Data quality control method, system and equipment for environmental monitoring and medium

Abstract

The invention provides a data quality control method, system and device for environmental monitoring and a medium, and the method comprises the steps: obtaining a target work order, and determining the monitoring data and instrument state parameters of the operation of a target device in a maintenance period according to the target work order; determining a calibration time node under the condition that the instrument state parameters change in the maintenance time period, and forwards tracing specified time by taking the calibration time node as a starting point, and determining a tracing time node; and according to the plurality of monitoring data between the tracing time node and the calibration time node, determining a response value when the target equipment executes the inspection operation and / or the calibration operation, returning the response value to the target work order for quality control judgment, and outputting a quality control result. According to the invention, the obtained monitoring data can be continuously and periodically calculated and analyzed, the stability and accuracy of the obtained response value are ensured, and the influence of data errors caused by counterfeiting of quality control work orders on quality control results is avoided, so that the quality of the monitoring data is improved.

Description

Technical Field

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

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

[0003] At present, the process management of the electronic work order system has improved supervision to a certain extent and ensured the accuracy of the data. However, in some cases, the operation and maintenance team may, out of improper motives, calibrate multiple times and select lower data, thereby affecting the authenticity of the quality control work order. This behavior seriously undermines the public's trust in environmental monitoring data and damages the fairness of environmental monitoring. When falsification of quality control work orders occurs, the authenticity and accuracy of environmental monitoring data cannot be ensured. Summary of the invention

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

[0005] In a first aspect, an embodiment of the present invention provides a data quality control method for environmental monitoring, comprising:

[0006] 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;

[0007] When the instrument status parameters change during the maintenance period, the calibration time node is determined, and the calibration time node is used as the starting point to trace back to the specified time to determine the traceability time node;

[0008] Based on multiple monitoring data between the traceability time node and the calibration time node, the response value when the target device performs the inspection operation and / or calibration operation is determined, and the response value is returned to the target work order for quality control judgment and output of the quality control result.

[0009] In one embodiment, it further includes:

[0010] Obtain historical work orders, filter 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 a second background value of the maintenance start time and a second span coefficient of the maintenance start time according to the instrument status parameters within the maintenance period;

[0012] 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;

[0013] 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 counterfeit work order.

[0014] In one embodiment, it further includes:

[0015] Determine a third background value of the maintenance end time and a 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 is the same as the third span coefficient, the target work order is determined as a work order type for performing an inspection operation;

[0017] 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, the target work order is determined as a work order type including an inspection operation and a calibration operation.

[0018] In one embodiment, it further includes:

[0019] In the case where the target work order is a work order type that only performs an inspection operation, the maintenance end time is marked as a first calibration time node, and a designated time is traced back according to the first calibration time node to determine a first tracing time node;

[0020] 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 first monitoring data;

[0021] When the stability condition is met, a first average value is calculated according to each 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.

[0022] In one embodiment, it further includes:

[0023] When the target work order is determined to be a work order type including an inspection operation and a calibration operation, the change time of the instrument status parameter within the maintenance period is determined as a second calibration time node, and a second tracing time node is determined by tracing back a specified time according to the second calibration time node;

[0024] Acquire multiple second monitoring data between the second calibration time node and the second tracing 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, a second average value is calculated according to each second monitoring data, and the second average value is returned to the target work order as a response value for inspection for quality control judgment;

[0026] The instrument response value generated by the target device at the end of the maintenance period is returned to the target work order as the calibrated response value for quality control judgment.

[0027] In one embodiment, it further includes:

[0028] If the stability condition is not met, the time node before the first calibration time node or the second calibration time node is re-determined as a new calibration time node, and a new tracing time node is determined by tracing back a specified time according to the new calibration time node;

[0029] Re-judge whether the stability conditions are 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 conditions are not met in real time. When the number reaches the set value, directly output the quality control failure result.

[0030] In one embodiment, the method of quality control determination includes:

[0031] Calculate the drift value based on the response value;

[0032] If the drift value is higher than the preset control line, a quality control failure result will be output.

