A method and system for analyzing water quality monitoring data

Abstract

This invention provides a water quality monitoring data analysis method and system, belonging to the field of data processing technology. Specifically, it includes: during water sampling, processing the water sample according to a sampling strategy to obtain the sample; when the monitoring results of the sampled water at the water quality monitoring station do not match the historical monitoring data, performing multiple monitoring processes on the remaining sampled water according to a preset strategy to obtain other monitoring results; determining an adjustment scheme for the water sample sampling strategy based on the deviation data between the monitoring results and other monitoring results in different monitoring processes; and using the adjustment scheme to determine the reagent anomaly identification strategy, thereby improving the timeliness of reagent anomaly identification and processing.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, and in particular relates to a method and system for analyzing water quality monitoring data. Background Technology

[0002] For unmanned water quality monitoring stations located in rural sewage, reservoirs, lakes, and water source areas, which achieve automatic water quality monitoring, similar technical solutions are provided in invention patent applications CN202510379380.2 "A Method, Device, Equipment and Medium for Watershed Water Quality Prediction" and CN202510053635.6 "A Method for Optimizing the Layout of Bay Water Quality Monitoring Stations." However, the above technical solutions all have the following technical problems:

[0003] In the process of water quality monitoring and analysis, existing technical solutions often use built-in refrigerators to store reagents in order to improve the maintenance-free period. However, long-term storage inevitably leads to changes in the reliability of the reagents. At the same time, the water quality status of the automatically controlled samples of the water quality monitoring device will also change over time, resulting in increasingly serious measurement deviations of the instrument. Therefore, it is necessary to determine how to implement anomaly identification strategies for reagent status in order to avoid affecting the accuracy of the automatic calibration results of the equipment when the reagent status is abnormal.

[0004] To address the aforementioned technical problems, this application provides a water quality monitoring data analysis method and system. Summary of the Invention

[0005] To achieve the objectives of this invention, the following technical solution is adopted:

[0006] Specifically, this application provides a water quality monitoring data analysis method, which includes:

[0007] S1 uses the automatic calibration data of the water quality monitoring station to determine the monitoring results of the water quality monitoring station under the self-controlled sample. Based on the monitoring results, when it is determined that the fluctuation of the water quality change trend of the self-controlled sample is within a preset range, proceed to the next step.

[0008] S2, based on the historical monitoring data of water samples from the water quality monitoring station, matches the monitoring results of different historical monitoring times with the previous historical monitoring times, and combines the time distribution data of the historical monitoring times to determine the water sample extraction strategy of the water quality monitoring station.

[0009] When S3 is extracting water samples, it extracts and processes the water samples according to the water sample extraction strategy. When the matching between the monitoring results of the extracted water samples and the historical monitoring data at the water quality monitoring station does not meet the requirements, it performs multiple monitoring processes on the remaining extracted water samples according to the preset strategy to obtain other monitoring results.

[0010] S4 determines an adjustment scheme for the water sample extraction and treatment strategy based on the deviation data between the monitoring results and other monitoring results in different monitoring treatments, and in combination with the monitoring treatments in which other monitoring results exist, and uses the adjustment scheme to determine the reagent anomaly identification strategy.

[0011] The beneficial effects of this application are as follows:

[0012] In this application, when the matching between the monitoring results of the extracted water sample and the historical monitoring data at the water quality monitoring station does not meet the requirements, the reagent is subjected to multiple monitoring processes based on the remaining extracted water sample according to a preset strategy to obtain other monitoring results. This achieves secondary verification processing of the same sample, thereby enabling the identification of reagent anomalies from the perspective of repeatability and improving the efficiency and reliability of anomaly identification processing.

[0013] In this application, an adjustment scheme for the water sample extraction and treatment strategy is determined based on the deviation data between the monitoring results in different monitoring and treatment cycles and other monitoring results. This not only avoids the waste of electricity and reagents caused by frequently following the water sample extraction strategy due to the similarity between the monitoring results and other monitoring results, but also enables the accurate identification of reagents in abnormal states, thereby ensuring the accuracy and timeliness of the identification and treatment of abnormal reagent states.

