CN109521155B - Quality control method and device - Google Patents
Quality control method and device Download PDFInfo
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- CN109521155B CN109521155B CN201811140724.0A CN201811140724A CN109521155B CN 109521155 B CN109521155 B CN 109521155B CN 201811140724 A CN201811140724 A CN 201811140724A CN 109521155 B CN109521155 B CN 109521155B
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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
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method, e.g. intermittent, or the display, e.g. digital
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention provides a quality control method, which comprises the following steps: determining a first substation comprising a first standard device and at least one quality control point; establishing a meta model of the first quality control point in each scene, and calculating pollutant concentration data of the first quality control point in each scene; when the difference value between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimum, determining an alternative model from a meta model library; the alternative model is sent to a first non-quality control point in non-quality control points closest to the first quality control point; acquiring pollutant concentration data of a first non-quality control point; and calculating the pollutant concentration data of the first non-quality control point according to the pollutant concentration data of the first non-quality control point and the alternative model. Therefore, quality control of pollutant concentration data of quality control points and non-quality control points is realized, accuracy of the pollutant concentration data is improved, robustness is enhanced, and accuracy and effectiveness of the whole environment monitoring work are improved.
Description
Technical Field
The present invention relates to the field of data processing and equipment precision, and in particular, to a quality control method and apparatus.
Background
With the rapid development of various industries, a large amount of harmful substances such as smoke, sulfur dioxide, nitrogen oxides, carbon monoxide, hydrocarbons, etc. are generated. The harmful substances are continuously discharged into the atmosphere, and when the content exceeds the limit of the environment, natural physical, chemical and ecological balance is destroyed, so that atmospheric pollution is formed, and life, work and health of people are endangered. With the advent of nationwide and wide range of haze weather, the term PM2.5 is coming into public view. PM2.5 refers to particulates having an ambient aerodynamic equivalent diameter of 2.5 microns or less. It can be suspended in air for a longer time, and the higher the content concentration of the suspension in the air is, the more serious the air pollution is.
With the rapid development of the economic society, environmental problems become one of important obstacle factors for the development of the society, and solving good environmental problems becomes an urgent problem for various countries.
One of the important bases for solving the environmental problems is to accurately grasp the current environmental situation, including which specific environmental problems exist, etc., and the environmental monitoring work is also the key for solving the environmental problems and knowing the current environmental situation in time, wherein the accuracy of the environmental monitoring data becomes the key point and the key link of the environmental monitoring work.
The environment monitoring data is the basis for formulating environment protection policies and measures, and is also the basis for environment management, law enforcement, statistics, information release and environment protection target responsibility system assessment. Therefore, whether the quality of the environment detection data is positive for the environment protection work.
The atmospheric pollution monitoring is to measure the type and concentration of pollutants in the atmospheric environment and observe the time-space distribution and change rule. The atmospheric pollution monitoring aims to identify pollutant in the atmosphere, master the distribution and diffusion rule of the pollutant, and monitor the emission and control conditions of an atmospheric pollution source. Because the monitoring area is large in range, manpower and material resources are limited, and difficulty is brought to atmospheric pollution monitoring.
In the prior art, the pollutant concentration data of a region are obtained through equipment of a national control point or a provincial control point, but the obtained pollutant concentration data cannot reflect the actual pollutant concentration of a region due to the limited quantity of the equipment.
Disclosure of Invention
The embodiment of the invention aims at overcoming the defects in the prior art and provides a quality control method and device.
In order to solve the above problems, in a first aspect, the present invention provides a quality control method, including:
determining a first substation, wherein the first substation comprises first standard equipment and at least one quality control point;
establishing a meta model of a first quality control point in the at least one quality control point under each scene; the meta-model of the first quality control point in each scene forms a meta-model library;
acquiring pollutant concentration data of the first quality control point;
calculating the pollutant concentration data of the first quality control point in each scene according to the pollutant concentration data of the first quality control point and the meta-model of the first quality control point in each scene;
comparing the pollutant concentration data of the first quality control point with the standard pollutant concentration data measured by the first standard equipment in each scene respectively;
determining an alternative model from the meta-model library when the difference between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimal; the alternative model is sent to a first non-quality control point in non-quality control points closest to the first quality control point; wherein the non-quality control point is not in any substation, and the alternative model is used as a meta-model of the first non-quality control point;
acquiring pollutant concentration data of the first non-quality control point;
and calculating the pollutant concentration data of the first non-quality control point according to the pollutant concentration data of the first non-quality control point and the alternative model.
