CN115773473A - Monitoring system and monitoring method for natural gas leakage in tunnel - Google Patents

Abstract

The invention discloses a system and a method for monitoring natural gas leakage in a tunnel, which comprises a sensor, an optical cable, a host, an alarm device and a display device, wherein the sensor is connected with the host through the optical cable, the host is respectively connected with the alarm device and the display device, the host comprises a control unit, a leakage source positioning calculation unit, a leakage source leakage rate inversion calculation unit and an early warning decision unit, the leakage source positioning calculation unit positions the position of a leakage source according to methane concentration data, the leakage source leakage rate inversion calculation unit calculates the leakage rate of the leakage source according to the methane concentration data, the early warning decision unit controls the starting and stopping of the alarm device according to the methane concentration data, and the leakage source positioning result and the leakage source leakage rate calculation result are both output to the display device. The invention realizes high automation, is automatically detected by the sensor, and has high efficiency through real-time early warning and judgment of the host. The links such as information acquisition, transportation, storage are all carried out through monitoring and early warning system, and the human factor influence is little.

Description

A monitoring system and method for monitoring natural gas leakage in a tunnel

technical field

The invention relates to a natural gas leakage monitoring system in a tunnel, and also relates to a monitoring method of the natural gas leakage monitoring system in the tunnel.

Background technique

Compressed natural gas and liquefied natural gas tanker road transportation is one of the commonly used transportation methods for natural gas, and compressed natural gas and liquefied natural gas are also power fuels for many vehicles. Tank trucks and natural gas vehicles passing through the tunnel, if leaks are caused by accidents such as high temperature (such as fire), impact, and pipe fittings falling off, a flammable and explosive gas cloud will be formed in the tunnel space, which may cause hypoxia, suffocation, and frostbite. When the formed flammable and explosive gas cloud encounters an ignition source, dangerous accidents such as steam cloud explosion may occur in the tunnel, and the generated high-temperature smoke and overpressure will cause serious damage to personnel and property.

However, currently my country's "Code for Design of Highway Tunnels" only requires gas concentration monitoring for tunnels passing through gas formations, but does not make general requirements for the monitoring of flammable and explosive gases in road tunnels. Therefore, it is very necessary to install methane monitoring systems in tunnels of.

Contents of the invention

The first object of the present invention is to provide a natural gas leakage monitoring system in tunnels that can effectively monitor and warn natural gas in tunnels, locate accident locations, and improve accident handling efficiency.

The first object of the present invention is achieved through the following technical measures: a natural gas leakage monitoring system in a tunnel, characterized in that it includes a sensor for collecting methane concentration, an optical cable, a host, an alarm device and a display device, the There are several sensors and they are connected to the host computer through optical cables. The host computer is connected to the alarm device and the display device respectively. Early warning decision-making unit, wherein, the leakage source location calculation unit locates the location of the leakage source according to the methane concentration data, the leakage source leakage rate inversion calculation unit calculates the leakage source leakage rate according to the methane concentration data, and the early warning decision-making The unit controls the start and stop of the alarm device according to the methane concentration data, and the leakage source location results and the calculation results of the leakage source leakage rate are output to the display device.

The invention can realize a high degree of automation, automatically detects through a methane sensor, realizes real-time early warning and judgment through a host, and has high working efficiency. All aspects of information collection, transportation, storage, etc. are carried out through the monitoring and early warning system, without manual participation, and the influence of human factors is small. The invention can realize early warning of natural gas leakage in the tunnel and calculation of the location and intensity of the leakage source. At the same time, the monitored methane concentration data can be used for early warning of natural gas leakage, and the intensity and location of the leakage source can be inverted, which can shorten the response time of accident disposal and improve the efficiency of natural gas leakage. The probability of early warning of leakage accidents will increase the pertinence and effectiveness of accident response measures. Using the monitored methane concentration data combined with machine learning methods to invert the source and intensity of natural gas leakage, it can provide location and leakage intensity information for accident rescue and accident disposal. In addition, it can also provide reference for accident disposal measures. Combined with the calculated leak source information, and provide appropriate disaster relief plans.

