A monitoring meter for toxic and harmful gases

Abstract

The application provides a kind of toxic and harmful gas monitoring meter. Including: optical gas sensor array, reaction gas chamber, miniature fiber optic spectrometer, light detector, light source and data processing system. Optical gas sensor array is arranged in reaction gas chamber, light source, optical gas sensor array, light detector and optical gas sensor array are sequentially connected by light path, and reaction gas chamber has gas inlet and gas outlet. Light source emits light signal to optical gas sensor array, and the light signal reflected by optical gas sensor array is transmitted to miniature fiber optic spectrometer through light detector, and data processing system analyzes the spectral information to obtain the type and concentration information of toxic and harmful gas in reaction gas chamber. The gas monitoring meter of the application can realize selective identification of trace target gas under atmospheric humidity environment, ultra-high sensitivity, fast response speed, good stability, high reusability, digital metering, intelligent detection and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of toxic and harmful gas metering, and particularly relates to a monitoring meter for toxic and harmful gas. BACKGROUND

[0002] With the development of world industry and cities, toxic and harmful gases (such as NH3, SO2, Cl2, H2S, CO2, H2, etc.) continuously pollute the air. The intake of toxic and harmful gases, even in trace amounts, can cause damage to the human body. Therefore, it is urgent to achieve trace detection (≤5ppm) of industrial toxic and harmful gases in the atmospheric environment. However, due to the complex composition of the atmosphere, such as gas cross-sensitivity and atmospheric humidity interference, it is a big challenge in the field of gas sensing. In addition, it is also a big technical problem to accurately detect the type and concentration of gas and realize network digital metering. Therefore, it is of great application significance to develop a metering monitoring device that can intelligently identify trace industrial toxic and harmful gases in an atmospheric humidity environment.

[0003] A sensor array is a kind of sensing element that can effectively solve the problem of gas cross-sensitivity, which is composed of multiple high-sensitivity gas sensors. Compared with traditional commercial electric gas sensors, optical gas sensors have the advantages of anti-electric and magnetic interference, and can work under normal temperature and humidity conditions, etc. In recent years, they have attracted widespread attention. The emergence of photon technology has promoted the development of optical sensors. Photonic crystals are a kind of artificial periodic dielectric structure with photonic band gap (PBG). Its unique photonic band gap (PBG) can reflect light of a specific wavelength. When external stimuli change the refractive index (RI) or thickness of the photonic crystal, the position of the PBG will shift, resulting in changes in optical signals and obvious structural colors. These optical signals can be easily obtained by the naked eye or instruments. Metal organic frameworks (MOFs) are widely used in gas sensing due to their large specific surface area, high porosity and adjustable structure. Therefore, metal organic frameworks with hydrophobic properties are used as sensing materials to prepare photonic crystal superstructure sensing layers. By optimizing the structure of the superstructure photonic crystal sensing layer, the humidity interference and trace detection problems of optical gas sensors can be effectively solved.

[0004] In addition, based on the Internet of Things and digital twin technology, the instrument can be intelligentized and digitized, which can quickly warn and prevent, greatly reducing the risk, and effectively saving manpower and financial resources.

[0005] At present, there are many methods for detecting industrial toxic and harmful gases in the prior art, including ion mobility spectrometry (IMS), Raman spectroscopy and gas chromatography mass spectrometry, etc. However, the detection instruments of these methods are expensive and bulky, which is not conducive to real-time detection on site, and the operation is complex and requires a long time for analysis. SUMMARY

[0006] The embodiment of the present application provides a toxic and harmful gas monitoring meter to effectively monitor and measure toxic and harmful gas in an atmospheric humidity environment.

[0007] In order to achieve the above object, the present application adopts the following technical scheme.

[0008] A toxic and harmful gas monitoring meter, comprising: an optical gas sensor array, a reaction gas chamber, a micro optical fiber spectrometer, a light detector, a light source and a data processing system.

