CN118209491B - Gas concentration detection and evaluation method and system for optical gas chamber - Google Patents
Gas concentration detection and evaluation method and system for optical gas chamber Download PDFInfo
- Publication number
- CN118209491B CN118209491B CN202410634214.8A CN202410634214A CN118209491B CN 118209491 B CN118209491 B CN 118209491B CN 202410634214 A CN202410634214 A CN 202410634214A CN 118209491 B CN118209491 B CN 118209491B
- Authority
- CN
- China
- Prior art keywords
- gas
- concentration
- spectrum
- separation
- fault
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000003287 optical effect Effects 0.000 title claims abstract description 101
- 238000001514 detection method Methods 0.000 title claims abstract description 88
- 238000011156 evaluation Methods 0.000 title claims abstract description 22
- 238000001228 spectrum Methods 0.000 claims abstract description 171
- 238000000926 separation method Methods 0.000 claims abstract description 112
- 238000000862 absorption spectrum Methods 0.000 claims abstract description 65
- 238000000034 method Methods 0.000 claims abstract description 33
- 238000012544 monitoring process Methods 0.000 claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims description 36
- 230000007613 environmental effect Effects 0.000 claims description 34
- 238000012545 processing Methods 0.000 claims description 21
- 230000002776 aggregation Effects 0.000 claims description 19
- 238000004220 aggregation Methods 0.000 claims description 19
- 230000005540 biological transmission Effects 0.000 claims description 14
- 230000003595 spectral effect Effects 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 10
- 230000003993 interaction Effects 0.000 claims description 9
- 230000002159 abnormal effect Effects 0.000 claims description 8
- 230000003213 activating effect Effects 0.000 claims description 8
- 238000007621 cluster analysis Methods 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000004913 activation Effects 0.000 claims 2
- 230000000694 effects Effects 0.000 abstract description 8
- 239000007789 gas Substances 0.000 description 254
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 238000010521 absorption reaction Methods 0.000 description 3
- 238000010183 spectrum analysis Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 description 2
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 230000008030 elimination Effects 0.000 description 2
- 238000003379 elimination reaction Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 230000007257 malfunction Effects 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/3103—Atomic absorption analysis
Landscapes
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The application provides a gas concentration detection and evaluation method and a system for an optical gas chamber, which relate to the technical field of gas concentration detection, and the method comprises the following steps: the spectrum monitoring module is used for acquiring a target optical air chamber; outputting a gas absorption spectrum; obtaining a plurality of separation spectra; outputting a gas concentration detection result; performing fault concentration identification to generate a preset safety concentration threshold; and performing concentration risk index evaluation based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index. The application can solve the technical problems in the prior art that the gas concentration detection result after separation is inaccurate due to insufficient gas separation precision, and the technical effects of improving the concentration detection accuracy of the mixed gas and ensuring the safe operation of the optical gas chamber are achieved by separating the absorption spectrum of the mixed gas, detecting the gas type and the concentration and adjusting the gas concentration.
Description
Technical Field
The application relates to the technical field of gas concentration detection, in particular to a gas concentration detection and evaluation method and system for an optical gas chamber.
Background
Currently, gas concentration detection techniques mainly include conventional analytical detection techniques and emerging optical sensor techniques. The emerging optical sensor technology has the advantages of high response speed, high precision, low cost and the like, and has wide application in the fields of environment monitoring, industrial control and the like.
The light source generates light with a specific wavelength, gas molecules absorb the light to form a specific spectrum, and the type and concentration of the gas can be determined by analyzing the absorption spectrum and the known spectrum. The traditional spectrum detection method has higher detection precision on a single gas type, but the gas to be detected can be various mixed gases, the traditional method usually carries out separation on the gas first and then detects the gas, but the gas separation precision is insufficient, so that the detection result of the concentration of the separated gas is inaccurate easily, and the detection effect on the mixed gas is poor.
Disclosure of Invention
The application aims to provide a gas concentration detection and evaluation method and a system for an optical gas chamber, which are used for solving the technical problem that the separated gas concentration detection result is inaccurate easily due to insufficient gas separation precision in the prior art.
In view of the above, the present application provides a gas concentration detection evaluation method and system for an optical gas cell.
In a first aspect, the present application provides a gas concentration detection evaluation method for an optical gas cell, the method being implemented by a gas concentration detection evaluation system for an optical gas cell, wherein the method comprises: the spectrum monitoring module is used for acquiring a target optical air chamber and comprises a light source generating device and a spectrum receiving device; transmitting a light beam to the target optical air chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device; activating a mixed spectrum separation module to perform spectrum separation treatment on the gas absorption spectrum to obtain a plurality of separation spectrums; performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result comprises a plurality of gas types and a plurality of gas concentrations; the historical fault information base connected with the target optical air chamber carries out fault concentration identification to generate a preset safety concentration threshold; and performing concentration risk index evaluation based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index.
Further, the method further comprises:
collecting environmental condition information in the target optical air chamber, wherein the environmental condition information comprises an environmental light source, an environmental temperature, an environmental humidity and air pressure; performing gas concentration influence identification based on the environmental condition information and the plurality of gas types to obtain a concentration influence factor; and carrying out feedback correction on the plurality of gas concentrations by using the concentration influence factors.
Further, the method further comprises:
the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer; performing interference noise treatment on the gas absorption spectrum through the interference analysis network layer to generate an optimized absorption spectrum; and carrying out spectrum separation processing on the optimized absorption spectrum through the spectrum separation network layer to generate a plurality of separation spectrums.
