Gas concentration and flow rate synchronous monitoring sensor and correction method

Abstract

The application provides a gas concentration and flow rate synchronous monitoring sensor and a correction method, relates to the technical field of coal mine safety monitoring, and comprises the following steps: introducing thermodynamic parameters such as temperature and specific heat into an ultrasonic gas monitoring model, realizing high-precision measurement of gas concentration and flow rate through multi-field coupling, optimizing the structure of the ultrasonic sensor, and using a BPNN model to correct sensor measurement data in real time, and the measurement result can be automatically adjusted according to actual environmental conditions. The application adopts the above-mentioned gas concentration and flow rate synchronous monitoring sensor and correction method, reduces the influence of airflow disturbance on the measurement result, improves the measurement precision in a complex environment, and significantly improves the measurement stability and accuracy of the sensor.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety monitoring technology, and in particular to a sensor and calibration method for simultaneous monitoring of gas concentration and flow. Background Technology

[0002] During coal mining, the accumulation and abnormal changes in methane gas have a significant impact on underground safety. Current underground methane monitoring methods commonly employ catalytic and infrared techniques, but these are susceptible to interference from dust, water mist, temperature and humidity fluctuations, airflow disturbances, and sensor aging and drift in complex coal mining environments. This leads to decreased measurement stability in low concentration ranges and high maintenance and calibration costs. Furthermore, on-site safety management requires not only methane concentration but also gas velocity / flow rate information to assess ventilation or extraction effectiveness; however, traditional solutions often require multiple sensors to measure concentration and flow rate separately, resulting in complex installation, data asynchrony, and error aggregation.

[0003] Ultrasonic time-of-flight (TOF) methods offer advantages in flow velocity measurement, including non-contact operation and low pressure loss, and the speed of sound can be calculated from propagation time information. Since sound velocity is related to gas composition, temperature, and pressure, it can theoretically be used for inversion of mixed gas composition. However, in coal mines, factors such as ultrasonic attenuation due to dust and water mist, installation deviations, non-ideal flow fields, and temperature and pressure fluctuations can introduce systematic errors and drifts in the concentration results derived from sound velocity inversion. Therefore, there is an urgent need for a sensor capable of accurately measuring methane concentration and flow rate in complex mine environments to improve the reliability and accuracy of mine safety monitoring, especially under low concentration and low wind speed conditions. Summary of the Invention

[0004] The purpose of this invention is to provide a sensor and calibration method for synchronous monitoring of gas concentration and flow rate. By optimizing sensor design and structure, using an ultrasonic binary vector measurement model and a backpropagation neural network (BPNN) error correction method, the invention achieves synchronous and accurate measurement of gas concentration and flow rate, thereby solving the problems of large measurement errors and insufficient accuracy in low concentration areas in existing technologies.

[0005] To achieve the above objectives, the present invention provides a gas concentration and flow rate synchronous monitoring sensor, comprising: At least two pairs of ultrasonic transducers and other auxiliary monitoring components; wherein each pair of ultrasonic transducers constitutes a sound channel for emitting and receiving ultrasonic waves in both the downstream and upstream directions, and for obtaining the downstream propagation time. and the time of reverse propagation .

[0006] Preferably, four ultrasonic transducers are arranged orthogonally to form a two-dimensional ultrasonic wind sensor. The wind speed is calculated by using vector synthesis methods to measure the wind speed v and the sound speed c in two directions. Calculate wind direction And calculate the speed of sound .

[0007] Preferably, the ultrasonic transducer is made of a gas-based type 1-3 piezoelectric composite material. The piezoelectric composite material uses a gas medium as a matrix and has piezoelectric ceramic pillars arranged in an array inside. The acoustic radiation surface of the ultrasonic transducer is provided with three gradient acoustic impedance matching layers. The three gradient acoustic impedance matching layers are, in sequence from the ultrasonic transducer radiation surface to the gas to be measured, a PEEK material layer, a PMI foam material layer, and a polyimide aerogel layer treated with parylene C coating. The acoustic impedance value of each of the three gradient acoustic impedance matching layers is distributed in a gradient decreasing distribution to realize the gradual transition of acoustic impedance between the piezoelectric material and the gas medium to be measured.

