A data quality control method, system, device and medium for environmental monitoring

Abstract

The present invention provides a data quality control method, system, device and medium for environmental monitoring. The method includes: obtaining a target work order, and determining the monitoring data and instrument status parameters of the target device during the maintenance period according to the target work order; determining a calibration time node when the instrument status parameter changes during the maintenance period, and tracing back a specified time forward from the calibration time node to determine a traced time node; determining a response value when the target device performs an inspection operation and / or a calibration operation according to a plurality of monitoring data between the traced time node and the calibration time node, and returning the response value to the target work order for quality control judgment and outputting a quality control result. The present invention can perform continuous and periodic calculation and analysis on the obtained monitoring data, ensure the stability and accuracy of the obtained response value, avoid data errors caused by falsifying quality control work orders from affecting the quality control result, and thus improve the quality of monitoring data.

Description

Technical Field

[0001] The present invention relates to the field of intelligent work orders for environmental monitoring, and particularly to a data quality control method, system, device and medium for environmental monitoring. Background Art

[0002] In today's era of globalization, environmental protection has become an urgent task widely recognized by the international community, and its strategic position has become increasingly prominent. As a key link in evaluating environmental quality, tracking pollution sources and formulating environmental protection policies, environmental monitoring is of great importance. However, with the rapid expansion of environmental monitoring stations, how to implement an efficient and comprehensive supervision strategy for the operation and maintenance work of monitoring stations has become an increasingly prominent problem.

[0003] At present, the process management of the electronic work order system has improved the supervision to a certain extent and ensured the accuracy of data. However, in some cases, the operation and maintenance team may, for improper motives, affect the authenticity of the quality control work order by calibrating multiple times and selecting lower data, which seriously weakens the public's trust in environmental monitoring data and damages the fairness of environmental monitoring; when the quality control work order is forged, the authenticity and accuracy of environmental monitoring data cannot be ensured. Summary of the Invention

[0004] Embodiments of the present invention provide a data quality control method, system, device and medium for environmental monitoring to solve the problems existing in the related technologies. The technical solutions are as follows:

[0005] In a first aspect, embodiments of the present invention provide a data quality control method for environmental monitoring, including:

[0006] Obtain a target work order, and determine the monitoring data and instrument status parameters of the target device during the maintenance period according to the target work order;

[0007] When the instrument status parameter changes during the maintenance period, determine the calibration time node, and trace back a specified time from the calibration time node as the starting point to determine the traceback time node;

[0008] According to multiple monitoring data between the traceback time node and the calibration time node, determine the response value when the target device performs an inspection operation and / or a calibration operation, and return the response value to the target work order for quality control judgment and output a quality control result.

[0009] In an implementation manner, it further includes:

[0010] Obtain a historical work order, screen out the most recent work order from the historical work orders, and determine the first background value recorded at the quality control end time of the most recent work order and the first span coefficient recorded at the quality control end time of the most recent work order;

[0011] Determine the second background value of the maintenance start time and the second span coefficient of the maintenance start time according to the instrument status parameters within the maintenance period;

[0012] Mark the target work order as a normal work order when the first background value is the same as the second background value, and the first span coefficient and the second span coefficient are the same;

[0013] Mark the target work order as a suspected forged work order when the first background value is different from the second background value, and / or the first span coefficient and the second span coefficient are different.

[0014] In one implementation, it further includes:

[0015] Determine the third background value of the maintenance end time and the third span coefficient of the maintenance end time according to the instrument status parameters within the maintenance period;

[0016] When the second background value is the same as the third background value, and the second span coefficient and the third span coefficient are the same, determine the work order type of the target work order for performing inspection operations;

[0017] When the second background value is different from the third background value, and / or the second span coefficient and the third span coefficient are different, determine the work order type of the target work order that includes inspection operations and calibration operations.

[0018] In one implementation, it further includes:

[0019] When the target work order is of the work order type that only performs inspection operations, mark the maintenance end time as the first calibration time node, and trace back a specified time forward from the first calibration time node to determine the first trace time node;

[0020] Obtain multiple first monitoring data between the first calibration time node and the first trace time node, and determine whether the set stability condition is satisfied according to the standard deviation of each first monitoring data;

[0021] When the stability condition is satisfied, calculate the first average value according to each first monitoring data, and return the first average value as the response value of the zero / span inspection to the target work order for quality control judgment.

[0022] In one implementation, it further includes:

[0023] When the target work order is determined to be of the work order type that includes inspection operations and calibration operations, determine the change moment of the instrument status parameters within the maintenance period as the second calibration time node, and trace back a specified time forward from the second calibration time node to determine the second trace time node;

[0024] Obtain multiple second monitoring data between the second calibration time node and the second traceability time node, and determine whether the stability condition is met according to the standard deviation of each second monitoring data;

[0025] When the stability condition is met, calculate the second average value according to each second monitoring data, and return the second average value as the response value of the inspection to the target work order for quality control judgment;

[0026] And use the instrument response value generated at the maintenance end time of the target device during the maintenance period as the calibration response value and return it to the target work order for quality control judgment.