The sensors of the present invention are distributed on the inner wall of the tunnel at intervals along the length direction of the tunnel, and the distance between two adjacent sensors is calculated by the following steps:

S1. Use the gas leakage and diffusion numerical simulation software to numerically simulate the gas leakage and diffusion process inside the tunnel under different gas cloud volumes, and obtain the gas cloud distribution form of the leaked gas inside the tunnel;

S2. Use the gas explosion consequence calculation software to carry out numerical experiments on the gas explosion consequences to quantify the maximum explosion overpressure value generated by the gas explosion in the tunnel under different leakage durations;

S3, according to the maximum explosion overpressure value under different gas cloud volumes, map to the gas cloud volume range when the maximum explosion overpressure is 20KPa (slight injury to the human body);

S4. The distance of the combustible gas cloud in the tunnel length direction at this time is taken as the maximum distance between adjacent sensors.

The second object of the present invention is to provide a monitoring method of the above-mentioned natural gas leakage monitoring system in a tunnel.

The second object of the present invention is achieved by the following technical measures: a monitoring method of the above-mentioned natural gas leakage monitoring system in the tunnel, which is characterized in that it specifically includes the following steps:

S1. The sensor monitors the methane concentration data, and transmits the methane concentration data to the host through the optical cable;

S2. The host computer receives the methane concentration data, judges the methane concentration data through the early warning decision-making unit, and obtains the judgment result;

S3. The alarm device responds to the determination result;

S4. The leakage source leakage rate inversion calculation unit in the main engine calculates the leakage source leakage rate, and the leakage source location calculation unit calculates the leakage source leakage position, and outputs the calculation result of the leakage source leakage rate and the leakage source location result to the display device.

In the present invention, in the step S2, the basis for the determination of the early warning decision-making unit is:

In the formula: C _i — methane concentration measured by the ith methane gas detector; LEL — lower explosion limit of methane gas, 5%.

In the present invention, in the step S4, calculating the leakage rate of the leakage source and the leakage position of the leakage source specifically includes:

(1) Calculate the forward distribution of the flow field when the leakage source is in a static state, and obtain the concentration parameters at different moments during the gas leakage process at each monitoring point when the leakage source is in a static state;

(2) Assuming that the leakage source in the tunnel has been in a state of uniform motion from entering the tunnel to exiting the tunnel, calculate the forward distribution of the flow field when the leakage source is in a state of uniform motion, and obtain the position of each monitoring point when the leakage source is in a state of uniform motion Concentration parameters at different moments during the gas leakage process;

(3) Assume that the prior distribution function of the leakage source intensity and leakage location is a uniform distribution function within a certain range;

(4) Calculate the likelihood function of the observed concentration distribution under the condition that the prior distribution of the leakage source intensity is established according to the observation data of each sensor;

(5) Combining the prior distribution, predicted concentration and observation data, use Bayesian theorem to calculate the approximate solution of the posterior distribution of the leakage rate parameter of the source term;

(6) Calculate the leakage rate of the leakage source and the corresponding value of the leakage position when the posterior distribution probability is the largest, and obtain the inversion results of the leakage rate and leakage position when the leakage source is in a static state, and the leakage source is in a state of uniform motion The leak rate inversion result at time.

The present invention calculates the forward distribution of the flow field when the leakage source is in a static state, including the following steps:

①The CFD three-dimensional numerical simulation method is used in the tunnel section within 100m from the leakage source along the longitudinal direction, and the concentration distribution of the tunnel gas leakage at different leakage source intensities and leakage source locations are respectively solved;

②A simplified one-dimensional gas diffusion model is used in the tunnel section away from the leakage source along the longitudinal direction of 100m, and the concentration distribution of the tunnel gas leakage at different leakage source intensities and leakage source locations is solved respectively;

③ Obtain the concentration parameters at different moments during the gas leakage process at each monitoring point calculated by the forward modeling model when the leakage source is in a static state.

