Gas concentration infrared sensor and detection method thereof

Abstract

The invention belongs to the technical field of detection, and discloses a gas concentration infrared sensor and a detection method thereof.The detection method comprises the steps that transmittance data of two channels of the infrared sensor are collected in real time, and meanwhile sensor surface temperature and environment humidity parameters are obtained to form a multi-parameter synchronous collection data set; establishing a humidity compensation function based on the collected environment humidity parameters, dynamically correcting the transmittance of the main detection channel, judging the condensation risk according to the transmittance change rate of the reference channel, calculating the transmittance change rate of the main detection channel, extracting the humidity interference characteristic quantity of the reference channel, and generating fusion characteristic parameters; performing gas existence judgment, and triggering a gas existence flag bit; according to a gas existence flag bit state, adopting a temperature self-adaptive response value calculation method and combining environment compensation parameters to carry out concentration conversion, and outputting a gas concentration value; and through a multi-parameter synchronous acquisition and environment compensation mechanism, the problem of environment interference in a high-temperature and high-humidity environment is effectively solved, and the measurement accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of sensor technology, and in particular to a gas concentration infrared sensor and a detection method thereof. Background Art

[0002] Gas concentration detection has important application value in industrial production, environmental monitoring and other fields. Infrared sensor technology has become one of the mainstream solutions for gas detection due to its advantages such as non-contact and high sensitivity. However, in some special industrial environments, such as chemical production, metallurgical processing and other high temperature and high humidity conditions, traditional gas detection methods often cannot meet actual needs. These environments not only have drastic temperature fluctuations, but also are accompanied by continuous high humidity, which poses severe challenges to the stability and accuracy of the sensor.

[0003] In the prior art, infrared gas sensors usually use a single-channel detection method to calculate the gas concentration by measuring the transmittance change in the characteristic absorption band of the target gas. However, this detection method has obvious defects in high temperature and high humidity environments: first, water vapor has multiple absorption peaks in the infrared band, which easily overlaps with the absorption peak of the target gas, resulting in deviations in the measurement results; second, thermal radiation interference and humidity fluctuations in high temperature environments can cause sensor baseline drift and reduce measurement stability; finally, there is a lack of an effective environmental parameter compensation mechanism, making it difficult to adapt to the precise measurement requirements under complex working conditions. These technical defects have seriously restricted the application effect of infrared sensors in special industrial environments.

[0004] In view of this, it is necessary to improve the gas detection technology of the infrared gas sensor in the prior art to solve the technical problems that it is sensitive to environmental interference and cannot achieve continuous detection. Summary of the invention

[0005] The purpose of the present invention is to provide a gas concentration infrared sensor and a detection method thereof to solve the above technical problems.

[0006] To achieve this object, the present invention adopts the following technical solutions: A method for detecting a gas concentration infrared sensor comprises the following steps: Step S1, real-time acquisition of transmittance data of dual channels of infrared sensors, and simultaneous acquisition of sensor surface temperature and ambient humidity parameters, to form a multi-parameter synchronous acquisition data set; the transmittance data includes the transmittance of the main detection channel and the transmittance of the reference channel; Step S2, establishing a humidity compensation function based on the collected environmental humidity parameters, dynamically correcting the transmittance of the main detection channel, and judging the condensation risk according to the change rate of the transmittance of the reference channel, and starting the anti-condensation mode when the condensation risk is detected; Step S3, calculating the corrected rate of change of the transmittance of the main detection channel, extracting the humidity interference characteristic of the reference channel, building a temperature compensation matrix in combination with the sensor surface temperature, and generating fusion characteristic parameters of fusion environment compensation; Step S4, determining the gas presence based on the fused characteristic parameters, when the characteristic parameters of multiple consecutive sampling periods meet the preset conditions and the humidity interference characteristic quantity is lower than the threshold, triggering the gas presence flag; Step S5, according to the gas presence flag status, a temperature-adaptive response value calculation method is used, combined with environmental compensation parameters, to perform concentration conversion and output a gas concentration value.

[0007] Optionally, the step S1 specifically includes: Step S11, configuring a dual-channel infrared detection system, setting the central wavelength of the main detection channel to the characteristic absorption peak of the target gas at 4.26 μm; setting the central wavelength of the reference channel to the characteristic absorption peak of water vapor at 2.7 μm; Step S12, establish a synchronous acquisition timing, set the sampling period of the main detection channel and the reference channel to 0.5s, adopt a time-interleaved sampling method, control the sampling of the two channels within a preset time interval, and collect the transmittance T1 of the main detection channel and the transmittance T2 of the reference channel; Step S13, installing a micro thermocouple array on the surface of the sensor housing, setting 4 temperature measurement points evenly distributed around the sensor optical window, using a median filter algorithm to process temperature data, and outputting the sensor surface temperature Ts.

