CN110675131A - Quality monitoring data quality control auditing method - Google Patents
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- CN110675131A CN110675131A CN201910956320.7A CN201910956320A CN110675131A CN 110675131 A CN110675131 A CN 110675131A CN 201910956320 A CN201910956320 A CN 201910956320A CN 110675131 A CN110675131 A CN 110675131A
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- 238000000034 method Methods 0.000 title claims abstract description 66
- 238000012544 monitoring process Methods 0.000 title claims abstract description 55
- 238000003908 quality control method Methods 0.000 title claims abstract description 17
- 239000000523 sample Substances 0.000 claims abstract description 67
- 238000004458 analytical method Methods 0.000 claims abstract description 31
- 238000007689 inspection Methods 0.000 claims abstract description 13
- 230000002159 abnormal effect Effects 0.000 claims abstract description 10
- 238000012550 audit Methods 0.000 claims abstract description 9
- 239000013062 quality control Sample Substances 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 21
- 238000005070 sampling Methods 0.000 claims description 7
- 229910052729 chemical element Inorganic materials 0.000 claims description 2
- 150000001875 compounds Chemical class 0.000 claims description 2
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 6
- 239000002351 wastewater Substances 0.000 description 6
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 5
- 229910052785 arsenic Inorganic materials 0.000 description 5
- RQNWIZPPADIBDY-UHFFFAOYSA-N arsenic atom Chemical compound [As] RQNWIZPPADIBDY-UHFFFAOYSA-N 0.000 description 5
- 229910052804 chromium Inorganic materials 0.000 description 5
- 239000011651 chromium Substances 0.000 description 5
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 229910052757 nitrogen Inorganic materials 0.000 description 3
- 238000007726 management method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 150000002611 lead compounds Chemical class 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000000746 purification Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
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- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
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Abstract
A quality monitoring data quality control auditing method adopts at least one of a historical data trend comparison method, an intra-point data correlation inspection method, an inter-point data correlation inspection method and a quality control sample correlation error inspection method to audit data of a sample in quality monitoring; when the data of the audited sample is abnormal, warning information is sent out to assist auditors to pay attention to the sample data with problems, and therefore reliability of the sample data is guaranteed. The invention provides an automatic auditing method, which is used for providing warning information for abnormal data and assisting an auditor to focus on problematic analysis indexes, so that auditing efficiency is improved.
Description
Technical Field
The invention relates to the field of quality monitoring, in particular to a quality control auditing method for quality monitoring data.
Background
The quality control and audit of the environmental quality monitoring data is one of important means for guaranteeing the reliability of the monitoring data. At present, most of environment quality monitoring and management information systems are carried out by means of manual inspection and data comparison, the workload is large, the efficiency is low, errors are prone to occurring, and the information systems basically flow into forms.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the defects of the prior art, an automatic auditing method is provided to provide warning information for abnormal data and assist auditors to focus on problematic analysis indexes, so that auditing efficiency is improved.
In order to solve the problems, the technical scheme provided by the invention is as follows: a quality monitoring data quality control auditing method adopts at least one of a historical data trend comparison method, an intra-point data correlation inspection method, an inter-point data correlation inspection method and a quality control sample correlation error inspection method to audit data of a sample in quality monitoring; when the data of the audited sample is abnormal, warning information is sent out to assist auditors to pay attention to the sample data with problems, and therefore reliability of the sample data is guaranteed.
Preferably, the historical data trend comparison method is adopted, wherein the contents of the same detection items in the sampling samples at the same place at different time are filled into an electronic form for comparison, and a pattern is automatically generated according to the data in the electronic form for reference of an auditor.
Preferably, in the historical data trend comparison method, the content of the same detection item of the sample at the same location at different time is filled into an electronic form and compared, where the content of the same detection item is: automatically comparing the data of the detection items of the sampling samples to be audited with the data of the same detection items of the previous sampling samples at the same place in the spreadsheet; the automatically generated patterns from data in the spreadsheet include bar charts, pie charts, and line charts.
Preferably, the point-to-point data correlation check method is adopted by comparing the analysis results of the monitoring items in the same quality monitoring analysis result at the same place with the analysis results of the associated detection items.
Preferably, the monitoring items and the associated detection items are: the monitoring items and the related detection items both contain the same chemical elements or compounds.
Preferably, the method for checking the data correlation between points is used for comparing the detection results of the same monitoring item at different places in the same quality monitoring.
Preferably, the quality control sample correlation error checking method comprises a parallel sample auditing method and a standard sample auditing method, wherein the parallel sample auditing method and the standard sample auditing method are used for detecting the same sample for more than two times to ensure the reliability of sample data.
Preferably, the parallel sample auditing method is to perform more than two times of analysis on the same sample and perform comparative analysis on the analysis results.