[0008] Preferably, other auxiliary monitoring components include: Temperature sensor, used to synchronously collect ambient temperature T; The signal processing circuit is used to amplify, filter, and shape the received ultrasonic echo signal; The detection circuit includes a time measurement circuit and a temperature measurement circuit, used to measure the propagation time in the upstream / downstream direction and the ambient temperature; The processor module has a built-in physical inversion module based on a mixed gas thermodynamic model and a backpropagation neural network intelligent correction module. The processor module calculates the gas sound velocity and axial velocity based on the downstream / countercurrent propagation time, and obtains the initial value of methane concentration based on the methane-air binary mixed gas sound velocity model. The BPNN intelligent correction module takes a feature vector as input, and the feature vector includes at least the calculated wind speed. Calculate the speed of sound Initial value of methane concentration Ambient temperature T, echo amplitude Amp, signal-to-noise ratio SNR, and output methane concentration compensation amount. With flow rate compensation Obtain the corrected concentration of the gas to be measured. With flow rate .

[0009] Preferably, the gas concentration and flow rate synchronous monitoring sensor also includes an annular measurement channel. The windward side of the annular measurement channel adopts an inwardly inclined structure to reduce the impact of flow field disturbance on measurement accuracy.

[0010] Preferably, the processor module also calculates the gas flow rate based on the corrected flow velocity and the cross-sectional area of ​​the measurement channel, and outputs the gas flow rate data.

[0011] Preferably, the BPNN intelligent correction module also has a quality judgment criterion: when the signal-to-noise ratio in the input feature vector is lower than a preset threshold, a data quality warning message is output, and no specific concentration or flow rate value is output.

[0012] A calibration method for a gas concentration and flow rate synchronous monitoring sensor includes the following steps: S1: Control the ultrasonic transducer to emit and receive ultrasonic waves in the downstream and upstream directions, and obtain the downstream propagation time. and the time of reverse propagation ; S2: Amplify, filter, and shape the received ultrasonic echo signal, and measure it. , And simultaneously collect ambient temperature T; S3: Based on , Obtain the calculated speed of sound With calculation of wind speed The initial value of methane concentration was obtained by inversion using a methane-air binary gas velocity model under the constraint of ambient temperature T. ; S4: Construct a BPNN neural network model to include at least the calculation of wind speed. Calculate the speed of sound Initial methane concentration The eigenvectors of ambient temperature T, echo amplitude Amp, and signal-to-noise ratio SNR are used as inputs, with the gas concentration compensation amount as the input. The flow velocity compensation amount Δv is used as the output to perform residual compensation and drift correction on the physical model solution results; S5: Output corrected methane concentration and the corrected flow rate .

[0013] Preferably, the specific formula for retrieving the initial value of methane concentration in step S3 is as follows: ; ; ; ; In the formula, Let be the initial concentration of gas α; CPα and CPβ be the isobaric specific heat capacities of gases α and β, respectively; CVα and CVβ be the isovolastic specific heat capacities of gases α and β, respectively; Mα and Mβ be the relative molecular masses of gases α and β, respectively; A, B, and D are parameters related to the specific heat ratio, relative molecular mass, and sound velocity of the gas mixture; parameter Y is derived from the sound velocity of the gas mixture. The ambient temperature T is determined.

[0014] Preferably, the gas concentration and flow rate synchronous monitoring sensor and calibration method are suitable for measuring the gas to be measured in a variety of mixed gases.

