CN111896681A - Semi-supervised semi-learning type atmospheric pollutant system - Google Patents
Semi-supervised semi-learning type atmospheric pollutant system Download PDFInfo
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- CN111896681A CN111896681A CN202010653290.5A CN202010653290A CN111896681A CN 111896681 A CN111896681 A CN 111896681A CN 202010653290 A CN202010653290 A CN 202010653290A CN 111896681 A CN111896681 A CN 111896681A
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- 239000003344 environmental pollutant Substances 0.000 title claims abstract description 32
- 231100000719 pollutant Toxicity 0.000 title claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 26
- 238000007781 pre-processing Methods 0.000 claims abstract description 23
- 238000004458 analytical method Methods 0.000 claims abstract description 17
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 claims description 21
- 238000004804 winding Methods 0.000 claims description 20
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims description 14
- 238000001514 detection method Methods 0.000 claims description 7
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 claims description 6
- 238000002372 labelling Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 description 8
- 238000012351 Integrated analysis Methods 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 2
- 238000003909 pattern recognition Methods 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 238000012271 agricultural production Methods 0.000 description 1
- 239000000809 air pollutant Substances 0.000 description 1
- 231100001243 air pollutant Toxicity 0.000 description 1
- 229910021529 ammonia Inorganic materials 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 150000002222 fluorine compounds Chemical class 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000005304 joining Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 150000004767 nitrides Chemical class 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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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
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array
-
- 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
- G01N33/0067—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method, e.g. intermittent, or the display, e.g. digital by measuring the rate of variation of the concentration
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- G01N33/0068—
Abstract
The invention discloses a semi-supervised and semi-learning type atmospheric pollutant system, which relates to the technical field of atmospheric pollutants and comprises a data processing module, a data preprocessing module, a learning classification module, a comprehensive analysis module, an auxiliary sorting module and a computer terminal module, wherein the output end of the data processing module is electrically connected with the input end of the data preprocessing module, the output end of the data preprocessing module is electrically connected with the input end of the learning classification module, the data acquisition module can realize the acquisition and the collection of data, the data preprocessing module realizes the dimensionality reduction processing of the data, so that the acquired data parameters can be transmitted with the data classification module, the learning classification module realizes the classification of the data, the comprehensive analysis module realizes the analysis processing of the data, and the auxiliary sorting module realizes the sorting of the analyzed data, and then, the data can be viewed and monitored through the computer terminal module.
Description
Technical Field
The invention relates to the technical field of atmospheric pollutants, in particular to a semi-supervised semi-learning type atmospheric pollutant system.
Background
The atmospheric environment refers to the physical, chemical and biological characteristics of air on which organisms live, and harmful gases such as ammonia, sulfur dioxide, carbon monoxide, nitrides, fluorides and the like discharged by human life or industrial and agricultural production can change the composition of the original air, cause pollution, cause global climate change and destroy ecological balance;
Semi-Supervised Learning (SSL) is a key problem in the research of the field of pattern recognition and machine Learning, and is a Learning method combining Supervised Learning and unsupervised Learning, wherein the Semi-Supervised Learning uses a large amount of unlabelled data and simultaneously uses labeled data to perform pattern recognition work, when the Semi-Supervised Learning is used, the Semi-Supervised Learning requires as few personnel as possible to perform work, and simultaneously can bring higher accuracy, the monitoring of atmospheric pollutants is realized by using the combination of the Semi-Supervised Learning and the atmospheric pollutants, the method is a new development direction, the workload of workers can be effectively reduced, the traditional method is to realize the analysis of detection data of the atmospheric pollutants by using a Semi-Supervised Learning machine, the estimation of concentration indexes of the atmospheric pollutants is realized in the analysis process, but due to the difference in height, the atmospheric pollution degrees are different, so that the condition of inaccurate evaluation is easily caused, and therefore a semi-supervised semi-learning type atmospheric pollutant system is provided for solving the problems.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a semi-supervised semi-learning type atmospheric pollutant system.
In order to achieve the purpose, the invention adopts the following technical scheme:
the utility model provides a semi-supervised semi-learning type atmospheric pollutants system, includes data processing module, data preprocessing module, study classification module, integrated analysis module, supplementary arrangement module, computer terminal module, data processing module's output and data preprocessing module's input electric connection, data preprocessing module's output and study classification module's input electric connection, study classification module's output and integrated analysis module's input electric connection, integrated analysis module's output and supplementary arrangement module's input electric connection, the output phrase computer terminal module's of supplementary arrangement module input electric connection.
Preferably, the data processing module comprises an atmospheric pollutant concentration acquisition device, and the data processing module is electrically connected with the data preprocessing module through a wireless network.
Preferably, the computer terminal module comprises a computer unit, a mouse unit and a keyboard unit.
Preferably, the learning classification module exists in the form of a learning classifier, so that classification processing of data is realized, and meanwhile, labeling and recording of unlabeled parameter classification can be realized.
Preferably, the auxiliary arrangement module realizes arrangement of the analysis data, so that workers can clearly see pollution conditions of atmospheric environmental pollutants in different heights through the computer terminal module.