Preferably, the method for examining and verifying the added standard sample comprises dividing the sample to be examined into more than two parts, adding a standard sample of monitoring item elements with known concentration into at least one part of the sample to be examined, calculating the difference between the concentration of the sample to be examined with the added standard sample and the concentration of the sample to be examined without the added standard sample, and comparing the calculated difference with the concentration of the standard sample.
The invention has the advantages that:
1. providing a monitoring data historical trend graph of a monitoring item: the method helps the auditor to find out unusual changes, concentrates on viewing the original analysis data, and reduces the viewing range.
2. Providing related auditing rules of all analysis items in the monitoring points: some analysis items have regular data size, and items which do not meet the rules are marked to attract the attention of auditors.
3. Providing related auditing rules of analysis items among different monitoring points: the analysis data of the same monitoring project is regular among different monitoring points, and projects which do not accord with the logic relation rule are marked to draw the attention of auditors.
4. Provided is an auditing method for analyzing item relevance, which comprises the following steps: the analysis data of quality control items such as parallel samples and standard samples are correlated, and the data with larger errors are marked to draw the attention of auditors.
Drawings
Fig. 1 is a schematic view of an auditing method according to a first embodiment.
Detailed Description
The quality control and audit of the environmental quality monitoring data is one of important means for guaranteeing the reliability of the monitoring data. Most of the current environmental quality monitoring and management information systems basically depend on manual inspection and data comparison, and have large workload and low efficiency. According to the method, analysis data such as monitoring items, parallel sample analysis items, labeled analysis items and historical analysis items of the same monitoring point are used as a basis, an automatic auditing method is provided, warning information can be sent out for abnormal data, and auditing personnel are assisted to focus on problematic sample data, so that auditing omission is effectively reduced, and auditing efficiency is improved.
The invention is described in one step with reference to the following examples and figures:
example one
The embodiment adopts four aspects of historical data trend comparison, point internal data correlation check, point-to-point data correlation check and quality control sample correlation error check for monitoring. When the condition that the project parameters are abnormal is monitored, the abnormal project parameters can be automatically marked to attract the attention of auditors.
In this embodiment, the quality monitoring of the wastewater is taken as an example, and the specific implementation process of the present invention is specifically described with reference to fig. 1. When the historical data trend comparison method is adopted to audit the data of the sample, the content of the same detection item in the sample at the same place at different time is filled into an electronic form, and a pattern is automatically generated according to the data in the form for reference of an auditor. For example: the auditor needs to audit whether the content of the trivalent chromium in the wastewater at the outlet of a certain treatment station in 2018 and 10 months is abnormal, the auditor can call out historical data of the content of the trivalent chromium in the wastewater at the outlet of the treatment station in 2018 and 3 months, 5 months and 7 months from a quality monitoring database, automatically generate a table containing the content data of the trivalent chromium in 2018 and 3 months, 5 months, 7 months and 10 months, and automatically generate patterns such as a bar chart, a broken line chart or a pie chart according to the data in the table. Thus, the auditor can quickly judge whether the content of the trivalent chromium in the wastewater from the outlet of a certain treatment station in 2018 in 10 months by seeing the content pattern of the trivalent chromium.
When the in-point data correlation inspection method is adopted to inspect the data of the sample, the analysis result of a certain monitoring item in the same quality monitoring analysis result in the same place is compared and analyzed with the analysis result of a certain detection item related to the monitoring item, and if the comparison result does not meet the requirement of the in-point inspection rule, error information is prompted to draw attention of an inspector. For example: and auditing the relation between two monitoring indexes of the ammonia nitrogen content and the total nitrogen content in the sample at the same sampling point by an auditor, and displaying warning information to remind the analyst to pay attention by the system if the ammonia nitrogen analysis data is larger than the total nitrogen analysis data. Because in-point audit regulations it has been specified that the ammonia nitrogen content is less than the total nitrogen content. The rule is generated by an editing tool provided by the system, and the tool is convenient for performing addition, deletion and modification operations on the relation between the checked projects.
When the data of the sample is checked by adopting the inter-point data correlation checking method, the detection results of the same monitoring item at different places are compared in the same quality monitoring, and if the detection results are abnormal, a warning is given out so as to draw the attention of a checker. For example: the auditor checks the arsenic content of the wastewater of a wastewater purification station at the inlet and the outlet during a certain quality monitoring: the arsenic content at the discharge outlet is instead greater than the arsenic content at the inlet, and the computer may sound and/or text to indicate an anomaly. Since in the inter-point audit regulations it has been specified that the arsenic content at the inlet is greater than the arsenic content at the outlet.
The quality control sample correlation error checking method comprises a parallel sample auditing method and a standard sample adding auditing method; the parallel sample auditing method is to analyze the same sample for multiple times and compare the results after multiple analyses. The method comprises the following specific steps that an auditor conducts least square normative simulation processing on multiple analysis result data of the same sample. If the linearity is beyond a reasonable range, displaying warning information: and (4) reminding an analyst that the analysis instrument is in a problem or the analysis operation is not standard, so that the data are inconsistent.
