CN113391040B - Automatic calibration method for data artificial intelligence of atmospheric micro station - Google Patents
Automatic calibration method for data artificial intelligence of atmospheric micro station Download PDFInfo
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- CN113391040B CN113391040B CN202110786067.2A CN202110786067A CN113391040B CN 113391040 B CN113391040 B CN 113391040B CN 202110786067 A CN202110786067 A CN 202110786067A CN 113391040 B CN113391040 B CN 113391040B
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0006—Calibrating gas analysers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0006—Calibrating gas analysers
- G01N33/0008—Details concerning storage of calibration data, e.g. in EEPROM
Abstract
An artificial intelligent automatic calibration method for data of an atmospheric micro-station belongs to the technical field of atmospheric micro-station environment monitoring. Collecting real-time data of an atmospheric micro station, and processing and storing the real-time data in a cloud platform; the cloud platform automatically acquires latest hour data of an environmental website corresponding to the atmosphere micro station deployment area; the cloud platform compares and judges the acquired and processed atmospheric micro-station data with the environment standard website data, and if the acquired and processed atmospheric micro-station data exceeds the error range, the cloud platform performs automatic calibration operation.
Description
Technical Field
The invention relates to a data artificial intelligent automatic calibration method for an atmospheric micro-station, and belongs to the technical field of atmospheric micro-station environment monitoring.
Background
Environmental monitoring is the basis of environmental remediation and is increasingly being attended by people and by national policies. Traditional high cost, low density environmental monitoring stations have failed to meet today's monitoring needs. The low-cost and high-density environment monitoring system adopting the novel technology can play a high-efficiency monitoring benefit, and has become a mainstream development trend of environment monitoring.
The gridding atmospheric environment monitoring system adopts a new sensing technology, so that the environment monitoring cost is effectively reduced. By deploying monitoring points in a large range, high-density monitoring on the regional environment is realized, a gridding monitoring system is formed, a channel between on-line monitoring and government supervision is opened, and decision support is provided for scientific haze control and accurate pollution control. Is beneficial to the real-time performance, the accuracy and the scientificity of environmental control of the environmental monitoring.
However, the sensor properties of the atmospheric micro monitoring station are determined to be influenced by environmental factors such as temperature, humidity and air pressure, and the regular calibration maintenance is needed, and because the atmospheric micro station adopts a large-scale deployed grid monitoring mode, the number of devices is large, and the labor cost for the calibration maintenance is increased.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a data artificial intelligence automatic calibration method for an atmospheric micro station.
A data artificial intelligence automatic calibration method for an atmospheric micro station, comprising the steps of:
collecting real-time data of an atmospheric micro station, and processing and storing the real-time data in a cloud platform;
the cloud platform automatically acquires latest hour data of an environmental website corresponding to the atmosphere micro station deployment area;
the cloud platform compares and judges the acquired and processed atmospheric micro-station data with the environment standard website data, and if the acquired and processed atmospheric micro-station data exceeds the error range, the cloud platform performs automatic calibration operation.
The method also comprises the following steps:
and step 1, carrying out hour concentration calculation and history hour concentration storage on the data to obtain a concentration value required by calibration and comparison.
Hour concentration calculation:
V h ＝(V 0 +V 1 +V 2 +V 3 +…+V 57 +V 58 +V 59 )/60；
V h is an hour concentration value;
V 0 …V 59 is the concentration value of each minute in one hour, V 0 Represents the concentration value of 0 time division, V 59 A concentration value of 59 minutes;
and 2, the cloud platform acquires updated latest standard data according to a specific website and can switch and store according to different regions deployed by the atmosphere micro station.
And 3, when the data are compared, the data are required to be satisfied to be the hour concentration value at the same time. Meanwhile, the error of the micro station data and the standard data of the website is required to be correctly judged to meet the requirement, and the equipment calibration operation is carried out when the error range is exceeded.
In order to satisfy the hour concentration value when the comparison data are the same, the time offset of the website data needs to be set according to the actual situation.
In the step 3, the calculation mode for judging the error between the micro station data and the standard station data is as follows:
|V S -V D |≥V TH；
V S : standard station data;
V D : micro station data;
V TH : a threshold to initiate calibration;
when the above condition is satisfied, an automatic calibration operation is performed.
Wherein V is TH The numerical value is manually changeable and can be adjusted according to actual conditions.
The automatic calibration operation can be classified into a coefficient K value calibration and a sensor zero point calibration.