Preferably, the atmospheric pollutant concentration detection device comprises a base, an upper end side wall of the base is fixedly connected with a mounting plate and a fixed plate in sequence, the mounting plate is connected with the fixed plate through a rotating shaft, a winding roller is sleeved on an outer side wall of the rotating shaft, a servo motor is fixedly connected with the side wall of the fixed plate, the tail end of an output shaft of a data processing module penetrates through the side wall of the fixed plate and is fixedly connected with the end of the rotating shaft, a winding rope is wound on the winding roller, the upper end of the winding rope penetrates through the side wall and is fixedly connected with the fixed plate, a connecting plate is fixedly connected with the mounting plate and the upper end of the fixed plate together, telescopic rods are symmetrically arranged at the upper ends of the connecting plate, the upper ends of the two telescopic rods are fixedly connected with an ascending box, and a PM, Ozone sensor, sulfur dioxide sensor, nitrogen oxide sensor.
Preferably, scales are arranged on the side wall of the winding rope.
Preferably, the side wall of the base is provided with a threaded hole.
The invention has the beneficial effects that: in the invention, the data acquisition module can realize the acquisition and collection of data, the data preprocessing module realizes the dimensionality reduction processing of the data, so that the acquired data parameters can be transmitted with the data classification module, the data classification is realized through the learning classification module, the comprehensive analysis module realizes the analysis processing of the data, the auxiliary arrangement module realizes the arrangement of the analyzed data, and the computer terminal module can realize the observation and monitoring of the arranged data;
through driving motor, axis of rotation, mounting panel, winding rope, the box of joining in marriage between the lift-off box use, realized the lift to PM2.5 sensor, PM sensor, ozone sensor, sulfur dioxide sensor, nitrogen oxide sensor, and then can realize the detection to the high air pollutant of difference, improved the precision of controlling atmospheric pollutants concentration.
Drawings
Fig. 1 is a schematic block diagram of the present invention.
FIG. 2 is a schematic view of the structure of the apparatus of the present invention.
Fig. 3 is an enlarged view of a portion a of the present invention.
Reference numbers in the figures: the device comprises a data processing module 1, a data preprocessing module 2, a learning classification module 3, a comprehensive analysis module 4, an auxiliary finishing module 5, a computer terminal module 6, a base 7, a fixing plate 8, a winding roller 9, a positioning plate 10, a servo motor 11, a rotating shaft 12, a mounting plate 13, a connecting plate 14, a winding rope 15, a telescopic rod 16 and an empty lifting box 17.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-3, a semi-supervised semi-learning type atmospheric pollutant system comprises a data processing module 1, a data preprocessing module 2, a learning classification module 3 and a comprehensive analysis module 4, auxiliary arrangement module 5, computer terminal module 6, the output of data processing module 1 and the input electric connection of data preprocessing module 2, data processing module 1 includes atmospheric pollutant concentration acquisition device, atmospheric pollutant concentration detection device includes base 7, the lateral wall of base 7 is provided with the screw hole, the upper end lateral wall of base 7 is fixedly connected with mounting panel 13 in proper order, fixed plate 8, be connected through axis of rotation 12 between mounting panel 13 and the fixed plate 8, the lateral wall cover of axis of rotation 12 is equipped with wire winding roller 9, the lateral wall fixedly connected with servo motor 11 of fixed plate 8, the output shaft end of data processing module 1 runs through the lateral wall of fixed plate 8 and with the tip fixed connection of axis of rotation 12;
a winding rope 15 is wound on the winding roller 9, scales are arranged on the side wall of the winding rope 15, the height measurement is realized, the upper end of the winding rope 15 penetrates through the side wall of the mounting plate 14 and is fixedly connected with a connecting plate 17, the mounting plate 13 and the upper end of the fixing plate 8 are fixedly connected with the connecting plate 14 together, telescopic rods 16 are symmetrically arranged at the upper end of the connecting plate 14, the upper ends of the two telescopic rods 16 are fixedly connected with a lift-off box 17, the outer side wall of the lift-off box 17 is sequentially provided with a PM data preprocessing module 2.5, a PM10 sensor, an ozone sensor, a sulfur dioxide sensor and a nitrogen oxide sensor, the learning classification module 5 exists in a learning classifier mode, the classification of data is realized, meanwhile, the marking and recording of unmarked parameter classification can be realized, and the data processing module 1 and the data;
the output of data preprocessing module 2 and the input electric connection of study classification module 3, the output of study classification module 3 and the input electric connection of comprehensive analysis module 4, the output of comprehensive analysis module 4 and the input electric connection of supplementary arrangement module 5, the input electric connection of the output phrase computer terminal module 6 of supplementary arrangement module 5, supplementary arrangement module has realized the arrangement to the analytic data, make the staff can clearly see the pollution condition of atmospheric environment pollutant in the different heights through computer terminal module 6, computer terminal module 6 includes the computer unit, mouse unit, keyboard unit.
