters of the gas analysis system;

[0032] Hardware replacement of the gas analysis system.

[0033] According to another aspect of an embodiment of the present application, a verification device for a gas analysis system is provided, the device comprising:

[0034] Measurement modules that perform the following operations:

[0035] The gas analysis system is tested using cylinder gases under multiple standard working conditions to determine multiple baseline linearity curves and corresponding first confidence intervals of the gas analysis system;

[0036] Testing the gas analysis system using simulated operating condition data to determine second confidence intervals for the multiple reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system;

[0037] Testing the gas analysis system using ideal operating condition data of the object to be measured to determine a third confidence interval of the plurality of baseline linearity curves;

[0038] Testing the gas analysis system using first actual operating condition data of the object to be measured to determine fourth confidence intervals of the multiple reference linearity curves;

[0039] A processing module is configured to validate the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

[0040] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in any of the above embodiments.

[0041] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0042] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, which implements the steps of the method described in any of the above embodiments when executed by a processor.

[0043] The beneficial effects of the technical solution provided in the embodiments of the present application are: based on the first confidence interval obtained by testing the gas analysis system under standard working conditions, the second confidence interval obtained by testing the gas analysis system under simulated working conditions, the third confidence interval obtained by testing the gas analysis system under ideal working conditions, and the fourth confidence interval obtained by testing the gas analysis system under actual working conditions, the gas analysis system is verified, thereby enabling the validity of the data measured by the gas analysis system to be determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments of the present application.

[0045] FIG1 is a schematic flow chart of a verification method for a gas analysis system provided in an embodiment of the present application;

[0046] FIG2 is a schematic diagram of the structure of a verification device for a gas analysis system provided in an embodiment of the present application;

[0047] FIG3 is a schematic structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following describes the embodiments of the present application in conjunction with the accompanying drawings. It should be understood that the embodiments described below in conjunction with the accompanying drawings are exemplary descriptions of the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions of the embodiments of the present application.

[0049] Those skilled in the art will understand that, unless otherwise stated, the singular forms "a", "an", "said", and "the" used herein may also include plural forms. It should be further understood that the terms "including" and "comprising" used in the embodiments of the present application mean that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements, and / or components, but do not exclude implementation as other features, information, data, steps, operations, elements, components, and / or combinations thereof supported by the present technical field. It should be understood that when we say that an element is "connected" or "coupled" to another element, the element can be directly connected or coupled to the other element, or it can refer to the element and the other element establishing a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used here can include wireless connection or wireless coupling. The term "and / or" used here indicates at least one of the items defined by the term, for example, "A and / or B" can be implemented as "A", or as "B", or as "A and B".

[0050] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0051] In some high-precision, continuous applications where precise data validity determination is required, mass concentration (calculated based on volume concentration) * gas flow rate = total emissions. Therefore, whether used for process control, energy efficiency control, or when precise measurement of total volume, volume, or mass concentration is required, the conversion of volume concentration to mass concentration and the determination of gas flow rate data validity directly impact the final result.

[0052] The above application areas include but are not limited to: precise measurement of continuous total gas volume, precise tracking of volume concentration changes, precise measurement of mass concentration, precise tracking of the impact of flow, temperature, and pressure on gas processes, high-precision process control of measurement, energy efficiency control, and other fields.

[0053] Specifically, the accuracy of volume concentration and mass concentration data is used as an example. An analytical system (including continuous analysis and / or temporary short-term analysis) is used, primarily using NDIR (non-dispersive infrared light principle), ultraviolet light source, or optical sensors in the form of modulated spectrum lasers, or electrochemical sensors, to measure and quantify volume concentration. The mass concentration is then calculated based on the measured volume concentration. The following problems exist in this process:

[0054] a. Sensor calibration usually uses two-point calibration, that is, using cylinder gas to calibrate the sensor's zero point and span point to obtain a baseline with a fixed slope. Depending on the sensor principle, the actual application data usually only has good baseline reproducibility or a slope close to the baseline within a certain range;

[0055] b. The sensor's measurement results only represent the volume concentration of the gas fed into the sensor, and cannot directly and effectively reflect the actual volume concentration of the sample in the process pipeline at the collection location. Therefore, there may be a large difference between the actual volume concentration in the process pipeline and the analysis result;

[0056] c. When the volume concentration measured by the sensor needs to be converted into mass flow, a complete and scientific volume concentration conversion formula should include the effects of gas temperature and pressure on concentration;

[0057] d. Analytical sensors rely on sampling and pre-treatment equipment to process the sample gas. This process can significantly alter the sample gas's temperature, humidity, pressure, and flow rate. These changes significantly impact the volume concentration of the components being detected in the gas, requiring continuous and dynamic evaluation to correct for any changes in the volume concentration analysis results.

[0058] e. Analytical result data needs to be continuously, persistently, and dynamically corrected and calibrated based on process changes, environmental changes, and changes in analytical concentration results;

[0059] Specifically, let's take the accuracy of gas flow data as an example. Flow measurement mainly uses differential pressure flowmeters (Pitot tube principle) or mass flowmeters. The main measurement problems are:

[0060] a. The flow measurement points selected in the process pipeline can still represent the actual flow of the pipeline when the flow changes;

[0061] b. Correction of the impact of data changes on actual testing due to process pipeline wear, increased attachments or modifications;

[0062] c. Correction of the effects of different installation locations, changes in pipe diameter before and after the installation point, changes in the direction of the pipeline, and device resistance on actual testing;

[0063] d. Correction of the impact of data changes on actual detection caused by blockage and loss of measurement hardware by particles, liquids, etc. in process pipelines

[0064] In summary, in practical applications, the main reasons for errors in the total gas emission results include at least but not limited to:

[0065] (1) The error in the measured volume concentration caused by the system calibration level, control accuracy error, acquisition and preprocessing control level, installation standard level, maintenance level and data processing capability can also be called volume concentration error.