Further, the method further comprises:
Collecting air chamber panoramic image data in a preset area of the target optical air chamber; positioning an interference source based on the air chamber panoramic image data, and establishing an interference source position distribution network; extracting a light beam emission route based on the light source generating device and the spectrum receiving device to obtain a light beam transmission position distribution area; locating a target interference source based on the interference source location distribution network and the beam transmission location distribution area; and carrying out spectrum interference test based on the target interference source, and constructing the interference analysis network layer by using interference test data.
Further, the method further comprises:
The spectrum separation network layer is constructed based on a Wave-U-Net network and comprises an encoder and a decoder; the encoder maps the optimized absorption spectrum to a low-dimensional space, and the decoder maps the optimized absorption spectrum mapped to the low-dimensional space back to the original space, so as to obtain the plurality of separation spectrums.
Further, the method further comprises:
The history fault information base is connected with a man-machine interaction module, and is updated in real time through the man-machine interaction module; extracting a historical fault gas concentration record and a historical fault factor record of the target optical gas chamber based on the historical fault information base; performing self-fault identification of the gas chamber equipment based on the historical fault factor record, and performing self-fault record rejection on the historical fault gas concentration record based on a self-fault identification result to generate a complete concentration fault record data set; and carrying out cluster analysis on the complete concentration fault record data set to generate the preset safety concentration threshold value.
Further, the method further comprises:
Clustering the complete concentration fault record data set to generate a plurality of clustering results; performing aggregation index calculation on the plurality of clustering results to obtain a plurality of aggregation indexes, wherein the plurality of aggregation indexes are ratios of clustering data amounts of the plurality of clustering results to total data amounts of the complete concentration fault record numbers; and eliminating abnormal clustering results based on the plurality of aggregation indexes, and taking the minimum concentration fault record data in the residual clustering results as the preset safe concentration threshold.
In a second aspect, the present application also provides a gas concentration detection and evaluation system for an optical gas cell for performing the gas concentration detection and evaluation method for an optical gas cell according to the first aspect, wherein the system comprises: the monitoring module acquisition unit is used for acquiring a spectrum monitoring module of the target optical air chamber, wherein the spectrum monitoring module comprises a light source generating device and a spectrum receiving device; a light beam emission unit for emitting a light beam to the target optical gas cell through the light source generation device, and outputting a gas absorption spectrum through the spectrum reception device; the spectrum separation processing unit is used for activating the mixed spectrum separation module to perform spectrum separation processing on the gas absorption spectrum to obtain a plurality of separation spectrums; a gas concentration analysis unit for performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result includes a plurality of gas types and a plurality of gas concentrations; the fault concentration recognition unit is used for carrying out fault concentration recognition on a historical fault information base connected with the target optical air chamber and generating a preset safety concentration threshold; and the gas concentration control unit is used for evaluating a concentration risk index based on the gas concentration detection result and the preset safety concentration threshold value and controlling the gas concentration of the target optical gas chamber according to the concentration risk index.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
The spectrum monitoring module is used for acquiring a target optical air chamber and comprises a light source generating device and a spectrum receiving device; transmitting a light beam to the target optical air chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device; activating a mixed spectrum separation module to perform spectrum separation treatment on the gas absorption spectrum to obtain a plurality of separation spectrums; performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result comprises a plurality of gas types and a plurality of gas concentrations; the historical fault information base connected with the target optical air chamber carries out fault concentration identification to generate a preset safety concentration threshold; and performing concentration risk index evaluation based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index. Through separating the absorption spectrum of the mixed gas, detecting the gas type and the concentration and adjusting the gas concentration, the technical effects of improving the concentration detection accuracy of the mixed gas and ensuring the safe operation of the optical gas chamber are achieved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent. It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the application or to delineate the scope of the application. Other features of the present application will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the application or the technical solutions of the prior art, the following brief description will be given of the drawings used in the description of the embodiments or the prior art, it being obvious that the drawings in the description below are only exemplary and that other drawings can be obtained from the drawings provided without the inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for detecting and evaluating the concentration of a gas in an optical gas cell according to the present application;
FIG. 2 is a schematic diagram of a gas concentration detection and evaluation system for an optical gas cell according to the present application.
Reference numerals illustrate: a monitoring module acquisition unit 11, a light beam emission unit 12, a spectrum separation processing unit 13, a gas concentration analysis unit 14, a failure concentration identification unit 15, and a gas concentration control unit 16.
Detailed Description
The application solves the technical problem in the prior art that the separated gas concentration detection result is inaccurate due to insufficient gas separation precision by providing the gas concentration detection and evaluation method and the system for the optical gas chamber. Through separating the absorption spectrum of the mixed gas, detecting the gas type and the concentration and adjusting the gas concentration, the technical effects of improving the concentration detection accuracy of the mixed gas and ensuring the safe operation of the optical gas chamber are achieved.
In the following, the technical solutions of the present application will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present application, but not all embodiments of the present application, and that the present application is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present application are shown.
Examples
Referring to fig. 1, the present application provides a method for detecting and evaluating a gas concentration in an optical gas chamber, wherein the method is applied to a system for detecting and evaluating a gas concentration in an optical gas chamber, and the method specifically comprises the following steps:
step one: the spectrum monitoring module is used for acquiring a target optical air chamber and comprises a light source generating device and a spectrum receiving device;
Specifically, the optical gas chamber is an existing experimental device for spectrum analysis, and the target optical gas chamber is the optical gas chamber to be subjected to gas concentration detection. The light source generating means typically comprises one or more light sources capable of generating light of a specific wavelength. By way of example, the light source generating means may be a laser, LED, incandescent lamp or other type of light emitting device, in particular in combination with the actual determination. The spectrum receiving device is responsible for collecting spectrum information after absorption or scattering of the gas passing through the spectrum receiving device, and the spectrum receiving device can comprise a spectrometer, a photoelectric detector, an optical fiber and other components, and is used for detecting light intensities of different wavelengths and converting optical signals into electric signals according to actual determination by a person skilled in the art.