[0015] Therefore, the present invention employs the above-mentioned gas concentration and flow rate synchronous monitoring sensor and calibration method, and the technical effects are as follows: (1) Single-channel synchronous output: The flow velocity and sound velocity are obtained simultaneously in one measurement, and the methane concentration is further inverted to realize the synchronous monitoring of concentration and flow rate; (2) Optimized design of monitoring structure: The inward inclined windward structure is adopted to reduce the disturbance to the flow field of the channel and improve the consistency and accuracy of measurement; (3) More robust for low concentrations: By utilizing the difference in sound velocity between methane and air and combining it with a mixed gas sound velocity model constrained by temperature / pressure, the stability of concentration inversion in the low concentration range is improved; (4) Intelligent error correction: By learning and compensating for the physical model residuals and drift, the system errors caused by dust and water mist, temperature and pressure fluctuations, echo attenuation, device aging, etc. are reduced, thereby improving the accuracy of on-site measurement and long-term reliability. (5) Maintainability and diagnostics: Health indicators are formed by using quality characteristics such as echo amplitude / signal-to-noise ratio to support anomaly alerts and maintenance decisions, thereby improving on-site availability. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of a direct methane flow detection device; Figure 2 This is a schematic diagram of the main structure of the ultrasonic sensor; Figure 3 This is a comparison chart before and after flow correction.

[0017] Figure Labels 1. Microcontroller system; 2. Drive circuit; 3. Channel selection circuit; 4. Transducer assembly; 401. First ultrasonic transducer; 402. Second ultrasonic transducer; 403. Third ultrasonic transducer; 404. Fourth ultrasonic transducer; 5. Signal processing circuit; 501. Amplification circuit; 502. Filtering circuit; 6. Detection circuit; 601. Time measurement circuit; 602. Temperature measurement circuit; 7. Wireless transmission module; 8. Host computer. Detailed Implementation

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0020] Example 1 A gas concentration and flow rate synchronous monitoring sensor, comprising: 1. Ultrasonic Sensor Design The proposed gas concentration and flow rate synchronous monitoring sensor based on ultrasonic time-of-flight and thermodynamic models mainly includes modules for wind speed, concentration, and temperature measurement, a microcontroller system, a wireless transmission module, and a host computer. It realizes the measurement of temperature, wind speed, methane concentration, and flow rate within the roadway. Its structural schematic is shown below. Figure 1 As shown. The ultrasonic sensor includes: a microcontroller system 1, a drive circuit 2, a channel selection circuit 3, and a transducer assembly 4 (including a first ultrasonic transducer 401, a second ultrasonic transducer 402, a third ultrasonic transducer 403, and a fourth ultrasonic transducer 404). The first ultrasonic transducer 401, the second ultrasonic transducer 402, the third ultrasonic transducer 403, and the fourth ultrasonic transducer 404 are all made of gas-based type 1-3 piezoelectric composite material. During fabrication, the piezoelectric ceramic is cut into a periodically arranged array of micropillars. The cut piezoelectric ceramic column array is placed in a vacuum chamber, and dry air or inert gas is used as the matrix to fill the gaps between the columns, forming a type 1-3 composite material with gas as the continuous phase and piezoelectric ceramic as the dispersed phase. The acoustic radiating surface of transducer assembly 4 is provided with three gradient acoustic impedance matching layers: the first matching layer is made of PEEK material, the second matching layer is made of PMI foam material, and the third matching layer is made of polyimide aerogel material coated with parylene C; the three matching layers are sequentially bonded to the radiating surface of transducer assembly 4, forming an acoustic impedance gradient transition from piezoelectric material to air. The system includes a signal processing circuit 5 (including an amplifier circuit 501 and a filter circuit 502), a detection circuit 6 (including a time measurement circuit 601 and a temperature measurement circuit 602), a LoRa (long-range low-power wireless transmission) wireless transmission module 7, and a host computer 8.