[0027] In one implementation, it further includes:

[0028] When the stability condition is not met, re-determine the previous time node of the first calibration time node or the second calibration time node as the new calibration time node, and trace back a specified time according to the new calibration time node to determine the new traceability time node;

[0029] Re-judge whether the stability condition is met according to the new monitoring data between the new calibration time node and the new traceability time node, and count the number of times when the stability condition is not met in real time. When the number of times reaches the set value, directly output the quality control failure result.

[0030] In one implementation, the method for quality control judgment includes:

[0031] Calculate the drift value according to the response value;

[0032] Output the quality control failure result when the drift value is higher than the preset control line.

[0033] In a second aspect, an embodiment of the present invention provides an environmental monitoring data quality control system that executes the environmental monitoring data quality control method as described above.

[0034] In a third aspect, an embodiment of the present invention provides an electronic device, which includes: a memory and a processor. Among them, the memory and the processor communicate with each other through an internal connection path. The memory is used to store instructions, and the processor is used to execute the instructions stored in the memory. When the processor executes the instructions stored in the memory, the processor executes the method in any one of the above aspects.

[0035] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium that stores a computer program. When the computer program runs on a computer, the method in any one of the above aspects is executed.

[0036] The advantages or beneficial effects in the above technical solutions at least include:

[0037] The present invention determines the calibration time node according to the change of the instrument status parameters, traces back a specified time forward from the calibration time node to determine the traced time node, determines the response value when the target device performs the inspection operation and / or calibration operation according to a plurality of monitoring data between the traced time node and the calibration time node, and performs quality control judgment according to the response value and outputs the quality control result; which is equivalent to continuously and periodically calculating and analyzing the obtained monitoring data, ensuring the stability and accuracy of the obtained response value, and can avoid the data error caused by the forgery of the quality control work order from affecting the quality control result, thereby improving the quality of the monitoring data.

[0038] The above summary is only for the purpose of the specification and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In the drawings, unless otherwise specified, the same reference numerals throughout the several views denote the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in accordance with the present invention and should not be regarded as limiting the scope of the present invention.

[0040] Figure 1 is a schematic flowchart of the data quality control method for environmental monitoring of the present invention;

[0041] Figure 2 is a schematic flowchart of the first logical judgment of the present invention;

[0042] Figure 3 is a schematic flowchart of the second logical judgment of the present invention;

[0043] Figure 4 is a schematic flowchart of the quality control judgment of the present invention;

[0044] Figure 5 is a schematic diagram of the five-minute sliding cycle number limit of the present invention;

[0045] Figure 6 is a schematic flowchart of the data quality control method taking SO 2 as an example;

[0046] Figure 7 is a schematic diagram of the modules of the data quality control system for environmental monitoring of the present invention;

[0047] Figure 8 is a block diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In the following text, only some exemplary embodiments are briefly described. As those skilled in the art can recognize, the described embodiments can be modified in various different ways without departing from the spirit or scope of the present invention. Therefore, the accompanying drawings and the description are considered to be exemplary in nature rather than restrictive.

[0049] In today's era of globalization, environmental protection has become an urgent task widely recognized by the international community, and its strategic position has become increasingly prominent. As a key link in assessing environmental quality, tracking pollution sources, and formulating environmental protection policies, environmental monitoring is of great importance. However, with the rapid expansion of environmental monitoring stations, how to implement an efficient and comprehensive supervision strategy for the operation and maintenance work of monitoring stations has become an increasingly prominent problem. At present, the process management of the electronic work order system has improved the supervision to a certain extent and ensured the accuracy of data. However, in some cases, the operation and maintenance team may, for improper motives, affect the authenticity of quality control work orders by calibrating multiple times and selecting lower data, which seriously weakens the public's trust in environmental monitoring data and damages the fairness of environmental monitoring.

[0050] To solve the above problems, this embodiment proposes a data quality control method for environmental monitoring, which can effectively supervise the authenticity of quality control work orders of national environmental monitoring stations and ensure the authenticity and accuracy of data.

[0051] As Figure 1 shown, a data quality control method for environmental monitoring in this embodiment includes the following steps:

[0052] Step S100: Obtain a target work order, and determine the monitoring data and instrument status parameters of the target device during the maintenance period according to the target work order.

[0053] The target work order records the target device information, maintenance period, and also records a large amount of quality control basic information, including information such as the site, monitoring item, and quality control type. The operation and maintenance personnel can also fill in the maintenance period in the target work order according to the actual situation, indicating that the monitoring items specified in the target work order are to be executed during the specified maintenance period.

[0054] It should be noted that in this embodiment, the inspection operations and / or calibration operations to be performed are collectively referred to as "maintenance", and the "maintenance period" is a time period composed of two time nodes, namely the start time of maintenance and the end time of maintenance. The start time of maintenance refers to the start time of the inspection and / or calibration operation, and the end time of maintenance refers to the end time of the inspection and / or calibration operation.