[0066] (2) When converting the system volume concentration into mass concentration, the use of an incomplete calculation formula (for example, simply using the empirical formula for converting volume concentration to mass concentration under standard gas state) results in the inability to truly restore the mass concentration in the process pipeline through the sensor volume concentration, which can also be called mass concentration error.

[0067] (3) Evaluation and calculation of errors in volume concentration measurement caused by changes in the system's operating environment, such as changes in ambient temperature and humidity, which affect the sensor and system and cause changes in volume concentration measurement data and the impact on the conversion of actual process pipeline mass concentration, can also be called environmental impact error.

[0068] (4) The error between the process pipeline flow measurement data and the verification database established based on the design parameters can also be called flow error.

[0069] (5) Other influences that lead to data errors or errors, such as the execution standards of system automatic calibration, special climate influences, the operation and maintenance of process equipment, and the influence caused by changes in fuel or raw material quality, etc., can also be called other influence errors.

[0070] Due to the existence of the above-mentioned various errors, it is impossible to determine the accuracy of the data measured by the analysis system. Therefore, the present application provides a verification method, device, electronic device, computer-readable storage medium, and computer program product for a gas analysis system, aiming to solve the above-mentioned technical problems of the prior art.

[0071] The solution of the present application can improve the controllable accuracy and data quality of gas analysis data within the control boundary range (which can correspond to the linearity confidence interval mentioned above).

[0072] The method of this application continuously determines and verifies the quality of system data by establishing boundaries and control procedures. When the system's preset application parameters change, the data can be accurately corrected in a timely manner. Data that is determined to be invalid can be effectively processed in the next step, so that the system is always within the preset data control accuracy, or provide traceability for the next upgrade, transformation, and data evaluation. It mainly realizes the following functions:

[0073] a. Establish data control boundaries and control methods for the entire system process, implement a full-range dynamic data control library including sensors, system components, and process application status, and effectively improve the controllable accuracy of the single linear baseline calibration system data;

[0074] b. Achieve comprehensive traceability of system data, provide more parameters for the correction of key system data, and effectively trace the source of corrected or verified data;

[0075] c. System data jitter comes from changes in application parameters that exceed the preset values, and timely and continuous determination of data accuracy and validity;

[0076] d. If the system data is abnormal but within the system control boundary, timely translation or extrapolation of the data judgment formula can achieve timely and continuous data accuracy control;

[0077] e. If the system data is abnormal and exceeds the system control boundary, the system will be automatically calibrated or the boundary will be supplemented to establish a new calibration baseline and width in a timely manner to adapt to the wider control boundary and ensure continuous control of data accuracy;

[0078] f. If the system data exceeds the controllable range of the system, the invalid data shall be recorded in time for system alarm and system function upgrade or modification.

[0079] The following describes several exemplary embodiments to illustrate the technical solutions of the embodiments of the present application and the technical effects produced by the technical solutions of the present application. It should be noted that the following embodiments can refer to, draw on, or combine with each other, and the same terms, similar features, and similar implementation steps in different embodiments will not be repeated.

[0080] In an embodiment of the present application, a method for verifying a gas analysis system is provided, as shown in FIG1 , the method comprising:

[0081] S101, testing a gas analysis system using cylinder gases under multiple standard working conditions to determine multiple baseline linearity curves and corresponding first confidence intervals of the gas analysis system;

[0082] S102. Testing the gas analysis system using simulated operating condition data to determine second confidence intervals for the multiple reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system;

[0083] S103, testing the gas analysis system using ideal operating condition data of the object to be measured, and determining a third confidence interval of the multiple reference linearity curves;

[0084] S104, testing the gas analysis system using first actual operating condition data of the object to be measured, and determining fourth confidence intervals of the multiple reference linearity curves;

[0085] S105: Verify the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

[0086] It should be noted that in this embodiment, the objects to be measured are specific to different application fields or industries. For example, in the shipping industry, the objects to be measured are ship engines. In fixed process equipment, the objects to be measured may be coal-fired boilers in power plants, blast furnaces in steel mills, ventilation systems in coal mines, and so on.

[0087] Specifically, in this embodiment, the linearity confidence interval is determined by the gas analysis system under different volume concentrations, ambient temperatures and humidity, and by the process sample gas under different temperature, pressure, flow rate, and humidity conditions, most closely approximating the baseline linearity curve obtained using a reference gas source or other determinable parameters. These baseline linearity curves are then wrapped around the confidence interval width to form a linearity data channel of a certain width. Because the linearity data channels measured under various operating conditions are continuously accumulated and ultimately formed into a union, a control database is formed.

[0088] Optionally, S101 may include: establishing at least five sensor baseline linearity curves and confidence interval widths that are evenly distributed between the sensor zero point and the span point or close to the primary detection range. Drift curves within a time unit determined by sensor design parameters include at least daily, weekly, and monthly drift curves; and combining the baseline linearity curves with the time drift curves to form a data confidence interval width based on the linearity curvature.

[0089] For example, a sensor with a concentration of 0-20% vol should include at least five baseline linearity curves: 0-20%; 40%; 60%; 80%; and 100% of the range. This is combined with the sensor drift curve to form the data confidence interval width. For example, if the sensor drift is 1% FS / week, the confidence interval width of the baseline curve is ±1% / week.

[0090] Then establish at least 5 or more sensor baseline linearity curves and confidence interval widths (which may correspond to the first confidence interval) that are evenly distributed between the zero point and the maximum range point, including all components of the gas analysis system, or close to the main detection range.

[0091] For example, the following measurements can be performed to obtain a first confidence interval:

[0092] a. Use zero-point concentration standard gas to perform zero-point measurement of the system under test under standard working conditions (temperature, humidity, flow);

[0093] b. Repeat step a above using a standard gas with a gas concentration of 20% of the detection range of the system being tested;

[0094] c. Repeat step a above using a standard gas with a gas concentration of 40% of the detection range of the system being tested;

[0095] d. Repeat step a above using a standard gas with a gas concentration of 60% of the detection range of the system being tested;

[0096] e. Repeat step a above using a standard gas with a gas concentration of 80% of the detection range of the system being tested.