The light source generating device and the spectrum receiving device form a spectrum monitoring module, and a device foundation is provided for subsequent gas concentration detection.
Step two: transmitting a light beam to the target optical air chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device;
Specifically, the light source generating device is started to emit a light beam, and the light beam can be a single-wavelength laser or a broad-spectrum light containing a plurality of wavelengths. The beam then irradiates the target optical cell, which is a closed container filled with the gas to be inspected. When a light beam passes through a gas, the gas molecules absorb light with a specific wavelength, depending on the chemical nature and concentration of the gas, and the absorption phenomenon causes the intensity of the light beam to be weakened at the specific wavelength, and the light beam after being absorbed by the gas is received by a spectrum receiving device to form a gas absorption spectrum. In short, the intensity of the light beam at different wavelengths can be directly measured by the spectrum receiving device, and then the difference spectrum of the light beam emitted by the light source generating device and the spectrum of the light beam passing through the gas is calculated by comparing the two spectra, so that the absorption spectrum of the gas can be obtained, which is a common technical means for those skilled in the art, and is not developed here.
Step three: activating a mixed spectrum separation module to perform spectrum separation treatment on the gas absorption spectrum to obtain a plurality of separation spectrums;
Specifically, the gas to be detected in the target optical gas chamber may contain multiple types of mixed gas, such as sulfur dioxide, carbon monoxide, nitric oxide, and the like, and in the prior art, after the mixed gas is separated by physical, chemical, and other methods, spectrum analysis is performed on each type of gas, so that concentration detection is realized, but in this way, inaccurate gas separation easily occurs, and the concentration detection result is inaccurate. The application directly separates the gas absorption spectrum of the mixed gas, and separates the spectrum corresponding to different gases as a plurality of separation spectrums.
Step four: performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result comprises a plurality of gas types and a plurality of gas concentrations;
Specifically, each of the separate spectra reflects the absorption characteristics of a gas for a particular wavelength of light, based on which the separate spectra are analyzed to identify the gas type. First, a person skilled in the art builds a spectral feature library of a plurality of known gases based on the prior art, and for example, may obtain all possible gases in a generated scene as a plurality of known gases based on the generated scene of the actual gas to be detected, and build the spectral feature library. And comparing the similarity of the plurality of separation spectrums with the spectrum characteristics of each known gas in the spectrum characteristic library, and acquiring the type of the known gas corresponding to the spectrum characteristics with the similarity larger than or equal to a preset similarity threshold value as a plurality of gas types, wherein the preset similarity threshold value is set by a person skilled in the art based on actual experience, namely the similarity threshold value for judging that the spectrum characteristics belong to the same gas type.
After determining the gas type, each of the separation spectra is further analyzed to calculate a gas concentration, and illustratively, based on a plurality of gas types, a spectral feature sample and a gas concentration sample corresponding to the plurality of gas types are collected, respectively, a concentration recognition model is constructed based on an existing machine learning model, such as a neural network model, the plurality of gas types correspond to the plurality of concentration recognition models, the spectral feature sample is input into the concentration recognition model, output supervision adjustment is performed on the gas concentration sample, and the concentration recognition model is trained to be converged. And finally, respectively inputting a plurality of separation spectrums corresponding to the plurality of gas types into a corresponding concentration recognition model to carry out concentration analysis, so that a plurality of gas concentrations can be output.
Therefore, the gas type and gas concentration detection after the mixed gas separation is realized, and the accuracy of the concentration detection is improved.
Step five: the historical fault information base connected with the target optical air chamber carries out fault concentration identification to generate a preset safety concentration threshold;
Specifically, if the gas concentration in the target optical gas cell is too high, it may cause the target optical gas cell to malfunction, and the historical malfunction information base is constructed by those skilled in the art based on the prior art and can be updated in real time. The historical fault information base contains fault records of all optical air chambers with the same specification as the target optical air chamber, including gas concentration and fault reasons when faults occur. Through carrying out statistical analysis on the historical fault information base, a preset safe concentration threshold value of the target optical air chamber is obtained, namely the maximum concentration when faults cannot occur, and the gas concentration adjustment is conveniently carried out when the concentration is detected to be too high, so that the safety of the optical air chamber is ensured. Wherein the predetermined safe concentration threshold includes concentration thresholds respectively corresponding to the plurality of gas types.
Step six: and performing concentration risk index evaluation based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index.
Specifically, the gas concentration detection result and the preset safety concentration threshold value are compared, whether a plurality of gas concentrations corresponding to a plurality of gas types in the gas concentration detection result are larger than the preset safety concentration threshold value is judged, if yes, a concentration risk index is assigned to be 1 to indicate that safety risk exists, if not, a concentration risk index is assigned to be 0 to indicate that safety risk does not exist.
If the concentration risk index is 1, that is, the safety risk exists, at this time, a concentration adjusting device of the target optical air chamber, such as a circulation port connected with other devices, may be obtained, and the circulation port is opened to enable the gas to flow out of the target optical air chamber, so as to reduce the concentration, until the concentration of a plurality of gases corresponding to the types of the plurality of gases is less than or equal to the predetermined safety concentration threshold. The concentration detection of the mixed gas is realized, so that the concentration adjustment is performed, the concentration detection accuracy is improved, and the safety of the optical air chamber is further ensured.