The calculation formula for the calibration of the coefficient K value is as follows:
K＝V S /(V D ±C)/K B；
k: automatically calibrating the proportionality coefficient;
V S : standard station data;
V D : micro station data;
c: a micro-station coefficient constant;
K B : old proportion coefficient of the micro station;
when the zero point of the sensor is calibrated, the platform directly transmits the standard concentration value to the atmospheric micro-station equipment, and the equipment automatically calibrates the zero point of the sensor.
The invention has the beneficial effects of solving the trouble that manual intervention and manual calibration are needed in the use of the atmospheric micro station, facilitating batch management and calibration maintenance and reducing a great deal of labor cost.
The comparison before and after using this calibration method is as follows:
as shown in fig. 2, prior to use: the sensor can drift under the condition of irregular calibration of the equipment, so that data can be accurately determined to have deviation, and the visual phenomenon is that the deviation from the standard station data is larger.
The device calibration needs to check the data condition of each station manually at fixed time, compare the data with the data of the provincial standard station, calculate the deviation and the correction coefficient, and then calibrate the remote device by manually sending instructions. The operation of a single site device as described above takes half an hour, and takes longer if all device sites are to be calibrated.
And manual calibration cannot guarantee real-time performance and calibration requirements of non-working days, so that the effect is not ideal.
As shown in fig. 3, after use: after the artificial intelligent automatic calibration scheme is used, the problem of data deviation caused by sensor drift is solved, the real-time performance of calibration is ensured, the drift correction can be responded in time, the time of manual intervention is saved, and a large amount of cost is saved.
And the effect of the manual automatic calibration scheme is obvious through comparison of the data curves before and after the use.
As can be seen from fig. 2 and 3, the device and the provincial control point data have a larger difference between values before starting the automatic calibration, and have a smaller difference between values after starting the automatic calibration.
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The invention, together with a further understanding of the many of its attendant advantages, will be best understood by reference to the following detailed description, when considered in conjunction with the accompanying drawings, which are included to provide a further understanding of the invention, and the accompanying drawings, illustrate and describe the invention and do not constitute a limitation to the invention, and wherein:
FIG. 1 is a flow chart of the automatic calibration of an atmospheric micro station according to the present invention.
FIG. 2 is a graph showing the effect of the present invention before use.
FIG. 3 is a graph showing the effect of the present invention after use.
The invention will be further described with reference to the drawings and examples.
Detailed Description
It will be apparent that many modifications and variations are possible within the scope of the invention, as will be apparent to those skilled in the art based upon the teachings herein.
The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Unless specifically stated or limited otherwise, the terms "mounted," "connected," "secured" and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
It will be understood by those skilled in the art that all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art unless defined otherwise.
In order to facilitate an understanding of the embodiments, a further explanation will be provided in connection with the following, and the respective embodiments do not constitute a limitation of the embodiments of the invention.
Example 1: as shown in fig. 1, a data artificial intelligence automatic calibration method for an atmospheric micro station includes the steps of:
the cloud platform collects real-time data of the atmospheric micro station, and processes and stores the real-time data;
the cloud platform automatically acquires latest hour data of an environmental website corresponding to the atmosphere micro station deployment area;
the cloud platform compares and judges the acquired and processed atmospheric micro-station data with the environment standard website data, and if the acquired and processed atmospheric micro-station data exceeds the error range, the cloud platform performs automatic calibration operation.
An artificial intelligence automatic calibration algorithm for data of an atmospheric micro station,
the cloud platform collects real-time data of the atmospheric micro station, and processes and stores the real-time data;
the cloud platform automatically acquires latest hour data of an environmental website corresponding to the atmosphere micro station deployment area;
the cloud platform performs comparison and judgment through the acquired and processed atmospheric micro-station data and the environment standard website data, and performs automatic calibration operation if the error range is exceeded;
in step 1, the data is required to be subjected to hour concentration calculation and history hour concentration storage so as to obtain a concentration value required by calibration and comparison.
And 2, the cloud platform can acquire updated latest standard data according to a specific website and can switch and store according to different regions deployed by the atmospheric micro station.
And 3, when the data are compared, the data are required to be satisfied to be the hour concentration value at the same time. Meanwhile, the error of the micro station data and the standard data of the website is required to be correctly judged to meet the requirement, and the equipment calibration operation is carried out when the error range is exceeded.
In order to satisfy the hour concentration value when the comparison data are the same, the time offset of the website data needs to be set according to the actual situation.
The error calculation mode for judging the micro station data and the standard station data is as follows:
|V S -V D |≥V TH ；
V S : standard station data;
V D : micro station data;
V TH : a threshold to initiate calibration;
when the above condition is satisfied, an automatic calibration operation is performed.
Wherein V is TH The numerical value is manually changeable and can be adjusted according to actual conditions.
The automatic calibration operation can be classified into a coefficient K value calibration and a sensor zero point calibration.