[0097] In an optional implementation, the first confidence interval may cover the sensor baseline linearity curve and the confidence interval width.

[0098] It should be noted that since the gas analysis system includes sampling components and sample preparation components, the linearity curve of the system is not absolutely covered relative to the linearity curve of the sensor, because the parts may cause positive or directional effects. Therefore, the baseline linearity curve and confidence interval width (corresponding to the first confidence interval) of the system can be determined separately.

[0099] It should be noted that concentration values ​​will change when the test cylinder gas is changed, requiring a new baseline to be established after the change. After each change in test concentration, the first instrument reading should be obtained after a period of time at least three times the response time of the system under test. At least three readings should be taken at each test concentration, with the interval between readings at least four times the response time. If the process gas is known or confirmed to contain interfering components before testing, these should be tested separately and recorded.

[0100] In this embodiment, S102 may include: using different simulated working conditions and configuring test gas concentrations according to preset parameters to test other analysis systems and obtain corresponding data.

[0101] The preset parameters during the test (including volume concentration, temperature, pressure, humidity, flow, etc.) should refer to the maximum parameter range during normal operation of the system as much as possible to ensure that the system test is effective in the largest possible range and covers most operating conditions.

[0102] For example, based on steps a to e above, the following measurement can be performed to obtain the second confidence interval:

[0103] f. Adjust the simulated operating temperature parameters to 80% of the standard operating conditions and repeat the test steps ae;

[0104] g. Adjust the simulated working temperature parameters to 120% of the standard working conditions and repeat the test steps ae;

[0105] h. Adjust the flow parameters of the simulated working condition to 80% of the standard working condition and repeat the test steps ae;

[0106] i. Adjust the flow parameters of the simulated working condition to 120% of the standard working condition and repeat the test steps ae;

[0107] j. Adjust the simulated humidity parameter to 80% of the standard working condition and repeat the test steps ae;

[0108] k. Adjust the simulated humidity parameter to 120% of the standard working condition and repeat the test steps a.e.;

[0109] l. If there are components in the actual use of the system that may interfere with the test results, configure them separately and repeat the ak test;

[0110] Based on the above test data, the baseline linearity curve and confidence interval width control database of the system in different concentration ranges under standard working conditions are obtained and established.

[0111] You can also continue to perform the following tests based on the actual process conditions:

[0112] 1. Perform the cross-variation test of the preset working condition fk variable and execute the ae steps;

[0113] 2. Adjust the ambient temperature to 0°C and repeat step a;

[0114] 3. Adjust the ambient temperature to 40°C and repeat step a;

[0115] 4. Adjust the ambient temperature to 50°C and repeat step a;

[0116] 5. Adjust the ambient temperature and humidity to 40°C and 30% RH, and repeat step a.

[0117] 6. Test according to the actual working location environmental parameters and repeat step a.

[0118] In the above steps, please note the following points:

[0119] 1) Zero-point concentration standard gas and standard test gases of different concentrations should have verifiable quantity and quality;

[0120] 2) The recording interval of system data should be clearly defined. Shorter data intervals and higher recording frequencies can help improve the data quality of the system.

[0121] 3) In the case of standard laboratory gas testing, the standard gases can be obtained from different gas cylinders or prepared from a single gas concentration using a calibrated dilution system;

[0122] 4) The ratio of concentrations in the simulation system needs to be known accurately so that linearity test failure does not occur;

[0123] 5) Each time the test conditions are changed and stabilized, record the first reading after a period of time at least equal to or greater than three times the system response time;

[0124] 6) When adjusting between steps, the data recorded in the first 15 minutes and the last 15 minutes are not included in the calculation as collected data, but can be used as a reference for experimental analysis data.

[0125] 7) For each test, at least three readings should be taken. The time interval between readings should be at least four times the response time;

[0126] 8) Negative values ​​in measurement tests should be recorded accordingly and should not be forced to zero.

[0127] In this embodiment, S103 may include: establishing a baseline linearity curve and confidence interval data set (which may correspond to a third confidence interval) including environmental parameter changes based on the process simulation baseline linearity curve and confidence interval width.

[0128] Specifically, a test bench or a simulation device (such as a pilot plant) similar to the actual process is used to simulate actual operating conditions according to preset ideal parameters. The system records and determines whether the system baseline linearity curve and confidence interval can fully cover the test data, environmental data, and fuel or raw material quality data under the test conditions of this phase. If the system records data beyond the set included in the original baseline linearity curve and confidence interval, a new database is formed that includes the test range of the marine engine test bench and the aforementioned range.

[0129] Specifically, in this embodiment, the following operations may be performed:

[0130] Use the system under test to obtain data collection under a preset power change curve;

[0131] Use the system under test to obtain data collection under a preset load change curve;

[0132] Use the system under test to obtain data collection under the preset power-load cross-change curve.

[0133] For example, the third confidence interval can be obtained by performing the following measurement:

[0134] Common power test: multiple measurements are performed with the power at 85% constant and the load varying from 10% to 100%.

[0135] Cross-change test: Multiple measurements are performed with the power variation range of 10-100% power and the load variation range of 10%-100%.

[0136] Specifically, in this embodiment, the measured components and measurement conditions of the fuel or raw materials that can be converted into exhaust gas include basic fuel testing conditions and fuel or raw material testing information. The basic fuel testing conditions include sampling environment conditions, sampling records, sample preparation records, testing environment records, testing time, testing batches, and other parameters related to the accuracy and representativeness of the testing information. The fuel or raw material testing information includes parameters related to combustion efficiency, such as moisture content, carbon content, lower heating value, net heating value, simulated distillation value, lower heating value, hydrocarbon composition and content, and impurity content.