[0055] Meanwhile, determine the sites and monitoring items to be monitored according to the target work order. At the same time, obtain the previous work order corresponding to the same site and the same monitoring item. The previous work order, as a historical work order, has completed the quality control work within its set quality control time period, and records the instrument status parameters from the start time to the end time of quality control. The instrument status parameters include the background value and the span coefficient.

[0056] The background value, also known as the intercept, refers to the signal value displayed by the instrument in the absence of the target substance. During zero calibration, the background value is used to determine the baseline level of the instrument when there is no substance to be measured. Ideally, this value should be close to zero, but in practice, it may be affected by instrument noise, environmental factors, etc.

[0057] The span coefficient, also known as the slope value, refers to the ratio of the change in the instrument response signal to the concentration of the standard substance when a standard substance (calibration gas) with a known concentration passes through the instrument. During span calibration, the span coefficient is used to determine the response sensitivity of the instrument to substances with known concentrations. This parameter helps ensure that the instrument can provide accurate measurement results when measuring substances to be measured at different concentrations.

[0058] It should be noted that in order to distinguish the instrument status parameters at different times in this embodiment, the instrument status parameters at the end time of quality control of the previous historical work order are named the first background value and the first span coefficient; while the instrument status parameters at the start time of maintenance of the current target work order are named the second background value and the second span coefficient, and the instrument status parameters at the end time of maintenance of the current target work order are named the third background value and the third span coefficient.

[0059] In some embodiments, it is necessary to perform a first logical judgment on the target work order to distinguish whether the target work order is a normal work order or a forged work order.

[0060] Specifically, as Figure 2 shown, the first logical judgment method is:

[0061] Step S110: Obtain the previous historical work order, which is also called the most recent work order, and retrieve the first background value recorded at the end time of quality control in the most recent work order and the first span coefficient recorded at the end time of quality control in the most recent work order;

[0062] Step S120: Determine the second background value at the start time of maintenance and the second span coefficient at the start time of maintenance according to the instrument status parameters of the target device during the maintenance period;

[0063] Step S130: Compare the first background value with the second background value, and compare the first span coefficient and the second span coefficient. When the first background value is the same as the second background value, and the first span coefficient and the second span coefficient are also the same, mark the target work order as a normal work order; in this comparison result, it means that no calibration has been performed again after the previous inspection, and the instrument status parameters have not been tampered with. Therefore, the target work order can be considered a normal work order; otherwise, execute Step S140.

[0064] Step S140: Assume that the comparison result is that the first background value is different from the second background value, and / or the first span coefficient and the second span coefficient are different, that is, either one parameter is inconsistent or both parameters are inconsistent, indicating that the instrument status parameters have changed during the two inspections before and after. This may be suspected of fraud. Therefore, in this case, mark the target work order as a suspected fraud work order. At the same time, make corresponding marks on the suspected fraud work order for attention.

[0065] Further, in addition to the fraud work orders mentioned in S140, when there are multiple intercept (background value) or slope (span coefficient) changes during the maintenance start time to the maintenance end time, it is also considered a fraud work order.

[0066] Further, for different categories of fraud work orders, differential marking methods can be adopted to facilitate quick identification and classification processing. To further enhance the warning effect, when the platform displays these fraud work orders, it will uniformly apply the visual effects of 'flashing' and'red highlighting' as an emergency alarm signal to immediately attract attention and promote a rapid response.

[0067] It should be noted that regardless of whether the target work order is judged to be a normal work order or a suspected fraud work order, the steps of Step S200 to Step S300 will continue to be executed for the second logical judgment to obtain the corresponding quality control results.

[0068] Step S200: Identify the instrument status parameters of the target device during the maintenance period. When the instrument status parameters change during the maintenance period, determine the calibration time node, and trace back a specified time from the calibration time node to determine the traceback time node.

[0069] As Figure 3 shown, in this embodiment, a second logical judgment is made on the target work order to further distinguish the work order type of the target work order; in this embodiment, the target work order can be divided into a work order that only performs inspection operations, or a work order that includes both inspection operations and calibration operations, and corresponding quality control operations are performed according to the work order type of the target work order.

[0070] Specifically, the method for judging the work order type of the target work order is:

[0071] Determine the third background value of the maintenance end time and the third span coefficient of the maintenance end time according to the instrument status parameters of the target device during the maintenance period;

[0072] Compare the second background value of the maintenance start time with the third background value of the maintenance end time, and compare the second span coefficient of the maintenance start time and the third span coefficient of the maintenance end time. When the second background value is the same as the third background value, and the second span coefficient and the third span coefficient are also the same, it means that this operation only involves the span inspection process and does not involve span calibration adjustment. Therefore, determine the target work order as the work order type that only performs inspection operations;

[0073] However, when the second background value is different from the third background value, and / or the second span coefficient and the third span coefficient are different, it means that this not only includes the span inspection process but also involves span calibration adjustment. Therefore, determine the target work order as the work order type that includes inspection operations and calibration operations.