[0021] The specific implementation steps are as follows: S1. The microcontroller system 1 controls the drive circuit 2 to generate an ultrasonic excitation signal, and selects the first ultrasonic transducer 401 and the third ultrasonic transducer 403 as the transmitting end and the second ultrasonic transducer 402 and the fourth ultrasonic transducer 404 as the receiving end through the channel selection circuit 3, so that the ultrasonic wave propagates along the sound channel to obtain the forward propagation time. ; S2. The microcontroller system 1 controls the channel selection circuit 3 to switch the transmitter / receiver, causing the second ultrasonic transducer 402 and the fourth ultrasonic transducer 404 to transmit and the first ultrasonic transducer 401 and the third ultrasonic transducer 403 to receive, thus obtaining the reverse propagation time. ; S3. The weak echo signal output by the transducer assembly 4 at the receiving end enters the signal processing circuit 5, which is then amplified by the amplifier circuit 501 and filtered by the filter circuit 502 to suppress downhole environmental noise and out-of-band interference. After forming a shaped signal suitable for timing, it is sent to the detection circuit 6. S4, the time measurement circuit 601 measures the arrival time of the echo. and The temperature measurement circuit 602 synchronously collects the ambient temperature. T ; S5. The microcontroller system 1 calculates the speed of sound in the gas based on the propagation time. With calculation of wind speed Based on the difference in sound velocity between methane and air and the sound velocity model of the mixed gas, the initial methane concentration was obtained by inversion under temperature constraints. .

[0022] To improve the reliability of low-concentration measurements in complex coal mining environments, the microcontroller system 1 incorporates a BPNN neural network model to perform residual compensation and drift correction on the concentration / flow rate results obtained from the difference in sound velocity between methane and air and the sound velocity model of mixed gases, and outputs the corrected methane concentration and flow rate.

[0023] Furthermore, the flow rate can be calculated based on the cross-sectional area. The corrected data is displayed through the display module and transmitted to the host computer 8 via the LoRa wireless transmission module 7 for centralized monitoring and management.

[0024] 2. Optimization of ultrasonic sensor structure This invention utilizes CFD (Computational Fluid Dynamics) numerical simulation to analyze the influence of different windward structures on flow field distribution, nodal wind speeds along the propagation path, average linear velocity along the path, and measurement errors. An inwardly inclined windward structure is preferred as the measurement channel structure. Figure 2 As shown. Studies have shown that the inward-sloping structure causes less disturbance to the flow field inside the annular measurement channel compared to the planar and outward-sloping structures, and can significantly improve the measurement accuracy of wind speed and concentration. Therefore, it can be used as the structural form in the preferred embodiment of the present invention.

[0025] 3. Ultrasonic sensor measurement method Four orthogonally arranged ultrasonic transceiver transducers can be used to form a two-dimensional ultrasonic wind sensor to obtain the influence of ultrasonic wave propagation on wind speed changes. A microcontroller drives a channel selection circuit to control the four transceiver transducers to receive and emit ultrasonic waves. Based on the ultrasonic time-of-flight method, time and temperature measurement circuits are used to synchronously calculate the gas flow rate and methane concentration in the pipe / tunnel, thereby achieving direct measurement of multiple parameters such as methane flow rate.

[0026] When ultrasound propagates in a medium, the velocity of the medium is superimposed on the velocity of the sound wave, thus affecting the speed of sound. This results in a difference between the downstream and upstream propagation times of the ultrasound signal. By measuring this difference, the flow velocity and the speed of sound can be derived. Taking one propagation path as an example, let the distance between the first ultrasonic transducer 401 and the second ultrasonic transducer 402 be... L The propagation time via leeway is The time for headwind propagation is The medium in Y The wind speed and sound speed in the direction of travel can be calculated using the following formula: (1); (2); In the formula, v Y for Y Measured wind speed in the direction; c Y for Y The speed of sound in the direction of travel.

[0027] Similarly, we can obtain X Wind speed measured in direction and measuring the speed of sound c X The wind speed can be calculated using the following formula through vector synthesis. Calculate wind direction Calculating the speed of sound in a gas mixture : (3); (4); (5); 4. Gas Concentration Measurement Methods According to the ideal gas model, the speed of sound This can be expressed by parameters such as the relative molecular mass of the gas and temperature, as follows: (6); In the formula, γ The isobaric and isochoric specific heat ratio of a gas; M This represents the relative molecular mass of the gas. R The molar gas constant; T The ambient temperature.