[0137] Parameters related to fuel or raw material consumption include but are not limited to: total filling volume data, total consumption volume data, real-time consumption data, initial data, storage capacity and silo design data, pipeline design data, supply system design data, heating device or processing device design data, etc.

[0138] Parameters related to the process equipment include but are not limited to: gas system design drawings, equipment design parameters, design power parameters, design load parameters, segmented real-time power parameters, segmented real-time load parameters, process pressure data, process temperature parameters, supercharger parameters, maintenance records, etc.

[0139] Device operating parameters include, but are not limited to, usage time, maintenance time, maintenance records, modification records, modification drawings, etc. Environmental data include: ambient temperature, ambient humidity, altitude, climate data, etc. Metering equipment data includes: data collection equipment related to data verification, relevant parameters of metering equipment, maintenance records, and usage records.

[0140] In a possible implementation, S105 may include:

[0141] If the fourth confidence interval is completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, the gas analysis system passes the verification;

[0142] A union range of the first confidence interval, the second confidence interval, and the third confidence interval is determined as a linearity confidence interval.

[0143] In this embodiment, if the fourth confidence interval determined based on actual operating conditions is completely covered by the aggregate of the confidence intervals determined based on the standard gas, simulated operating conditions, and ideal operating conditions, then the data obtained by the gas analysis system is accurate. Furthermore, the aggregate of the confidence intervals determined based on the standard gas, simulated operating conditions, and ideal operating conditions is determined as the linearity confidence interval, which serves as a basis for determining the accuracy of analysis results when the gas analysis system is subsequently used for gas analysis.

[0144] In a possible implementation, S105 may further include:

[0145] If the fourth confidence interval is not completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, measuring the gas analysis system using the first operating condition data to determine a fifth confidence interval of the multiple baseline linearity curves;

[0146] The first operating condition data includes the simulated operating condition data and second actual operating condition data, and the second actual operating condition data is the first actual operating condition data corresponding to a portion of the fourth confidence interval that is not covered by the union range of the first confidence interval, the second confidence interval, and the third confidence interval;

[0147] A union of the first confidence interval, the second confidence interval, the third confidence interval, the fourth confidence interval, and the fifth confidence interval is determined as the linearity confidence interval.

[0148] Specifically, in this embodiment, if the fourth confidence interval determined based on the actual operating conditions is not completely covered by the aggregate interval of the confidence intervals determined based on the standard gas, simulated operating conditions, and ideal operating conditions, it is necessary to update the simulated operating condition data based on the actual operating condition data that exceeds the aggregate interval and re-determine a confidence interval (which may correspond to the fifth confidence interval mentioned above). At the same time, the aggregate interval of the confidence intervals determined based on the standard gas, simulated operating conditions, ideal operating conditions, and actual operating conditions and the newly determined confidence interval is determined as the linearity confidence interval, so as to determine the accuracy of the analysis results when the gas analysis system is subsequently used for gas analysis.

[0149] Specifically, in this embodiment, based on the data obtained during actual use, if there are parameters that exceed the existing control library, a simulation system can be used to reproduce the actual operating conditions, and the system can be tested and tested in the simulation system repeatedly to obtain new system data. The data under the actual operating conditions of the system can be reviewed and updated to review the established data control library.

[0150] For example, if some parameters in the actual working condition exceed the existing parameters in the data control library, the test process for updating them is as follows:

[0151] 1. Use air or zero-point concentration gas to simulate the actual ship working conditions (temperature, humidity, flow) of the system zero point measurement;

[0152] 2. Repeat the above steps using a gas concentration that is 60% of the actual operating range.

[0153] 3. Repeat the above steps using a gas concentration that is 80% of the actual operating range.

[0154] 4. Repeat the above steps using a gas concentration that is 100% of the actual operating range.

[0155] 5. Repeat the above steps using a gas concentration that is 120% of the actual operating range.

[0156] In the above steps, please note the following points:

[0157] 1) Zero-point concentration standard gas and standard test gases of different concentrations should have verifiable quantity and quality;

[0158] 2) The recording interval of system data should be clearly defined. Shorter data intervals and higher recording frequencies can help improve the data quality of the system.

[0159] 3) Standard gases can be obtained from different gas cylinders or prepared from a single gas concentration using a calibrated dilution system;

[0160] 4) The concentration ratio in the simulation system needs to be accurately and controllably known;

[0161] 5) Each time the test conditions are changed and stabilized, record the first reading after at least three times the system response time;

[0162] 6) The data recorded before and 15 minutes after the start of the test will not be counted as collected data;

[0163] 7) Negative values ​​in measurement tests should be recorded accordingly and should not be forced to zero;

[0164] 8) When the calibration standard gas is replaced, the concentration value will change, and the impact on the baseline linearity should be checked.

[0165] In one possible implementation, the method further includes:

[0166] Measuring third actual working condition data of the object to be measured using the gas analysis system to obtain measurement data;

[0167] determining a confidence interval from the linearity confidence intervals based on the measurement data;

[0168] Invalid data and valid data in the measurement data are determined based on the determined confidence interval.

[0169] In one possible implementation, determining invalid data and valid data in the measurement data based on the determined confidence interval includes:

[0170] Determining first data in the measurement data that does not exceed the determined confidence interval as the valid data;

[0171] Second data in the measurement data that exceeds the determined confidence interval within a first moment or a first time period is determined as the invalid data.

[0172] Specifically, in this embodiment, when the measured data is within the range of the control database, it can be determined as valid data. However, valid data does not mean completely correct data. The data needs to be corrected or calibrated to make it usable for output and further application.

[0173] In this embodiment, all raw data should be recorded, including the current signal (mA) readings of gas sensors, system temperature, pressure, flow and other related sensors. Regardless of whether the system has been calibrated, only positive values ​​cannot be recorded without recording negative values, or negative values ​​cannot be forced to be recorded as zero.