In one possible implementation, the method further includes before:
performing a standard gas experiment on the quality control equipment, and screening the quality control equipment passing through the standard gas experiment;
and setting the quality control equipment passing through the standard gas experiment in the quality control point and the non-quality control point.
In one possible implementation manner, the establishing a meta-model of a first quality control point in the at least one quality control point under each scene specifically includes:
using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 Calculating a meta model of the first quality control point in the first scene; wherein θ 1 And theta 2 Is a preset model training parameter, theta 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained.
In one possible implementation, the method further comprises thereafter:
determining the number of quality control points and the number of non-quality control points of the first area;
in a preset time, acquiring pollutant concentration data measured by a quality control point of the first area and pollutant concentration data measured by a non-quality control point of the first area;
determining contaminant concentration data for a quality control point of the first region and contaminant concentration data for a non-quality control point of the first region;
calculating the average value of the pollutant concentration data of the quality control points of the first area and the pollutant concentration data of the non-quality control points of the first area;
and obtaining pollutant concentration data of the first area according to the average value.
In a second aspect, the present invention provides a quality control device, comprising:
the determining unit is used for determining a first substation, and the first substation comprises first standard equipment and at least one quality control point;
the building unit is used for building a meta model of a first quality control point in the at least one quality control point under each scene; the meta-model of the first quality control point in each scene forms a meta-model library;
the acquisition unit is used for acquiring pollutant concentration data of the first quality control point;
the calculation unit is used for calculating the pollutant concentration data of the first quality control point in each scene according to the pollutant concentration data of the first quality control point and the meta model of the first quality control point in each scene;
the comparison unit is used for comparing the pollutant concentration data of the first quality control point with the standard pollutant concentration data measured by the first standard equipment under each scene respectively;
the determining unit is further configured to determine an alternative model from the meta-model library when a difference between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimal;
the sending unit is used for sending the alternative model to a first non-quality control point in non-quality control points closest to the first quality control point; wherein the non-quality control point is not in any substation, and the alternative model is used as a meta-model of the first non-quality control point;
the acquisition unit is further used for acquiring pollutant concentration data of the first non-quality control point;
the calculation unit is further configured to calculate contaminant concentration data of the first non-quality control point according to the contaminant concentration data of the first non-quality control point and the candidate model.
In one possible implementation, the apparatus further includes:
the screening unit is used for carrying out a standard gas experiment on the quality control equipment and screening out the quality control equipment passing through the standard gas experiment;
the setting unit is used for setting the quality control equipment passing through the standard gas experiment in the quality control point and the non-quality control point.
In a possible implementation manner, the establishing unit is specifically configured to:
using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 Calculating a meta model of the first quality control point in the first scene; wherein θ 1 And theta 2 Is a preset model training parameter, theta 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained.
In a possible implementation manner, the determining unit is further configured to determine the number of quality control points and the number of non-quality control points in the first area;
the acquisition unit is further used for acquiring pollutant concentration data measured by the quality control points of the first area and pollutant concentration data measured by the non-quality control points of the first area in a preset time;
the determining unit is further configured to determine contaminant concentration data of a quality control point of the first area and contaminant concentration data of a non-quality control point of the first area;
the calculating unit is further used for calculating the average value of the pollutant concentration data of the quality control point of the first area and the pollutant concentration data of the non-quality control point of the first area;
the calculation unit is further configured to obtain contaminant concentration data of the first area according to the average value.
In a third aspect, the present invention provides an apparatus comprising a memory for storing a program and a processor for performing the method of any of the first aspects.
In a fourth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any of the first aspects.
In a fifth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method according to any of the first aspects.
By applying the quality control method and the quality control device provided by the embodiment of the invention, the quantity of the equipment for acquiring the pollutant concentration data is increased through the quality control points in the sub-station and the non-quality control points outside the sub-station, then the pollutant concentration data of the quality control points and the pollutant concentration data of the standard equipment are subjected to quality control to obtain the alternative model of the non-quality control points, so that the quality control of the pollutant concentration data of the non-quality control points is also carried out, thereby realizing the quality control of the pollutant concentration data of the quality control points and the non-quality control points, improving the accuracy of the measured pollutant concentration data, enhancing the robustness and improving the accuracy and the effectiveness of the whole environment monitoring work.