[0014] A further technical solution is that the automatic calibration data includes the water quality monitoring data of the water quality monitoring station under self-controlled samples.

[0015] It is understandable that the historical monitoring count refers to the number of historical monitoring counts after the reagent was replaced.

[0016] Specifically, the self-controlled sample is a standard sample used for calibration processing at the water quality monitoring station.

[0017] A further technical solution is that the monitoring results include monitoring data from different automatic calibration processes.

[0018] A further technical solution involves determining that the fluctuation trend of the water quality change trend of the self-controlled sample is within a preset range, specifically including:

[0019] Based on the monitoring results of the self-controlled sample in different automatic calibration processes, the number of automatic calibration processes of the self-controlled sample in the most recent preset time period is determined and used as the reference number of calibration processes.

[0020] The number of deviation processing steps in the reference standard processing steps is determined by the deviation of the monitoring results between different reference calibration processing steps;

[0021] Based on the number of deviation processing operations, it is determined whether the fluctuation of the water quality change trend of the self-controlled sample is within a preset range.

[0022] A further technical solution is that the method for determining the adjustment scheme of the water sample extraction and processing strategy is as follows:

[0023] Based on the deviation data between the monitoring results and other monitoring results in different monitoring treatment cycles, the deviation amount between the monitoring results and other monitoring results in different monitoring treatment cycles is determined.

[0024] Based on the deviation from other monitoring results, determine the number of monitoring processes where the deviation from other monitoring results is outside the preset deviation range, and treat these as suspected anomalies.

[0025] The number of suspected anomalies is used to determine the adjustment plan for the water sample extraction and processing strategy.

[0026] Furthermore, when the number of suspected anomalies does not meet the requirements, i.e., when it exceeds the preset threshold for the number of suspected anomalies, it is determined that the reagent is abnormal, and the abnormality alert for the reagent is directly processed, and the water sample extraction process is no longer performed.

[0027] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described water quality monitoring data analysis method when running the computer program.

[0028] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0029] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0030] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings;

[0031] Figure 1This is a flowchart of a water quality monitoring data analysis method;

[0032] Figure 2 It is a flowchart for determining the fluctuation of water quality trends in self-controlled samples within a preset range;

[0033] Figure 3 This is a flowchart illustrating the method for determining the water sampling strategy at a water quality monitoring station.

[0034] Figure 4 This is a flowchart illustrating the method for determining the adjustment scheme of water sample extraction and treatment strategy;

[0035] Figure 5 It is a framework diagram of a computer system. Detailed Implementation

[0036] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0037] In this invention, given the risk of water quality deterioration and fluctuation in the self-controlled samples, and the inability to guarantee the reliability of automatic calibration processing, a sampling strategy is determined. This involves extracting samples that can be used for multiple testing processes in a single extraction. When the measurement results of a sample show deviations, the remaining samples are used for secondary analysis of water quality monitoring data, thereby ensuring the reliability of the calibration analysis process.

[0038] Based on the monitoring results of the self-controlled sample in different automatic calibration treatments, if there is an automatic calibration treatment in which the water quality monitoring results are inconsistent with those in other automatic calibration treatments, then the fluctuation of the water quality trend of the self-controlled sample is determined to be within the preset range.

[0039] The number of historical monitoring times that are inconsistent with the monitoring results of the most recent preset time period is taken as the number of water quality change monitoring times. When the number of water quality change monitoring times is greater than the preset monitoring time threshold, the water sampling strategy is to extract multiple samples that can be used for water quality measurement in one time because there is a risk of water quality change.

[0040] When the monitoring results of the sampled water are inconsistent with the previous historical monitoring data, it is necessary to use the remaining sampled water to perform multiple monitoring processes to obtain other monitoring results.

[0041] When the monitoring results in different monitoring treatments are consistent with the verification monitoring results, it is not necessary to draw multiple samples that can be used for water quality measurement in one go. Only when the monitoring results are inconsistent with the previous historical monitoring data is it necessary to draw samples that can be tested multiple times.