Further, the fourth step of the present application further comprises:
collecting environmental condition information in the target optical air chamber, wherein the environmental condition information comprises an environmental light source, an environmental temperature, an environmental humidity and air pressure; performing gas concentration influence identification based on the environmental condition information and the plurality of gas types to obtain a concentration influence factor; and carrying out feedback correction on the plurality of gas concentrations by using the concentration influence factors.
Specifically, when the gas concentration is detected, the environment may affect the detection result, for example, an increase in temperature may cause an increase in gas concentration, and a decrease in temperature may cause a decrease in gas concentration; humidity can affect the diffusion and settling of the gas, resulting in a change in concentration. Based on this, it is necessary to compensate the gas concentration detection result based on the environment to improve the detection accuracy.
First, the existing environmental sensor is used to monitor parameters such as the intensity of an environmental light source, the environmental temperature, the environmental humidity, the air pressure and the like in the target optical air chamber in real time to form environmental condition information. The effect of environmental conditions on the concentration measurements of different gas types was further analyzed. For example, different temperatures and humidities may affect the diffusion rate of the gas and the characteristics of the absorption spectrum, resulting in a deviation in concentration. Specifically, the historical detection concentration deviation record set and the historical environmental condition record set corresponding to different gas types can be obtained by calling the historical detection record, and the similarity between the environmental condition information and any record in the historical environmental condition record set is further compared, and the similarity is a common technical means in the field, for example, the similarity can be calculated through cosine similarity and other methods. And further acquiring a history detection concentration deviation record corresponding to the history environmental condition record with the similarity larger than the preset threshold value as a concentration influence factor. And performing deviation compensation on the plurality of gas concentrations by using a concentration influence factor, so as to realize feedback correction of the plurality of gas concentrations and improve the gas concentration detection precision.
Further, the third step of the present application further comprises:
the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer; performing interference noise treatment on the gas absorption spectrum through the interference analysis network layer to generate an optimized absorption spectrum; and carrying out spectrum separation processing on the optimized absorption spectrum through the spectrum separation network layer to generate a plurality of separation spectrums.
Further, the application also comprises the following steps:
Collecting air chamber panoramic image data in a preset area of the target optical air chamber; positioning an interference source based on the air chamber panoramic image data, and establishing an interference source position distribution network; extracting a light beam emission route based on the light source generating device and the spectrum receiving device to obtain a light beam transmission position distribution area; locating a target interference source based on the interference source location distribution network and the beam transmission location distribution area; and carrying out spectrum interference test based on the target interference source, and constructing the interference analysis network layer by using interference test data.
Further, the application also comprises the following steps:
The spectrum separation network layer is constructed based on a Wave-U-Net network and comprises an encoder and a decoder; the encoder maps the optimized absorption spectrum to a low-dimensional space, and the decoder maps the optimized absorption spectrum mapped to the low-dimensional space back to the original space, so as to obtain the plurality of separation spectrums.
The gas absorption spectrum is subjected to spectrum separation treatment through a mixed spectrum separation module, and the specific method for obtaining a plurality of separation spectrums is as follows:
Firstly, a mixed spectrum separation module is established, wherein the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer, and the construction method of the interference analysis network layer comprises the following steps:
The method comprises the steps of collecting air chamber panoramic image data in a preset area of the target optical air chamber, wherein the preset area is set by a person skilled in the art, for example, a certain radius area taking the target optical air chamber as an origin is obtained by enlarging the range according to the transmission range of an actual light beam in the target optical air chamber, for example, enlarging the transmission range by two times, that is, the light beam can be reflected or scattered by other objects in the indoor transmission process of the target optical air chamber, the obtained gas absorption spectrum is inaccurate, interference source analysis processing is needed, and visible light images, infrared images and the like in the preset area are collected as air chamber panoramic image data through the existing image equipment such as a camera and a camera. The panoramic image data is further analyzed, interference sources which can influence the detection of the gas concentration, such as a reflecting surface, dust, water vapor and the like, are identified, specifically, all the interference sources which can occur can be counted based on the prior art, corresponding image convolution kernel features are established for the interference sources, convolution kernel comparison is carried out in the panoramic image data, and the interference sources corresponding to the panoramic image data are identified. And distributing the interference sources according to the positions of the interference sources in the image to obtain an interference source position distribution network.
And extracting a light beam emission route based on the light source generating device and the spectrum receiving device, then emitting a light beam to the target optical air chamber through the light source generating device, and detecting the light beam of the target optical air chamber to obtain a position through which the light beam passes as a light beam transmission position distribution area. And combining the interference source position distribution network and the beam transmission position distribution area, determining an overlapping area in the interference source position distribution network and the beam transmission position distribution area, and taking an interference source corresponding to the overlapping area and the position of the interference source as a target interference source.
Finally, performing spectrum interference test on the target interference source, namely performing spectrum detection on the light source generating device based on the prior art by changing the wavelength, the intensity or the emission angle of the light beam emitted by the light source generating device to obtain an initial spectrum detection sample, performing spectrum detection on the position of the target interference source to obtain an interference spectrum detection sample, forming interference test data by the initial spectrum detection sample and the interference spectrum detection sample, analyzing a spectrum difference sample between the initial spectrum detection sample and the interference spectrum detection sample, taking the initial spectrum detection sample as input, performing output supervision adjustment on the spectrum difference sample, and training the existing machine learning model to obtain an interference analysis network layer. Providing a model basis for interference analysis.