[0008] Optionally, after step S13, the following steps are further included: Step S14, installing a capacitive humidity sensor at the air inlet of the sensor, processing the raw data using a sliding average filter, and outputting the ambient humidity Hr; Step S15, designing a data preprocessing module to remove outliers and perform noise filtering on the collected raw transmittance data, wherein the transmittance of the main detection channel T1 and the transmittance of the reference channel T2 are smoothed using an adaptive Kalman filter algorithm, and the filter window width is set to 5 sampling points; Step S16, construct a multi-parameter synchronous acquisition data set, align the processed T1, T2, Ts, and Hr data according to the timestamp, and store them in a ring buffer. The buffer capacity is set to 60 groups of data, corresponding to a continuous monitoring time of 30 seconds.

[0009] Optionally, the step S2 specifically includes: Step S21, establishing a humidity compensation function library, dividing the compensation interval according to the ambient humidity Hr and selecting the corresponding compensation function F (Hr); Step S22, implement dynamic correction of the transmittance of the main detection channel, select the corresponding compensation function according to the real-time collected ambient humidity Hr, and calculate the corrected transmittance of the main detection channel T2 = T1 × F (Hr); Step S23, design a condensation risk warning mechanism, calculate the instantaneous change rate φ2=ΔT2 / Δt of the reference channel transmittance T2, set the change rate threshold to 0.15% / s, and trigger a condensation risk warning when φ2 of three consecutive sampling periods exceeds the threshold; Step S24, constructing an anti-condensation control strategy, and executing an anti-condensation mode when a condensation risk is detected; Step S25, implement real-time evaluation of the compensation effect, dynamically adjust the compensation function parameters by comparing the standard deviation change of the transmittance of the main detection channel before and after compensation, and automatically switch to a higher-order compensation function when the standard deviation decreases by less than 20%.

[0010] Optionally, the step S3 specifically includes: Step S31, calculating the corrected main detection channel transmittance change rate φ1, and using the five-point difference method to calculate the instantaneous change rate φ; Step S32, extracting the humidity interference characteristic quantity Q, and calculating it by using the sliding window integration method: Q=∫(φ2)dt, the integration time window is set to a preset time t, where φ2 is the reference channel transmittance change rate; Step S33, constructing a temperature compensation matrix, dividing the compensation interval according to the sensor surface temperature Ts, and randomly selecting the compensation coefficient k according to the compensation interval.

[0011] Optionally, after step S33, the following steps are further included: Step S34, designing a characteristic parameter fusion algorithm to generate a characteristic parameter Φ for fusion environment compensation, the calculation formula is: Φ=φ1 / (1+0.2Q)×k; Step S35, implement characteristic parameter quality assessment, set the effective range of characteristic parameter Φ, and automatically start the data re-collection mechanism when the Φ value exceeds the range, and mark the abnormal data flag; Step S36, establish a characteristic parameter optimization mechanism, dynamically adjust the fusion algorithm weight coefficient by comparing the standard deviation of the Φ value of 10 consecutive sampling periods, and automatically optimize the weight coefficient of the humidity interference characteristic value Q when the standard deviation exceeds 0.02.

[0012] Optionally, the step S4 specifically includes: Step S41, setting gas presence determination conditions, requiring that the characteristic parameter Φ of 5 consecutive sampling periods satisfy: Φ1>0.15%, Φ2>0.18%, Φ3>0.20%, Φ4>0.18%, Φ5>0.15%; Step S42, implement humidity interference verification, calculate the average Q_avg of the humidity interference characteristic quantity Q in the corresponding determination period, when Q_avg<0.5, determine that the humidity interference is within the allowable range, otherwise delay the determination and wait for the next sampling period; Step S43, design a determination result confirmation mechanism. When it is preliminarily determined that the gas exists, extend the observation for 2 sampling periods. If the subsequent Φ value continues to be greater than 0.12%, the determination result of the gas existence is confirmed. Step S44, implement grading processing of the determination results, and divide the confidence level according to the number of sampling cycles that continuously meet the determination conditions: 5-7 cycles are low confidence, 8-10 cycles are medium confidence, and more than 10 cycles are high confidence.