[0042] Example 1

[0043] Specifically, such as Figure 1 As shown, this application provides a water quality monitoring data analysis method, specifically including:

[0044] S1 uses the automatic calibration data of the water quality monitoring station to determine the monitoring results of the water quality monitoring station under the self-controlled sample. Based on the monitoring results, when it is determined that the fluctuation of the water quality change trend of the self-controlled sample is within a preset range, proceed to the next step.

[0045] Furthermore, the automatic calibration data includes water quality monitoring data from the water quality monitoring station under self-controlled samples.

[0046] It is understandable that the historical monitoring count refers to the number of historical monitoring counts after the reagent was replaced.

[0047] Specifically, the self-controlled sample is a standard sample used for calibration processing at the water quality monitoring station.

[0048] Specifically, the monitoring results include monitoring data from different automatic calibration processes.

[0049] Specifically, such as Figure 2 As shown, determining that the fluctuation of the water quality trend of the self-controlled sample is within a preset range specifically includes:

[0050] Based on the monitoring results of the self-controlled sample in different automatic calibration processes, the number of automatic calibration processes of the self-controlled sample in the most recent preset time period is determined and used as the reference number of calibration processes.

[0051] The number of deviation processing steps in the reference standard processing steps is determined by the deviation of the monitoring results between different reference calibration processing steps;

[0052] Based on the number of deviation processing operations, it is determined whether the fluctuation of the water quality change trend of the self-controlled sample is within a preset range.

[0053] It should be noted that the number of deviation processing times is the reference calibration processing times when the deviation of the monitoring results from the reference calibration processing times does not meet the requirements, which is greater than the preset number threshold. That is, when the deviation of the monitoring results is greater than the preset deviation, it is determined that the deviation does not meet the requirements.

[0054] For a specific example, the number of reference calibration processes that do not meet the requirements in terms of deviation from the monitoring results of the reference calibration process number is taken as the data deviation number. When the data deviation number is more than 3 times, it is determined that the deviation does not meet the requirements.

[0055] Specifically, when the proportion of deviation processing times in the reference calibration processing times is above a preset percentage, it is determined that the fluctuation of the water quality trend of the self-controlled sample is outside the preset range, and the self-controlled sample needs to be replaced immediately. It is impossible to use the self-controlled sample to accurately assess the true state of the reagent. When the proportion of deviation processing times in the reference calibration processing times is not above the preset percentage, but within the preset percentage range, it is determined that the fluctuation of the water quality trend of the self-controlled sample is outside the preset range. When it is outside the preset percentage range, there is no need to replace the reagent, and the self-controlled sample can be used to accurately assess the state of the reagent.

[0056] In one embodiment, when the percentage of deviation processing times in the reference calibration processing times is greater than 0.1, it is determined that the fluctuation of the water quality trend of the self-controlled sample is outside the preset range, and the self-controlled sample needs to be replaced immediately. The self-controlled sample cannot be used to accurately assess the true state of the reagent. When the percentage of deviation processing times in the reference calibration processing times is between 0.05 and 0.1, it is determined that the fluctuation of the water quality trend of the self-controlled sample is within the preset range. When it is less than 0.05, there is no need to replace the reagent, and the self-controlled sample can be used to accurately assess the state of the reagent.

[0057] In another possible embodiment, determining that the fluctuation of the water quality trend of the self-controlled sample is within a preset range specifically includes:

[0058] S11 Based on the monitoring results of the self-controlled sample in different automatic calibration processing times, determine the number of automatic calibration processing times of the self-controlled sample in the most recent preset time period, and use it as the reference calibration processing times. By the deviation of the monitoring results between different reference calibration processing times, determine the number of deviation processing times in the reference standard processing times.

[0059] It should be noted that if there are no deviation treatment times in the above steps, it can be directly determined that the fluctuation of the water quality trend of the self-controlled sample is not within the preset range, and there is no need to replace the reagent. The self-controlled sample can be used to achieve an accurate assessment of the reagent status.

[0060] In another possible embodiment, if there are deviation processing times, it is necessary to further determine whether the deviation processing times meet the requirements. Specifically, when the proportion of deviation processing times in the reference calibration processing times is above a preset proportion, it is determined that the fluctuation of the water quality change trend of the self-controlled sample is not within the preset range, and the self-controlled sample needs to be replaced immediately. It is impossible to use the self-controlled sample to accurately assess the true state of the reagent.