Drawings
FIG. 1 is a schematic flow chart of a quality control method according to a first embodiment of the present invention;
fig. 2 is a schematic flow chart of a quality control method according to a second embodiment of the present invention.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In order to better explain the method related to the present application, a "quality control point" will be first described below.
In order to achieve the purpose of fine control and management of regional atmospheric pollution, a target region is divided into different grids according to different monitoring requirements and environmental characteristics to carry out point location arrangement, and the concentration of relevant pollutants in each grid is monitored in real time, which is called gridding monitoring. The key pollution area divided by the urban meshing supervision work is called as a hot spot mesh. The high-density grid monitoring network is used for reasonably arranging various functional monitoring points in the area, can reflect the air quality change of the key polluted area, meets the requirement of area environment air monitoring, and objectively evaluates the air quality of the key polluted area.
The distribution condition of the pollutants can be evaluated according to the diffusion, migration and conversion rules of the local pollutants, and reasonable monitoring points can be determined by combining the feasibility of resources and economy, so that the obtained data is representative.
At the determined reasonable monitoring point location, a gridding monitoring device can be set. The gridding monitoring equipment is a detection method adopting light scattering, has small volume and light weight, and is used for continuously and automatically monitoring the pollutant condition in the ambient air.
At a site, there is generally one standard monitoring device (also referred to as a national control device or a provincial control device), at least 3 pieces of grid-connected monitoring devices can be installed in a certain range of the site, and the 3 pieces of grid-connected monitoring devices are referred to as quality control devices, form a quality control point, and a plurality of quality control points can be distributed on the site.
The point where the gridding monitoring apparatus is located, which is not within the site, is referred to as a normal point.
Fig. 1 is a schematic flow chart of a quality control method according to an embodiment of the invention. The application scenario of the method is a meshed monitoring network, the execution subject of the method may be a device with a computing function, for example, a computer, a mobile phone or a quality control device, and the computer, the mobile phone or the quality control device may be connected with the meshed monitoring device, and the connection may be performed by a wireless or wired communication manner, which is not limited in this application. As shown in fig. 1, the method comprises the steps of:
The first standard device may be a national control device or a provincial control device.
Prior to step 101, the method further comprises, prior to: performing a standard gas experiment on the quality control equipment, and screening the quality control equipment passing through the standard gas experiment; and setting the quality control equipment passing through the standard gas experiment in the quality control point and the non-quality control point. Therefore, consistency of the grid monitoring equipment of the quality control points and the non-quality control points is guaranteed.
The metamodels of the first quality control point under each scene form a metamodel library.
In the following, taking 3 scenes and 3 quality control points in the first substation as examples, the first scene, the second scene, the third scene, the first quality control point, the second quality control point and the third quality control point are respectively recorded. The metamodels of the first quality control point in the three scenes can be marked as a1, a2 and a3, the metamodels of the second quality control point in the three scenes can be marked as b1, b2 and b3, and the metamodels of the third quality control point in the three scenes can be marked as c1, c2 and c3.
Among them, the scenes include, but are not limited to, a dust scene, a high humidity scene, a firework scene, and a strong wind scene.
By way of example, and not limitation, the generation process of the meta model a1 is described, and the corresponding scene may be the first scene. It should be noted that the generation formulas of each meta-model are different, and the present application will be described by taking a1 as an example.
Firstly, PM2.5 and humidity data of the first quality control point in the past month are read as input quantities, and data of the first substation in the past month are read as output quantities to conduct linear regression. Can obtain theta 1 And theta 2 These two models train parameters.
Then, at θ 1 And theta 2 The two model training parameters are known quantities and are calculated using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 And calculating a meta-model of the first quality control point in the first scene.
Wherein θ 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained. Therefore, the meta-model in the first scene can be calculated, and a meta-model library is convenient to construct.
And 103, acquiring pollutant concentration data of the first quality control point.
Specifically, after the meshed monitoring device is put in a fixed (may also be referred to as a preset) point location, the meshed monitoring device may acquire pollutant concentration data of the point location in real time, where the pollutant concentration data may include a type of pollutant and a concentration value of the pollutant under the type of pollutant.