And inputting the gas absorption spectrum into the interference analysis network layer, outputting a corresponding spectrum difference, and performing interference noise treatment on the gas absorption spectrum by using the spectrum difference, namely performing deviation correction on the gas absorption spectrum according to the spectrum difference, and taking the corrected gas absorption spectrum as an optimized absorption spectrum to realize interference identification and elimination, thereby improving the accuracy of spectrum analysis and further improving the accuracy of gas concentration detection.
Further, the optimized absorption spectrum is subjected to spectrum separation processing through the spectrum separation network layer, and the plurality of separation spectrums are generated, wherein the spectrum separation network layer is constructed based on a Wave-U-Net network. The Wave-U-Net network is a framework based on a convolutional neural network, combines the characteristics of the conventional convolutional neural network for image segmentation and the conventional deep neural network for generating an original audio waveform, and can effectively process and analyze waveform data, including spectrum data. The spectrum separation network layer comprises an encoder and a decoder, wherein the encoder is a downsampled encoder, the decoder is an upsampled decoder, the encoder maps the optimized absorption spectrum to a low-dimensional space, and the decoder maps the optimized absorption spectrum mapped to the low-dimensional space back to the original space to obtain the plurality of separation spectrums.
Specifically, the spectral separation network layer is obtained through training of training data. Specifically, a spectrum separation network layer is firstly constructed based on a Wave-U-Net network, then a mixed gas absorption spectrum sample and a separated gas absorption spectrum sample of a plurality of groups of mixed gas are collected by a person skilled in the art, the mixed gas absorption spectrum sample is input into the spectrum separation network layer, and output supervision adjustment is carried out on an encoder and a decoder by the separated gas absorption spectrum sample, so that the encoder and the decoder trained until converged form the spectrum separation network layer.
And finally, inputting the optimized absorption spectrum into the spectrum separation network layer to perform spectrum separation treatment, and outputting a plurality of separation spectrums. Therefore, spectrum separation is realized, support is provided for subsequent gas concentration detection, and concentration detection accuracy is improved.
Further, the fifth step of the present application further comprises:
The history fault information base is connected with a man-machine interaction module, and is updated in real time through the man-machine interaction module; extracting a historical fault gas concentration record and a historical fault factor record of the target optical gas chamber based on the historical fault information base; performing self-fault identification of the gas chamber equipment based on the historical fault factor record, and performing self-fault record rejection on the historical fault gas concentration record based on a self-fault identification result to generate a complete concentration fault record data set; and carrying out cluster analysis on the complete concentration fault record data set to generate the preset safety concentration threshold value.
Further, the application also comprises the following steps:
Clustering the complete concentration fault record data set to generate a plurality of clustering results; performing aggregation index calculation on the plurality of clustering results to obtain a plurality of aggregation indexes, wherein the plurality of aggregation indexes are ratios of clustering data amounts of the plurality of clustering results to total data amounts of the complete concentration fault record numbers; and eliminating abnormal clustering results based on the plurality of aggregation indexes, and taking the minimum concentration fault record data in the residual clustering results as the preset safe concentration threshold.
Specifically, the method for identifying the fault concentration by receiving the historical fault information base of the target optical air chamber and generating the preset safety concentration threshold is as follows:
the man-machine interaction module is a contact bridge between the user and the system, and provides an intuitive and easy-to-use interface, so that the user can conveniently update the historical fault information base in real time. The user can add, modify or delete the data in the historical fault information base by simply clicking, dragging or inputting and the like. The historical fault information base stores past fault records of the optical air chamber, including historical gas concentration records and historical fault factor records, wherein the fault factors are fault reasons, such as equipment self faults, gas concentration caused faults and the like. And performing self-fault identification of the air chamber equipment based on the historical fault factor record, namely identifying and deleting the historical gas concentration record corresponding to the equipment self-fault, and taking the remaining historical gas concentration record as a complete concentration fault record data set, thereby eliminating the influence of the equipment self-fault on fault concentration identification and improving the fault concentration identification accuracy.
Further performing cluster analysis on the complete concentration fault record data set to generate the preset safe concentration threshold value, wherein the method comprises the following steps of:
Based on the existing clustering algorithm, such as a k-means algorithm, the complete concentration fault record data set is clustered to generate a plurality of clustering results, the data quantity contained in the plurality of clustering results is extracted to obtain the clustering data quantity of the plurality of clustering results, the total data quantity of the complete concentration fault record number is counted, and then the ratio of the clustering data quantity of the plurality of clustering results to the total data quantity of the complete concentration fault record number is calculated as a plurality of aggregation indexes. Finally, based on the plurality of aggregation indexes, abnormal clustering result elimination is carried out, namely, if the clustering data amount of the clustering result is very small, namely, the aggregation indexes are very small, the data in the clustering result is inaccurate, and the abnormal clustering result is possible, namely, the abnormal clustering result can be obtained, a threshold value of the abnormal index can be set by a person skilled in the art by combining the total data amount of the complete concentration fault record number, for example, the total data amount can be set to be 0.05, and the discrete value can be eliminated by a person skilled in the art by combining actual experience. And finally, taking the minimum concentration fault record data in the residual clustering result as the preset safety concentration threshold value. And the analysis of the safe concentration threshold value is realized, the setting precision of the threshold value is improved, and the control accuracy of the gas concentration is further improved.