[0009] The optical gas sensor array is arranged in the reaction gas chamber, the light source, the optical gas sensor array, the light detector and the optical gas sensor array are sequentially connected through an optical path, the micro optical fiber spectrometer, the data processing system and the alarm display screen are sequentially connected in circuit, and the reaction gas chamber is provided with an air inlet and an air outlet for the input and output of trace industrial toxic and harmful gas.

[0010] After the light source emits light signals to the reaction gas chamber, the light signals are absorbed by the optical gas sensor array, the light signals reflected by the optical gas sensor array are transmitted to the light detector, the light detector converts the light signals into optical signals, the optical signals are transmitted to the micro optical fiber spectrometer, the micro optical fiber spectrometer analyzes the optical signals to obtain the spectral information of the gas in the reaction gas chamber, the spectral information is transmitted to the data processing system, the data processing system analyzes the spectral information to obtain the type and concentration information of the toxic and harmful gas in the reaction gas chamber.

[0011] Preferably, the monitoring meter further comprises: a shell, a power supply system and an alarm display screen.

[0012] The shell is an outer packaging protective shell for protecting, protecting and containing the internal components; the power supply system supplies power to the monitoring meter; the alarm display screen is used for monitoring and displaying the type and concentration information of the toxic and harmful gas in the reaction gas chamber, and making alarm and warning.

[0013] Preferably, the optical gas sensing array is composed of a plurality of optical gas sensors based on superstructure MOFs photonic crystal sensing layers, and the superstructure MOFs photonic crystal sensing layer comprises a silicon substrate and a MOFs superstructure photonic crystal.

[0014] Preferably, the MOFs material of the superstructure MOFs photonic crystal sensing layer is a hydrophobic MOFs with specific requirements of specific surface area and porosity, and the MOFs superstructure photonic crystal is a man-made periodic medium with photonic band gap prepared from MOFs nanoparticles.

[0015] Preferably, the preparation method of the superstructure MOFs photonic crystal sensing layer comprises the following steps:

[0016] The effects of various intermolecular forces, assembly lattices and preparation processes on the structure of the superstructure MOFs photonic crystal and on the adsorption of target gases are simulated by COMSOL software, and the optimal photonic crystal sensing layer is constructed; the structure of the optimal photonic crystal sensing layer is optimized and parameters are set by using the first-principle density functional theory, the competitive adsorption process of the superstructure MOFs photonic crystal sensing layer to various toxic and harmful gases and water molecules is simulated, and the optimal adsorption site of each gas is determined.

[0017] Theoretical calculation of gas adsorption energy of the photonic crystal sensing layer is performed, the adsorption performance of various MOFs materials to various toxic and harmful gases is tested, and the MOFs material with the best adsorption to the target gas and the most suitable MOFs material are selected.

[0018] The synthesized monodisperse MOFs nanoparticles are used to synthesize the superstructure MOFs photonic crystal by self-assembly technology, the MOFs superstructure photonic crystal optical sensors of various toxic and harmful gases are used to form a superstructure MOFs photonic crystal optical gas sensor array, and the prepared superstructure MOFs photonic crystal optical gas sensor array is placed in a gas sensing reaction chamber for subsequent sensing performance detection of trace toxic and harmful gases.

[0019] Preferably, the MOFs superstructure photonic crystal optical sensors of various toxic and harmful gases comprise: a MOFs superstructure photonic crystal NH3 optical sensor, a MOFs superstructure photonic crystal SO2 optical sensor, a MOFs superstructure photonic crystal Cl2 optical sensor, a MOFs superstructure photonic crystal H2S optical sensor, a MOFs superstructure photonic crystal CO2 optical sensor and a MOFs superstructure photonic crystal H2 optical sensor.