The present invention calculates the forward distribution of the flow field when the leakage source is in a state of uniform motion, including the following steps:

① Consider the leakage concentration field continuously released in the tunnel as a continuous instantaneous point source within a certain time sequence along the longitudinal length of the tunnel. When the length of the tunnel is L and the strength of the leakage source continuously released in the tunnel is q ₀ The leakage source is regarded as an instantaneous release point source every certain distance Δx, and the tunnel design driving speed is u ₀ , and the leakage amount of each point source is calculated as

个点源以时间间隔u₀·Δx依次释放后的流场纵向浓度分布；②A one-dimensional gas diffusion model is used to solve the

Longitudinal concentration distribution of the flow field after point sources are released sequentially at time interval u ₀ ·Δx;

③ Obtain the concentration parameters at different moments during the gas leakage process at each monitoring point calculated by the forward modeling model when the leakage source is in a state of uniform motion.

The prior distribution function of leakage source intensity and leakage position described in the present invention is:

In the formula:

p(Y _k )——prior distribution of leakage source intensity;

W _max - the upper limit of the estimated parameter;

W _min ——The lower limit of the estimated parameter.

The calculation formula of step (4) of the present invention is:

表示利用正演模型计算出来的传感器数值，σ_f·k表示正演模型计算出的浓度数据标准差，σ_β·k表示利用传感器测得的浓度数据标准差。where C _β represents the measured concentration value of the sensor,

Indicates the sensor value calculated by the forward modeling model, σ _{f k} indicates the standard deviation of the concentration data calculated by the forward modeling model, and σ _{β k} indicates the standard deviation of the concentration data measured by the sensor.

Compared with prior art, the present invention has following remarkable effect:

(1) The present invention can realize a high degree of automation, automatically detect through the methane sensor, realize real-time early warning and judgment through the host computer, and have high work efficiency. All aspects of information collection, transportation, storage, etc. are carried out through the monitoring and early warning system, without manual participation, and the influence of human factors is small.

(2) The present invention can realize the early warning of natural gas leakage in the tunnel and the calculation of the location and intensity of the leakage source. At the same time, the monitored methane concentration data can be used to provide early warning of natural gas leakage, and the intensity and location of the leakage source can be inverted, which can shorten the response to accident disposal Time, increase the probability of early warning of leakage accidents, and enhance the pertinence and effectiveness of accident response measures.

(3) The present invention utilizes the monitored methane concentration data combined with machine learning methods to invert natural gas leakage sources and leakage intensity, which can provide location and leakage intensity information for accident rescue and accident disposal. In addition, it can also provide information for accident disposal measures. For reference, combined with the calculated leakage source information, an appropriate disaster relief plan is provided.

Description of drawings

The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

Fig. 1 is a schematic diagram of the composition and structure of a natural gas leakage monitoring system in a tunnel of the present invention;

Fig. 2 is a flow diagram of the monitoring method of the present invention;

Fig. 3 is a flow chart of leak location and leak rate inversion in the present invention;

Fig. 4 is the gas cloud concentration distribution schematic diagram that numerical calculation of the present invention obtains;

Fig. 5 is a schematic diagram of the calculation results of the concentration of each measuring point obtained by the forward modeling model of the present invention to calculate the uniform motion leak source;

Fig. 6 is a schematic diagram of the calculation results of the concentration of each measuring point obtained by the three-dimensional simulation calculation of the uniform motion leakage source of the present invention;

Fig. 7 is a schematic diagram of the leakage source position inversion result of the leakage source in the static state of the present invention;

Fig. 8 is a schematic diagram of leakage source strength inversion results of the leakage source in the state of uniform motion according to the present invention.

Detailed ways

As shown in Figure 1, it is a kind of natural gas leakage monitoring system in the tunnel of the present invention, and it comprises the sensor 1 that is used to collect methane concentration, optical cable 2, host computer 3, warning device 4 and display device (not drawing in the figure), sensor 1. Distributed on the inner wall of the tunnel at intervals along the length direction of the tunnel. The host 3 and the alarm device 4 are installed in a cabinet 5. There are several sensors 1 connected to the host 3 through the optical cable 2. The host 3 is connected to the alarm device 4 and the display respectively. The device is connected, and the host computer 3 includes a control unit, a leakage source location calculation unit connected thereto, a leakage source leakage rate inversion calculation unit, and an early warning decision-making unit, wherein the leakage source location calculation unit locates the location of the leakage source according to the methane concentration data , the leakage rate inversion calculation unit of the leakage source calculates the leakage rate of the leakage source according to the methane concentration data, the early warning decision-making unit controls the start and stop of the alarm device according to the methane concentration data, and the leakage source location results and the calculation results of the leakage source leakage rate are output to the display on the device.