[0061] If the number of deviation processing times is not above the preset percentage in the reference calibration processing times, specifically if it is not within the preset percentage range, the impact on the overall calibration reliability is not significant due to the small number of deviation processing times. Therefore, there is no need to replace the reagents. The self-controlled sample can be used to accurately assess the reagent status. In other cases, the number of similar processing times should be determined.

[0062] S12 determines the number of similar treatments in the number of deviation treatments based on the monitoring results of different deviation treatments;

[0063] Furthermore, it should be noted that the number of similar processing times refers to the number of deviation processing times required to meet the requirements for the deviation between monitoring results. Specifically, if the deviation of the monitoring results is less than a preset threshold, it is determined that the deviation meets the requirements.

[0064] Additionally, it is understandable that when different deviation treatments do not have similar treatments in other deviation treatments, it indicates that the deviation of the monitoring results between different deviation treatments is also quite serious. Therefore, it can be directly determined that the fluctuation of the water quality change trend of the self-controlled sample is not within the preset range, and the self-controlled sample needs to be replaced immediately. It is impossible to use the self-controlled sample to accurately assess the true state of the reagent.

[0065] In another possible embodiment, when there are similar processing times among other deviation processing times, that is, when there are similar processing times among other deviation processing times, the deviation processing times that belong to similar processing times are divided into the same group. When the number of groups is less than the preset group number threshold, it indicates that the monitoring results between different deviation processing times are highly similar. Therefore, it can be directly determined that the fluctuation of the water quality change trend of the self-controlled sample is within the preset range.

[0066] Furthermore, if the number of combinations is not less than the preset combination number threshold, specifically when the number of combinations is more than 4, it indicates that the deviation of the monitoring results between different deviation treatment times is also quite serious. Therefore, it can be directly determined that the fluctuation of the water quality change trend of the self-controlled sample is not within the preset range, and the self-controlled sample needs to be replaced immediately. The self-controlled sample cannot be used to accurately assess the true state of the reagent. In other cases, proceed to the next step.

[0067] S13 determines whether the fluctuation of the water quality change trend of the self-controlled sample is within a preset range based on the number of similar treatments with different deviation treatments.

[0068] In one possible embodiment, the water quality fluctuation value of the self-controlled sample is determined by multiplying the proportion of the number of deviation processing times in the number of reference calibration processing times by the number of combinations. When the water quality fluctuation value is within a preset fluctuation value range, it is determined that the fluctuation of the water quality trend of the self-controlled sample is within the preset range. When the water quality fluctuation value is greater than the preset fluctuation threshold, it is determined that the fluctuation of the water quality trend of the self-controlled sample is not within the preset range, and the self-controlled sample needs to be replaced immediately. It is impossible to use the self-controlled sample to accurately assess the true state of the reagent. In other cases, it is not necessary to replace the reagent, and the self-controlled sample can be used to achieve an accurate assessment of the reagent state.

[0069] S2, based on the historical monitoring data of water samples from the water quality monitoring station, matches the monitoring results of different historical monitoring times with the previous historical monitoring times, and combines the time distribution data of the historical monitoring times to determine the water sample extraction strategy of the water quality monitoring station.

[0070] Furthermore, the time distribution data of the historical monitoring times is determined based on the monitoring time of the historical monitoring times.

[0071] Specifically, such as Figure 3 As shown, the method for determining the water sampling strategy of the water quality monitoring station is as follows:

[0072] By matching the monitoring results of different historical monitoring times with the previous historical monitoring times, the historical monitoring times in which the monitoring results within the most recent preset time period are inconsistent with the previous historical monitoring results are determined, and these are taken as the water quality change monitoring times;

[0073] The water sampling strategy for the water quality monitoring station is determined based on the number of water quality change monitoring sessions.

[0074] It is understandable that when the number of water quality change monitoring exceeds the preset monitoring number threshold, it indicates that the probability of the monitoring results changing is relatively high. Therefore, in this application, when the monitoring results change, reagent verification is required, and the need for verification is high. In order to avoid sampling again, verification is also required based on a second sampling of water samples. Since a baseline monitoring result is required, at least three monitoring is required, which will result in waste of reagents. Therefore, in this case, the water sampling strategy is to directly extract a preset amount of water samples, and when there is an anomaly in the monitoring results, that is, when the number of historical monitoring results that are inconsistent with the monitoring results in the most recent preset time period is greater than the preset monitoring number, a second verification is directly performed.