[0013] Optionally, the step S5 specifically includes: Step S51, designing a gas presence flag status analysis mechanism, starting the concentration calculation process when the flag is 1, maintaining the standby monitoring state when the flag is 0, and continuously updating the environmental parameters; Step S52, constructing a temperature adaptive response value calculation model, and using a piecewise weighted algorithm to calculate the response value β; Step S53, implementing dynamic calibration of the response value, adjusting the response value according to the ambient humidity Hr; Step S54, designing a concentration conversion algorithm, using a nonlinear conversion formula: C = α × β1^1.2 / (1+0.1β1), where α is a calibration coefficient, and the initial value is set to 1.0; Step S55, establishing a concentration output smoothing mechanism, and using an exponentially weighted moving average method to obtain an output concentration value C_output; Step S56, designing the data output format, packaging the output concentration value C_output with the timestamp, the temperature compensation coefficient k, and the humidity interference characteristic value Q for output, to form a complete data packet.

[0014] The present invention also provides a gas concentration infrared sensor, which uses the above-mentioned gas concentration infrared sensor detection method to achieve detection, and the gas concentration infrared sensor includes: Dual-channel infrared detection module, including main detection channel and reference channel, which are used to detect target gas absorption peak and water vapor characteristic absorption peak respectively, and equipped with beam splitter prism to realize beam separation; Environmental parameter acquisition module, including a micro-thermocouple array installed on the sensor surface and a capacitive humidity sensor at the air inlet, for real-time acquisition of sensor surface temperature and environmental humidity; A signal processing module is used to filter, compensate and calculate characteristic parameters of the collected transmittance data; A gas determination module, which determines the existence of gas based on fused characteristic parameters, and includes a determination condition setting unit and a confidence evaluation unit; The concentration calculation module adopts a temperature-adaptive response value calculation method and combines environmental compensation parameters to perform concentration conversion.

[0015] Compared with the prior art, the present invention has the following beneficial effects: first, the transmittance data of the main detection channel and the reference channel are synchronously collected through the dual channels of the infrared sensor, and the environmental temperature and humidity parameters are obtained at the same time to form a multi-parameter data set; then, a compensation function is established based on the humidity parameter to dynamically correct the main channel data, and the reference channel data is used to judge the condensation risk, and the anti-condensation mode is started in time; then, the corrected main channel transmittance change rate is calculated, the humidity interference characteristic quantity is extracted, and a compensation matrix is ​​constructed in combination with the temperature parameter to generate characteristic parameters of the fused environmental compensation; then, the gas presence is determined based on the fused characteristic parameters, and the gas presence flag is triggered when multiple consecutive sampling cycles meet the preset conditions and the humidity interference is lower than the threshold; finally, according to the flag state, a temperature-adaptive response value calculation method is adopted, and the concentration conversion is performed in combination with the environmental compensation parameters, and the final gas concentration value is output; This method effectively solves the interference problem of infrared gas detection under high temperature and high humidity environments through multi-parameter synchronous acquisition and environmental compensation mechanism, improves the measurement accuracy, and realizes high precision, high reliability and rapid response of gas concentration detection, which is particularly suitable for continuous online monitoring of high temperature and high humidity conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0018] Figure 1 This is one of the flow charts of the detection method of the gas concentration infrared sensor of the first embodiment.

[0019] Figure 2 This is the second flow chart of the detection method of the gas concentration infrared sensor of the first embodiment. DETAILED DESCRIPTION

[0020] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] In the description of the present invention, it should be understood that the terms "upper", "lower", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. It should be noted that when a component is considered to be "connected" to another component, it may be directly connected to the other component or there may be a centrally arranged component at the same time.

[0022] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0023] Embodiment 1: Combination Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a method for detecting gas concentration by an infrared sensor, comprising the following steps: Step S1, real-time acquisition of transmittance data of the dual channels of the infrared sensor, and acquisition of the sensor surface temperature and ambient humidity parameters, to form a multi-parameter synchronous acquisition data set; the transmittance data includes the transmittance of the main detection channel and the transmittance of the reference channel; the transmittance data includes the transmittance of the main detection channel in the target gas absorption peak band and the reference channel transmittance in the water vapor characteristic absorption band. The synchronous acquisition of ambient temperature and humidity provides key parameters for subsequent environmental compensation. The core of this step is the synchronous acquisition of multiple parameters to ensure the time consistency and integrity of the data, laying the foundation for subsequent accurate calculations.

[0024] Step S2, establishing a humidity compensation function based on the collected environmental humidity parameters, dynamically correcting the transmittance of the main detection channel, and judging the condensation risk according to the change rate of the transmittance of the reference channel, and starting the anti-condensation mode when the condensation risk is detected; Based on the collected environmental humidity parameters, a humidity compensation function is established to dynamically correct the transmittance of the main detection channel to eliminate the influence of the water vapor absorption band on the target gas detection. At the same time, the change rate of the reference channel transmittance is used to determine whether the sensor has a condensation risk. When the condensation risk is detected, the anti-condensation mode is activated (such as increasing the heater power or starting the purge device) to prevent the sensor performance from deteriorating. The key to this step is real-time environmental compensation and condensation risk prevention and control to ensure the stability and reliability of detection.