[0174] The time interval between each reading and recording is the recording frequency of the system data. A faster recording frequency can better reflect the changes in the system analysis gas, but a faster recording frequency may also cause the system data to jump or be unstable. Therefore, this method uses a dual-frequency recording method for recording frequency. One set of high-speed frequencies is determined based on the time when the measured gas may change, and the other set of stable frequencies is determined based on the system stabilization time and response time. Among them, the time when the first reading appears after the gas to be measured is introduced into the gas analysis system is the response time of the system. The time from the introduction of the gas to be measured until the reading stabilizes at the actual gas volume concentration is the stabilization time of the system.

[0175] For example, high-speed frequency data records sensor readings in the system in seconds or milliseconds, while the stable frequency is determined as 15 seconds or 1 minute based on the system's stabilization time or response time. Typically, the stable frequency is three times the system's response time or one time the stabilization time.

[0176] Optionally, the second data may also be determined as invalid data if at least one of the following conditions is met:

[0177] a first preset value exceeding a measurement range of a sensor in the gas analysis system;

[0178] The detection time is shorter than the stabilization time of the sensor;

[0179] The detection time is less than the response time of the sensor.

[0180] Specifically, in this embodiment, when switching between detection modes, the detection time must exceed the stabilization time. For example, when switching from slave unit 1 to slave unit 2, the instrument needs sufficient time to stabilize; data before reaching a stable state is invalid. This also applies to single operating modes, as the stabilization time is typically greater than the response time. Therefore, data where the detection time is less than the response time is invalid.

[0181] In this embodiment, the first duration can be one data acquisition frequency, or four times or more of the stable frequency. That is, data that exceeds the width of the linearity confidence interval within one data acquisition frequency is invalid. Alternatively, if the slope of the curve formed by data that continuously exceeds four times the stable frequency has deviated from all baseline linearity curve slopes in the system control database and exceeds the maximum allowable confidence interval width, the data is invalid.

[0182] In some embodiments, data is recorded as invalid data when the following conditions occur:

[0183] 1. The recorded data exceeds the sensor measurement range by more than 25% (which may correspond to the first preset value above); for example, if the sensor signal is 4-20mA, but the recorded signal is lower than 3mA or higher than 25mA, the data recorded is invalid.

[0184] 2. When a single sensor needs to switch and detect more than one group of samples, the data is less than the sensor stabilization time.

[0185] 3. When a single sensor detects a single sample, the data is less than the sensor response time.

[0186] 4. Abnormal jitter data of sensor data caused by uncertain reasons other than process adjustment (such as power supply fluctuations) that exceeds the confidence interval width within one data frequency.

[0187] 5. The slope of the curve formed by continuously recording data for more than 4 times the stable frequency has deviated from the slope of all benchmark linearity curves in the system control database, and the data has exceeded the maximum allowable confidence interval width, which should be judged as invalid.

[0188] 6. If any item in the actual measurement data exceeds the data boundary value recorded in the control database and the equipment allowable parameter boundary value, all test data will be judged as invalid.

[0189] In a possible implementation, determining a confidence interval from the linearity confidence interval includes: determining, based on a measurement parameter in the measurement data, a confidence interval corresponding to the measurement parameter from the linearity confidence interval.

[0190] Specifically, in this embodiment, a linearity curve of 0-20% or 0-40% of the established range in the system range 0-10% vol can be obtained. It is assumed that the confidence interval of the 0-20% curve is judged to be a 1.5-2.0% data confidence interval based on other parameters, and the data confidence interval of the 0-40% curve is 1.6-1.9%.

[0191] When the sensor volume concentration readings fluctuate between 1.8-2.1% vol, the 0-20% range curve should generally be selected to ensure a linearity curve that covers the measured data as much as possible. However, when the concentration exceeds 2% vol, the 0-20% range curve will not be fully satisfied. However, the 0-40% range curve has less controllable linearity in actual readings than the 0-20% range curve. Therefore, for readings between 1.9-2%, the 0-20% range curve is used to determine the confidence interval, while for readings above 2.1%, the 0-40% range curve is used to determine the confidence interval.

[0192] Another scenario for the same parameters might be: at a concentration of 1.8% vol, the confidence interval for the 0-20% curve is 1.9%, while the confidence interval for the 0-40% curve is 1.7%. In this case, the confidence interval for the 0-40% curve should be selected. In actual use, the decision on which curve to use to determine the confidence interval will be based on comprehensive data from other sensors, ensuring the most accurate confidence interval possible.

[0193] It should be noted that due to its optical characteristics, the sensor is not completely linear. The best linearity of the actual sensor is usually between 30-70% of the measuring range. By establishing multiple linearity curves, multiple more densely located and more precise control lines between the measuring ranges can be obtained.

[0194] In one possible implementation, the following is also included:

[0195] Periodically updating the linearity confidence interval; or,

[0196] The linearity confidence interval is updated in any of the following cases:

[0197] Adjustment of process parameters of the gas analysis system;

[0198] Hardware replacement of the gas analysis system.

[0199] In actual use, system data may exceed the range of the data control library. This is usually caused by factors such as process adjustments and system updates. In this case, additional testing is required to update the system data control library. The data before the data control library is updated should be recorded as invalid data. After the update, the invalid data can be reviewed and verified. If it meets the requirements, it can be modified and recorded as valid data.

[0200] System hardware changes, such as filter element replacements, pipe length changes, and major component replacements, can impact the system, primarily affecting the temperature, pressure, and flow rate of incoming sensors. The baseline linearity curve for the existing data control library is determined based on the initial system setup. Therefore, after a hardware replacement, the system's baseline linearity should be rechecked to determine the impact of component replacement on the data control library and update the library accordingly.

[0201] In this embodiment, the data control library can also be updated periodically to adapt to actual measurement needs. The period can be set according to the actual needs of the user and is not limited in this embodiment of the application.