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

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

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

[0036] The advantages or beneficial effects of the above technical solution include at least:

[0037] The present invention determines a calibration time node according to changes in instrument status parameters, traces back a specified time from the calibration time node as a starting point, determines a traceback time node, determines a response value when a target device performs an inspection operation and / or a calibration operation according to a plurality of monitoring data between the traceback time node and the calibration time node, performs quality control judgment according to the response value, and outputs a quality control result; this is equivalent to performing continuous and periodic calculation and analysis on the acquired monitoring data, ensuring the stability and accuracy of the acquired response value, and avoiding the influence of data errors caused by falsification of quality control work orders on the quality control results, thereby improving the quality of monitoring data.

[0038] The above summary is for illustrative purposes only 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 accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0040] Figure 1 It is a flow chart of the data quality control method for environmental monitoring of the present invention;

[0041] Figure 2 It is a schematic diagram of the flow chart of the first logical judgment of the present invention;

[0042] Figure 3 It is a flow chart of the second logic judgment of the present invention;

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

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

[0045] Figure 6 This is a flow chart of the data quality control method using SO2 as an example of the present invention;

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

[0047] Figure 8 The structure block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0049] In today's era of globalization, environmental protection has become an urgent task universally recognized by the international community, and its strategic position has become increasingly prominent. Environmental monitoring is a key link in assessing environmental quality, tracking pollution sources, and formulating environmental protection policies. Its importance is self-evident. However, with the rapid expansion of environmental monitoring sites, how to implement efficient and comprehensive supervision strategies for the operation and maintenance of monitoring sites has become an increasingly prominent problem. At present, the process management of the electronic work order system has improved supervision to a certain extent and ensured the accuracy of the data. However, in some cases, the operation and maintenance team may have improper motives and calibrate multiple times and select lower data, thereby affecting the authenticity of the quality control work order. This behavior seriously undermines the public's trust in environmental monitoring data and damages the fairness of environmental monitoring.

[0050] In order 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 environmental monitoring sites across the country and ensure the authenticity and accuracy of the data.

[0051] like Figure 1 As 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 equipment during the maintenance period according to the target work order.

[0053] The target work order records the target equipment information, maintenance period, and a large amount of basic quality control information, including site, monitoring items, quality control type, etc. The operation and maintenance personnel can also fill in the maintenance period in the target work order according to the actual situation, which means that the monitoring items specified in the target work order will be executed during the specified maintenance period.

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

[0055] At the same time, the sites and monitoring items that need to be monitored are determined according to the target work order, and the previous work order corresponding to the same site and the same monitoring item is obtained. The previous work order, as a historical work order, has completed the quality control work within the set quality control time period, and records the instrument status parameters from the start time of quality control to the end time of quality control, where 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 when there is no target substance. When performing a 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 reality it may be affected by instrument noise, environmental factors, etc.

[0057] The span factor, 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 (standard gas) when a known concentration of the standard substance (standard gas) passes through the instrument. When performing a span calibration, the span factor is used to determine the instrument's response sensitivity to a substance of known concentration. This parameter helps ensure that the instrument can provide accurate measurement results when measuring different concentrations of the substance being measured.

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

[0059] In some embodiments, a first logical judgment needs to be performed on the target work order to distinguish whether the target work order is a normal work order or a fake work order.

[0060] Specifically, Figure 2 As 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: determining a second background value of the maintenance start time and a second span coefficient of the maintenance start time according to the instrument status parameters of the target device running within the maintenance period;

[0063] Step S130: Compare the first background value with the second background value, and compare the first span coefficient with the second span coefficient. 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, the target work order is marked as a normal work order. This comparison result means that no calibration has been performed again since the previous inspection, and the instrument status parameters have not been tampered with. Therefore, the target work order can be considered to be a normal work order. Otherwise, execute step S140.

[0064] Step S140: Assuming that the comparison result is that the first background value is different from the second background value, and / or the first span coefficient is different from the second span coefficient, that is, any one parameter is inconsistent or both parameters are inconsistent, it means that the instrument status parameter has changed between the two inspections, which may be suspected of fraud, so in this case, the target work order is marked as a suspected fraud work order. At the same time, the suspected fraud work order is marked accordingly to indicate attention.

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

[0066] Furthermore, for different types of fraudulent work orders, differentiated labeling methods can be used to facilitate rapid identification and classification. To further enhance the warning effect, the platform will uniformly apply the visual effects of 'flashing' and 'highlighted in red' when displaying these fraudulent work orders as emergency alarm signals to immediately attract attention and promote rapid response.