[0075] In addition, if the number of water quality change monitoring times does not exceed the preset monitoring time threshold, there is no need to directly extract the preset amount of water samples. When the water quality monitoring results of the extracted water samples are inconsistent with the monitoring results of the previous historical monitoring times, the water samples will be extracted and processed for reagent verification.

[0076] Optionally, the method for determining the water sampling strategy of the water quality monitoring station is as follows:

[0077] By matching the monitoring results of different historical monitoring times with the previous historical monitoring times, the historical monitoring times in which the monitoring results within the most recent preset time period are inconsistent with the previous historical monitoring results are determined, and these are taken as the water quality change monitoring times;

[0078] Based on the distribution data of the monitoring time of the number of water quality change monitoring times within the most recent preset time period, the interval length of the monitoring time for different number of water quality change monitoring times is determined.

[0079] The number of water quality change monitoring times that have an interval of less than a preset interval threshold are taken as the number of aggregated monitoring times, and the water sampling strategy of the water quality monitoring station is determined by the number of aggregated monitoring times.

[0080] It should be noted that when the number of clustered monitoring is high, i.e., exceeds the preset threshold, it indicates that the water quality of the monitoring target of the water quality monitoring station may frequently change due to the location of the water quality monitoring station and the flow of the water body. Therefore, based on this, the preset amount of water samples are directly extracted, and when the monitoring results are abnormal, a secondary verification process is directly performed.

[0081] When S3 is extracting water samples, it extracts and processes the water samples according to the water sample extraction strategy. When the matching between the monitoring results of the extracted water samples and the historical monitoring data at the water quality monitoring station does not meet the requirements, it performs multiple monitoring processes on the remaining extracted water samples according to the preset strategy to obtain other monitoring results.

[0082] It is understood that the water sample is obtained by extracting and processing the water sample according to the aforementioned water sampling strategy, specifically including:

[0083] The water sample is obtained by extracting the water sample using the extraction amount corresponding to the water sample extraction strategy.

[0084] Specifically, determining that the matching between the monitoring results of the extracted water sample and historical monitoring data at the water quality monitoring station does not meet the requirements includes:

[0085] The monitoring results of the extracted water samples at the water quality monitoring station are used as real-time monitoring results;

[0086] The number of historical monitoring times that are inconsistent with the real-time monitoring results is obtained and used as the deviation monitoring times;

[0087] By measuring the number of deviations within the most recent preset time period, it is determined whether the matching between the monitoring results of the extracted water sample at the water quality monitoring station and the historical monitoring data meets the requirements.

[0088] It is understandable that when the proportion of deviation monitoring times in the most recent preset time period to the historical monitoring times does not meet the requirements, that is, when the proportion of deviation monitoring times in the most recent preset time period to the historical monitoring times is greater than 0.3, it is determined that the matching between the monitoring results of the extracted water sample at the water quality monitoring station and the historical monitoring data does not meet the requirements.

[0089] It is understood that the monitoring results include one of the following: CODcr, CODMn, ammonia nitrogen, total phosphorus, total ammonia, expandable chlorophyll, and cyanobacteria.

[0090] S4 determines an adjustment scheme for the water sample extraction and treatment strategy based on the deviation data between the monitoring results and other monitoring results in different monitoring and treatment cycles, and uses the adjustment scheme to determine the anomaly identification strategy for reagents.

[0091] Furthermore, based on the remaining extracted water samples, multiple monitoring processes are performed according to a preset strategy to obtain other monitoring results, specifically including:

[0092] The remaining extracted water samples were subjected to a preset number of monitoring processes to obtain a preset number of other monitoring results.

[0093] Specifically, such as Figure 4 As shown, the method for determining the adjustment scheme of the water sample extraction and treatment strategy is as follows:

[0094] Based on the deviation data between the monitoring results and other monitoring results in different monitoring treatment cycles, the deviation amount between the monitoring results and other monitoring results in different monitoring treatment cycles is determined.