[0074] Step S300: Determine the response value when the target device performs inspection operations and / or calibration operations according to multiple monitoring data between the traceability time node and the calibration time node, and return the response value to the target work order for quality control judgment and output the quality control result.

[0075] When the target work order is the work order type that only performs inspection operations, execute steps S310 to S315.

[0076] Step S310: Mark the maintenance end time as the first calibration time node, and trace back a specified time forward from the first calibration time node to determine the first traceability time node.

[0077] In this embodiment, the specified time can be preset to five minutes, and the first traceability time node refers to the time point corresponding to five minutes earlier on the time axis based on the first calibration time node.

[0078] Step S311: Obtain multiple first monitoring data between the first calibration time node and the first traceability time node, and judge whether the set stability condition is satisfied according to the standard deviation of each first monitoring data.

[0079] In this embodiment, the first monitoring data is obtained by continuously taking five monitoring data forward from the first calibration time node, and the five monitoring data are separated by one minute each.

[0080] It should be noted that the monitoring data refers to the measured value of the concentration of specific pollutants obtained by continuously collecting, processing, and analyzing environmental air quality samples using a continuous monitoring instrument at the monitoring point.

[0081] Such as Figure 4As shown, in this embodiment, the standard deviation of five data points is calculated based on five first monitoring data, and the calculation formula of the standard deviation is as follows:

[0082]

[0083] In the formula, SD represents the standard deviation of a set of monitoring data, X represents the monitoring data values of 5 one-minute periods, μ is the arithmetic mean of the 5 one-minute monitoring data, and the value of n is 5, representing five monitoring data.

[0084] If the standard deviation is less than or equal to the set standard deviation requirement value, then this set of first monitoring data is considered stable, and at this time, the stability condition is met, and steps S312 to S313 can be executed; if the standard deviation calculated for the five data points is greater than the set standard deviation requirement value, then this set of first monitoring data is considered unstable and the stability condition is not met, and at this time, steps S314 to S315 are executed.

[0085] Step S312: Calculate the first average value based on each first monitoring data under the condition of meeting the stability condition, and return the first average value as the response value of the zero / span check to the target work order.

[0086] It should be noted that in order to distinguish the average value of other monitoring data in this embodiment, the arithmetic mean calculated from the five first monitoring data in step S312 is called the first average value μ.

[0087] Step S313: Perform quality control judgment based on the response value of the zero / span check. Specifically:

[0088] Substitute the obtained response value of the zero / span check into the following formula to calculate the zero drift or span drift.

[0089] Among them, the zero drift calculation formula is: SE 0 = u 0 , where SE 0 is the zero drift, which refers to the deviation between the reading of the instrument and the zero input after the instrument runs stably without repairing, maintaining or adjusting the instrument; u 0 is the response value of the zero check.

[0090] The span drift calculation formula is: SE k (%) = (u k - S 1 ) / S 1 * 100%;

[0091] In the formula, SE kIt refers to span drift, which means the deviation between the reading of the instrument and the concentration value of the standard gas for specified inspection after the instrument runs stably without maintenance, servicing or adjustment of the instrument; u k is the response value for span inspection; S 1 refers to the concentration value of the standard gas for specified inspection, which is usually NO in pollutant monitoring 2 , SO 2 , O 3 The full-scale specified value for is 0 - 500 ppb, the specified value for CO is 0 - 50 ppb, and the concentration of the standard gas for specified inspection is the standard gas at 80% full scale.

[0092] Judge whether the absolute value of zero drift is less than or equal to the preset first control line, or judge whether the absolute value of span drift is less than or equal to the preset second control line; if the absolute value of zero drift is less than or equal to the preset first control line, or the absolute value of span drift is less than or equal to the preset second control line, it is determined that the corresponding quality control inspection work in the target work order is qualified; assume that if the absolute value of zero drift is greater than the preset first control line, or the absolute value of span drift is greater than the preset second control line, it is determined that the corresponding quality control inspection work in the target work order is unqualified.

[0093] Step S314: When the stable condition is not met, perform a sliding operation once to determine a new calibration time node and a new traceability time node.

[0094] Specifically, re-determine the previous time node of the first calibration time node as the new calibration time node, and trace back a specified time forward according to the new calibration time node to determine the new traceability time node.

[0095] In this embodiment, the time point one minute before the first calibration time node is determined as the new calibration time node, and starting from the new calibration time node, a new traceability time node is obtained five minutes forward.

[0096] Step S315: Obtain the new monitoring data between the new calibration time node and the new traceability time node, and re-judge whether the stable condition is met according to the new monitoring data.