By way of example and not limitation, the contaminants may be any of fine particulate matter (PM 2.5), inhalable particulate matter (PM 10), nitrogen dioxide (NO 2), sulfur dioxide (SO 2), carbon monoxide (CO), ozone (O3), and total volatile organic compounds (Total Volatile Organic Compounds, TVOC).
The present application is described with respect to PM2.5 as an example. It will be appreciated that in subsequent studies, the contaminants may be any combination of the above contaminants, and that units of different contaminants may be processed by normalization to obtain normalized contaminant concentration data for comprehensive determination of the normalized contaminant concentration data.
By way of example and not limitation, continuing to take 3 scenes as an example, the contaminant concentration data of the first quality control point is respectively brought into the metamodel of the first scene, the metamodel of the second scene and the metamodel of the third scene to obtain three contaminant concentration data.
And step 105, comparing the pollutant concentration data of the first quality control point with the standard pollutant concentration data measured by the first standard equipment in each scene.
And 106, determining an alternative model from the meta-model library when the difference value between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimum.
Specifically, the pollutant concentration data of the first quality control point in the first scene, the pollutant concentration data of the second scene and the pollutant concentration data of the third scene are compared with the standard pollutant concentration data measured by the national control device, when the difference value is minimum, the corresponding meta model is determined as an alternative model, for example, the difference value between the obtained standard pollutant concentration data and a1, a2 and a3 is: difference from a1 < difference from a2 < difference from a3, a1 may be determined as an alternative model.
The non-quality control points are points which are not in the sub-station, and grid monitoring equipment is also arranged in the non-quality control points.
The pollutant concentration data can be obtained through the gridding monitoring equipment of the non-quality control points.
At this time, the meta model of the quality control point closest to the first quality control point (and the distance between the first non-quality control point and the first quality control point is inferior to the distance between the first quality control point and the first non-quality control point) may be selected as the candidate model when the data of the first quality control point is invalid, and the calculation method of the meta model is similar to the above description and will not be repeated here.
Therefore, the quantity of equipment for acquiring the pollutant concentration data is increased through the quality control points in the sub-station and the non-quality control points outside the sub-station, then the pollutant concentration data of the quality control points and the pollutant concentration data of standard equipment are quality controlled to obtain an alternative model of the non-quality control points, so that the quality control of the pollutant concentration data of the non-quality control points is also carried out, the quality control of the pollutant concentration data of the quality control points and the non-quality control points is realized, the accuracy of the measured pollutant concentration data is improved, the robustness is enhanced, and the accuracy and the effectiveness of the whole environment monitoring work are improved.
Subsequently, the pollutant concentration data in the region can be used to check the pollutant concentration data.
Specifically, the method further comprises the following steps: firstly, determining the number of quality control points and the number of non-quality control points of a first area; then, in a preset time, acquiring pollutant concentration data measured by a quality control point of the first area and pollutant concentration data measured by a non-quality control point of the first area; next, determining contaminant concentration data for a quality control point of the first region and contaminant concentration data for a non-quality control point of the first region; then, calculating the average value of the pollutant concentration data of the quality control points of the first area and the pollutant concentration data of the non-quality control points of the first area; and finally, obtaining pollutant concentration data of the first area according to the average value.
The preset time may be one hour, one day, one month, etc., and may be set as needed. Thereby, the accuracy of the acquired contaminant concentration data of the first region is improved.
Fig. 2 is a schematic structural diagram of a quality control device according to a second embodiment of the present invention. The quality control device can be applied in a quality control method, as shown in fig. 2, and the quality control device includes: a determining unit 201, a setting-up unit 202, an obtaining unit 203, a calculating unit 204, a comparing unit 205, and a transmitting unit 206.
The determining unit 201 is configured to determine a first substation, where the first substation includes a first standard device and at least one quality control point.
The establishing unit 202 is configured to establish a meta-model of a first quality control point of the at least one quality control points under each scene. And the metamodels of the first quality control point under each scene form a metamodel library.
The acquiring unit 203 is configured to acquire contaminant concentration data of the first quality control point.