[0025] Step S3, calculating the corrected rate of change of the transmittance of the main detection channel, extracting the humidity interference characteristic of the reference channel, building a temperature compensation matrix in combination with the sensor surface temperature, and generating fusion characteristic parameters of fusion environment compensation; The corrected data is further processed and analyzed. First, the corrected rate of change of the transmittance of the main detection channel is calculated, the humidity interference characteristic of the reference channel is extracted, and the influence of water vapor on the detection result is quantified. Then, the temperature compensation matrix is ​​constructed in combination with the sensor surface temperature to generate fusion characteristic parameters that incorporate environmental compensation. The core of this step is to eliminate the cross-interference of temperature and humidity through multi-parameter fusion, and generate high-quality data that can accurately reflect the characteristics of the target gas.

[0026] Step S4, determining the gas presence based on the fused characteristic parameters, when the characteristic parameters of multiple consecutive sampling periods meet the preset conditions and the humidity interference characteristic quantity is lower than the threshold, triggering the gas presence flag; Based on the fusion characteristic parameters and the preset judgment conditions (such as the change rules of characteristic parameters for multiple consecutive sampling cycles), it is judged whether the target gas exists in the air. At the same time, the threshold judgment of the humidity interference characteristic quantity is used to eliminate the misjudgment caused by the fluctuation of environmental humidity. When all the judgment conditions are met, the gas presence flag is triggered. The core of this step is to improve the accuracy and anti-interference ability of gas detection through multi-condition joint judgment.

[0027] Step S5, according to the gas presence flag status, a temperature-adaptive response value calculation method is used, combined with environmental compensation parameters, to perform concentration conversion and output a gas concentration value.

[0028] According to the status of the gas presence flag, the temperature-adaptive response value calculation method is used, and the concentration conversion is performed in combination with the environmental compensation parameters to output the final gas concentration value. The core of this step is to ensure that accurate concentration values ​​can be output at different ambient temperatures through the temperature-adaptive algorithm design, and at the same time, the detection accuracy is further improved by combining the environmental compensation parameters. The final output concentration value is smoothed and range-checked.

[0029] The working principle of the present invention is as follows: first, the transmittance data of the main detection channel and the reference channel are synchronously collected through the dual channels of the infrared sensor, and the environmental temperature and humidity parameters are obtained at the same time to form a multi-parameter data set; then, a compensation function is established based on the humidity parameter to dynamically correct the main channel data, and the reference channel data is used to judge the condensation risk, and the anti-condensation mode is started in time; then, the corrected main channel transmittance change rate is calculated, the humidity interference characteristic quantity is extracted, and a compensation matrix is ​​constructed in combination with the temperature parameter to generate characteristic parameters of the fused environmental compensation; then, the gas presence is determined based on the fused characteristic parameters, and the gas presence flag is triggered when multiple consecutive sampling cycles meet the preset conditions and the humidity interference is lower than the threshold; finally, according to the flag state, a temperature-adaptive response value calculation method is adopted, and the concentration conversion is performed in combination with the environmental compensation parameters, and the final gas concentration value is output; This method effectively solves the interference problem of infrared gas detection under high temperature and high humidity environments through multi-parameter synchronous acquisition and environmental compensation mechanism, improves the measurement accuracy, and realizes high precision, high reliability and rapid response of gas concentration detection, and is particularly suitable for continuous online monitoring of high temperature and high humidity conditions.

[0030] In this embodiment, it is specifically explained that step S1 specifically includes: Step S11, configuring a dual-channel infrared detection system, setting the central wavelength of the main detection channel to the characteristic absorption peak of the target gas at 4.26 μm; setting the central wavelength of the reference channel to the characteristic absorption peak of water vapor at 2.7 μm; wherein the optical paths of the two channels use a beam splitter prism to achieve beam separation, so that the light intensity consistency error is less than 1%; The central wavelength of the main detection channel is set to the characteristic absorption peak of the target gas, 4.26μm, for accurate detection of the concentration of the target gas; the central wavelength of the reference channel is set to the characteristic absorption peak of water vapor, 2.7μm, for monitoring the interference of environmental humidity on the detection results. Through the dual-channel design, the separation of the target gas signal and the humidity interference signal is achieved, providing a basis for subsequent environmental compensation.