As shown in Figure 2, the gas leakage monitoring system in the tunnel of the present invention is installed, specifically:

1. Determine the vertical spacing of the sensors:

(1) Modeling is carried out according to the tunnel structure data. The length (X), width (Y) and height (Z) of the highway tunnel numerical experimental model in this implementation case are 200m×6m×6m respectively, and the gas leakage and diffusion numerical simulation software is used to simulate Numerical simulation of the leakage and diffusion process of compressed natural gas inside the tunnel is carried out to obtain the distribution of the leaked gas cloud inside the tunnel.

(2) According to the gas cloud concentration distribution at different times obtained from the numerical simulation of natural gas leakage and diffusion, the gas explosion consequence calculation software is used to conduct numerical experiments on the gas explosion consequences. The calculation results are shown in Figure 4. Numerical experiments were carried out to quantify the maximum explosion overpressure value generated by the gas explosion in the tunnel under different leakage durations.

(3) According to the maximum explosion overpressure value under different gas cloud volumes, it is mapped to the gas cloud volume range corresponding to the maximum explosion overpressure of 20KPa (slight injury to the human body).

(4) The distance of the combustible gas cloud in the tunnel length direction at this time is taken as the arrangement spacing of methane concentration sensors. Assuming that the arrangement spacing of methane concentration sensors obtained in this case is 20m, there are 9 methane concentration sensors in this implementation case model.

2. Arrange the monitoring system according to the vertical spacing of the sensors, and monitor the data in real time.

A monitoring method of the above-mentioned natural gas leakage monitoring system in a tunnel, specifically comprising the following steps:

S1. When the methane gas produced by the leakage of the tanker diffuses in the tunnel, the sensor monitors the real-time methane concentration data, and transmits the methane concentration data to the host computer through the optical cable;

S2. The host computer receives the methane concentration data, judges the methane concentration data through the early warning decision-making unit, and obtains the judgment result; the basis for the judgment of the early warning decision-making unit is:

In the formula: C _i — methane concentration measured by the ith methane gas detector; LEL — lower explosion limit of methane gas, 5%.

S3. The alarm device responds to the determination result;

S4. The leakage source leakage rate inversion calculation unit in the main engine calculates the leakage source leakage rate, and the leakage source location calculation unit calculates the leakage source leakage position, and outputs the calculation result of the leakage source leakage rate and the leakage source location result to the display on the device.

As shown in Figure 3, the calculation of the leakage rate of the leakage source and the location of the leakage source specifically includes:

(1) Calculate the forward distribution of the flow field when the leakage source is in a static state, and obtain the concentration parameters at different moments during the gas leakage process at each monitoring point when the leakage source is in a static state;

In this example, the calculated leakage source intensity is 0.1kg/s, 0.2kg/s, 0.3kg/s, 0.4kg/s, 0.5kg/s, 0.6kg/s, 0.7kg/s, 0.8kg/s , 0.9kg/s, 1.0kg/s, the leakage location is the forward modeling distribution of the static leakage source flow field every 5m in the tunnel space.

①The CFD three-dimensional numerical simulation method is used in the tunnel section within 100m from the leakage source along the longitudinal direction, and the concentration distribution of the tunnel gas leakage at different leakage source intensities and leakage source locations are respectively solved;

②A simplified one-dimensional gas diffusion model is used in the tunnel section away from the leakage source along the longitudinal direction of 100m, and the equation is calculated by using the method of time antecedent and central difference, and the tunnel gas leakage at different leakage source intensities and locations is solved by programming Concentration distribution;

③ Extract the concentration parameters during the gas leakage process at each monitoring point calculated by the forward modeling model when the leakage source is in a static state, where each measurement point records data every 20s, and the leakage duration is 600s.