[0095] Based on the deviation from other monitoring results, determine the number of monitoring processes where the deviation from other monitoring results is outside the preset deviation range, and treat these as suspected anomalies.

[0096] The adjustment plan for the water sample extraction and processing strategy is determined by the number of suspected anomalies and the number of monitoring and processing times of other monitoring results within a preset time period.

[0097] Table 1 Monitoring results of monitoring data from different dimensions

[0098]

[0099] It should be noted that, within a preset time period, in one possible embodiment, if the number of monitoring and processing of other monitoring results within the most recent month is less than the preset threshold for the number of monitoring and processing times, in order to ensure the reliability of the water sample verification process, even if the monitoring results are consistent with the previous monitoring data, it is still necessary to perform extraction and processing according to the original extraction and processing strategy at least once out of every three times, and to determine other monitoring results, thereby achieving the verification process of the reagent.

[0100] It should also be noted that, within a preset time period, in one possible embodiment, if the number of monitoring and processing of other monitoring results within the most recent month is not less than the preset monitoring and processing threshold, and if the number of suspected abnormalities does not meet the requirements, i.e., is greater than the preset suspected abnormality threshold, then it is determined that the reagent is abnormal, and the abnormality alert for the reagent is directly processed, and the water sample extraction process is no longer performed.

[0101] Specifically, in one possible embodiment, when the number of suspected anomalies meets the requirement, that is, when it is not greater than the preset threshold for the number of suspected anomalies, if there are no suspected anomalies or the number of suspected anomalies is within the range of the number of anomalies, that is, less than 3 times, then it is only necessary to extract a preset amount of water samples and perform secondary verification processing if the results are inconsistent with previous monitoring results.

[0102] Furthermore, in one possible embodiment, if there are suspected anomalies and the number of suspected anomalies is not within the preset number of anomalies, then if the number of suspected anomalies is more than 6, the water sample extraction strategy is still followed to obtain the anomaly identification processing of the extracted water sample and reagent. If the number of anomaly risks is between 3 and 6, the water sample extraction strategy is followed according to the preset extraction frequency to obtain the anomaly identification processing of the extracted water sample and reagent. In other cases, only when the results are inconsistent with previous monitoring results is it necessary to extract a preset amount of water sample and perform secondary verification processing.

[0103] In one possible embodiment, the water sample is extracted according to the water sample extraction strategy once every three times to obtain anomaly identification processing of the extracted water sample and reagents. The other two times, the water sample is extracted in a preset amount only if it is inconsistent with the previous monitoring results, and then a secondary verification process is performed on it.

[0104] In another embodiment, the method for determining the adjustment scheme of the water sample extraction and processing strategy is as follows:

[0105] S41 determines the amount of deviation between the monitoring results and other monitoring results in different monitoring processing times based on the deviation data between the monitoring results and other monitoring results in different monitoring processing times. Based on the amount of deviation with other monitoring results, the number of monitoring processing times in which the amount of deviation between the monitoring results and other monitoring results is not within the preset deviation range is determined and these are regarded as suspected abnormal times.

[0106] It should be noted that in the above steps, in one possible embodiment, if the number of monitoring and processing of other monitoring results within the most recent month is less than the preset monitoring and processing threshold, in order to ensure the reliability of the water sample verification process, even if the monitoring results are consistent with the previous monitoring data, it is still necessary to perform extraction and processing according to the original extraction and processing strategy at least once every three times, and to determine other monitoring results, so as to achieve the verification process of the reagent.

[0107] It should also be noted that, within a preset time period, in one possible embodiment, if the number of monitoring and processing of other monitoring results within the most recent month is not less than the preset monitoring and processing threshold, and if the number of suspected abnormalities does not meet the requirements, i.e., is greater than the preset suspected abnormality threshold, then it is determined that the reagent is abnormal, and the abnormality alert for the reagent is directly processed, and the water sample extraction process is no longer performed.