[0031] Step S12, establish a synchronous acquisition timing, set the sampling period of the main detection channel and the reference channel to 0.5s, adopt a time-interleaved sampling method, control the sampling of the two channels within a preset time interval, and collect the transmittance T1 of the main detection channel and the transmittance T2 of the reference channel; The sampling period of the main detection channel and the reference channel is set to 0.5s, and the time-interleaved sampling method is adopted to ensure that the data collection of the two channels is completed within the preset time interval. This design not only ensures the time synchronization of the data, but also avoids mutual interference between channels. By accurately controlling the sampling timing, the collected transmittance T1 of the main detection channel and the transmittance T2 of the reference channel are highly consistent.

[0032] Step S13, installing a micro thermocouple array on the surface of the sensor housing, setting 4 temperature measurement points evenly distributed around the sensor optical window, using a median filter algorithm to process temperature data, and outputting the sensor surface temperature Ts.

[0033] A micro thermocouple array is installed on the surface of the sensor housing, and 4 temperature measurement points are evenly distributed around the optical window to ensure the representativeness and accuracy of temperature measurement. The median filter algorithm is used to process temperature data, effectively eliminate outlier interference, and output a stable sensor surface temperature Ts. This step provides reliable data support for subsequent temperature compensation.

[0034] Step S14, install a capacitive humidity sensor at the air inlet of the sensor, set the humidity sampling period to 1s, the measurement range to 0-100%RH, the accuracy to ±2%RH, use sliding average filtering to process the raw data, and output the ambient humidity Hr; A capacitive humidity sensor is installed at the air inlet of the sensor to monitor the ambient humidity in real time. The raw data is processed by sliding average filtering to smooth humidity fluctuations and output a stable ambient humidity Hr. This step provides key parameters for the establishment of the humidity compensation function and the judgment of condensation risk.

[0035] Step S15, designing a data preprocessing module to remove outliers and perform noise filtering on the collected raw transmittance data, wherein the transmittance of the main detection channel T1 and the transmittance of the reference channel T2 are smoothed using an adaptive Kalman filter algorithm, and the filter window width is set to 5 sampling points; The collected raw transmittance data is processed by outlier removal and noise filtering, and the transmittance of the main detection channel T1 and the transmittance of the reference channel T2 are smoothed by adaptive Kalman filtering algorithms. The filter window width is set to 5 sampling points to ensure data smoothness while retaining effective signal characteristics.

[0036] Step S16, construct a multi-parameter synchronous acquisition data set, align the processed T1, T2, Ts, and Hr data according to the timestamp, and store them in a ring buffer. The buffer capacity is set to 60 groups of data, corresponding to 30 seconds of continuous monitoring time. This design not only ensures the temporal consistency of the data, but also provides sufficient data support for subsequent real-time analysis and processing.

[0037] In this embodiment, it is specifically described that step S2 specifically includes: Step S21, establish a humidity compensation function library, divide the compensation interval according to the ambient humidity Hr, and select the corresponding compensation function F (Hr); specifically: divide into three compensation intervals: when Hr<60%, use the linear compensation function F1 (Hr) = 1 + 0.02 × (Hr-40) / 20; when 60% ≤ Hr < 80%, use the quadratic compensation function F2 (Hr) = 1 + 0.05 + 0.001 × (Hr-60) ^ 2; when Hr ≥ 80%, use the exponential compensation function F3 (Hr) = 1.1 × exp (0.005 × (Hr-80)).

[0038] Step S22, implement dynamic correction of the transmittance of the main detection channel, select the corresponding compensation function according to the real-time collected ambient humidity Hr, and calculate the corrected transmittance of the main detection channel T2 = T1 × F (Hr); This step effectively eliminates the interference of humidity on the target gas detection by dynamically adjusting the compensation function, and improves the accuracy of the detection results. The corrected transmittance T2 more truly reflects the absorption characteristics of the target gas.

[0039] Step S23, design a condensation risk warning mechanism, calculate the instantaneous change rate φ2=ΔT2 / Δt of the reference channel transmittance T2, set the change rate threshold to 0.15% / s, and trigger a condensation risk warning when φ2 of three consecutive sampling periods exceeds the threshold.

[0040] Step S24, constructing an anti-condensation control strategy, and executing the anti-condensation mode when the condensation risk is detected; the anti-condensation mode specifically includes the following operations: increasing the sensor heater power to 120% of the rated value, shortening the sampling interval to 0.3s, and starting the optical window purge device at the same time, with a purge air flow speed of 0.5m / s and a duration of 30s; These measures can effectively prevent condensation on the sensor window and ensure the reliability and stability of the detection data. The implementation of the anti-condensation mode significantly improves the adaptability of the sensor in high temperature and high humidity environments.

[0041] Step S25, implement real-time evaluation of the compensation effect, dynamically adjust the compensation function parameters by comparing the standard deviation change of the transmittance of the main detection channel before and after compensation, and automatically switch to a higher-order compensation function when the standard deviation decreases by less than 20%.