[0067] It should be noted that no matter whether the target work order is judged to be a normal work order or a suspected fraudulent work order, steps S200 to S300 will continue to be executed to perform a second logical judgment to obtain the corresponding quality control result.

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

[0069] like Figure 3 As shown, this embodiment performs a second logical judgment 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 an inspection operation, or a work order that includes both an inspection operation and a calibration operation, and the corresponding quality control operation is performed according to the work order type of the target work order.

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

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

[0072] The second background value at the maintenance start time is compared with the third background value at the maintenance end time, and the second span coefficient at the maintenance start time is compared with the third span coefficient at the maintenance end time. 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, it means that this operation only involves the span inspection process and does not involve span calibration adjustment. Therefore, the target work order is determined as a work order type that only performs inspection operations;

[0073] 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, it means that this not only includes the span inspection process but also involves the span calibration adjustment. Therefore, the target work order is determined as a work order type that includes inspection operations and calibration operations.

[0074] Step S300: Determine the response value when the target device performs the inspection operation and / or calibration operation based on multiple monitoring data between the tracing time node and the calibration time node, 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 a work order type that only performs an inspection operation, steps S310 to S315 are executed.

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

[0077] In this embodiment, the specified time may be preset to five minutes, and the first tracing time node refers to a time point corresponding to five minutes earlier than the first calibration time node on the time axis.

[0078] Step S311: acquiring a plurality of first monitoring data between the first calibration time node and the first tracing time node, and determining whether a set stability condition is satisfied according to a standard deviation of each first monitoring data.

[0079] In this embodiment, the first monitoring data is obtained by obtaining five monitoring data consecutively based on the first calibration time node, and the five monitoring data are separated by one minute respectively.

[0080] It should be noted that monitoring data refers to the measured values ​​of specific pollutant concentrations that are obtained through continuous sample collection, processing, and analysis of ambient air quality at monitoring points using continuous monitoring instruments.

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

[0082]

[0083] Where SD represents the standard deviation of a set of monitoring data, X represents five 1-minute monitoring data values, μ is the arithmetic mean of five 1-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, the first group of monitoring data is considered to be stable, and the stability condition is met. Steps S312 to S313 can be executed; if the standard deviation calculated from the five data points is greater than the set standard deviation requirement value, the first group of monitoring data is considered to be unstable and the stability condition is not met. Steps S314 to S315 are executed.

[0085] Step S312: When the stability condition is met, a first average value is calculated according to each 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.

[0086] It should be noted that, in order to distinguish the average values ​​of other monitoring data, in this embodiment, the arithmetic average value calculated according to 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 point / span check, specifically:

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

[0089] The zero drift calculation formula is: SE0=u0, where SE0 is the zero drift, which refers to the deviation between the instrument reading and the zero input after the instrument runs stably without repair, maintenance or adjustment of the instrument; u0 is the response value of the zero check.

[0090] The span drift calculation formula is: SE k (%)=(u k -S1) / S1*100%;

[0091] Where, SE k It refers to the span drift, which refers to the deviation between the instrument reading and the concentration value of the specified inspection standard gas after the instrument runs stably without repair, maintenance or adjustment of the instrument; kIt is the response value of span check; S1 refers to the concentration value of the standard gas used for inspection. In pollutant monitoring, the full-scale specified values ​​of NO2, SO2, and O3 are usually 0-500ppb, and the specified value of CO is 0-50ppb. The concentration of the standard gas used for inspection is 80% of the full-scale standard gas.

[0092] Determine whether the absolute value of the zero drift is less than or equal to the preset first control line, or determine whether the absolute value of the span drift is less than or equal to the preset second control line; if the absolute value of the zero drift is less than or equal to the preset first control line, or the absolute value of the span drift is less than or equal to the preset second control line, determine that the corresponding quality control inspection work carried out in the target work order is qualified; assuming that the absolute value of the zero drift is greater than the preset first control line, or the absolute value of the span drift is greater than the preset second control line, determine that the corresponding quality control inspection work carried out in the target work order is unqualified.

[0093] Step S314: When the stability condition is not met, a sliding operation is performed to determine a new calibration time node and a new tracing time node.

[0094] Specifically, a time node before the first calibration time node is re-determined as a new calibration time node, and a new tracing time node is determined by tracing back a designated time according to the new calibration time node.