[0097] In this embodiment, five new monitoring data are also obtained between the new calibration time node and the new traceability time node, and the time interval between the five new monitoring data is one minute; the standard deviation is calculated based on the five new monitoring data, and it is determined whether the standard deviation at this time meets the stability condition. If the stability condition is met, steps S312 to S313 are executed; if the standard deviation at this time still does not meet the stability condition, steps S314 to S315 are re-executed, and the above steps are looped until the first set of monitoring data that meets the stability condition is found, and the average value is calculated based on the monitoring data that meets the stability condition and uploaded to the work order as the response value for zero / span check.

[0098] Meanwhile, during the above loop process, the number of times that the stability condition is not met is counted in real time, and when the number reaches the set value, the quality control failure result is directly output. As Figure 5 shown, in this embodiment, if the standard deviations of the 10 groups of monitoring data searched forward do not meet the requirements, the response value cannot be obtained, and the quality control of the target work order is automatically determined to fail.

[0099] When the target work order is determined to be a work order type that includes inspection operations and calibration operations, steps S320 to S323 are executed.

[0100] Step S320: Determine the change moment of the instrument status parameter during the maintenance period as the second calibration time node, and trace back a specified time forward based on the second calibration time node to determine the second traceability time node.

[0101] In this embodiment, the change moment of the instrument status parameter during the maintenance period is determined as the second calibration time node, and on the time axis, it slides forward five minutes based on the second calibration time node, and this time is marked as the second traceability time node.

[0102] Step S321: Obtain multiple second monitoring data between the second calibration time node and the second traceability time node, and determine whether the stability condition is met according to the standard deviation of each second monitoring data.

[0103] In this embodiment, five second monitoring data are obtained between the second calibration time node and the second traceability time node, and the time interval between the five second monitoring data is one minute.

[0104] It should be noted that the method for calculating the standard deviation of the five second monitoring data and the method for determining whether the stability condition is met according to the calculated standard deviation are the same as those in the foregoing step S311, and will not be repeated here.

[0105] Step S322: Calculate the second average value according to each second monitoring data under the condition of meeting the stability condition, and return the second average value as the response value of the inspection to the target work order for quality control judgment.

[0106] It should be noted that the second average value is obtained by calculating the arithmetic mean, and the method of calculating the second average value and performing quality control judgment based on the inspected response value is the same as the aforementioned steps S312 and S313, and will not be described repeatedly here.

[0107] The steps executed under the condition that the stability condition is not satisfied are the same as those of S314 to S315, and will not be described repeatedly here.

[0108] Step S323: For the calibrated response value, use the instrument response value generated at the end time of maintenance during the maintenance period of the target device as the calibrated response value and return it to the target work order for quality control judgment.

[0109] In this embodiment, the method for performing quality control judgment based on the calibrated response value is as follows: Calculate the span drift based on the calibrated response value, compare the calculated span drift value with the preset qualified standard or control line to determine whether the measurement result of the instrument is within the acceptable error range; if the span drift value exceeds this range, it indicates that the device needs further adjustment or repair. Record the calibrated response value and the span drift calculation result, and generate a quality control report when necessary, which can be used for subsequent data analysis and equipment performance tracking.

[0110] It should be noted that the formula for span drift in this step is the same as the aforementioned one:

[0111] SE k (%) = (u k - S 1 ) / S 1 * 100%, where u k is the calibrated response value, and S 1 is the actual concentration value of the calibration gas.

[0112] In this embodiment, taking the atmospheric pollutant SO 2 as an example, the specific processing process of this method for the atmospheric pollutant SO 2 is introduced in detail. As Figure 6 shown, it is specifically as follows:

[0113] S1: Obtain the quality control basic information in the target work order, including information such as the site, monitoring item, quality control type, etc.

[0114] In the introduction of this example, taking the span check / calibration of SO 2 as an example for detailed introduction, the span check / calibration of the SO 2 monitoring instrument should be carried out during a period with a relatively low pollutant concentration according to the actual situation, and the inspection frequency is about once every seven days. Before performing the span check / calibration, first introduce the zero gas into the monitoring instrument for zero point check / calibration, and then perform the span check after the zero point check / calibration is completed.

[0115] S2. Obtain the first instrument status parameter information of the quality control end time in the previous work order for the site and monitoring items, including the first intercept (the first background value) and the first slope (the first span coefficient).

[0116] In the current SO 2 span check / calibration work order, obtain the SO of a specific site 2 The first instrument status parameter information recorded at the end of the quality control process in the most recent work order for the span check / calibration item. These information specifically include two key parameters: the first intercept (the first background value), which represents the instrument reference reading without significant external interference; the first slope (the first span coefficient), which reflects the ratio between the response value of the monitoring instrument to the standard gas and the standard gas concentration value, and can be used to evaluate the performance and accuracy of the monitoring instrument.

[0117] S3. Fill in the maintenance start time and maintenance end time of the SO 2 inspection / calibration in the target work order.

[0118] The operation and maintenance personnel manually enter the maintenance start time and maintenance end time in the target work order, and the input format of the time is X year / X month / X day X hour:X minute.