The method for auditing the added standard sample comprises the following steps: before a quality inspector distributes a sample to be detected to an analyst, the sample to be detected is divided into two parts, and a standard sample of a specific monitoring item element with known concentration is added into one of the samples to be detected (for example, a lead compound is added, so that the lead concentration is increased by 0.1mg/L, namely, the standard concentration is added). And (4) auditing the added standard sample by an auditor, comparing the difference of the lead concentration of the two specific samples, and if the difference is larger than the added standard concentration, indicating that the analysis process has problems or suspected data is counterfeit.
It will be apparent that modifications and variations are possible without departing from the principles of the invention as set forth herein.
Claims (9)
1. A quality monitoring data quality control auditing method is characterized in that a historical data trend comparison method, an intra-point data correlation inspection method, an inter-point data correlation inspection method and a quality control sample correlation error inspection method are adopted for a sample in quality monitoring to audit data of the sample; when the data of the audited sample is abnormal, warning information is sent out to assist auditors to pay attention to the sample data with problems, and therefore reliability of the sample data is guaranteed.
2. The quality control auditing method according to claim 1 where the historical data trend comparison method is used to populate an electronic form with the content of the same test item at different times in the same sample at the same location and compare it, and automatically generate a pattern based on the data in the electronic form for reference by the auditor.
3. The quality monitoring data quality control auditing method according to claim 2, characterized in that the contents of the same detection items of the same sampling sample at the same place in the historical data trend comparison method at different times are filled in an electronic form and compared, and the comparison is carried out by: automatically comparing the data of the detection items of the sampling samples to be audited with the data of the same detection items of the previous sampling samples at the same place in the spreadsheet; the automatically generated patterns from data in the spreadsheet include bar charts, pie charts, and line charts.
4. The quality control auditing method for quality monitoring data according to claim 1 characterized in that the point-to-point data correlation checking method is adopted by comparing the analysis results of monitoring items in the same quality monitoring analysis result at the same place with the analysis results of associated detection items.
5. A quality monitoring data quality control auditing method according to claim 4, characterized in that the monitoring items and associated detection items are: the monitoring items and the related detection items both contain the same chemical elements or compounds.
6. The quality control auditing method for quality monitoring data according to claim 1 where the inter-point data correlation check method is used to compare the detection results of the same monitoring item at different locations in the same quality monitoring.
7. The quality control auditing method for quality monitoring data according to claim 1, characterized in that the quality control sample correlation error checking method comprises a parallel sample auditing method and a standard sample auditing method, and the parallel sample auditing method and the standard sample auditing method both carry out more than two detections on the same sample to ensure the reliability of sample data.
8. The quality control auditing method for quality monitoring data according to claim 7 characterized in that the parallel sample auditing method is to analyze the same sample twice more and compare the analysis results.
9. The quality control auditing method according to claim 7, characterized in that the standard sample adding auditing method is to divide the sample to be examined into two or more parts, add a standard sample of monitoring item elements of known concentration to at least one part of the sample to be examined, find the difference between the concentration of the sample to be examined to which the standard sample is added and the concentration of the sample to be examined to which the standard sample is not added, and compare the found difference with the concentration of the standard sample.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111429100A (en) * | 2020-03-25 | 2020-07-17 | 陕西合友网络科技有限公司 | Construction project cost system and cost method |
| CN113702601A (en) * | 2021-10-28 | 2021-11-26 | 北京万维盈创科技发展有限公司 | Method and device for identifying falsification of exhaust gas monitoring data |
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| CN109034252A (en) * | 2018-08-01 | 2018-12-18 | 中国科学院大气物理研究所 | The automatic identification method of air quality website monitoring data exception |
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2019
- 2019-10-10 CN CN201910956320.7A patent/CN110675131A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104135521A (en) * | 2014-07-29 | 2014-11-05 | 广东省环境监测中心 | Method and system of identifying data abnormal values of environment automatic monitoring network |
| CN107436277A (en) * | 2017-07-12 | 2017-12-05 | 广东旭诚科技有限公司 | The single index data quality control method differentiated based on similarity distance |
| CN109034252A (en) * | 2018-08-01 | 2018-12-18 | 中国科学院大气物理研究所 | The automatic identification method of air quality website monitoring data exception |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111429100A (en) * | 2020-03-25 | 2020-07-17 | 陕西合友网络科技有限公司 | Construction project cost system and cost method |
| CN113702601A (en) * | 2021-10-28 | 2021-11-26 | 北京万维盈创科技发展有限公司 | Method and device for identifying falsification of exhaust gas monitoring data |
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Application publication date: 20200110 |