[0202] The linearity confidence intervals in the embodiments of this application are derived from a control database formed by continuously accumulating data channels measured under various operating conditions. Measured data falling within the control database range is considered valid data. Valid data is data that can be used for further correction or control of data accuracy and falls within the confidence interval. Through correction or further calibration and regression, the data can be made usable for output and further application.

[0203] Specifically, in this embodiment, the system data correction is applicable to partially controllable errors, and the correction method is selected according to the different error contents. Specifically:

[0204] 1. Correction of volume concentration error

[0205] The system uses its own sensor data to calculate the difference between the gas sample state (temperature, pressure, flow rate and humidity) in the process pipeline and the gas sample state in front of the gas sensor. Based on the data difference, perform the following steps to correct the data:

[0206] The change in gas dew point generated during the gas collection and processing is calculated.

[0207] The total amount of condensate is calculated based on the change in gas dew point.

[0208] Based on the total amount of condensate and gas solubility, the gas dissolution loss and the error impact on volume concentration are calculated.

[0209] At the same time, the mechanical drift and optical drift errors of the volume concentration parameters that may occur as the system is used over time should be corrected based on the relevant parameters of the measuring equipment, maintenance records, usage records, etc.

[0210] 2. Correction of mass concentration error

[0211] The data obtained by the system is the volume concentration measured by the sensor. When converting the mass concentration, it should be converted to standard state or conditions, or to process state conditions.

[0212] For example: given under standard conditions (0℃, 1013hPa, dry flue gas with an oxygen content of 11%).

[0213] Where t is the temperature in degrees Celsius; p is the difference between the static pressure of the sample gas and the standard pressure; and h is the absolute water vapor content (by volume).

[0214] 3. Correction of environmental impact errors

[0215] The system is installed in the use environment, and the following data are corrected using the ambient temperature, ambient humidity, etc.:

[0216] Ambient temperature corrects the temperature of the gas before it enters the sensor.

[0217] Ambient humidity provides comparative correction for temperature control during sample collection and preparation.

[0218] 4. Correction of flow error

[0219] For example, CFD simulation technology is used to combine turbine exhaust system design drawings, measured data on the turbine exhaust system structure, turbine design data, turbine design power data, turbine design load data, turbine turbocharger data, and turbine maintenance records to establish a turbine exhaust, power, and load model. This model is then used to form a correction database and correction function. This correction function is then used to correct the measured gas emission flow rate data.

[0220] The effect of ship sway caused by climate data is used to correct data errors caused by sensor displacement.

[0221] CFD simulation technology can also be used to create aerodynamic simulation diagrams for power boilers and coal mines. Using the power boiler's output parameters and the design parameters of the mine's ventilation system's fans, combined with CFD and operational data, an aerodynamic model is developed to match actual process pipeline flow variations under varying operating conditions, boiler output, and mine fan speeds. Regression comparisons are performed between actual test data and CFD simulation data to determine errors and implement continuous, dynamic corrections.

[0222] It should be noted that, in this embodiment, data calibration is applied to the process of establishing the system control database to form a calibration function, and is also applied to calibrate data obtained in the actual measurement process after the control database is established.

[0223] When the system establishes a calibration function, the calibration function is valid only when the data is within the valid calibration range. The valid calibration range refers to the width of the confidence interval generated when the measured value lies within the calibration system's standard conditions, from zero to the maximum value. For data outside the valid calibration range, such as deviation from the baseline linearity curve, a wider range of tests can be used to extrapolate the calibration curve or establish a new calibration curve and function.

[0224] After the calibration function is established, the variability test of the data is performed to ensure that the calibration function is continuously effective. The following control functions are achieved through continuous calibration of the data:

[0225] First, the data at the intersection of the two baseline linearity curves:

[0226] The baseline linearity ultimately used for data regression is determined through the data's operating trend, ensuring that the data is always within a higher controllable accuracy range.

[0227] For example, the benchmark linearity curve in the system data control library includes a 0-20% range and a 0-40% range. The actual measured data is 18% to 22% and shows an upward trend. At this time, the slope of the change curve can be compared with the above two benchmark linearities to determine the one with the smaller slope difference as the benchmark linearity for data comparison, control, and calibration.

[0228] Second, data that fluctuates and temporarily exceeds the scope of the data control library:

[0229] For fluctuating data that exceeds one data recording frequency but is less than the system response time range, the baseline linearity and confidence interval width around the area where the data is located in the control database can be used to judge the data to confirm whether the data is normal. If it is abnormal, it will be recorded as invalid data; if it is normal, the data in the corresponding process will be judged again to determine whether the data is normal. If it is abnormal, it will be recorded as invalid data; if the process data is judged to be normal, it is data jitter caused by uncertainty, and it will be judged and recorded as invalid jitter data; invalid data and invalid jitter data play a very important role in the status of system connection operation and the upgrade of system functions.

[0230] Third, for the continuous occurrence of data anomalies that exceed the scope of the data control library:

[0231] When this happens in actual use, the data cannot be calibrated directly. Instead, the data must be judged first.

[0232] It usually presents a regular trend or an irregular trend. The calibration function of the data control library can be used to judge the data. If it presents a regular upward or downward trend, the surrounding benchmark linearity and confidence interval should be further checked to see if they are available. If it presents an upward or downward trend and a translation relationship with the benchmark linearity, the system automatic calibration function can be started, and the system gas calibration procedure can be executed using a reference gas with a close zero and concentration, so as to establish a new calibration curve and function extrapolation or expand the control range boundary of the control database (usually this situation is caused by a large drift of the instrument, and the data can usually be returned to the valid range by calibrating the zero point and range). If calibration is impossible or there is still no matching characteristic with the benchmark linearity after calibration, it can be determined as a system failure and recorded as invalid data. If the data presents an irregular trend, it should be determined as invalid data, and the relevant data matching it should be recorded for use in later data analysis and fault analysis.