(2) Assuming that the leakage source in the tunnel has been in a state of uniform motion from entering the tunnel to exiting the tunnel, calculate the forward distribution of the flow field when the leakage source is in a state of uniform motion, and obtain the position of each monitoring point when the leakage source is in a state of uniform motion Concentration parameters at different moments during the gas leakage process;

In this example, the calculated leakage source strength in the tunnel is 0.1kg/s, 0.2kg/s, 0.3kg/s, 0.4kg/s, 0.5kg/s, 0.6kg/s, 0.7kg/s, 0.8kg /s, 0.9kg/s, and 1.0kg/s, assuming that it is in a state of uniform motion from entering the tunnel to exiting the tunnel, calculate the forward distribution of the flow field when the leakage source is in motion.

① Consider the leakage concentration field continuously released in the tunnel as a continuous instantaneous point source along the longitudinal length of the tunnel in a certain time series. When the tunnel length is 200m and the strength of the leakage source continuously released in the tunnel is 0.1kg/s, The continuous release leakage source is regarded as a point source every 5m at a certain distance, and the speed of driving in the tunnel is 60km/h, and the leakage amount of each point source is calculated as

②A one-dimensional gas diffusion model is used to solve the longitudinal concentration distribution of the flow field after the release of 39 point sources in the tunnel. The leakage duration is 60s, and one data is recorded every 1s. When the leakage source intensity is 0.9kg/s, the calculation results are as follows: Figure 5 shows.

③ Obtain the concentration parameters at different moments during the gas leakage process at each monitoring point calculated by the forward modeling model when the leakage source is in a state of uniform motion.

Using the method of three-dimensional numerical experiment, the concentration distribution of each measuring point at each time is obtained, which is used as the concentration value measured by the sensor for inversion calculation. For the leakage source in the static state in the tunnel, the leakage concentration in the tunnel is 0.26kg/s, and the location of the leakage source is 50m; for the leakage source in the moving state in the tunnel, the leakage concentration is 0.77kg/s, and the calculation results are shown in Figure 6.

(3) Assume that the prior distribution function of the leakage source intensity and leakage location is a uniform distribution function within a certain range;

Its calculation formula is:

In the formula:

p(Y _k )——prior distribution of leakage source intensity;

W _max - the upper limit of the estimated parameter;

W _min ——The lower limit of the estimated parameter.

When the leak source is in a static state, the prior distribution of the leak source intensity obeys U[0, 1], and the prior distribution of the leak source position obeys U[0, 200]; when the leak source is in a state of uniform motion, its leak source intensity The prior distribution obeys U[0,1].

(4) According to the observation data of each sensor, calculate the likelihood function of the observed concentration distribution under the condition that the prior distribution of the leakage source intensity is established, and the calculation formula is:

Right now:

表示第i各传感器的第j个测量浓度值，

表示利用正演模型计算出来的第i各传感器的第j个测量浓度值，σ为正演模型计算浓度和测量浓度间的标准差，设误差与测量浓度为同一量级，假设标准差与测量浓度相同。in

Indicates the j-th measured concentration value of each i-th sensor,

Indicates the j-th measured concentration value of each i-th sensor calculated by the forward modeling model, σ is the standard deviation between the calculated concentration and the measured concentration of the forward modeling model, the error and the measured concentration are assumed to be of the same order of magnitude, and the standard deviation is assumed to be the same as the measured concentration same concentration.

(5) Combining the prior distribution, predicted concentration and observation data, Bayesian theorem is used to calculate the approximate solution of the posterior distribution of the source leakage rate parameter, p(Y _k |β)=(p(Y _k )p(β| Y _k ))/(p(β)), where p(Y _k ) is the prior distribution, and p(β|Y _k ) is the likelihood function.

(6) Carry out curve fitting according to the calculated probability values at each leakage source intensity and location, and take the maximum value of the probability of the fitting curve as the inversion result. For the leakage source in static state, the inversion result of the leakage source position is shown in Figure 7, the inversion result of the leakage source position is 39.95m, the error is 10.05m, the inversion result of the leakage source intensity is 0.17kg/s, and the error is 0.07kg /s; for the leakage source in a state of uniform motion, the leakage source intensity corresponding to the probability maximum value obtained after fitting is 0.706kg/s, and the error is 0.064kg/s. The inversion result of the leakage source intensity is shown in Figure 8.