[0108] Specifically, when the number of suspected anomalies meets the requirements, i.e., it is not greater than the preset threshold for the number of suspected anomalies, if there are no suspected anomalies or the number of suspected anomalies is within the range of the number of anomalies, i.e., less than 3 times, then it is only necessary to extract a preset amount of water samples and perform secondary verification processing if the results are inconsistent with previous monitoring results.

[0109] It should also be noted that if there are suspected abnormalities and the number of suspected abnormalities is not within the preset abnormality range, then proceed to the next step to determine the number of result deviations.

[0110] S42 determines the deviation between the monitoring results of different suspected anomalies, and based on the deviation, determines other suspected anomalies whose deviation from the monitoring results of the suspected anomalies is greater than a preset deviation threshold, and uses them as the result deviation number. Suspected anomalies with the same result deviation number are classified into the same type, and the number of types is obtained.

[0111] It should also be noted that if there are no deviations in the results of different suspected anomalies in the above steps, the monitoring results of different suspected anomalies will be similar. Therefore, the monitoring results may be inconsistent due to water quality. In this case, it is only necessary to extract a preset amount of water sample and perform secondary verification if the results are inconsistent with previous monitoring results.

[0112] Furthermore, if there are discrepancies in the number of suspected anomalies, it is necessary to further determine whether the number of types meets the requirements. It is understood that when the number of types is 3 or more, it indicates that there is a certain degree of deviation in the water quality data of different suspected anomalies. Therefore, based on this, it is determined that the reagent is abnormal, and the abnormality warning of the reagent is directly processed, and no further water sample extraction is performed.

[0113] Another understandable approach is that if the number of types is less than three, the process proceeds directly to the next step: determining the water sample extraction and processing strategy.

[0114] S43 determines the adjustment scheme of the water sample extraction and processing strategy by the number of suspected anomalies, the number of types, and the number of monitoring and processing times of other monitoring results within a preset time period.

[0115] In one possible embodiment, the abnormal risk value of the reagent is determined based on the sum of the ratio of the number of suspected abnormalities to the number of preset abnormalities and the ratio of the number of types to the number of preset types. When the abnormal risk value is greater than the preset risk threshold, it is determined that the reagent is abnormal, and the abnormality reminder of the reagent is directly processed, and the water sample extraction process is no longer performed.

[0116] Specifically, if the abnormal risk value is not greater than the preset risk threshold, or if the abnormal risk value is within the preset risk value range (i.e., the risk is relatively high), then the water sample extraction process will still be carried out according to the water sample extraction strategy to obtain the abnormal identification and processing of the extracted water sample and reagent.

[0117] If the abnormal risk value is not within the preset risk value range, and if the number of monitoring and processing of other monitoring results within the preset time period is greater than the preset number of processing, then regardless of whether the monitoring result is consistent with previous monitoring data, the water sample is extracted and processed according to the preset extraction frequency and the water sample extraction strategy to obtain the abnormal identification and processing of the extracted water sample and reagent.

[0118] It should be noted that in other cases, the water sample is extracted according to the preset extraction frequency and the water sample extraction strategy to obtain the abnormal identification and processing of the extracted water sample and reagent. In other cases, it is only necessary to extract the preset amount of water sample and perform secondary verification processing when the results are inconsistent with previous monitoring results.

[0119] In one possible embodiment, according to a preset sampling frequency, specifically, once every three times, the water sample is extracted according to the water sample extraction strategy to obtain the extracted water sample and reagent anomaly identification processing, and the other two times, the water sample is extracted in a preset amount only if it is inconsistent with the previous monitoring results, and then a secondary verification process is performed on it.

[0120] It is understood that the determination of the reagent anomaly identification strategy using the aforementioned adjustment scheme specifically includes:

[0121] When the adjustment scheme indicates that the reagent is abnormal, there is no need to perform abnormal reagent identification processing.

[0122] When the adjustment scheme requires sampling a preset amount of water samples and performing secondary verification only when the results are inconsistent with previous monitoring results, the water samples sampled during the secondary verification process are used for reagent anomaly identification. In other cases, the reagent anomaly identification strategy is not changed, and the original water sample sampling strategy and anomaly identification strategy are still used for reagent anomaly identification.