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

[0096] Step S315: Acquire new monitoring data between the new calibration time node and the new tracing time node, and re-determine whether the stability condition is met based on 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 to determine whether the standard deviation at this time meets the stability condition. If the stability condition is met, step S312 to step S313 are executed; if the standard deviation at this time still does not meet the stability condition, step S314 to step S315 are re-executed, and the above steps are repeated until the first group 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 as the response value of the zero point / span check and uploaded to the work order.

[0098] At the same time, in the above cycle process, the number of times that the stability condition is not met is counted in real time, and the quality control failure result is directly output when the number reaches the set value. Figure 5As shown, in this embodiment, if the standard deviations of the 10 sets 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 have failed.

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

[0100] Step S320: Determine the time when the instrument status parameter changes within the maintenance period as a second calibration time node, and trace back a specified time according to the second calibration time node to determine a second tracing time node.

[0101] In this embodiment, the time when the instrument status parameter changes during the maintenance period is determined as the second calibration time node, and the time is slid forward five minutes based on the second calibration time node on the time axis, and the time is marked as the second tracing time node.

[0102] Step S321: Acquire multiple second monitoring data between the second calibration time node and the second tracing 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 between the second calibration time node and the second tracing time node are obtained, 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 judging whether the stability condition is met based on the calculated standard deviation are the same as those in the aforementioned step S311 and will not be described again here.

[0105] Step S322: When the stability condition is met, a second average value is calculated based on each second monitoring data, and the second average value is returned to the target work order as the inspection response value for quality control judgment.

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

[0107] The steps performed when the stability condition is not met are the same as steps S314 to S315 and will not be described again here.

[0108] Step S323: For the calibrated response value, 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 the calibrated response value for quality control judgment.

[0109] The method for quality control judgment based on the calibrated response value in this embodiment is: calculate the span drift based on the calibrated response value, compare the calculated span drift value with the preset qualified standard or control line, and 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 equipment needs further adjustment or maintenance. And record the calibration response value and span drift calculation results, 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 above:

[0111] SE k (%)=(u k -S1) / S1*100%, where u k is the calibrated response value, and S1 is the actual concentration value of the standard gas.

[0112] In this embodiment, the atmospheric pollutant SO2 is taken as a representative, and the specific treatment process of the atmospheric pollutant SO2 by the method is described in detail. Figure 6 As shown, the details are as follows:

[0113] S1: Obtain basic quality control information in the target work order, including site, monitoring items, quality control type and other information.

[0114] In this case, the SO2 span check / calibration is used as a representative for detailed introduction. The span check / calibration of the SO2 monitoring instrument should be checked during the period of low pollutant concentration according to the actual situation, and the inspection frequency is about once every seven days. Before the span check / calibration, the zero gas should be passed into the monitoring instrument to perform the zero point check / calibration. After the zero point check / calibration is completed, the span check should be performed.

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

[0116] In the work order of this SO2 span check / calibration, obtain the first instrument status parameter information recorded at the end of the quality control process in the most recent work order for the SO2 span check / calibration project of a specific site. This information specifically includes two key parameters: the first intercept (first background value), which represents the instrument baseline reading without significant external interference; the first slope (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, which 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 SO2 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. The time entry format is X year / X month / X day X hour:X minute.

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

[0120] Take SO2 span check / calibration as the monitoring item of this target work order, obtain SO2 monitoring data within the maintenance start time and maintenance end time range of the target work order in minutes, as well as the slope (background value) and intercept (span coefficient).

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

[0122] The specific content of this logical judgment is as follows Figure 3 As shown, the second intercept (second background value) and the second slope (second span coefficient) at the start time of the maintenance of the SO2 span inspection / calibration are compared with the first intercept (first background value) and the first slope (first span coefficient) recorded on the work order after the last quality control to check whether the data are consistent. If both are completely consistent (i.e., the background value and the span coefficient have not changed), it is inferred that no instrument calibration operation has been performed since the last inspection, and the SO2 span quality control work order filled in this time is regarded as a normal work order; if there is an inconsistency (one or both of the background value and the span coefficient are different from the last time), it indicates that the instrument calibration may have been performed after the last inspection, and the SO2 span quality control work order filled in this time is therefore suspected of being falsified, and needs to be marked accordingly for attention. Whether it is a normal work order or a suspected falsified work order, the second logical judgment will continue to be carried out according to the established process.