[0119] S4. Obtain the monitoring data of the target device and the minute data of the instrument status parameters within the range of the maintenance start time and maintenance end time of the target work order.

[0120] Take SO 2 span check / calibration as the monitoring item of the current target work order, and obtain the SO within the range of the maintenance start time and maintenance end time of the target work order in minutes 2 monitoring data, as well as the slope (background value) and intercept (span coefficient).

[0121] S5. Conduct the first logical judgment on the target work order to distinguish whether the target work order is a normal work order or a forged work order. If it is a forged work order, it should be marked.

[0122] The specific content of this logical judgment is as Figure 3 shown. Compare the second intercept (the second background value) and the second slope (the second span coefficient) at the maintenance start time point of the current SO 2 span check / calibration with the first intercept (the first background value) and the first slope (the first span coefficient) recorded on the work order after the previous quality control end. Check whether the data is consistent. If both are exactly the same (that is, there is no change in the background value and the span coefficient), it is inferred that no instrument calibration operation has been performed since the last inspection, and the SO filled in this time 2The span quality control work order is regarded as a normal work order; if there are inconsistencies (one or both of the background value and the span coefficient are different from the previous time), it indicates that the instrument calibration may have been carried out after the previous inspection, and the SO filled in this time 2 The span quality control work order thus has a suspicion of fraud and needs to be marked accordingly for attention. Whether it is a normal work order or a work order suspected of fraud, the second logical judgment will continue to be carried out according to the established process.

[0123] S6. Conduct a second logical judgment on the target work order to further distinguish whether the target work order is only a work order for inspection or a work order that includes both inspection and calibration;

[0124] The specific content of this logical judgment is as Figure 4 shown. Compare the second intercept (second background value) and the second slope (second span coefficient) corresponding to the start time of maintenance in this SO 2 span quality control with the third intercept (third background value) and the third slope (third span coefficient) corresponding to the end time of maintenance to check whether the two are consistent. If both are consistent (that is, neither the background value nor the slope has changed), it indicates that this operation only involves the SO 2 span inspection process and does not involve the SO 2 span calibration adjustment; on the contrary, if one or both of the two parameters are inconsistent, it indicates that this operation not only includes the SO 2 span inspection, but also involves the SO 2 span calibration adjustment.

[0125] S7. For work orders that are only for inspection, taking the end time of maintenance as the node, automatically statistically obtain the response value of the span inspection according to the five-minute sliding judgment for quality control judgment.

[0126] For the work orders in which the SO 2 span quality control only involves inspection items in this logical judgment, taking the end time of maintenance of the SO 2 span inspection as the corresponding node, and automatically obtain the response value of the SO 2 span inspection according to the five-minute sliding judgment.

[0127] Specifically, the specific process of the five-minute sliding judgment is as Figure 5 shown, and the specific steps are as follows:

[0128] Initial data selection: Take the end time point of maintenance of the SO 2 span inspection as the first calibration time node. Starting from the first calibration time node, trace back five minutes to determine the first trace time node, which is equivalent to continuously taking the first group of 5 one-minute monitoring data starting from the end time point of maintenance of the SO 2 span inspection. Call this group of monitoring data the first monitoring data.

[0129] Standard deviation calculation and evaluation: First, calculate the standard deviation for the five data points of the first group regarding SO 2 span check, that is, calculate the standard deviation of the first monitoring data. If this standard deviation is less than or equal to the set SO 2 standard deviation requirement value of the monitoring instrument, it is considered that the first monitoring data is stable and can enter the next calculation process.

[0130] Data stability determination and loop processing: If the standard deviation of the first monitoring data is less than or equal to the set SO 2 standard deviation requirement value of the monitoring instrument, it means that the standard deviation of the first monitoring data meets the SO 2 standard deviation requirement of the span check. At this time, further calculate the arithmetic mean μ of the first monitoring data to obtain the first mean value, and use this value as the SO 2 response value of the check; if the standard deviation of the first monitoring data is greater than the set SO 2 standard deviation requirement value of the monitoring instrument, re-determine the previous time node of the first calibration time node as the new calibration time node. In this embodiment, a time window of 1 minute is slid forward starting from the first calibration time node, and a second group of 5 one-minute monitoring data is continuously taken forward starting from the new calibration time node. Calculate the standard deviation according to the re-selected 5 one-minute monitoring data, and repeat the above standard deviation calculation and evaluation process.

[0131] Loop count limit: The above data selection and evaluation process will be looped, but the maximum loop count is set to 10 times, and the maximum loop count is represented by i. This means that if the standard deviations of 10 consecutive groups of data searched forward do not meet the requirements, it is considered that an effective response value cannot be obtained from the current dataset, and it is judged that this quality control fails, and further inspection or data collection measures may need to be taken.

[0132] Processing result: If a data group that meets the SO 2 standard deviation requirement of the span check is found within 10 loops, use this data group to calculate the arithmetic mean μ as the SO 2 response value of the span check.