In summary, the method for detecting and evaluating the gas concentration of the optical gas chamber provided by the application has the following technical effects:
The spectrum monitoring module is used for acquiring a target optical air chamber and comprises a light source generating device and a spectrum receiving device; transmitting a light beam to the target optical air chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device; activating a mixed spectrum separation module to perform spectrum separation treatment on the gas absorption spectrum to obtain a plurality of separation spectrums; performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result comprises a plurality of gas types and a plurality of gas concentrations; the historical fault information base connected with the target optical air chamber carries out fault concentration identification to generate a preset safety concentration threshold; and performing concentration risk index evaluation based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index. Through separating the absorption spectrum of the mixed gas, detecting the gas type and the concentration and adjusting the gas concentration, the technical effects of improving the concentration detection accuracy of the mixed gas and ensuring the safe operation of the optical gas chamber are achieved.
Examples
Based on the same inventive concept as the gas concentration detection and evaluation method for an optical gas cell in the foregoing embodiment, the present application further provides a gas concentration detection and evaluation system for an optical gas cell, referring to fig. 2, the system includes:
The monitoring module acquisition unit 11 is used for acquiring a spectrum monitoring module of the target optical air chamber, wherein the spectrum monitoring module comprises a light source generating device and a spectrum receiving device;
A light beam emitting unit 12, wherein the light beam emitting unit 12 is used for emitting a light beam to the target optical gas chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device;
the spectrum separation processing unit 13 is used for activating a mixed spectrum separation module to perform spectrum separation processing on the gas absorption spectrum to obtain a plurality of separation spectrums;
A gas concentration analysis unit 14 for performing gas type and concentration analysis based on the plurality of separation spectra, and outputting a gas concentration detection result, wherein the gas concentration detection result includes a plurality of gas types and a plurality of gas concentrations;
a fault concentration recognition unit 15, where the fault concentration recognition unit 15 is configured to perform fault concentration recognition by using a historical fault information base connected to the target optical air chamber, and generate a predetermined safe concentration threshold;
and a gas concentration control unit 16, wherein the gas concentration control unit 16 is configured to perform concentration risk index evaluation based on the gas concentration detection result and the predetermined safe concentration threshold value, and perform gas concentration control on the target optical gas chamber according to the concentration risk index.
Further, the gas concentration analysis unit 14 in the system is also configured to:
collecting environmental condition information in the target optical air chamber, wherein the environmental condition information comprises an environmental light source, an environmental temperature, an environmental humidity and air pressure;
performing gas concentration influence identification based on the environmental condition information and the plurality of gas types to obtain a concentration influence factor;
and carrying out feedback correction on the plurality of gas concentrations by using the concentration influence factors.
Further, the spectral separation processing unit 13 in the system is configured to:
the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer;
Performing interference noise treatment on the gas absorption spectrum through the interference analysis network layer to generate an optimized absorption spectrum;
and carrying out spectrum separation processing on the optimized absorption spectrum through the spectrum separation network layer to generate a plurality of separation spectrums.
Further, the spectral separation processing unit 13 in the system is configured to:
Collecting air chamber panoramic image data in a preset area of the target optical air chamber;
positioning an interference source based on the air chamber panoramic image data, and establishing an interference source position distribution network;
Extracting a light beam emission route based on the light source generating device and the spectrum receiving device to obtain a light beam transmission position distribution area;
Locating a target interference source based on the interference source location distribution network and the beam transmission location distribution area;
And carrying out spectrum interference test based on the target interference source, and constructing the interference analysis network layer by using interference test data.
Further, the spectral separation processing unit 13 in the system is configured to:
the spectrum separation network layer is constructed based on a Wave-U-Net network and comprises an encoder and a decoder;
the encoder maps the optimized absorption spectrum to a low-dimensional space, and the decoder maps the optimized absorption spectrum mapped to the low-dimensional space back to the original space, so as to obtain the plurality of separation spectrums.
Further, the spectral separation processing unit 13 in the system is configured to:
The history fault information base is connected with a man-machine interaction module, and is updated in real time through the man-machine interaction module;
extracting a historical fault gas concentration record and a historical fault factor record of the target optical gas chamber based on the historical fault information base;
Performing self-fault identification of the gas chamber equipment based on the historical fault factor record, and performing self-fault record rejection on the historical fault gas concentration record based on a self-fault identification result to generate a complete concentration fault record data set;
and carrying out cluster analysis on the complete concentration fault record data set to generate the preset safety concentration threshold value.
Further, the spectral separation processing unit 13 in the system is configured to:
Clustering the complete concentration fault record data set to generate a plurality of clustering results;
Performing aggregation index calculation on the plurality of clustering results to obtain a plurality of aggregation indexes, wherein the plurality of aggregation indexes are ratios of clustering data amounts of the plurality of clustering results to total data amounts of the complete concentration fault record numbers;
And eliminating abnormal clustering results based on the plurality of aggregation indexes, and taking the minimum concentration fault record data in the residual clustering results as the preset safe concentration threshold.
The embodiments of the present invention are described in a progressive manner, and each embodiment focuses on the difference from the other embodiments, and the method and specific example for detecting and evaluating the gas concentration of the optical gas chamber in the first embodiment of fig. 1 are equally applicable to the system for detecting and evaluating the gas concentration of the optical gas chamber in the present embodiment, and by the foregoing detailed description of the method for detecting and evaluating the gas concentration of the optical gas chamber in the present embodiment, those skilled in the art can clearly understand that the system for detecting and evaluating the gas concentration of the optical gas chamber in the present embodiment is not described in detail herein for brevity of the description. For the system disclosed in the embodiment, since the system corresponds to the method disclosed in the embodiment, the description is simpler, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalent techniques thereof, the present application is also intended to include such modifications and variations.