[0233] In the above embodiment, the system data is calibrated using, on the one hand, the baseline linearity and width established based on system testing and experimentation. On the other hand, a wider range of data calibration control libraries can be established by introducing more data and models. Depending on the content of the calibration data required, the data range used for calibration varies, as follows:

[0234] First, the calibration data range for the system volume concentration data

[0235] 1. Check the baseline linearity curve and confidence interval of the sensor and gas analysis system to see if the volume concentration parameters obtained by measurement are consistent.

[0236] 2. Drift parameters of system equipment: used to shift the baseline linearity when system data shifts based on usage time.

[0237] 3. Detection information related to the conversion of fuel or raw materials into exhaust gas is used to calculate the maximum limit data of possible volume concentration after combustion.

[0238] 4. Maximum volume concentration limit data of process equipment design parameters under different operating conditions.

[0239] 5. System maintenance records are used to determine the working status of the gas analysis system and sensors during system automatic calibration or calibration, and further determine the curve used.

[0240] 6. The device usage time and maintenance records are used to determine the linearity of the increase in emission volume concentration caused by the passage of usage time.

[0241] The above process can establish the effective calibration range of gas volume concentration.

[0242] Second, the calibration data range for the system mass concentration data

[0243] Fuel or raw material test data can be used to directly measure and calculate the mass concentration of the target gas after use. This data can be used as a reference for the mass concentration of the current batch of fuel. Due to fuel inconsistencies and test errors, this data is generally used to establish a calibration curve rather than directly verify the mass concentration.

[0244] Third, the calibration data range for system flow data

[0245] Exhaust calibration curves and functions are developed using device power data, load data, and operational temperature, pressure, and flow data. In actual operating conditions, a CFD model of the device's detection locations is established, and a flow data calibration model is constructed using known data from the model input points and the resulting data relationships. Because flow data has many influencing parameters, the data control library here has a large confidence interval width. This confidence interval width can be gradually narrowed as data accumulates with continued system use. The initial data control library is primarily used to determine whether the data is within a valid confidence interval.

[0246] Fourth, data used to calibrate the system's total emissions data

[0247] The fuel consumption can be obtained by obtaining relatively accurate data or establishing a calibration function curve through the total fuel filling data, total fuel consumption data, real-time fuel consumption data, initial fuel data, fuel tank design data, fuel pipeline design data, fuel supply system design data, fuel heating device or processing device design data, etc.

[0248] The fuel carbon conversion factor has a large uncertainty and is significantly affected by the fuel quality. Therefore, the data from the system emission equivalent calibration is mostly used to determine the maximum limit of the system total data.

[0249] The present application provides a verification device for a gas analysis system. As shown in FIG2 , the verification device 20 for a gas analysis system may include a measurement module 201 and a processing module 202 . The measurement module 201 is configured to perform the following operations:

[0250] The gas analysis system is tested using cylinder gases under multiple standard working conditions to determine multiple baseline linearity curves and corresponding first confidence intervals of the gas analysis system;

[0251] Testing the gas analysis system using simulated operating condition data to determine second confidence intervals for the multiple reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system;

[0252] Testing the gas analysis system using ideal operating condition data of the object to be measured to determine a third confidence interval of the plurality of baseline linearity curves;

[0253] Testing the gas analysis system using first actual operating condition data of the object to be measured to determine fourth confidence intervals of the multiple reference linearity curves;

[0254] The processing module 202 is configured to verify the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

[0255] Furthermore, the processing module 202 is specifically configured to:

[0256] If the fourth confidence interval is completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, the gas analysis system passes the verification;

[0257] A union range of the first confidence interval, the second confidence interval, and the third confidence interval is determined as a linearity confidence interval.

[0258] In another possible implementation, the measuring module 201 is further configured to:

[0259] If the fourth confidence interval is not completely within the union of the first confidence interval, the second confidence interval, and the third confidence interval, measuring the gas analysis system using the first operating condition data to determine a fifth confidence interval of the multiple baseline linearity curves;

[0260] The first operating condition data includes the simulated operating condition data and second actual operating condition data, and the second actual operating condition data is the first actual operating condition data corresponding to a portion of the fourth confidence interval that is not covered by the union range of the first confidence interval, the second confidence interval, and the third confidence interval;

[0261] The processing module 202 is specifically configured to determine the union of the first confidence interval, the second confidence interval, the third confidence interval, the fourth confidence interval, and the fifth confidence interval as the linearity confidence interval.

[0262] In another possible implementation, the measurement module 201 is further configured to: measure third actual operating condition data of the object to be measured using the gas analysis system to obtain measurement data;

[0263] The processing module 202 is further configured to: determine a confidence interval from the linearity confidence interval according to the measurement data; and determine invalid data and valid data in the measurement data based on the determined confidence interval.

[0264] In another possible implementation, when the processing module 202 determines invalid data and valid data in the measurement data based on a determined confidence interval, it is specifically used to: determine the first data in the measurement data that does not exceed the determined confidence interval as the valid data; and determine the second data in the measurement data that exceeds the determined confidence interval at a first moment or within a first time period as the invalid data.

[0265] In yet another possible implementation, when determining a confidence interval from the linearity confidence interval, the processing module 202 is specifically configured to: determine, according to a measurement parameter in the measurement data, a confidence interval corresponding to the measurement parameter from the linearity confidence interval.

[0266] In yet another possible implementation, the processing module 202 is further configured to:

[0267] Periodically updating the linearity confidence interval; or,

[0268] The linearity confidence interval is updated in any of the following cases:

[0269] The measured data contains data that exceeds the linearity confidence interval;

[0270] Adjustment of process parameters of the gas analysis system;

[0271] Hardware replacement of the gas analysis system.

[0272] The device of the embodiment of the present application can execute the method provided by the embodiment of the present application, and its implementation principle is similar. The actions performed by each module in the device of each embodiment of the present application correspond to the steps in the method of each embodiment of the present application. For the detailed functional description of each module of the device, please refer to the description in the corresponding method shown in the previous text, and will not be repeated here.