[0020] Preferably, the data processing system is used for data preprocessing of the received spectral information, the data preprocessing comprises extraction and normalization of characteristic values, virtual modeling and simulation of the working environment of the optical gas sensor array are performed based on the preprocessed spectral information by using digital twinning technology, data acquisition and transmission processes of the optical gas sensor array in various scenarios are simulated, extended spectral information is obtained, the abscissa of the spectral information is the wavelength of the reflection peak, the ordinate is the intensity of the reflection peak, gas response characteristics in the extended spectral information are extracted by using a feature extraction method, the types of gases are classified and recognized by a neural network according to the gas response characteristics, the types and concentration information of various toxic and harmful gases in the reaction chamber are obtained, when the concentration range of a certain toxic and harmful gas exceeds a set threshold value, the alarm display screen is displayed and an alarm is sent.

[0021] As can be seen from the technical solutions provided by the above-mentioned embodiments of the present application, the gas monitoring meter adopts a three-dimensional self-assembly method, and the preparation process is relatively simple and low in price. For trace target gas detection, the gas monitoring meter can realize selective identification, ultra-high sensitivity, fast response speed, good stability, high reusability, digital metering, intelligent detection and the like of trace target gas in an atmospheric humidity environment.

[0022] Additional aspects and advantages of the present application will be described in the following description and will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0024] Figure 1 A structural schematic diagram of a gas monitoring meter based on the Internet of Things and digital twinning is provided for the embodiments of the present application.

[0025] Figure 2 A structural diagram of a superstructure MOFs photonic crystal sensing layer is provided for the embodiments of the present application.

[0026] Figure 3 A structural schematic diagram of a superstructure MOFs photonic crystal optical gas sensor array is provided for the embodiments of the present application.

[0027] Figure 4 A sensing mechanism schematic diagram of a superstructure MOFs photonic crystal optical gas sensor array in a humid air environment is provided for the embodiments of the present application.

[0028] Figure 5 A work flow diagram of a gas monitoring meter based on the Internet of Things and digital twinning is provided for the embodiments of the present application.

[0029] Figure 6 A gas optical fingerprint spectrum is provided for the embodiments of the present application.

[0030] Figure 7 A gas classification result diagram based on an artificial neural network is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0031] Embodiments of the present application are described in detail below with reference to several examples illustrated in the accompanying drawings, wherein like reference numerals refer to like elements or elements having the same function throughout the several examples. The embodiments described below are merely exemplary and are not to be construed as limiting the application.

[0032] As will be understood by those familiar with the art, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. It should also be understood that the use of the term "including" as well as other like terms, means "including but not limited to" and therefore specifies the presence of stated features, integers, steps, operations, elements, and / or components but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we refer to an element being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements can also be present. In addition, the use of "connection" or "coupling" herein also includes wireless connection or coupling. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0033] As will be understood by those familiar with the art, the terms used herein have their ordinary meanings and are used in the art as follows, unless specifically defined otherwise. It should be further understood that the use of relational terms, such as "first", "second", "top" and "bottom", are used solely to distinguish one from another entity or action without necessarily implying a strict time sequence or without necessarily implying a spatial sequence or without necessarily implying a sequence in quality, and the like.

[0034] In order to facilitate the understanding of the embodiments of the present application, further explanation will be made in combination with the accompanying drawings and several specific examples below, and each example does not constitute a limitation to the embodiments of the present application.

[0035] The application integrates a photonic crystal-based intelligent sensor array, an Internet of Things and a digital twin technology, and develops a novel Internet of Things and digital twin-based toxic and harmful gas monitoring meter. First, an optical gas sensor array composed of optical gas sensors based on photonics solves the defects of cross-sensitivity of multiple gases and susceptibility to environmental humidity interference. Second, the digital metrology model based on the Internet of Things and the digital twin can provide comprehensive system modeling and simulation to conduct various simulation experiments and tests, provide a theoretical basis and technical route for the experiments, greatly reduce the cost and risk of actual tests, and enable faster optimization and improvement. Finally, combined with artificial intelligence, big data and deep learning technology, the collected data of the device can be analyzed in depth and quantified and classified. The monitoring meter realizes the automation and modernization of gas detection, and can significantly improve the efficiency of industrial production and safety monitoring. Based on the Internet of Things and digital twin technology, real-time network metrology detection and early warning of industrial toxic and harmful gases are realized. When the concentration of toxic and harmful gases exceeds the threshold, the type and concentration value of the toxic and harmful gases will be displayed on the display screen of the monitoring meter after the alarm.

[0036] The working flow chart of the toxic and harmful gas monitoring meter provided by the embodiment of the application is shown in Figure 5 , and the structural schematic diagram is shown in Figure 1 , which comprises a shell, a power supply system, an optical gas sensor array, a reaction gas chamber, a miniature fiber optic spectrometer, a light detector, a light source, an alarm display screen and a data processing system.

[0037] The shell is an outer packaging protective shell for protecting, protecting and accommodating the internal components; the power supply system is a power supply device of the monitoring meter; the reaction gas chamber is used for gas sensing detection; the optical gas sensor array is a gas sensing device of the monitoring meter of the application; the miniature fiber optic spectrometer is a small-sized optical spectrum analysis system capable of accurately measuring the wavelength of the optical signal and performing spectral analysis; the light detector converts the optical signal into an output signal by using the photoelectric effect; the light source is a halogen lamp light source for providing the optical signal; the data processing system displays the spectral information; the alarm display screen is used for monitoring and displaying the index information of the specified area, and making an alarm and a warning.

[0038] The connection relationship and working process of each component are simply described as follows. Figure 1 The gas monitoring meter of the application comprises two power supplies, wherein the lower power supply is connected to the light source, the light source is a halogen lamp light source, and serves as incident light; after the light source emits an optical signal to the optical gas sensor array, the reflected optical signal is converted into an optical signal easy to detect by the light detector, the optical signal can be analyzed by the fiber optic spectrometer to obtain the spectral information of the test sample, the spectral information is a reflection spectrum, the abscissa is the wavelength of the reflection peak, and the ordinate is the intensity of the reflection peak, and then the data processing system displays the spectral information (such asFigure 1 9 is a computer). In addition, the other line of the fiber spectrometer is also connected to the alarm display screen, which is used to directly read the spectrum information and alarm signals, and the alarm display screen is connected to the power supply above.

[0039] Gas sensing process: when the halogen lamp light source is projected as incident light onto the optical sensor in the optical gas sensor array, due to the three-dimensional photonic crystal of the sensing layer having a photonic band gap, the reflected light signal is captured by the light detector and analyzed by the fiber spectrometer to obtain the reflection spectrum, the abscissa is the wavelength of the reflection peak, and the ordinate is the reflection peak intensity. The collected reflection spectrum is the original reflection spectrum. The reaction chamber has a gas inlet and a gas outlet for the introduction and discharge of trace industrial toxic and harmful gases. When trace industrial toxic and harmful gases are introduced, due to the adsorption of the sensor sensing material, the refractive index (RI) of the material will change, the photonic band gap will change, and the wavelength and intensity of the reflection peak will also move. The spectrum obtained after detection testing.

[0040] The above optical gas sensing array is composed of a plurality of optical gas sensors based on the superstructure MOFs photonic crystal sensing layer, Figure 2 A structure diagram of a superstructure MOFs photonic crystal sensing layer provided by the embodiment of the present application, the superstructure MOFs photonic crystal sensing layer includes a silicon substrate and a MOFs superstructure photonic crystal.

[0041] On the basis of the above scheme, the silicon substrate is rectangular, circular or polygonal, etc.

[0042] On the basis of the above scheme, the MOFs material of the superstructure MOFs photonic crystal sensing layer is a hydrophobic MOFs with a large specific surface area and a very high porosity.