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

[0124] The specific content of this logical judgment is as follows Figure 4 As shown, the second intercept (second background value) and the second slope (second span coefficient) corresponding to the maintenance start time in this SO2 span quality control are compared with the third intercept (third background value) and the third slope (third span coefficient) corresponding to the maintenance end time to check whether the two are consistent. If both are consistent (that is, the background value and the slope have not changed), it means that this operation only involves the SO2 span inspection process and does not involve the SO2 span calibration adjustment; on the contrary, if one or two parameters of the two are inconsistent, it means that this operation not only includes the SO2 span inspection, but also involves the SO2 span calibration adjustment.

[0125] S7. For work orders that are only for inspection, the maintenance end time is used as the node, and the response value of the span inspection is automatically obtained based on the five-minute sliding judgment for quality control judgment.

[0126] For work orders in which SO2 span quality control only involves inspection items in this logical judgment, the maintenance end time of the SO2 span inspection is used as the corresponding node, and the response value of the SO2 span inspection is automatically obtained based on the five-minute sliding judgment.

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

[0128] Initial data selection: The maintenance end time point of the SO2 span check is taken as the first calibration time node. Starting from the first calibration time node, trace back five minutes to determine the first tracing time node, which is equivalent to continuously taking the first group of 5 1-minute monitoring data starting from the maintenance end time point of the SO2 span check. This group of monitoring data is called the first monitoring data.

[0129] Standard deviation calculation and evaluation: First, calculate the standard deviation for the first set of 5 data points about the SO2 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 SO2 monitoring instrument standard deviation requirement, the first monitoring data is considered to be 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 standard deviation requirement of the SO2 monitoring instrument, it means that the standard deviation of the first monitoring data meets the standard deviation requirement of the SO2 span check. At this time, the arithmetic mean μ of the first monitoring data is further calculated to obtain the first average value, and this value is used as the response value of the SO2 check; if the standard deviation of the first monitoring data is greater than the set standard deviation requirement of the SO2 monitoring instrument, the previous time node of the first calibration time node is re-determined as a new calibration time node. In this embodiment, a time window of 1 minute is slid forward from the first calibration time node as the starting point, and a second group of 5 1-minute monitoring data is continuously taken from the new calibration time node, and the standard deviation is calculated based on the re-selected 5 1-minute monitoring data, and the above standard deviation calculation and evaluation process is repeated.

[0131] Cycle number limit: The above data selection and evaluation process will be repeated, but the maximum number of cycles is set to 10 times, and the maximum number of cycles is represented by i. This means that if the standard deviations of the 10 sets of data that are searched forward continuously fail to meet the requirements, it is considered that no valid response value can be obtained from the current data set, and it is judged that this quality control has failed, and further inspection or data collection measures may be required.

[0132] Processing results: If a data set that meets the standard deviation requirements of the SO2 span check is found within 10 cycles, the arithmetic mean μ is calculated using the data set as the response value of the SO2 span check.

[0133] Check quality control: When the arithmetic mean μ is uploaded to the work order as the response value of the SO2 span check, the span drift formula is entered to calculate whether the SO2 span drift is within the qualified range.

[0134] When the absolute value of the span drift does not exceed the second control line set for the SO2 span check, the SO2 span check is considered qualified. When the absolute value of the span drift exceeds the second control line set for the SO2 span check, the SO2 span check is considered unqualified.

[0135] S8. For work orders that include inspection and calibration, the calibration time node is identified based on the change of the intercept (background value) and slope (span coefficient), and the inspection and calibration results are automatically obtained according to the acquisition rules for quality control judgment.

[0136] For work orders that include both SO2 span check and span calibration, data processing is more complicated: For work orders for SO2 span check, the system first focuses on the time point when the intercept (background value) and slope (span coefficient) change during this process. Once the change of any one of the background value and span coefficient in this SO2 span check is detected, the system immediately determines this time point as the second calibration time node, and uses the second calibration time node as the benchmark to trace back five minutes to determine the second traceability time node, calculate the standard deviation based on the monitoring data between the second calibration time node and the second traceability time node, and calculate the arithmetic mean of the monitoring data between the second calibration time node and the second traceability time node when the standard deviation meets the stability condition to determine the SO2 span check response value. In this process, the five-minute sliding judgment rule is also followed to ensure the stability and accuracy of the SO2 span check response value.