[0133] Check that the quality control is qualified: When the arithmetic mean μ is used as the SO 2 response value of the span check and uploaded to the work order, substitute it into the span drift formula to calculate whether the SO 2 span drift is within the qualified range.

[0134] When the absolute value of the span drift does not exceed the SO 2 second control line set for the span check, it is determined that this SO 2Span check is qualified. When the absolute value of span drift exceeds the second control line set for span check, it is determined that this SO 2 span check is unqualified. 2 Span check is unqualified.

[0135] S8. For work orders containing inspection and calibration, identify the calibration time nodes based on the change moments of the intercept (background value) and slope (span coefficient), and automatically statistically obtain the results of inspection and calibration according to the acquisition rules for quality control judgment.

[0136] For work orders containing both SO 2 span check and span calibration, the data processing is more complex: for work orders of SO 2 span check, the system first focuses on the time points when the intercept (background value) and slope (span coefficient) change during this process. Once it detects a change in either the background value or the span coefficient during this SO 2 span check, the system immediately determines this time point as the second calibration time node. Based on the second calibration time node, trace back five minutes to determine the second trace time node. Calculate the standard deviation based on the monitoring data between the second calibration time node and the second trace time node. When the standard deviation meets the stable condition, calculate the arithmetic mean of the monitoring data between the second calibration time node and the second trace time node to determine the SO 2 span check response value. During this process, the rule of five-minute sliding judgment is also followed to ensure the stability and accuracy of obtaining the SO 2 span check response value.

[0137] Compared with the SO 2 span check result, the acquisition of the SO 2 span calibration response value is relatively direct, that is, directly capture the SO 2 maintenance end time of span check / calibration in the target work order as the SO 2 instrument response value as the SO 2 span calibration response value.

[0138] During the entire SO 2 span check / calibration process, through a precisely designed dual logical judgment mechanism and an automatic data capture method of five-minute sliding judgment, the authentication work of the authenticity of the target work order for this time is completed.

[0139] In another embodiment of the present invention, an environmental monitoring data quality control system is also provided. This system closely follows the quality control process of instrument status parameters and realizes the comprehensive tracking and management of the quality control process through highly integrated functional modules, such as Figure 7 shown.

[0140] Specifically, the data quality control system for environmental monitoring includes two major systems: the central platform system and the environmental monitoring sub-station system. The central platform system is divided into the following modules:

[0141] Work order management module: responsible for recording, allocating, and tracking all quality control work orders for gaseous pollutants such as NO 2 , SO 2 , O 3 , etc. Here, it refers to the target work order for SO 2 span check / calibration.

[0142] Sliding calculation module: This module uses a five-minute sliding window. By continuously moving the data window forward, it calculates the standard deviation and determines whether it is within the set standard deviation range, thereby ensuring the stability and accuracy of obtaining the zero / span check response value.

[0143] Logic determination module: Based on the judgment of whether the intercept and slope of the instrument status parameter data in different monitoring periods are consistent, it distinguishes forged work orders and triggers an alarm status. In this embodiment, through two consecutive logical judgments, it distinguishes whether there are forged work orders during the SO 2 span check / calibration process and verifies the accuracy of the data.

[0144] Backhaul command module: As a module for conveying instructions, it sends backhaul instructions to the site end through a predetermined communication protocol and transmission method, and supports the functions of remote control and management. After sending the backhaul command, the backhaul command module also needs to receive feedback information from the site end device to confirm the execution status of the instruction and the backhaul status of the data. The specific implementation method in this embodiment is that the central platform sends an instruction for SO 2 span check / calibration to the site end.

[0145] The environmental monitoring sub-station is divided into the following modules, including:

[0146] Quality control backhaul module: This module seamlessly docks with the data acquisition module and is responsible for backhauling the monitoring data and instrument status parameters within the range of the quality control start time and end time according to the instruction.

[0147] Data acquisition module: Real-time obtains monitoring data and instrument status parameters from environmental monitoring equipment.

[0148] The system in the embodiment of the present invention executes the data quality control method for environmental monitoring as described above. The functions of the various modules of the system can refer to the corresponding descriptions in the above method and will not be elaborated here.

[0149] In another embodiment of the present invention, an electronic device is further provided. Figure 8 The structural block diagram of the electronic device according to an embodiment of the present invention is shown. As Figure 8As shown in the figure, the electronic device includes: a memory 100 and a processor 200. The memory 100 stores a computer program that can run on the processor 200. When the processor 200 executes the computer program, it implements the data quality control method for environmental monitoring in the above embodiments. The number of the memory 100 and the processor 200 can be one or more.

[0150] The electronic device further includes:

[0151] a communication interface 300, configured to communicate with external devices and perform data interaction and transmission.