[0028] Coalbed methane can be considered an ideal gas mixture. Ultrasonic waves propagate in the gas with high-frequency, low-amplitude vibrations; this process is considered adiabatic. Let... α and β These are the gas to be tested and the background gas, respectively. M α and M β They are respectively α , β Given the relative molecular mass of the gases, the isobaric and isovolic specific heat ratio of the gas mixture is: (7); In the formula, forα Initial concentration of the gas; for β The concentration of the gas; C Pα and C Pβ They are respectively α , β Specific heat capacity at constant pressure of a gas; C Vα and C Vβ They are respectively α , β Specific heat capacity at constant volume of a gas.

[0029] The relative molecular mass of the gas mixture is: (8); According to equations (4) to (6), we can obtain (9); Solving equation (7) yields only a single root, allowing us to determine the concentration of gas α: (10); In the formula, A , B , D These are parameters related to specific heat ratio, relative molecular mass, and sound velocity of the mixed gas.

[0030] Parameter Y The speed of sound can be calculated from a gas mixture. and ambient temperature T Once the background gas and the gas to be measured are determined, other parameters can be obtained by looking up tables, such as ambient temperature. T It can also be obtained through a high-precision temperature sensor. Therefore, the velocity of sound in the mixed gas can be calculated. Then you can obtain it. α gas concentration .

[0031] 5. Backpropagation Neural Network (BPNN) Error Correction Method This invention first uses the ultrasonic time-of-flight method, placing the ultrasonic sensor in a laboratory pipe, and obtaining the measured wind speed and the measured sound velocity of the mixed gas through formulas (3)-(5); then, the sound velocity of the mixed gas and the ambient temperature are input into the sound velocity model of the methane-air binary mixed gas, and the initial concentration of methane is obtained by inversion through formula (10) using parameters such as the specific heat ratio, average relative molecular mass, and gas constant of the mixed gas at constant pressure and volume. Then, the gas flow rate measurement value is obtained by combining the cross-sectional area of ​​the measurement channel.

[0032] Based on laboratory calibration experiments, a large number of experiments were conducted under optimal operating conditions covering wind speeds of 0–5 m / s, methane volume fractions of 1%–9%, ​​and temperatures of 15–45℃. The calculated wind speeds output from the sensors were collected. Calculate the speed of sound Initial methane concentration and ambient temperature T The system uses the echo amplitude (Amp) and signal-to-noise ratio (SNR) of sensor signals to form an error correction database suitable for low concentration, low wind speed, and complex operating conditions.

[0033] The BPNN intelligent correction module takes the physical model calculation results and field characteristics as input, and outputs compensation amounts to correct for concentration and flow rate. Input feature vector f At least including , , , T Echo amplitude (Amp) and signal-to-noise ratio (SNR); network output is and It sets quality judgment criteria; if the signal-to-noise ratio is lower than a set threshold, the current data is deemed unreliable, and a "data quality warning" is output instead of a specific concentration / flow rate value to prevent false alarms. The corrected output is... (11); The BPNN model is trained using an error correction training library. The trained weights are then filled into the corresponding storage blocks of the neural network weights in the PLC (Programmable Logic Controller). The forward inference process is then fixed in the PLC. During runtime, the input vector is fed into the trained BPNN model. The model performs forward inference correction through weight matrix operations and outputs the corrected gas concentration and flow rate.

[0034] The above-mentioned sensors and correction methods are used in the following examples: S1. This embodiment provides a gas concentration and flow rate synchronous monitoring sensor based on ultrasonic time difference and thermodynamic model. The sensor includes: an annular measurement channel, at least four ultrasonic transceiver transducers (which can form a two-dimensional orthogonal measurement), a temperature sensor, a control and acquisition circuit, a wireless transmission module, and a host computer. The windward side of the measurement channel adopts an inwardly inclined structure to reduce flow field distortion and structural disturbance errors caused by flow around the channel, and to improve the uniformity of flow velocity distribution inside the measurement channel.