Claims (4)
1. A gas concentration detection evaluation method for an optical gas cell, comprising:
the spectrum monitoring module is used for acquiring a target optical air chamber and comprises a light source generating device and a spectrum receiving device;
Transmitting a light beam to the target optical air chamber through the light source generating device, and outputting a gas absorption spectrum through the spectrum receiving device;
Activating a mixed spectrum separation module to perform spectrum separation treatment on the gas absorption spectrum to obtain a plurality of separation spectrums;
performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result comprises a plurality of gas types and a plurality of gas concentrations;
The historical fault information base connected with the target optical air chamber carries out fault concentration identification to generate a preset safety concentration threshold;
Performing concentration risk index assessment based on the gas concentration detection result and the preset safety concentration threshold value, and performing gas concentration control on the target optical gas chamber according to the concentration risk index;
the activation mixing spectrum separation module performs spectrum separation processing on the gas absorption spectrum to obtain a plurality of separation spectrums, and the activation mixing spectrum separation module comprises:
the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer;
Performing interference noise treatment on the gas absorption spectrum through the interference analysis network layer to generate an optimized absorption spectrum;
Performing spectrum separation processing on the optimized absorption spectrum through the spectrum separation network layer to generate a plurality of separation spectrums;
the spectrum separation network layer is constructed based on a Wave-U-Net network and comprises an encoder and a decoder;
The encoder maps the optimized absorption spectrum to a low-dimensional space, and the decoder maps the optimized absorption spectrum mapped to the low-dimensional space back to an original space to obtain the plurality of separation spectrums;
The method for identifying the fault concentration of the historical fault information base connected with the target optical air chamber comprises the steps of:
The history fault information base is connected with a man-machine interaction module, and is updated in real time through the man-machine interaction module;
extracting a historical fault gas concentration record and a historical fault factor record of the target optical gas chamber based on the historical fault information base;
Performing self-fault identification of the gas chamber equipment based on the historical fault factor record, and performing self-fault record rejection on the historical fault gas concentration record based on a self-fault identification result to generate a complete concentration fault record data set;
Performing cluster analysis on the complete concentration fault record data set to generate the preset safe concentration threshold;
The step of performing cluster analysis on the complete concentration fault record data set to generate the preset safe concentration threshold value comprises the following steps:
Clustering the complete concentration fault record data set to generate a plurality of clustering results;
Performing aggregation index calculation on the plurality of clustering results to obtain a plurality of aggregation indexes, wherein the plurality of aggregation indexes are ratios of clustering data amounts of the plurality of clustering results to total data amounts of the complete concentration fault record numbers;
And eliminating abnormal clustering results based on the plurality of aggregation indexes, and taking the minimum concentration fault record data in the residual clustering results as the preset safe concentration threshold.
2. The method of claim 1, further comprising, prior to outputting the gas concentration detection result:
collecting environmental condition information in the target optical air chamber, wherein the environmental condition information comprises an environmental light source, an environmental temperature, an environmental humidity and air pressure;
performing gas concentration influence identification based on the environmental condition information and the plurality of gas types to obtain a concentration influence factor;
and carrying out feedback correction on the plurality of gas concentrations by using the concentration influence factors.
3. The method of claim 1, wherein the method for constructing the interference analysis network layer comprises:
Collecting air chamber panoramic image data in a preset area of the target optical air chamber;
positioning an interference source based on the air chamber panoramic image data, and establishing an interference source position distribution network;
Extracting a light beam emission route based on the light source generating device and the spectrum receiving device to obtain a light beam transmission position distribution area;
Locating a target interference source based on the interference source location distribution network and the beam transmission location distribution area;
And carrying out spectrum interference test based on the target interference source, and constructing the interference analysis network layer by using interference test data.
4. A gas concentration detection evaluation system for an optical gas cell, characterized by the steps for carrying out the method of any one of claims 1 to 3, the system comprising:
The monitoring module acquisition unit is used for acquiring a spectrum monitoring module of the target optical air chamber, wherein the spectrum monitoring module comprises a light source generating device and a spectrum receiving device;
a light beam emission unit for emitting a light beam to the target optical gas cell through the light source generation device, and outputting a gas absorption spectrum through the spectrum reception device;
the spectrum separation processing unit is used for activating the mixed spectrum separation module to perform spectrum separation processing on the gas absorption spectrum to obtain a plurality of separation spectrums;
A gas concentration analysis unit for performing gas type and concentration analysis based on the plurality of separation spectra, outputting a gas concentration detection result, wherein the gas concentration detection result includes a plurality of gas types and a plurality of gas concentrations;
The fault concentration recognition unit is used for carrying out fault concentration recognition on a historical fault information base connected with the target optical air chamber and generating a preset safety concentration threshold;
The gas concentration control unit is used for evaluating a concentration risk index based on the gas concentration detection result and the preset safety concentration threshold value and controlling the gas concentration of the target optical gas chamber according to the concentration risk index;