The calculating unit 204 is configured to calculate the pollutant concentration data of the first quality control point in each scene according to the pollutant concentration data of the first quality control point and the meta-model of the first quality control point in each scene.
The comparing unit 205 is configured to compare the pollutant concentration data of the first quality control point with the standard pollutant concentration data measured by the first standard device in each scene.
The determining unit 201 is further configured to determine an alternative model from the meta model library when a difference between the contaminant concentration data of the first quality control point and the standard contaminant concentration data is minimal.
The sending unit 206 is configured to send the candidate model to a first non-quality control point of the non-quality control points closest to the first quality control point; wherein the non-quality control point is not in any substation, and the alternative model is used as a meta-model of the first non-quality control point.
The obtaining unit 203 is further configured to obtain contaminant concentration data of the first non-quality control point.
The calculating unit 204 is further configured to calculate the pollutant concentration data of the first non-quality control point according to the pollutant concentration data of the first non-quality control point and the alternative model.
Further, the apparatus further comprises: a screening unit 207 and a setting unit 208.
The screening unit 207 is configured to perform a standard gas experiment on the quality control device, and screen the quality control device passing the standard gas experiment.
The setting unit 208 is configured to set the quality control device passing the standard gas experiment in the quality control point and the non-quality control point.
Further, the establishing unit 202 is specifically configured to:
using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 Calculating a meta model of the first quality control point in the first scene; wherein θ 1 And theta 2 Is a preset model training parameter, theta 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained.
Further, the determining unit 201 is further configured to determine the number of quality control points and the number of non-quality control points in the first area;
the obtaining unit 203 is further configured to obtain, in a preset time, the pollutant concentration data measured at the quality control point of the first area and the pollutant concentration data measured at the non-quality control point of the first area.
The determining unit 201 is further configured to determine contaminant concentration data of a quality control point of the first region and contaminant concentration data of a non-quality control point of the first region.
The calculating unit 204 is further configured to calculate a mean value of the pollutant concentration data of the quality control point of the first region and the pollutant concentration data of the non-quality control point of the first region.
The calculation unit 204 is further configured to obtain contaminant concentration data of the first region based on the average value.
Therefore, the quantity of equipment for acquiring the pollutant concentration data is increased through the quality control points in the sub-station and the non-quality control points outside the sub-station, then the pollutant concentration data of the quality control points and the pollutant concentration data of standard equipment are quality controlled to obtain an alternative model of the non-quality control points, so that the quality control of the pollutant concentration data of the non-quality control points is also carried out, the quality control of the pollutant concentration data of the quality control points and the non-quality control points is realized, the accuracy of the measured pollutant concentration data is improved, the robustness is enhanced, and the accuracy and the effectiveness of the whole environment monitoring work are improved.
An embodiment of the present invention provides an apparatus, including a memory and a processor, where the memory is configured to store a program, and the memory may be connected to the processor through a bus. The memory may be non-volatile memory, such as a hard disk drive and flash memory, in which software programs and device drivers are stored. The software program can execute various functions of the above method provided in the first embodiment of the present invention; the device driver may be a network and interface driver. The processor is configured to execute a software program, where the software program is executed to implement the method provided in the first embodiment of the present invention.
A fourth embodiment of the present invention provides a computer program product containing instructions, which when executed on a computer, cause the computer to perform the method provided by the first embodiment of the present invention.
The fifth embodiment of the present invention provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method provided in the first embodiment of the present invention is implemented.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The foregoing detailed description of the invention has been presented for purposes of illustration and description, and it should be understood that the invention is not limited to the particular embodiments disclosed, but is intended to cover all modifications, equivalents, alternatives, and improvements within the spirit and principles of the invention.
Claims (10)
1. A quality control method, comprising:
determining a first substation, wherein the first substation comprises first standard equipment and at least one quality control point;
establishing a meta model of a first quality control point in the at least one quality control point under each scene; the meta-model of the first quality control point in each scene forms a meta-model library;
acquiring pollutant concentration data of the first quality control point;
calculating the pollutant concentration data of the first quality control point in each scene according to the pollutant concentration data of the first quality control point and the meta-model of the first quality control point in each scene;
comparing the quality control data of the first quality control point with the standard pollutant concentration data measured by the first standard equipment in each scene respectively;
determining an alternative model from the meta-model library when the difference between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimal;
the alternative model is sent to a first non-quality control point in non-quality control points closest to the first quality control point; wherein the non-quality control point is not in any substation, and the alternative model is used as a meta-model of the first non-quality control point;
acquiring pollutant concentration data of the first non-quality control point;
and calculating the pollutant concentration data of the first non-quality control point according to the pollutant concentration data of the first non-quality control point and the alternative model.