[0043] On the basis of the above scheme, the superstructure MOFs photonic crystal is a man-made periodic medium prepared from MOFs nanoparticles and has a photonic band gap. Due to the lattice period being comparable to the visible wavelength, the structural color can be identified and judged by the naked eye. The manufacturing method of the superstructure MOFs photonic crystal sensing layer includes the following steps:

[0044] Step 1: Design of superstructure MOFs photonic crystal sensing layer

[0045] Step 1.1: Structure design simulation of photonic crystal sensing layer

[0046] The structural design of the sensing layer is carried out by COMSOL software, and a superstructure MOFs photonic crystal model meeting the requirements is simulated and constructed. By simulating the influence of various intermolecular forces, assembly lattices, preparation processes and the like on the structure of the superstructure MOFs photonic crystal and the influence of the same on the adsorption of the target gas, the densest photonic crystal structure is predicted and optimized. Finally, the photonic crystal sensing layer structure and preparation scheme with the best adsorption performance for the target gas are selected.

[0047] Step 1.2 Simulation and calculation of the adsorption performance of the sensing layer to various gases

[0048] The structure of the best photonic crystal sensing layer obtained in step 1.1 is optimized and parameterized by using the first-principle density functional theory, the competitive adsorption process of the superstructure MOFs photonic crystal sensing layer to NH3, SO2, Cl2, H2S, CO2, H2 and other industrial toxic and harmful gases and water molecules is simulated, and the best adsorption site of each gas is determined. Secondly, the gas adsorption energy of the photonic crystal sensing layer is theoretically calculated, the adsorption performance of different types of MOFs materials to NH3, SO2, Cl2, H2S, CO2, H2 and other gases is predicted, and the MOFs material with the best adsorption to the target gas is selected.

[0049] On the basis of the above scheme, the MOFs are at least six hydrophobic MOFs.

[0050] Step 2 Preparation of the superstructure MOFs photonic crystal sensing layer

[0051] Step 2.1, the synthesized monodisperse MOFs nanoparticles are synthesized into superstructure MOFs photonic crystals by self-assembly technology, Figure 2 The preparation process of the superstructure MOFs photonic crystal is shown.

[0052] On the basis of the above scheme, the photonic crystal preparation technology includes solvent evaporation self-assembly, spin coating technology, solid-liquid interface self-assembly technology (LB), microfluidic technology, spray drying method and gravity deposition and the like.

[0053] The structural diagram of the superstructure MOFs photonic crystal optical gas sensor array provided by the embodiment of the application is shown in Figure 3 The superstructure MOFs photonic crystal optical gas sensor array is composed of a MOFs superstructure photonic crystal NH3 optical sensor, a MOFs superstructure photonic crystal SO2 optical sensor, a MOFs superstructure photonic crystal Cl2 optical sensor, a MOFs superstructure photonic crystal H2S optical sensor, a MOFs superstructure photonic crystal CO2 optical sensor and a MOFs superstructure photonic crystal H2 optical sensor and the like.

[0054] Figure 4 A schematic diagram of the sensing mechanism of the superstructure MOFs photonic crystal optical gas sensor array in a humid air environment is provided for the embodiments of the present application. The prepared superstructure MOFs photonic crystal optical gas sensor array is placed in a gas sensing reaction chamber for subsequent detection of the sensing performance of a series of trace gases (NH3, SO2, Cl2, H2S, CO2, H2).

[0055] On the basis of the above scheme, the sensing performance detection of the series of trace gases (NH3, SO2, Cl2, H2S, CO2, H2) includes sensing performance detection of trace gases (NH3, SO2, Cl2, H2S, CO2, H2) under different humidity environments (such as RH 20%, RH 40%, RH 60%, RH 80%, RH 100%).

[0056] Digital twin technology refers to the use of digital models to simulate and virtually model physical entities. In the network digital metrology monitor system based on the Internet of Things and digital twin technology, digital twin technology can be used for simulation and optimization of sensor networks. In the composition system of the monitor, sensors are an important part of the system, which can collect various environmental data. Through digital twin technology, the working environment of the sensor can be virtually modeled and simulated, simulating the data collection and transmission process in various scenarios; through optimization analysis, the performance and reliability of the sensor can be improved, making it better cope with various complex environments.