the spectral separation processing unit in the system is further configured to:
the mixed spectrum separation module comprises an interference analysis network layer and a spectrum separation network layer;
Performing interference noise treatment on the gas absorption spectrum through the interference analysis network layer to generate an optimized absorption spectrum;
and carrying out spectrum separation processing on the optimized absorption spectrum through the spectrum separation network layer to generate a plurality of separation spectrums.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410634214.8A CN118209491B (en) | 2024-05-22 | 2024-05-22 | Gas concentration detection and evaluation method and system for optical gas chamber |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410634214.8A CN118209491B (en) | 2024-05-22 | 2024-05-22 | Gas concentration detection and evaluation method and system for optical gas chamber |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118209491A CN118209491A (en) | 2024-06-18 |
| CN118209491B true CN118209491B (en) | 2024-08-06 |
Family
ID=91449163
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410634214.8A Active CN118209491B (en) | 2024-05-22 | 2024-05-22 | Gas concentration detection and evaluation method and system for optical gas chamber |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118209491B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104359861A (en) * | 2014-09-26 | 2015-02-18 | 中国石油大学(华东) | Light interference gas detection alarm device |
| CN117969436A (en) * | 2023-12-27 | 2024-05-03 | 重庆理工大学 | Monitoring low concentration NO and SO2Is a method of (2) |
| CN118032711A (en) * | 2024-04-12 | 2024-05-14 | 华夏天信传感科技(大连)有限公司 | Signal control method and system of laser gas sensor |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5325137B2 (en) * | 2010-02-16 | 2013-10-23 | 浜松ホトニクス株式会社 | Gas concentration calculation device and gas concentration measurement module |
| RU2495493C2 (en) * | 2010-10-25 | 2013-10-10 | Государственное образовательное учреждение высшего профессионального образования "Московский государственный университет геодезии и картографии" (МИИГАиК) | Method of predicting mortality risk of population in area of occurrence and rising concentration of pollutants in atmospheric air |
| JP2013113664A (en) * | 2011-11-28 | 2013-06-10 | Yokogawa Electric Corp | Laser gas analyzer |
| EP3704966A4 (en) * | 2017-10-30 | 2021-10-13 | KT&G Corporation | Aerosol generating device and method for controlling same |
| CN108195729B (en) * | 2018-03-05 | 2020-08-04 | 重庆大学 | PM2.5 concentration detection device based on photoacoustic spectroscopy |
| CN114235742B (en) * | 2021-12-17 | 2023-07-25 | 中国石油大学(华东) | Breathing gas-based large-class marker composite spectrum detection system and method |
| CN115935855B (en) * | 2023-01-09 | 2023-05-09 | 北京科技大学 | Urban greening method and device based on optimized tree pollen concentration index |
| CN116465841A (en) * | 2023-02-28 | 2023-07-21 | 山东省科学院激光研究所 | Method and system for detecting concentration of multiple gases by eliminating cross interference |
| CN116990248A (en) * | 2023-09-06 | 2023-11-03 | 深圳先闻科技有限公司 | Odor detection method, device, terminal and storage medium based on spectrum analysis |
| CN117846706A (en) * | 2024-02-18 | 2024-04-09 | 北京市市政一建设工程有限责任公司 | Monitoring and alarming method and control device for harmful gas of underground tunnel structure |
| CN117805047A (en) * | 2024-02-29 | 2024-04-02 | 深圳天益建设工程有限公司 | Inflammable gas remote monitoring system |
-
2024
- 2024-05-22 CN CN202410634214.8A patent/CN118209491B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104359861A (en) * | 2014-09-26 | 2015-02-18 | 中国石油大学(华东) | Light interference gas detection alarm device |
| CN117969436A (en) * | 2023-12-27 | 2024-05-03 | 重庆理工大学 | Monitoring low concentration NO and SO2Is a method of (2) |
| CN118032711A (en) * | 2024-04-12 | 2024-05-14 | 华夏天信传感科技(大连)有限公司 | Signal control method and system of laser gas sensor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118209491A (en) | 2024-06-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CA2134957C (en) | Transformer oil gas extractor | |
| US5910765A (en) | Sensor module | |
| WO2010106712A1 (en) | Etching apparatus, analysis apparatus, etching treatment method, and etching treatment program | |
| CN109211803B (en) | Device for rapidly identifying micro plastic based on microscopic multispectral technology | |
| CN110161013A (en) | Laser induced breakdown spectroscopy data processing method and system based on machine learning | |
| CN110108658B (en) | Infrared spectrum identification method and system for polluted gas | |
| CN116881749B (en) | Pollution site construction monitoring method and system | |
| CN113340874B (en) | Quantitative analysis method based on combination ridge regression and recursive feature elimination | |
| CN112834481B (en) | Raman spectrum enhancement measurement system and measurement method | |
| Kuzmiakova et al. | An automated baseline correction protocol for infrared spectra of atmospheric aerosols collected on polytetrafluoroethylene (Teflon) filters | |
| CN113758890A (en) | Gas concentration calculation method, device, equipment and storage medium | |
| GB2561879A (en) | Spectroscopic analysis | |
| CN109374530A (en) | The optoacoustic spectroscopy on-line monitoring method of sulfur hexafluoride gas decomposition product | |
| CN114222526B (en) | Multi-wavelength breath analysis system and method | |
| CN114184599B (en) | Single-cell Raman spectrum acquisition number estimation method, data processing method and device | |
| CN117538492B (en) | On-line detection method and system for pollutants in building space | |
| CN118209491B (en) | Gas concentration detection and evaluation method and system for optical gas chamber | |
| CN112651173B (en) | Agricultural product quality nondestructive testing method based on cross-domain spectral information and generalizable system | |
| CN112630180B (en) | Ultraviolet/visible light absorption spectrum model for detecting concentration of organophosphorus pesticide in water body | |
| CN116973348B (en) | Water quality analysis method and system for COD (chemical oxygen demand) on line by ultraviolet light method | |
| CN107462330B (en) | Color recognition method and system | |
| CN116662751A (en) | Tobacco leaf moisture content detection method for removing abnormal samples based on principal component analysis and lever value method | |
| CN118190852B (en) | Composition component identification method and system applied to gas detection | |
| CN111044504A (en) | Coal quality analysis method considering uncertainty of laser-induced breakdown spectroscopy | |
| CN111412987B (en) | Dynamic scanning detection device and method based on spectral characteristics |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |