CN-121978051-A - Infrared multi-gas identification method based on dynamic filter

CN121978051ACN 121978051 ACN121978051 ACN 121978051ACN-121978051-A

Abstract

The invention discloses an infrared multi-gas identification method based on a dynamic filter, which belongs to the technical field of infrared spectrum detection and gas perception, and comprises the steps of firstly obtaining an original response signal sequence of a multi-sampling channel under no gas, then constructing a self-adaptive weight operator aiming at pure gases with different concentrations to inhibit low signal-to-noise ratio channel interference, enabling the weight operator to act on gas response signals to obtain weighted response, mapping the signals to a feature space through orthogonal basis function projection transformation to obtain feature points representing the spectral features of the gas, finally extracting feature fingerprints and vector centers of known gases, executing the same signal processing flow on the mixed gas to be detected, and realizing type identification by combining the distribution of the feature points of the mixed gas in the feature space. The invention improves the system integration level by utilizing the tunable characteristic of the dynamic filter, realizes component identification by means of feature vector modeling, can still efficiently distinguish mixed gas under the conditions of low channel number and low signal to noise ratio, and has detection instantaneity and accuracy.

Inventors

ZHOU YI
LU LI
Ying Xiangxiao
ZHOU JIAN
WANG LINGFANG
CAO YAOYUN
CHEN JIANXIN

Assignees

中国科学院上海技术物理研究所

Dates

Publication Date: 20260505
Application Date: 20260408

Claims (10)

1. An infrared multi-gas identification method based on a dynamic filter is characterized by comprising the following steps: step 1, acquiring detection original response signal sequences under different sampling channels without gas; Step 2, constructing a weight operator based on a gas response signal sequence, acquiring detection original response signal sequences under different sampling channels for different types of gases under a plurality of known concentration conditions, and constructing a self-adaptive weight operator for inhibiting low signal-to-noise ratio channel interference according to the acquired gas response signal sequences; The method comprises the steps of 3, performing orthogonal feature space mapping based on self-adaptive weighting, namely, applying a weight operator to a gas response signal sequence to obtain weighted response, performing projective transformation on the gas response signal sequence to be detected by using a group of mutually orthogonal basis functions, mapping a one-dimensional response signal sequence into a feature space with at least two dimension components, and obtaining feature point coordinates representing the spectral distribution characteristics of the gas by extracting orthogonal projections of signals in a specific frequency domain or a spatial domain in the transformation process; And 4, constructing and classifying mixed gas vector features, namely repeating the steps 2 to 3 under the condition of gases with different concentrations, extracting normalized coordinate vectors in a feature space as feature fingerprints of the gas components, calculating feature vector centers of feature point data sets of the gases in the feature vector space, executing the operations of the steps 1 to 3 on the mixed gas to be tested to obtain feature points of the mixed gas, and combining the feature vector centers of the known gases to realize the type identification of the mixed gas according to the distribution of the feature points of the mixed gas in the feature space.
2. The method for identifying multiple gases by infrared rays based on a dynamic filter according to claim 1, wherein the step 1 is specifically: Under the condition that no target gas exists, different control signals are applied to the dynamic filter, and an original response signal sequence output by the infrared detector is obtained: ; Wherein, the Is under the condition of no gas The intensity of the response at the individual sampling channels, Is a discrete sampling node which is used for sampling, The total sampling channel number.
3. The method for identifying multiple gases in infrared based on dynamic filter according to claim 2, wherein in step 2, adaptive weighting operator The calculation formula is as follows: ; Wherein, the Is under the gas condition The intensity of the response at the individual sampling channels, Is the detection gas in the gas chamber.
4. The method for identifying multiple gases by infrared rays based on a dynamic filter according to claim 3, wherein the step 3 is specifically: And (3) applying a weight operator to the gas response signal sequence to obtain a weighted response: ; Wherein, the Is the first under the gas condition The total energy of the weighted response obtained by the action of the weighted response and the weight operator Expressed as: ; At the selected position Under the order harmonics, the orthogonal components of the feature vector are calculated: ; ; Wherein, the The number of harmonics selected for vector analysis, Is the first The real part of the order vector, Is the first The imaginary part of the order vector, 、 The method is an orthogonal basis function and is used for extracting phase and amplitude characteristics in the multichannel signals; through the mapping transformation, the gas response signal sequence is converted into characteristic points in a high-dimensional characteristic space: 。
5. The method for identifying multiple gases by infrared rays based on a dynamic filter according to claim 3, wherein the step 4 is specifically: repeating the steps 2 to 3 under the gases with different concentrations, extracting normalized coordinate vectors in a feature space as feature fingerprints of the gas components, obtaining a group of feature point data sets of the gas in the feature vector space according to the feature coordinate vectors, and calculating feature vector centers of the feature point data sets: ; Wherein, the As the center of the eigenvector of the gas, For the real part of the vector of the gas at different concentrations Is used for the average value of (a), Is the vector of the gas at different concentrations Is to mix the gases with the known characteristic vector centers to detect, and the mixed gas responds to Expressed as: ; Wherein, the For the number of gas species in the mixed gas, Is the first The concentration of the seed gas is determined, Is the first The seed gas is at the first Absorption response function per unit concentration at each channel.
6. The method for infrared multi-gas identification based on dynamic filter according to claim 5, wherein the unit concentration absorption response function The definition is as follows: ; Wherein, the To be only provided with The concentration of the seed gas is Probe response at that time, will Substituting the vector calculation formula: ; ; obtaining feature point coordinates: ; Wherein, the Vector points corresponding to the background without gas; taking a vector point corresponding to the non-gas background as a reference origin to obtain: ; Wherein: 。
7. The method for infrared multi-gas identification based on dynamic filter according to claim 6, wherein for a dual gas mixing case The above formula can be simplified as: ; Wherein, the 、 The vector characteristic points of the two gases are respectively, And The relative contribution ratio of the two gases in the mixed gas is respectively, 。
8. The method for infrared multi-gas identification based on dynamic filters as claimed in claim 4, wherein, Take the value 1.
9. The method for identifying the infrared multiple gases based on the dynamic filter according to claim 2, wherein the dynamic filter in the step 1 is an optical filter device with a central wavelength or equivalent spectral response capable of continuously or discretely changing along with an external control signal, and the working state of the optical filter device is adjusted by the external control signal, so that the rapid switching of a plurality of equivalent spectral channels is realized in the same optical system.
10. The method of claim 1, wherein the original response signal sequence in step 1 is obtained by synchronous or asynchronous acquisition of a plurality of discrete sampling channels with different center wavelengths, the signal sequence reflects the coupling relation between the gas absorption characteristic and the spectral response of the filter, and implies the overall distribution information of the gas absorption spectrum in the coverage band.