[0057] Building a digital twin model mainly includes data collection, three-dimensional modeling, real-time data integration, simulation and simulation, and interaction and visualization. Data collection is mainly collected by optical gas sensor arrays. Three-dimensional modeling is a virtual representation of physical entities created in three-dimensional modeling software using collected sensor data. Real-time data integration is to integrate real-time data (sensor data) in the physical world into the digital twin model, so that the model can reflect the current state of the physical entity and predict future behavior. Simulation and simulation are used to test the performance of physical entities under different conditions using digital twin models, which helps to optimize design and operation strategies and reduce potential risks. Interaction and visualization are to present the digital twin model to users in an intuitive and interactive way through a three-dimensional visualization platform, which helps users better understand the model and make more informed decisions.

[0058] Deep learning data preprocessing: Before performing deep learning classification algorithms, we need to preprocess the collected raw sensor data, including feature value extraction, normalization, etc., to improve data quality. The deep learning classification algorithms we use include but are not limited to logistic regression, support vector machine (SVM), decision tree, random forest, k-nearest neighbor, artificial neural network, etc.

[0059] Specifically, how to achieve selective identification of trace target gas in atmospheric humidity environment: according to Figure 6 , "Performance test of trace industrial toxic and harmful gas sensor in wet air", we will take the sensing data obtained by testing trace toxic and harmful gas in wet air environment as the original data set, which will be used for subsequent digital twin technology model establishment and prediction and deep learning classification algorithm data set, based on the establishment of Internet of Things and digital twin model. After the actual sensing data is obtained, it is preprocessed through deep learning classification algorithm (but not limited to deep learning) for data preprocessing, classification identification and prediction of various trace gases. The final alarm module introduces a display screen and alarm program software, which will display the obtained spectral information on the display screen. After multiple data calibration and measurement, an accurate toxic and harmful gas concentration range is obtained, and when the threshold is exceeded, the display screen will display a prompt to remind the staff.

[0060] Figure 6 A gas optical "fingerprint" spectrum diagram provided for the embodiment of the present application. The gas optical "fingerprint" spectrum refers to when the sensor array is exposed to the toxic and harmful gas analyte, the analyte is sensed by the sensor array, and then the sensing data is analyzed using a pattern recognition system to identify the specific gas "optical fingerprint" spectrum.

[0061] Figure 7 A gas classification result diagram based on artificial neural network provided for the embodiment of the present application. The sensing data obtained by gas sensing test will be used as the data set for subsequent big data artificial neural network operation. The artificial neural network classification algorithm data processing process includes signal acquisition preprocessing and pattern recognition algorithm.

[0062] The reason why the present application adopts a sensor array instead of a single gas sensor is that the sensor array can classify and identify multiple gases to determine the type and concentration.

[0063] On the basis of the above scheme, signal preprocessing is to reduce the baseline or normalize the signal value of the sensor array. Pattern recognition includes qualitative identification of gas types and quantitative estimation of concentration.

[0064] On the basis of the above scheme, the classification process mainly uses feature extraction method to extract gas response characteristics and then combines neural network to classify gas types.

[0065] On the basis of the above scheme, the feature extraction method includes principal component analysis (PCA), linear discriminant analysis (LDA), local linear embedding (LLE), local linear mapping (LPP), isometric mapping (Isomap), etc.

[0066] On the basis of the above scheme, PCA is a linear feature extraction method, which reflects more original information with less information, and these less information is independent of each other.LDA is a supervised learning algorithm, its goal is to reduce the internal difference as much as possible, while expanding the difference between different categories.When the data is small, the PCA feature extraction effect is better than LDA, but when the data is large, the LDA feature extraction effect is better than PCA.