The calculation formula for the calibration of the coefficient K value is as follows:
K＝V S /(V D ±C)/K B ；
k: automatically calibrating the proportionality coefficient;
V S : standard station data;
V D : micro station data;
c: a micro-station coefficient constant;
K B : old proportion coefficient of the micro station;
when the zero point of the sensor is calibrated, the platform directly transmits the standard concentration value to the atmospheric micro-station equipment, and the equipment automatically calibrates the zero point of the sensor.
Example 2: as shown in fig. 1, a data artificial intelligence automatic calibration method for an atmospheric micro station includes the steps of: the following will further illustrate an atmospheric micro-station apparatus in a certain city.
The automatic calibration function of the device is firstly configured on the platform.
Standard data source, atmospheric micro station to be calibrated, time offset of data; a calibration mode; and starting a calibrated threshold value, clicking and storing after the information configuration is completed, and completing automatic calibration operation by the equipment.
The detailed steps are as follows:
and step 1, selecting standard data source site numbers. And selecting the standard data source site number nearest to the equipment to be calibrated as a standard source for use according to the equipment sites in different areas.
And 2, setting the number of the atmospheric micro station to be calibrated. Each atmospheric micro station has a unique number corresponding to the unique number, and the equipment needs to start an automatic calibration rule to set the number at the number position of the target MN.
And step 3, setting the time offset of the comparison data. The setting is used for eliminating time offset errors of the standard data source and the hour concentration of the station to be calibrated, and is set to 1 if the standard source is advanced by 1 hour from the hour concentration of the equipment to be calibrated, is set to-1 if the standard source is lagged by 1 from the hour concentration of the equipment to be calibrated, and is set to 0 if no deviation exists.
And 4, setting a calibration mode. The calibration mode is divided into two modes of concentration calibration and K value calibration, and corresponds to the calculation.
And 5, setting a threshold value for starting calibration. The value determines whether the platform performs automatic calibration operation on the equipment, and if the absolute error meets the set value, the platform performs calibration according to the error calculation mode of the micro-station data and the standard station data, which is mentioned in the step 3.
As described above, the embodiments of the present invention have been described in detail, but it will be apparent to those skilled in the art that many modifications can be made without departing from the spirit and effect of the present invention. Accordingly, such modifications are also entirely within the scope of the present invention.
Claims (1)
1. An automatic calibration method for data artificial intelligence of an atmospheric micro station is characterized by comprising the following steps:
collecting real-time data of an atmospheric micro station, and processing and storing the real-time data in a cloud platform;
the cloud platform automatically acquires latest hour data of an environmental website corresponding to the atmosphere micro station deployment area;
the cloud platform performs comparison and judgment through the acquired and processed atmospheric micro-station data and the environment standard website data, and performs automatic calibration operation if the error range is exceeded;
the method also comprises the following steps:
step 1, carrying out hour concentration calculation and history hour concentration storage on data to obtain a concentration value required by calibration and comparison;
the hour concentration calculation formula:
V h ＝(V 0 +V 1 +V 2 +V 3 +…+V 57 +V 58 +V 59 )/60；
V h is an hour concentration value;
V 0 …V 59 is the concentration value of each minute in one hour, V 0 Represents the concentration value of 0 time division, V 59 A concentration value of 59 minutes;
step 2, the cloud platform acquires updated latest standard data according to a specific website and can switch and store according to different regions deployed by the atmosphere micro station;
step 3, when the data are compared, the data are required to be satisfied as the hour concentration value at the same time; meanwhile, the error of the micro station data and the standard data of the website is required to be correctly judged to meet the requirement, and the equipment calibration operation is carried out when the error range is exceeded;
in order to meet the requirement of comparing the hour concentration value of the data at the same time, the time offset of the website data is required to be set according to the actual situation;
in the step 3, the calculation mode for judging the error between the micro station data and the standard station data is as follows:
|V S -V D |≥V TH ；
V S standard station data;
V D is micro station data;
V TH a threshold for initiating calibration;
when the above conditions are satisfied, performing an automatic calibration operation;
wherein V is TH The numerical value is set manually and is adjusted according to actual conditions;
the automatic calibration operation is divided into coefficient K value calibration and sensor zero point calibration, and the calculation formula of the coefficient K value calibration is as follows:
K＝V S /(V D ±C)/K B ；
k is an automatic calibration proportionality coefficient;
V S standard station data;
V D is micro station data;
c is the coefficient constant of the micro station;
K B is the old scaling factor of the micro station;
when the zero point of the sensor is calibrated, the platform directly transmits the standard concentration value to the atmospheric micro-station equipment, and the equipment automatically calibrates the zero point of the sensor.
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