[0123] It should be noted that the determination of whether they are consistent is based on the deviation between the verified monitoring results and the actual monitoring results, divided by whether the monitoring results are within the preset range. Specifically, consistency will be determined when the deviation is between 0 and 0.02.

[0124] Example 2

[0125] Secondly, such as Figure 5As shown, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described water quality monitoring data analysis method when running the computer program.

[0126] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0127] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0128] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for analyzing water quality monitoring data, characterized in that, Specifically, it includes: Using the automatic calibration data of the water quality monitoring station, determine the monitoring results of the water quality monitoring station under the self-controlled sample. Based on the monitoring results, determine that the fluctuation of the water quality change trend of the self-controlled sample is within a preset range, and then proceed to the next step. Based on the historical monitoring data of water samples from the water quality monitoring station, the monitoring results of different historical monitoring times are matched with the previous historical monitoring times, and combined with the time distribution data of the historical monitoring times, the water sampling strategy of the water quality monitoring station is determined. When water samples are extracted, the water samples are extracted and processed according to the water sample extraction strategy. When the matching between the monitoring results of the extracted water samples and the historical monitoring data at the water quality monitoring station does not meet the requirements, the reagents are processed multiple times based on the remaining extracted water samples according to the preset strategy to obtain other monitoring results. Based on the deviation data between the monitoring results in different monitoring and treatment cycles and other monitoring results, an adjustment scheme for the water sample extraction and treatment strategy is determined, and the adjustment scheme is used to determine the anomaly identification strategy for reagents. The automatic calibration data includes water quality monitoring data from the water quality monitoring station under a self-controlled sample, which is a standard sample used for calibration processing of the water quality monitoring station.

2. The water quality monitoring data analysis method as described in claim 1, characterized in that, Determining that the fluctuation of the water quality trend of the self-controlled sample is within a preset range specifically includes: Based on the monitoring results of the self-controlled sample in different automatic calibration processes, the number of automatic calibration processes of the self-controlled sample in the most recent preset time period is determined and used as the reference number of calibration processes. The number of deviation processing steps in the reference calibration processing steps is determined by the deviation of the monitoring results between different reference calibration processing steps; Based on the number of deviation processing operations, it is determined whether the fluctuation of the water quality change trend of the self-controlled sample is within a preset range.

3. The water quality monitoring data analysis method as described in claim 1, characterized in that, The time distribution data of the historical monitoring times is determined based on the monitoring time of the historical monitoring times.

4. The water quality monitoring data analysis method as described in claim 1, characterized in that, The method for determining the water sampling strategy of the water quality monitoring station is as follows: By matching the monitoring results of different historical monitoring times with the previous historical monitoring times, the historical monitoring times in which the monitoring results within the most recent preset time period are inconsistent with the previous historical monitoring results are determined, and these are taken as the water quality change monitoring times; The water sampling strategy for the water quality monitoring station is determined based on the number of water quality change monitoring sessions.

5. The water quality monitoring data analysis method as described in claim 4, characterized in that, If the number of water quality monitoring changes does not exceed the preset monitoring number threshold, there is no need to directly extract the preset number of water samples. When the monitoring results of the extracted water samples are inconsistent with the monitoring results of the previous historical monitoring times, the water samples will be extracted and processed for reagent verification.

6. The water quality monitoring data analysis method as described in claim 1, characterized in that, The water sample is extracted and processed according to the aforementioned water sampling strategy, specifically including: The water sample is obtained by extracting the water sample using the extraction amount corresponding to the water sample extraction strategy.

7. The water quality monitoring data analysis method as described in claim 1, characterized in that, The method for determining the adjustment scheme of the water sample extraction and treatment strategy is as follows: Based on the deviation data between the monitoring results and other monitoring results in different monitoring treatment cycles, the deviation amount between the monitoring results and other monitoring results in different monitoring treatment cycles is determined. Based on the deviation from other monitoring results, determine the number of monitoring processes where the deviation from other monitoring results is outside the preset deviation range, and treat these as suspected anomalies. The number of suspected anomalies is used to determine the adjustment plan for the water sample extraction and processing strategy.

8. A computer system, comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that, when the processor runs the computer program, it executes a water quality monitoring data analysis method according to any one of claims 1-7.

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