Description

Infrared multi-gas identification method based on dynamic filter Technical Field The invention belongs to the technical field of infrared spectrum detection and gas perception, and particularly relates to an infrared multi-gas identification method based on a dynamic filter. Background With the continuous improvement of gas detection requirements in the fields of industrial emission monitoring, environmental safety, energy utilization and public health, gas detection technology based on infrared absorption principle is widely applied due to high selectivity and high stability. According to different working mechanisms, the commonly used absorption spectrum technology at present comprises non-dispersive infrared spectrum technology, photoacoustic spectrum technology, fourier transform infrared spectrum technology and other technologies. Different technical routes have trade-offs in sensitivity, selectivity, volume, cost and real-time performance, and practical application scenes often select or combine a plurality of methods according to requirements so as to achieve balance between performance and practicability. The non-dispersive infrared technology has the advantages of high sensitivity, easy maintenance, strong environmental adaptability and the like. However, current research in the field of non-dispersive infrared gas detection is focused mainly on single gas detection, with relatively little research in multi-component gas detection. The phenomenon mainly results from the complexity of multi-component gas detection technology, including the problems of high cost, large volume, poor reliability and the like due to the fact that a plurality of fixed filters are needed for different gases. In addition, the existing multi-gas detection and quantitative analysis method relies on the means of line-by-line integration, nonlinear least square fitting and the like, but has the defects of complex calculation process, poor real-time performance and sensitivity to noise and system drift. In recent years, some researches attempt to introduce a statistical analysis or machine learning method to process multichannel signals, but the model training process relies on a large amount of sample data, so that the physical interpretability is weak, and the generalization capability is limited when the working condition changes. Disclosure of Invention In order to solve the technical problems, the invention provides an infrared multi-gas identification method based on a dynamic filter, which is used for acquiring multi-channel gas information through the dynamic filter and carrying out feature vector calculation, and realizing gas type identification based on feature values and distribution in a feature space. Dynamic filters refer to optical filters whose center wavelength or equivalent spectral response may be varied continuously or discretely with external control signals (e.g., voltage, current, etc.). The working state of the dynamic filter is regulated by an external control signal, so that the rapid switching of a plurality of equivalent spectrum channels can be realized in the same optical system. Compared with a fixed filter, the dynamic filter has the advantages of channel reconfigurability, wide spectrum coverage range, high system integration level and the like, and is particularly suitable for multi-component gas detection and miniaturized sensor application. The gas detection research based on the dynamic filter is less, and is concentrated on single gas quantitative analysis or simple characteristic extraction based on peak intensity, and a feasible analysis method is still lacked for how to fully mine multi-gas distinguishing information contained in a dynamic response sequence under the condition of low channel number and how to realize classification of mixed gas. The method utilizes multichannel infrared gas absorption signals acquired by a dynamic filter, and maps response characteristics of different gas components in a time-frequency domain into a distinguishing geometric distribution mode in a characteristic space by constructing a vector model, so that the identification of gas types is realized. The specific technical scheme is as follows: an infrared multi-gas identification method based on a dynamic filter comprises the following steps: step 1, acquiring detection original response signal sequences under different sampling channels without gas; Step 2, constructing a weight operator based on a gas response signal sequence, acquiring detection original response signal sequences under different sampling channels for different types of gases under a plurality of known concentration conditions, and constructing a self-adaptive weight operator for inhibiting low signal-to-noise ratio channel interference according to the acquired gas response signal sequences; The method comprises the steps of 3, performing orthogonal feature space mapping based on self-adaptive weighting, namely, applying a weight op