[0042] When the standard deviation decreases by less than 20%, it means that the current compensation function is not effective enough, and the system automatically switches to a higher-order compensation function. This step achieves dynamic optimization of compensation parameters to ensure the accuracy and adaptability of humidity compensation.

[0043] In this embodiment, it is specifically described that step S3 specifically includes: Step S31, calculating the corrected main detection channel transmittance change rate φ1, and using the five-point difference method to calculate the instantaneous change rate φ.

[0044] Step S32, extract the humidity interference characteristic quantity Q, and calculate it using the sliding window integration method: Q=∫(φ2)dt, the integration time window is set to a preset time t, where φ2 is the reference channel transmittance change rate.

[0045] Step S33, constructing a temperature compensation matrix, dividing the compensation interval according to the sensor surface temperature Ts, and randomly selecting the compensation coefficient k according to the compensation interval; Specifically: when Ts<100℃, the compensation coefficient k=1.0; when 100℃≤Ts<150℃, k=0.95+0.001×(Ts-100); when Ts≥150℃, k=0.90+0.0005×(Ts-150).

[0046] Step S34, designing a characteristic parameter fusion algorithm to generate a characteristic parameter Φ for fusion environment compensation, the calculation formula is: Φ=φ1 / (1+0.2Q)×k.

[0047] Step S35, implement characteristic parameter quality assessment, set the effective range of characteristic parameter Φ, and automatically start the data re-collection mechanism when the Φ value exceeds the range, and mark the abnormal data flag.

[0048] Step S36, establish a characteristic parameter optimization mechanism, dynamically adjust the fusion algorithm weight coefficient by comparing the standard deviation of the Φ value of 10 consecutive sampling periods, and automatically optimize the weight coefficient of the humidity interference characteristic value Q when the standard deviation exceeds 0.02.

[0049] In this embodiment, it is specifically described that step S4 specifically includes: Step S41, setting the gas presence determination conditions, requiring that the characteristic parameter Φ of 5 consecutive sampling periods satisfies: Φ1>0.15%, Φ2>0.18%, Φ3>0.20%, Φ4>0.18%, Φ5>0.15%, and the change rate between adjacent sampling points does not exceed ±20%.

[0050] Step S42, implement humidity interference verification, calculate the average Q_avg of the humidity interference characteristic quantity Q in the corresponding determination period, when Q_avg<0.5, determine that the humidity interference is within the allowable range, otherwise delay the determination and wait for the next sampling cycle.

[0051] Step S43, design a determination result confirmation mechanism. When it is preliminarily determined that gas exists, extend the observation for 2 sampling cycles. If the subsequent Φ value continues to be greater than 0.12%, the determination result of gas existence is confirmed.

[0052] Step S44, implement grading processing of the determination results, and divide the confidence level according to the number of sampling cycles that continuously meet the determination conditions: 5-7 cycles are low confidence, 8-10 cycles are medium confidence, and more than 10 cycles are high confidence.

[0053] In this embodiment, it is specifically described that step S5 specifically includes: Step S51, design a gas presence flag status analysis mechanism, start the concentration calculation process when the flag is 1, maintain the standby monitoring state when the flag is 0, and continuously update the environmental parameters.

[0054] Step S52, construct a temperature adaptive response value calculation model, and use a piecewise weighted algorithm to calculate the response value β; specifically: when Ts<100℃, β=ΣΦ / n; when 100℃≤Ts<150℃, β=0.95×ΣΦ / n; when Ts≥150℃, β=0.90×ΣΦ / n, where Φ is a characteristic parameter and n is the number of valid sampling points.

[0055] Step S53, implement dynamic calibration of the response value, and adjust the response value according to the ambient humidity Hr; specifically: when Hr<60%, β1=β×1.0; when 60%≤Hr<80%, β1=β×0.98; when Hr≥80%, β1=β×0.95.

[0056] Step S54, designing a concentration conversion algorithm, using a nonlinear conversion formula: C = α × β1^1.2 / (1+0.1β1), where α is a calibration coefficient, and the initial value is set to 1.0.

[0057] Step S55, establish a concentration output smoothing mechanism, and use the exponentially weighted moving average method to obtain the output concentration value C_output; specifically: C_output=0.7×C_prev+0.3×C_current, where C_prev is the previous output value and C_current is the current calculated value.

[0058] Step S56, designing the data output format, packaging the output concentration value C_output with the timestamp, the temperature compensation coefficient k, and the humidity interference characteristic value Q for output, to form a complete data packet.