[0137] Compared with the SO2 span check result, the capture of the SO2 span calibration response value is more direct, that is, the SO2 instrument response value of the maintenance end time of the SO2 span check / calibration filled in the target work order is directly captured as the SO2 span calibration response value.

[0138] During the entire SO2 span inspection / calibration process, the authenticity of the target work order was authenticated through a precisely designed dual logic judgment mechanism and a five-minute sliding judgment automatic counting method.

[0139] In another embodiment of the present invention, a data quality control system for environmental monitoring is also provided. The system closely focuses on the quality control process of instrument status parameters and realizes comprehensive tracking and management of the quality control process through highly integrated functional modules. 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 substation 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 NO2, SO2, and O3, here referring to the target work order for SO2 span inspection / calibration.

[0142] Sliding calculation module: This module uses five minutes as a 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 the zero / span check response value.

[0143] Logical judgment module: Based on the consistency between the intercept and slope of the instrument status parameter data in different monitoring periods, it distinguishes the fraudulent work orders and triggers the alarm state. In this embodiment, two consecutive logical judgments are made to distinguish whether there are fraudulent work orders in the process of SO2 span inspection / calibration, and verify the accuracy of the data.

[0144] Return command module: As a module for conveying instructions, it will send return instructions to the site end through a predetermined communication protocol and transmission method, and can support remote control and management functions. After sending the return command, the return command module also needs to receive feedback information from the site end device to confirm the execution of the instruction and the return status of the data. The specific implementation method in this embodiment is that the central platform sends an SO2 span check / calibration instruction to the site end.

[0145] The environmental monitoring substation is divided into the following modules, including:

[0146] Quality control feedback module: This module seamlessly connects to the data acquisition module and is responsible for returning monitoring data and instrument status parameters within the quality control start and end time range according to instructions.

[0147] Data acquisition module: obtain monitoring data and instrument status parameters from environmental monitoring equipment in real time.

[0148] The system of the embodiment of the present invention executes the data quality control method for environmental monitoring as described above. The functions of each module of the system can refer to the corresponding description in the above method, which will not be repeated here.

[0149] In another embodiment of the present invention, an electronic device is provided. Figure 8 FIG. 2 shows a structural block diagram of an electronic device according to an embodiment of the present invention. Figure 8 As shown, the electronic device includes: a memory 100 and a processor 200, wherein the memory 100 stores a computer program that can be run on the processor 200. When the processor 200 executes the computer program, the data quality control method for environmental monitoring in the above embodiment is implemented. The number of the memory 100 and the processor 200 can be one or more.

[0150] The electronic device also includes:

[0151] The communication interface 300 is used to communicate with external devices and perform data exchange 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 connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or 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 chip, the memory 100, the processor 200 and the communication interface 300 can communicate with each other through an internal interface.

[0154] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present invention when the program is executed by a processor.

[0155] An embodiment of the present invention further provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the method provided by the embodiment of the present invention.

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

[0157] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) 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 supporting 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 RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct rambus RAM (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 process or function according to the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. 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 description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction 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 may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0161] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0162] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A data quality control method for environmental monitoring, It is 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; Based on the multiple monitoring data between the traceability time node and the calibration time node, the response value when the target device performs the inspection operation and / or calibration operation is determined, and the response value is returned to the target work order for quality control judgment and output of the quality control result.

2. The data quality control method for environmental monitoring according to claim 1, It is 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; Determine 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; 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 2, It is characterized in that Also includes: 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, the target work order is determined as a work order type including the inspection operation and the calibration operation.

4. The data quality control method for environmental monitoring according to claim 3, It is characterized in that Also includes: 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.

5. The data quality control method for environmental monitoring according to claim 4, It is characterized in that Also includes: 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 a response value for inspection to perform quality control judgment; 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.

6. The data quality control method for environmental monitoring according to claim 5, It is 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.

7. The data quality control method for environmental monitoring according to claim 1, It is 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.

8. A data quality control system for environmental monitoring, It is characterized in that Execute the data quality control method for environmental monitoring as described in any one of claims 1 to 7.

9. An electronic device, It is 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 7.

10. A computer-readable storage medium, It is 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 according to any one of claims 1 to 7 is implemented.

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