[0152] If the memory 100, the processor 200, and the communication interface 300 are implemented independently, the memory 100, the processor 200, and the communication interface 300 can be interconnected through a bus and complete communication with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0153] Optionally, in a specific implementation, if the memory 100, the processor 200, and the communication interface 300 are integrated on a single chip, the memory 100, the processor 200, and the communication interface 300 can complete communication with each other through an internal interface.

[0154] An embodiment of the present invention provides a computer-readable storage medium that stores a computer program. When the program is executed by a processor, it implements the method provided in the embodiment of the present invention.

[0155] An embodiment of the present invention further provides a chip, which includes a processor configured to call and run an instruction stored in a memory, so that a communication device installed with the chip executes the method provided in the embodiment of the present invention.

[0156] An embodiment of the present invention further provides a chip, including: an input interface, an output interface, a processor, and a memory. The input interface, the output interface, the processor, and the memory are connected through an internal connection path. The processor is configured to execute code in the memory. When the code is executed, the processor is configured to execute the method provided in the embodiment of the invention.

[0157] It should be understood that the above-mentioned processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor that supports the advanced RISC machines (ARM) architecture.

[0158] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM).

[0159] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0160] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0161] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" can explicitly or implicitly include at least one of these features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0162] As described above, only the specific implementation manners of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various changes or substitutions, and these should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A data quality control method for environmental monitoring, characterized in that: include: Obtain a target work order, and determine monitoring data and instrument status parameters of the target equipment during the maintenance period according to the target work order; When the instrument status parameter changes within the maintenance period, a calibration time node is determined, and a designated time is traced back from the calibration time node as a starting point to determine a traceback time node; Determine, based on the plurality of monitoring data between the tracing time node and the calibration time node, a response value when the target device performs an inspection operation and / or a calibration operation, and return the response value to the target work order for quality control judgment and output of a quality control result; It also includes: determining a second background value of a maintenance start time and a second span coefficient of the maintenance start time according to the instrument status parameter within the maintenance period; Determining a third background value of a maintenance end time and a third span coefficient of the maintenance end time according to the instrument status parameter within the maintenance period; When the second background value is the same as the third background value, and the second span coefficient is the same as the third span coefficient, determining the target work order as a work order type for performing an inspection operation; When the second background value is different from the third background value and / or the second span coefficient is different from the third span coefficient, determining the target work order as a work order type including the inspection operation and the calibration operation; In the case where the target work order is determined to be a work order type for performing an inspection operation, marking the maintenance end time as a first calibration time node, and tracing back the specified time according to the first calibration time node to determine a first tracing time node; Acquire a plurality of first monitoring data between the first calibration time node and the first tracing time node, and determine whether a set stability condition is met according to a standard deviation of each of the first monitoring data; When the stability condition is met, a first average value is calculated according to each of the first monitoring data, and the first average value is returned to the target work order as a response value of the zero point / span check for quality control judgment; In the case where the target work order is determined to be a work order type including the inspection operation and the calibration operation, determining the time when the instrument status parameter changes within the maintenance period as a second calibration time node, and tracing back the specified time according to the second calibration time node to determine a second tracing time node; Acquire multiple second monitoring data between the second calibration time node and the second tracing time node, and determine whether a set stability condition is met according to a standard deviation of each second monitoring data; When the stability condition is met, a second average value is calculated according to each of the second monitoring data, and the second average value is returned to the target work order as an inspection response value for quality control judgment.

2. The data quality control method for environmental monitoring according to claim 1, characterized in that: Also includes: Obtain historical work orders, filter out the most recent work order from the historical work orders, and determine a first background value recorded at the quality control end time of the most recent work order and a first span coefficient recorded at the quality control end time of the most recent work order; When the first background value is the same as the second background value, and the first span coefficient is the same as the second span coefficient, marking the target work order as a normal work order; When the first background value is different from the second background value, and / or the first span coefficient is different from the second span coefficient, the target work order is marked as a suspected fake work order.

3. The data quality control method for environmental monitoring according to claim 1, characterized in that: Also includes: The instrument response value generated by the target device at the maintenance end time of the maintenance period is returned to the target work order as a calibrated response value for quality control judgment.

4. The data quality control method for environmental monitoring according to claim 3, characterized in that: Also includes: If the stability condition is not met, re-determine the first calibration time node or the previous time node of the second calibration time node as a new calibration time node, and trace back the specified time according to the new calibration time node to determine a new traceback time node; Re-judge whether the stability condition is met based on the new monitoring data between the new calibration time node and the new traceability time node, and count the number of times the stability condition is not met in real time. When the number reaches a set value, directly output a quality control failure result.

5. The data quality control method for environmental monitoring according to claim 1, characterized in that: The quality control judgment method includes: Calculating a drift value according to the response value; When the drift value is higher than a preset control line, a quality control failure result is output.

6. A data quality control system for environmental monitoring, characterized in that: Execute the data quality control method for environmental monitoring as described in any one of claims 1 to 5.

7. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the data quality control method for environmental monitoring as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the data quality control method for environmental monitoring as described in any one of claims 1 to 5 is implemented.

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