[0059] Embodiment 2: The present invention further provides a gas concentration infrared sensor, which uses the detection method of the gas concentration infrared sensor of the first embodiment to achieve detection. The gas concentration infrared sensor includes: The dual-channel infrared detection module includes a main detection channel and a reference channel, which are used to detect the absorption peak of the target gas and the characteristic absorption peak of water vapor respectively, and is equipped with a beam splitter prism to achieve beam separation.

[0060] The environmental parameter acquisition module includes a micro-thermocouple array installed on the sensor surface and a capacitive humidity sensor at the air inlet, which is used to collect the sensor surface temperature and environmental humidity in real time.

[0061] The signal processing module is used to filter, compensate and calculate characteristic parameters of the collected transmittance data.

[0062] The gas determination module determines the existence of gas based on the fusion characteristic parameters, and includes a determination condition setting unit and a confidence evaluation unit.

[0063] The concentration calculation module adopts a temperature-adaptive response value calculation method and combines environmental compensation parameters to perform concentration conversion.

[0064] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting gas concentration using an infrared sensor, characterized in that: The following steps are involved: Step S1, real-time acquisition of transmittance data of dual channels of infrared sensors, and simultaneous acquisition of sensor surface temperature and ambient humidity parameters, to form a multi-parameter synchronous acquisition data set; the transmittance data includes the transmittance of the main detection channel and the transmittance of the reference channel; Step S2, establishing a humidity compensation function based on the collected environmental humidity parameters, dynamically correcting the transmittance of the main detection channel, and judging the condensation risk according to the change rate of the transmittance of the reference channel, and starting the anti-condensation mode when the condensation risk is detected; Step S3, calculating the corrected rate of change of the transmittance of the main detection channel, extracting the humidity interference characteristic of the reference channel, building a temperature compensation matrix in combination with the sensor surface temperature, and generating fusion characteristic parameters of fusion environment compensation; Step S4, determining the gas presence based on the fused characteristic parameters, when the characteristic parameters of multiple consecutive sampling periods meet the preset conditions and the humidity interference characteristic quantity is lower than the threshold, triggering the gas presence flag; Step S5, according to the gas presence flag status, a temperature-adaptive response value calculation method is used, combined with environmental compensation parameters, to perform concentration conversion and output a gas concentration value.

2. The detection method of the gas concentration infrared sensor according to claim 1, characterized in that: The step S1 specifically includes: Step S11, configuring a dual-channel infrared detection system, setting the central wavelength of the main detection channel to the characteristic absorption peak of the target gas at 4.26 μm; setting the central wavelength of the reference channel to the characteristic absorption peak of water vapor at 2.7 μm; Step S12, establish a synchronous acquisition timing, set the sampling period of the main detection channel and the reference channel to 0.5s, adopt a time-interleaved sampling method, control the sampling of the two channels within a preset time interval, and collect the transmittance T1 of the main detection channel and the transmittance T2 of the reference channel; Step S13, installing a micro thermocouple array on the surface of the sensor housing, setting 4 temperature measurement points evenly distributed around the sensor optical window, using a median filter algorithm to process temperature data, and outputting the sensor surface temperature Ts.

3. The detection method of the gas concentration infrared sensor according to claim 2, characterized in that: After step S13, the following steps are also included: Step S14, installing a capacitive humidity sensor at the air inlet of the sensor, processing the raw data using a sliding average filter, and outputting the ambient humidity Hr; Step S15, designing a data preprocessing module to remove outliers and perform noise filtering on the collected raw transmittance data, wherein the transmittance of the main detection channel T1 and the transmittance of the reference channel T2 are smoothed using an adaptive Kalman filter algorithm, and the filter window width is set to 5 sampling points; Step S16, construct a multi-parameter synchronous acquisition data set, align the processed T1, T2, Ts, and Hr data according to the timestamp, and store them in a ring buffer. The buffer capacity is set to 60 groups of data, corresponding to a continuous monitoring time of 30 seconds.

4. The detection method of the gas concentration infrared sensor according to claim 1, characterized in that: The step S2 specifically includes: Step S21, establishing a humidity compensation function library, dividing the compensation interval according to the ambient humidity Hr and selecting the corresponding compensation function F (Hr); Step S22, implement dynamic correction of the transmittance of the main detection channel, select the corresponding compensation function according to the real-time collected ambient humidity Hr, and calculate the corrected transmittance of the main detection channel T2 = T1 × F (Hr); Step S23, design a condensation risk warning mechanism, calculate the instantaneous change rate φ2=ΔT2 / Δt of the reference channel transmittance T2, set the change rate threshold to 0.15% / s, and trigger a condensation risk warning when φ2 of three consecutive sampling periods exceeds the threshold; Step S24, constructing an anti-condensation control strategy, and executing an anti-condensation mode when a condensation risk is detected; Step S25, implement real-time evaluation of the compensation effect, dynamically adjust the compensation function parameters by comparing the standard deviation change of the transmittance of the main detection channel before and after compensation, and automatically switch to a higher-order compensation function when the standard deviation decreases by less than 20%.