2. The quality control method according to claim 1, further comprising, before the method:
performing a standard gas experiment on the quality control equipment, and screening the quality control equipment passing through the standard gas experiment;
and setting the quality control equipment passing through the standard gas experiment in the quality control point and the non-quality control point.
3. The quality control method according to claim 1, wherein the establishing a meta-model of a first quality control point of the at least one quality control points in each scene specifically includes:
using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 Calculating a meta model of the first quality control point in the first scene; wherein θ 1 And theta 2 Is a preset model training parameter, theta 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained.
4. The quality control method according to claim 1, further comprising, after the method:
determining the number of quality control points and the number of non-quality control points of the first area;
in a preset time, acquiring pollutant concentration data measured by a quality control point of the first area and pollutant concentration data measured by a non-quality control point of the first area;
determining contaminant concentration data for a quality control point of the first region and contaminant concentration data for a non-quality control point of the first region;
calculating the average value of the pollutant concentration data of the quality control points of the first area and the pollutant concentration data of the non-quality control points of the first area;
and obtaining pollutant concentration data of the first area according to the average value.
5. A quality control device, comprising:
the determining unit is used for determining a first substation, and the first substation comprises first standard equipment and at least one quality control point;
the building unit is used for building a meta model of a first quality control point in the at least one quality control point under each scene; the meta-model of the first quality control point in each scene forms a meta-model library;
the acquisition unit is used for acquiring pollutant concentration data of the first quality control point;
the calculation unit is used for calculating the pollutant concentration data of the first quality control point in each scene according to the pollutant concentration data of the first quality control point and the meta model of the first quality control point in each scene;
the comparison unit is used for comparing the pollutant concentration data of the first quality control point with the standard pollutant concentration data measured by the first standard equipment under each scene respectively;
the determining unit is further configured to determine an alternative model from the meta-model library when a difference between the pollutant concentration data of the first quality control point and the standard pollutant concentration data is minimal;
the sending unit is used for sending the alternative model to a first non-quality control point in non-quality control points closest to the first quality control point; wherein the non-quality control point is not in any substation, and the alternative model is used as a meta-model of the first non-quality control point;
the acquisition unit is further used for acquiring pollutant concentration data of the first non-quality control point;
the calculation unit is further configured to calculate contaminant concentration data of the first non-quality control point according to the contaminant concentration data of the first non-quality control point and the candidate model.
6. The quality control device of claim 5, further comprising:
the screening unit is used for carrying out a standard gas experiment on the quality control equipment and screening out the quality control equipment passing through the standard gas experiment;
the setting unit is used for setting the quality control equipment passing through the standard gas experiment in the quality control point and the non-quality control point.
7. The quality control apparatus according to claim 5, wherein the establishing unit is specifically configured to:
using the formula y=θ 1 ×x 1 +θ 2 ×x 2 +θ 0 Calculating a meta model of the first quality control point in the first scene; wherein θ 1 And theta 2 Is a preset model training parameter, theta 0 To preset the intercept, x 1 For the pollutant concentration data of the first quality control point at the first time, x 2 The humidity data of the first quality control point at the first time is obtained.
8. The quality control device of claim 5, wherein,
the determining unit is further used for determining the number of quality control points and the number of non-quality control points in the first area;
the acquisition unit is further used for acquiring pollutant concentration data measured by the quality control points of the first area and pollutant concentration data measured by the non-quality control points of the first area in a preset time;
the determining unit is further configured to determine contaminant concentration data of a quality control point of the first area and contaminant concentration data of a non-quality control point of the first area;
the calculating unit is further used for calculating the average value of the pollutant concentration data of the quality control point of the first area and the pollutant concentration data of the non-quality control point of the first area;
the calculation unit is further configured to obtain contaminant concentration data of the first area according to the average value.
9. An apparatus comprising a memory for storing a program and a processor for performing the method of any of claims 1-4.
10. A computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any of claims 1-4.
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