[0067] The design platform of the gas monitoring meter alarm program software is based on MATLAB software.MATLAB software provides App designer interactive application development environment.It can conveniently create graphical user interface application programs.

[0068] On the basis of the above scheme, these application programs can interact with the compiled MATLAB code to realize the deployment of the application program.Compared with other development tools, App designer has the characteristics of user-friendly, high customization of program, rich built-in functions and support for code reuse.

[0069] On the basis of the above scheme, the writing of the gas monitoring meter alarm program software is carried out by using optical Morpho3.2 software for secondary development.

[0070] In summary, the present application integrates intelligent sensors, Internet of Things and digital twin technology to establish the monitoring and data analysis capability of toxic and harmful gases in industrial production and living scenes, and brings more efficient, accurate and reliable measurement system and safety protection to pharmaceutical, chemical and other enterprises and life.The content of the present application includes research on industrial toxic and harmful gas sensor array based on photonics, research on digital metrology model based on Internet of Things and digital twin, research on application of digital metrology technology in chemical, pharmaceutical and other enterprise laboratory scenes, and research on application of digital metrology technology in safety production scenes.

[0071] Compared with the traditional semiconductor electrical gas monitor, it needs to be used at high temperature, which is easy to cause energy consumption and danger, and the sensitivity of the device is greatly affected by humidity.The gas monitoring meter of the present application can work at room temperature, and is resistant to electric, magnetic and humidity interference.It is low in price and easy to prepare, convenient to carry, can be used for on-site detection, resistant to atmospheric humidity interference, high in stability and can be reused.

[0072] The gas monitoring meter of the present application is internally composed of a three-dimensional photonic crystal optical gas sensor array. Compared with one-dimensional photonic crystals and two-dimensional photonic crystals, three-dimensional photonic crystals have advantages in spatial distribution, can greatly increase internal pores and gas adsorption sites, and promote gas diffusion. In addition, three-dimensional photonic crystals have complete photonic band gaps, which are conducive to the transduction of optical signals. Trace detection (<1ppm) of toxic and harmful gases in the atmosphere can be achieved; and under different atmospheric humidity environments, selective recognition and rapid detection of trace (<1ppm) toxic and harmful gases can still be achieved, early detection and early prevention can be achieved. The alarm module introduced in the gas monitoring meter sets a threshold on the device, and once the gas concentration exceeds the threshold, it will be displayed to the display screen to remind the relevant staff.

[0073] Those skilled in the art can understand that the drawings are only schematic of an embodiment, and the modules or flows in the drawings are not necessarily essential for implementing the present application.

[0074] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and the necessary general hardware platform. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

[0075] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, they are described more simply, and the relevant parts refer to the part of the method embodiments. The above-described device and system embodiments are only schematic, and the units described as separate components can be or can not be physically separated, and the components displayed as units can be or can not be physical units, i.e. they can be located in one place, or distributed on multiple network units. According to the actual needs, some or all of the modules can be selected to achieve the purpose of the present embodiment. Those skilled in the art can understand and implement without creative labor.