[0035] S2, the processor module controls the drive circuit to generate an ultrasonic excitation signal and controls the channel selection circuit to enable each transducer to transmit and receive sequentially, obtaining the downstream propagation time and upstream propagation time on the two propagation paths; the weak echo signal output by the receiving transducer assembly 4 is amplified, filtered, and shaped before being sent to the detection circuit to complete the propagation time measurement; simultaneously, the temperature sensor synchronously collects and measures the ambient temperature data. The echo amplitude and signal-to-noise ratio are extracted synchronously as input features for subsequent data quality assessment and intelligent correction.

[0036] S3. The processor module uses the ultrasonic time-of-flight method to calculate the wind speed component and the sound velocity of the mixed gas in the corresponding direction based on the downstream and upstream propagation times along each propagation path. For two orthogonal propagation paths, the axial velocity, wind direction, and calculated sound velocity of the gas in the channel are obtained through vector synthesis. Then, the speed of sound will be calculated. With ambient temperature T Input a thermodynamic model of a methane-air binary gas mixture, and obtain the measured methane concentration based on the isobaric and isochoric specific heat ratio, average relative molecular mass, and gas constant of the gas mixture. .

[0037] S4. To establish the intelligent correction model, this embodiment constructs a multi-source training dataset. The training data includes: laboratory calibration data and CFD numerical simulation data. Preferably, 1000 sets of experiments are conducted covering wind speeds of 0–5 m / s, methane volume fractions of 1%–9%, ​​and temperatures of 15–45°C, collecting the calculated wind speed output from the sensors. Calculate the speed of sound Initial methane concentration and ambient temperature T The system uses the echo amplitude (Amp) and signal-to-noise ratio (SNR) of sensor signals to form an error correction database suitable for low concentration, low wind speed, and complex operating conditions.

[0038] S5. Input the training data into the BPNN intelligent correction model for training. The model uses temperature, measured wind speed, and measured sound speed as core input features, and introduces echo amplitude and signal-to-noise ratio as extended input features. The model outputs corrected wind speed and methane concentration values. When the signal-to-noise ratio is lower than a set threshold, the current data is determined to be unreliable, and a "data quality warning" is output. After training, the model weights and threshold parameters are stored in the corresponding storage block of the PLC's neural network weights. Online forward inference is performed on the real-time acquired physical model solution results to output the corrected methane concentration and flow rate.

[0039] S6. To verify the effectiveness of this invention, a gas measurement experiment was conducted in a mine roadway. A high-precision reference anemometer was used as a control, and the original measurement values ​​of the sensor and the output values ​​after BPNN correction were recorded. The experimental results are as follows: Figure 3 As shown in the figure, it can be clearly seen that the wind speed measurement error after correction is significantly reduced compared with that before correction, indicating that the present invention can effectively improve the accuracy and reliability of synchronous monitoring of low-concentration methane concentration and flow rate under complex working conditions.

[0040] Therefore, the present invention employs the above-mentioned gas concentration and flow synchronous monitoring sensor and calibration method, which reduces the impact of airflow disturbance on the measurement results, improves the measurement accuracy in complex environments, and significantly improves the measurement stability and accuracy of the sensor.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A gas concentration and flow rate synchronous monitoring sensor, characterized in that, include: At least two pairs of ultrasonic transducers and other auxiliary monitoring components; wherein each pair of ultrasonic transducers constitutes a sound channel for emitting and receiving ultrasonic waves in both the downstream and upstream directions, and for obtaining the downstream propagation time. and the time of reverse propagation ; The ultrasonic transducer is made of a gas-based type 1-3 piezoelectric composite material. The piezoelectric composite material uses a gas medium as a matrix and has piezoelectric ceramic pillars arranged in an array inside. The acoustic radiation surface of the ultrasonic transducer is provided with three gradient acoustic impedance matching layers. The three gradient acoustic impedance matching layers are, in sequence from the ultrasonic transducer radiation surface to the gas to be measured, a PEEK material layer, a PMI foam material layer, and a polyimide aerogel layer treated with parylene C coating. The acoustic impedance value of each of the three gradient acoustic impedance matching layers is distributed in a gradient decreasing distribution to realize the gradual transition of acoustic impedance between the piezoelectric material and the gas medium to be measured. The ultrasonic transducers are four in number and arranged orthogonally to form a two-dimensional ultrasonic wind sensor, which measures wind speed in two directions. v and measuring the speed of sound c Calculated wind speed is obtained using vector synthesis method. Calculate wind direction And calculate the speed of sound ; Other auxiliary monitoring components include: Temperature sensor used to synchronously collect ambient temperature T ; The signal processing circuit is used to amplify, filter, and shape the received ultrasonic echo signal; The detection circuit includes a time measurement circuit and a temperature measurement circuit, used to measure the propagation time in the upstream / downstream direction and the ambient temperature; The processor module has a built-in physical inversion module based on a mixed gas thermodynamic model and a backpropagation neural network intelligent correction module. The processor module calculates the gas sound velocity and axial velocity based on the downstream / countercurrent propagation time, and obtains the initial value of methane concentration based on the methane-air binary mixed gas sound velocity model. The BPNN intelligent correction module takes a feature vector as input, and the feature vector includes at least the calculated wind speed. Calculate the speed of sound Initial value of methane concentration Ambient temperature T Echo amplitude (Amp), signal-to-noise ratio (SNR), and output methane concentration compensation. With flow rate compensation Obtain the corrected concentration of the gas to be measured. With flow rate .