[0273] In an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory. The processor executes the above-mentioned computer program to implement the steps of a verification method for a gas analysis system. Compared with the related art, it can be achieved that: the verification method for a gas analysis system provided can realize the determination of the validity of data measured by the gas analysis system.

[0274] In an optional embodiment, an electronic device is provided, as shown in FIG3 . The electronic device 30 shown in FIG3 includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 30 may further include a transceiver 304, which may be used for data exchange between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0275] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0276] Bus 302 may include a path for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, for example. Bus 302 may be divided into an address bus, a data bus, a control bus, and so on. For ease of illustration, FIG3 shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0277] The memory 303 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium that can be used to carry or store computer programs and can be read by a computer, without limitation here.

[0278] The memory 303 is used to store the computer program for executing the embodiment of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the computer program stored in the memory 303 to implement the steps shown in the above method embodiment.

[0279] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps and corresponding contents of the aforementioned method embodiment can be implemented.

[0280] An embodiment of the present application also provides a computer program product, including a computer program, which can implement the steps and corresponding contents of the aforementioned method embodiment when executed by a processor.

[0281] The terms "first," "second," "third," "fourth," "1," "2," and the like (if any) in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or sequential sequence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the application described herein can be implemented in an order other than that shown or described in the drawings.

[0282] It should be understood that, although each operation step is indicated by arrows in the flowchart of the embodiment of the present application, the order of implementation of these steps is not limited to the order indicated by the arrows. Unless otherwise clearly stated herein, in some implementation scenarios of the embodiment of the present application, the implementation steps in each flowchart can be performed in other orders according to demand. In addition, some or all of the steps in each flowchart can include multiple sub-steps or multiple stages based on actual implementation scenarios. Some or all of these sub-steps or stages can be executed at the same time, and each sub-step or stage in these sub-steps or stages can also be executed at different times respectively. Under different scenarios at the execution time, the execution order of these sub-steps or stages can be flexibly configured according to demand, and the embodiment of the present application does not limit this.

[0283] The above description is only an optional implementation method for some implementation scenarios of this application. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical concept of the solution of this application, the use of other similar implementation methods based on the technical ideas of this application also falls within the protection scope of the embodiments of this application.

Claims

1. A verification method for a gas analysis system, characterized in that: include: Using cylinder gases under multiple standard working conditions to test the gas analysis system respectively, and determining multiple reference linearity curves and corresponding first confidence intervals of the gas analysis system; Testing the gas analysis system using simulated operating condition data to determine second confidence intervals of the plurality of reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system; Testing the gas analysis system using ideal operating condition data of the object to be measured to determine a third confidence interval of the plurality of reference linearity curves; Testing the gas analysis system using first actual operating condition data of the object to be measured to determine fourth confidence intervals of the plurality of reference linearity curves; The gas analysis system is validated based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

2. The method according to claim 1, characterized in that The verifying the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval and the fourth confidence interval includes: If the fourth confidence interval is completely within the union of the first confidence interval, the second confidence interval and the third confidence interval, the gas analysis system passes the verification; A union range of the first confidence interval, the second confidence interval, and the third confidence interval is determined as a linearity confidence interval.

3. The method according to claim 2, characterized in that The verifying the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval and the fourth confidence interval further includes: If the fourth confidence interval is not completely within the union of the first confidence interval, the second confidence interval and the third confidence interval, measuring the gas analysis system using the first operating condition data to determine a fifth confidence interval of the plurality of reference linearity curves; The first operating condition data includes the simulated operating condition data and the second actual operating condition data, and the second actual operating condition data is the first actual operating condition data corresponding to the portion of the fourth confidence interval that is not covered by the union range of the first confidence interval, the second confidence interval and the third confidence interval; A union of the first confidence interval, the second confidence interval, the third confidence interval, the fourth confidence interval, and the fifth confidence interval is determined as the linearity confidence interval.

4. The method according to claim 2 or 3, characterized in that: The method further comprises: Using the gas analysis system to measure third actual working condition data of the object to be measured, to obtain measurement data; Determining a confidence interval from the linearity confidence intervals based on the measurement data; Invalid data and valid data in the measurement data are determined based on the determined confidence interval.

5. The method according to claim 4, characterized in that The determining, based on the determined confidence interval, invalid data and valid data in the measurement data comprises: Determine the first data in the measurement data that does not exceed the determined confidence interval as the valid data; Second data in the measurement data that exceeds the determined confidence interval within a first time point or a first time period is determined as the invalid data.

6. The method according to claim 4, characterized in that Determine a confidence interval from the linearity confidence interval, comprising: According to the measurement parameter in the measurement data, a confidence interval corresponding to the measurement parameter is determined from the linearity confidence interval.

7. The method according to claim 4, characterized in that Also includes: Periodically updating the linearity confidence interval; or, The linearity confidence interval is updated in any of the following cases: Adjustment of process parameters of the gas analysis system; Hardware replacement of the gas analysis system.

8. A verification device for a gas analysis system, characterized in that: include: Measurement modules that perform the following operations: Using cylinder gases under multiple standard working conditions to test the gas analysis system respectively, and determining multiple reference linearity curves and corresponding first confidence intervals of the gas analysis system; Testing the gas analysis system using simulated operating condition data to determine second confidence intervals of the plurality of reference linearity curves, wherein the simulated operating condition data is obtained by simulating the actual operating condition of the object to be measured by the simulation system; Testing the gas analysis system using ideal operating condition data of the object to be measured to determine a third confidence interval of the plurality of reference linearity curves; Testing the gas analysis system using first actual operating condition data of the object to be measured to determine fourth confidence intervals of the plurality of reference linearity curves; A processing module is configured to verify the gas analysis system based on the first confidence interval, the second confidence interval, the third confidence interval, and the fourth confidence interval.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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