The working principle is as follows: when the device is used, firstly, the servo motor 11 is started, the servo motor 11 drives the rotating shaft 12 to rotate, in the rotating process of the rotating shaft 12, the unwinding process of the winding rope 15 is realized, in the unwinding process of the winding rope 15, because a large amount of hydrogen is filled in the lift-off box 7, the lifting work of the lift-off box 17 is realized, in the upward moving process of the lift-off box 17, the PM data preprocessing module 2 on the lift-off box 17 is driven, the sensor of the auxiliary arrangement module 5, the sensor of the PM positioning plate 10, the ozone sensor, the sulfur dioxide sensor and the nitrogen oxide sensor synchronously move, the PM data preprocessing module 2, the sensor of the auxiliary arrangement module 5, the ozone sensor, the sulfur dioxide sensor, the atmospheric environment and the atmospheric environment are detected, the nitrogen oxide sensor realizes the detection of the concentration of nitrogen oxide in the atmospheric environment, and the PM10 sensor realizes the detection of the concentration of PM10 in the atmospheric environment;
because the data processing module 1 is connected with the data preprocessing module 2 through a wireless network, and then the data receiving work is realized, the dimensionality reduction processing of the data preprocessing module 2 is realized, the learning classification module 3 can receive the data preprocessing module 2, the data is analyzed and classified through the work of the learning classification module 3, the data analysis work is realized through the comprehensive analysis module 4, the auxiliary data arrangement work is realized through the auxiliary data arrangement module 5, the data receiving work is realized through the computer terminal module 6, and then the monitoring of the environmental concentration is realized through the computer terminal module 6 by a worker.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the equipment or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" 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 defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. A semi-supervised semi-learning type atmospheric pollutant system comprises a data processing module (1), a data preprocessing module (2), a learning classification module (3), a comprehensive analysis module (4), an auxiliary sorting module (5) and a computer terminal module (6), it is characterized in that the output end of the data processing module (1) is electrically connected with the input end of the data preprocessing module (2), the output end of the data preprocessing module (2) is electrically connected with the input end of the learning classification module (3), the output end of the learning classification module (3) is electrically connected with the input end of the comprehensive analysis module (4), the output end of the comprehensive analysis module (4) is electrically connected with the input end of the auxiliary sorting module (5), the input end of the output phrase computer terminal module (6) of the auxiliary arrangement module (5) is electrically connected.
2. The semi-supervised semi-learning type atmospheric pollutant system according to claim 1, wherein the data processing module (1) comprises an atmospheric pollutant concentration acquisition device, and the data processing module (1) and the data preprocessing module (2) are electrically connected through a wireless network.
3. A semi-supervised semi-learning atmospheric pollutants system as claimed in claim 1, wherein the computer terminal module (6) comprises a computer unit, a mouse unit, a keyboard unit.
4. A semi-supervised semi-learning atmospheric pollutant system according to claim 1, characterized in that the learning classification module (5) is in the form of a learning classifier, which realizes classification processing of data and simultaneously can realize labeling recording of unlabeled parameter classification.
5. The semi-supervised semi-learning type atmospheric pollutant system according to claim 1, wherein the auxiliary sorting module is used for sorting the analysis data, so that workers can clearly see the pollution conditions of atmospheric environmental pollutants at different heights through the computer terminal module (6).
6. The semi-supervised semi-learning type atmospheric pollutant system according to claim 1, wherein the atmospheric pollutant concentration detection device comprises a base (7), an upper end side wall of the base (7) is fixedly connected with a mounting plate (13) and a fixing plate (8) in sequence, the mounting plate (13) is connected with the fixing plate (8) through a rotating shaft (12), the outer side wall of the rotating shaft (12) is sleeved with a winding roller (9), the side wall of the fixing plate (8) is fixedly connected with a servo motor (11), the tail end of an output shaft of the data processing module (1) penetrates through the side wall of the fixing plate (8) and is fixedly connected with the end part of the rotating shaft (12), a winding rope (15) is wound on the winding roller (9), the upper end of the winding rope (15) penetrates through the side wall of the fixing plate (14) and is fixedly connected with a connecting plate (17), and the mounting plate (13) and the upper end of the fixing plate (, the upper end symmetry of connecting plate (14) is provided with telescopic link (16), two the upper end of telescopic link (16) all with lift-off box (17) fixed connection, the lateral wall of lift-off box (17) has set gradually PM2.5, PM10 sensor, ozone sensor, sulfur dioxide sensor, nitrogen oxide sensor.
7. A semi-supervised semi-learning atmospheric pollutants system as claimed in claim 6, wherein the winding rope (15) is provided with graduations on its side walls.
8. A semi-supervised semi-learning atmospheric pollutants system according to claim 6, wherein the base (7) is provided with threaded holes in its side walls.
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| CN202010653290.5A CN111896681A (en) | 2020-07-08 | 2020-07-08 | Semi-supervised semi-learning type atmospheric pollutant system |
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| CN202010653290.5A CN111896681A (en) | 2020-07-08 | 2020-07-08 | Semi-supervised semi-learning type atmospheric pollutant system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114405219A (en) * | 2022-02-21 | 2022-04-29 | 南昌工程学院 | Atmospheric pollutant treatment method based on semi-supervised learning |
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