2. The gas concentration and flow rate synchronous monitoring sensor according to claim 1, characterized in that, The gas concentration and flow rate synchronous monitoring sensor also includes an annular measurement channel. The windward side of the annular measurement channel adopts an inward inclined structure to reduce the impact of flow field disturbance on measurement accuracy.

3. The gas concentration and flow rate synchronous monitoring sensor according to claim 1, characterized in that, The processor module also calculates the gas flow rate based on the corrected flow velocity and the cross-sectional area of ​​the measurement channel, and outputs the gas flow rate data.

4. The gas concentration and flow rate synchronous monitoring sensor according to claim 1, characterized in that, The BPNN intelligent correction module also has a quality judgment criterion: when the signal-to-noise ratio in the input feature vector is lower than a preset threshold, a data quality warning message is output, and no specific concentration or flow rate value is output.

5. The calibration method for a gas concentration and flow rate synchronous monitoring sensor according to claim 1, characterized in that, Includes the following steps: S1: Control the ultrasonic transducer to emit and receive ultrasonic waves in the downstream and upstream directions, and obtain the downstream propagation time. and the time of reverse propagation ; S2: Amplify, filter, and shape the received ultrasonic echo signal, and measure it. , Simultaneously collect ambient temperature T ; S3: Based on , Obtain the calculated speed of sound With calculation of wind speed And using a methane-air binary gas sound velocity model, at an ambient temperature... T Initial values ​​of methane concentration were obtained through inversion under constraints. ; S4: Construct a BPNN neural network model to include at least the calculation of wind speed. Calculate the speed of sound Initial methane concentration Ambient temperature T The eigenvectors of echo amplitude (Amp) and signal-to-noise ratio (SNR) are used as inputs, with the gas concentration compensation amount as the input. and flow rate compensation Δ v As output, residual compensation and drift correction are performed on the physical model solution results; S5: Output corrected methane concentration and the corrected flow rate .

6. The calibration method for a gas concentration and flow rate synchronous monitoring sensor according to claim 5, characterized in that, The specific formula for retrieving the initial value of methane concentration in step S3 is as follows: ； ； ； ； In the formula, for α Initial concentration of the gas; C Pα and C Pβ They are respectively α , β Specific heat capacity at constant pressure of a gas; C Vα and C Vβ They are respectively α , β Specific heat capacity at constant volume of a gas; M α and M β They are respectively α , β The relative molecular mass of a gas; A , B , D These are parameters related to specific heat ratio, relative molecular mass, and sound velocity of the gas mixture; parameters Y Speed ​​of sound of mixed gas and ambient temperature T Sure.

7. The calibration method for a gas concentration and flow rate synchronous monitoring sensor according to claim 5, characterized in that, The gas concentration and flow synchronous monitoring sensor and calibration method are suitable for measuring the target gas in various mixed gases.

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