5. The detection method of the gas concentration infrared sensor according to claim 1, characterized in that: The step S3 specifically includes: Step S31, calculating the corrected main detection channel transmittance change rate φ1, and using the five-point difference method to calculate the instantaneous change rate φ; Step S32, extracting the humidity interference characteristic quantity Q, and calculating it by using the sliding window integration method: Q=∫(φ2)dt, the integration time window is set to a preset time t, where φ2 is the reference channel transmittance change rate; Step S33, constructing a temperature compensation matrix, dividing the compensation interval according to the sensor surface temperature Ts, and randomly selecting the compensation coefficient k according to the compensation interval.

6. The detection method of the gas concentration infrared sensor according to claim 5, characterized in that: After step S33, the following steps are also included: Step S34, designing a characteristic parameter fusion algorithm to generate a characteristic parameter Φ for fusion environment compensation, the calculation formula is: Φ=φ1 / (1+0.2Q)×k; Step S35, implement characteristic parameter quality assessment, set the effective range of characteristic parameter Φ, and automatically start the data re-collection mechanism when the Φ value exceeds the range, and mark the abnormal data flag; Step S36, establish a characteristic parameter optimization mechanism, dynamically adjust the fusion algorithm weight coefficient by comparing the standard deviation of the Φ value of 10 consecutive sampling periods, and automatically optimize the weight coefficient of the humidity interference characteristic value Q when the standard deviation exceeds 0.

02.

7. The detection method of the gas concentration infrared sensor according to claim 6, characterized in that: The step S4 specifically includes: Step S41, setting gas presence determination conditions, requiring that the characteristic parameter Φ of 5 consecutive sampling periods satisfy: Φ1>0.15%, Φ2>0.18%, Φ3>0.20%, Φ4>0.18%, Φ5>0.15%; Step S42, implement humidity interference verification, calculate the average Q_avg of the humidity interference characteristic quantity Q in the corresponding determination period, when Q_avg<0.5, determine that the humidity interference is within the allowable range, otherwise delay the determination and wait for the next sampling period; Step S43, design a determination result confirmation mechanism. When it is preliminarily determined that the gas exists, extend the observation for 2 sampling periods. If the subsequent Φ value continues to be greater than 0.12%, the determination result of the gas existence is confirmed. Step S44, implement grading processing of the determination results, and divide the confidence level according to the number of sampling cycles that continuously meet the determination conditions: 5-7 cycles are low confidence, 8-10 cycles are medium confidence, and more than 10 cycles are high confidence.

8. The detection method of the gas concentration infrared sensor according to claim 1, characterized in that: The step S5 specifically includes: Step S51, designing a gas presence flag status analysis mechanism, starting the concentration calculation process when the flag is 1, maintaining the standby monitoring state when the flag is 0, and continuously updating the environmental parameters; Step S52, constructing a temperature adaptive response value calculation model, and using a piecewise weighted algorithm to calculate the response value β; Step S53, implementing dynamic calibration of the response value, adjusting the response value according to the ambient humidity Hr; Step S54, designing a concentration conversion algorithm, using a nonlinear conversion formula: C = α × β1^1.2 / (1+0.1β1), where α is a calibration coefficient, and the initial value is set to 1.0; Step S55, establishing a concentration output smoothing mechanism, and using an exponentially weighted moving average method to obtain an output concentration value C_output; Step S56, designing the data output format, packaging the output concentration value C_output with the timestamp, the temperature compensation coefficient k, and the humidity interference characteristic value Q for output, to form a complete data packet.

9. A gas concentration infrared sensor, characterized in that: The detection is achieved by using the detection method of the gas concentration infrared sensor according to any one of claims 1 to 8, wherein the gas concentration infrared sensor comprises: Dual-channel infrared detection module, including main detection channel and reference channel, which are used to detect target gas absorption peak and water vapor characteristic absorption peak respectively, and equipped with beam splitter prism to realize beam separation; Environmental parameter acquisition module, including a micro-thermocouple array installed on the sensor surface and a capacitive humidity sensor at the air inlet, for real-time acquisition of sensor surface temperature and environmental humidity; A signal processing module is used to filter, compensate and calculate characteristic parameters of the collected transmittance data; A gas determination module, which determines the existence of gas based on fused characteristic parameters, and includes a determination condition setting unit and a confidence evaluation unit; The concentration calculation module adopts a temperature-adaptive response value calculation method and combines environmental compensation parameters to perform concentration conversion.

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