[0076] The above merely describes preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any changes or replacements within the technical scope disclosed by the present application, which can be easily thought by those skilled in the art, should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A monitoring and measuring instrument for toxic and harmful gases, characterized in that, include: Optical gas sensor array, reaction chamber, miniature fiber optic spectrometer, photodetector, light source and data processing system; The optical gas sensor array is disposed in the reaction gas chamber. The light source, the optical gas sensor array, the photodetector and the optical gas sensor array are connected in sequence through an optical path. The miniature fiber optic spectrometer, the data processing system and the alarm display screen are connected in sequence by circuit. The reaction gas chamber has an inlet and an outlet for the introduction and discharge of trace industrial toxic and harmful gases. After the light source emits a light signal into the reaction chamber, the light signal is absorbed by the optical gas sensor array. The light signal reflected by the optical gas sensor array is transmitted to the photodetector. The photodetector converts the light signal into an optical signal and transmits the optical signal to the miniature fiber optic spectrometer. The miniature fiber optic spectrometer analyzes the optical signal to obtain the spectral information of the gas in the reaction chamber and transmits the spectral information to the data processing system. The data processing system analyzes the spectral information to obtain the types and concentrations of toxic and harmful gases in the reaction chamber. By simulating the effects of various intermolecular forces, lattice assembly, and fabrication processes on the photonic crystal structure of superstructure MOFs and their influence on the adsorption of target gases using COMSOL software, an optimal photonic crystal sensing layer was constructed. The structure of the optimal photonic crystal sensing layer was then optimized and its parameters were set using first-principles density functional theory. The competitive adsorption process of the superstructure MOFs photonic crystal sensing layer on various toxic and harmful gases and water molecules was simulated to determine the optimal adsorption sites for each gas. The gas adsorption energy of the photonic crystal sensing layer is theoretically calculated to predict the influence of different types of MOFs materials on the adsorption performance of various toxic and harmful gases, and to select the most suitable MOFs material with the best adsorption for the target gas. The synthesized monodisperse MOF nanoparticles were used to synthesize superstructured MOF photonic crystals through self-assembly technology. A superstructured MOF photonic crystal optical gas sensor array was constructed using MOF superstructured photonic crystal optical sensors for various toxic and harmful gases. The prepared superstructured MOF photonic crystal optical gas sensor array was placed in a gas sensing reaction chamber for subsequent series of trace toxic and harmful gas sensing performance detection.

2. The monitoring and measuring instrument according to claim 1, characterized in that, The monitoring and measuring instrument also includes: a housing, a power supply system, and an alarm display screen; The housing is an outer protective shell used to protect and house the internal components; the power system supplies power to the monitoring and measuring instrument; the alarm display screen is used to monitor and display the types and concentrations of toxic and harmful gases in the reaction chamber, and to issue alarms and warnings.

3. The monitoring and measuring instrument according to claim 1, characterized in that, The optical gas sensing array consists of multiple optical gas sensors based on a superstructure MOFs photonic crystal sensing layer, which includes a silicon substrate and a MOFs superstructure photonic crystal.

4. The monitoring and measuring instrument according to claim 1, characterized in that, The MOFs material of the superstructure MOFs photonic crystal sensing layer is a hydrophobic MOF with specific surface area and porosity meeting specific requirements. The MOFs superstructure photonic crystal is an artificial periodic medium with a photonic bandgap prepared from MOFs nanoparticles.

5. The monitoring and measuring instrument according to claim 1, characterized in that, The MOFs superstructure photonic crystal optical sensors for various toxic and harmful gases include: MOFs superstructure photonic crystal NH3 optical sensor, MOFs superstructure photonic crystal SO2 optical sensor, MOFs superstructure photonic crystal Cl2 optical sensor, MOFs superstructure photonic crystal H2S optical sensor, MOFs superstructure photonic crystal CO2 optical sensor and MOFs superstructure photonic crystal H2 optical sensor.

6. The monitoring and measuring instrument according to any one of claims 1 to 5, characterized in that: The data processing system is used to preprocess the received spectral information. This preprocessing includes feature extraction and normalization. Based on the preprocessed spectral information, the system uses digital twin technology to virtually model and simulate the working environment of the optical gas sensor array, simulating the data acquisition and transmission process of the optical gas sensor array in various scenarios to obtain expanded spectral information. The horizontal axis of this spectral information represents the wavelength of the reflection peak, and the vertical axis represents the intensity of the reflection peak. The system uses feature extraction methods to extract gas response features from the expanded spectral information. A neural network is used to classify and identify the types of gases based on these gas response features, obtaining the types and concentrations of various toxic and harmful gases in the reaction chamber. When the concentration of a certain toxic or harmful gas exceeds a set threshold, the system displays this information on an alarm display screen and issues an alarm.

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