The embodiments of the present invention are not limited thereto. According to the above content of the present invention, according to the common technical knowledge and conventional means in this field, the present invention can also make other various forms of modification, replacement or change, all of which fall within the rights of the present invention. within the scope of protection.

Claims (9)

1. The utility model provides a natural gas leakage monitoring system in tunnel which characterized in that: it is including sensor, optical cable, host computer, alarm device and display device that is used for gathering methane concentration, the sensor is a plurality of and is connected with the host computer through the optical cable, the host computer links to each other with alarm device, display device respectively, the host computer includes the control unit, leaks source location calculating unit, leaks source leakage rate back calculation unit and early warning decision-making unit who is connected with it respectively, wherein, leak source location calculating unit and fix a position the source position according to methane concentration data, leak source leakage rate back calculation unit and calculate leaking source leakage rate according to methane concentration data, early warning decision-making unit opens and stops according to methane concentration data control alarm device, leaks source location result and leaks source leakage rate calculation result and all exports to display device.

2. The in-tunnel natural gas leakage monitoring system according to claim 1, characterized in that: the sensors are distributed on the inner wall of the tunnel at intervals along the length direction of the tunnel, and the distance between every two adjacent sensors is calculated through the following steps:

s1, carrying out numerical simulation on the gas leakage diffusion process in the tunnel under different gas cloud volumes by using gas leakage diffusion numerical simulation software to obtain the distribution form of gas cloud of leaked gas in the tunnel;

s2, carrying out a numerical experiment on the gas explosion consequence by using gas explosion consequence calculation software to quantify the maximum explosion overpressure value generated by gas explosion in the tunnel under different leakage time lengths;

s3, mapping to a gas cloud volume range corresponding to the maximum explosion overpressure of 20KPa according to the maximum explosion overpressure values under different gas cloud volumes;

and S4, taking the distance of the combustible gas cloud in the length direction of the tunnel as the maximum distance between adjacent sensors.

3. The monitoring method of the natural gas leakage monitoring system in the tunnel according to claim 1, characterized by comprising the following steps:

s1, monitoring methane concentration data by a sensor, and transmitting the methane concentration data to a host through an optical cable;

s2, the host receives the methane concentration data, and the early warning decision unit judges the methane concentration data to obtain a judgment result;

s3, the alarm device responds to the judgment result;

and S4, calculating the leakage rate of the leakage source by a leakage source leakage rate inversion calculation unit in the host, calculating the leakage position of the leakage source by a leakage source positioning calculation unit, and outputting the calculation result of the leakage rate of the leakage source and the positioning result of the leakage source to a display device.

4. The monitoring method according to claim 3, characterized in that: in step S2, the basis for the early warning decision unit is:

in the formula: c _i -the methane concentration measured by the ith methane gas detector; LEL-lower explosion limit of methane gas, 5%.

5. The monitoring method according to claim 4, wherein: in step S4, calculating the leakage rate and the leakage position of the leakage source specifically includes:

(1) Calculating the forward distribution of a flow field when the leakage source is in a static state to obtain concentration parameters of different moments in the gas leakage process at each monitoring point position when the leakage source is in the static state;

(2) Assuming that a leakage source in a tunnel is always in a uniform motion state from the beginning of entering the tunnel to the end of exiting the tunnel, calculating forward distribution of a flow field when the leakage source is in the uniform motion state, and obtaining concentration parameters of different moments in the gas leakage process at each monitoring point position when the leakage source is in the uniform motion state;

(3) The prior distribution function of the leakage source intensity and the leakage position is assumed to be a uniform distribution function in a certain range;

(4) Calculating a likelihood function of the observed concentration distribution under the condition that the prior distribution of the intensity of the leakage source is established according to the observed data of each sensor;

(5) Calculating the posterior distribution approximate solution of the source item leakage rate parameter by using Bayesian theorem in combination with the prior distribution, the predicted concentration and the observation data;

(6) And calculating the values of the leakage rate and the leakage position of the leakage source as corresponding values when the posterior distribution probability is maximum, and obtaining the inversion result of the leakage rate and the leakage position when the leakage source is in a static state and the inversion result of the leakage rate when the leakage source is in a constant-speed motion state.

6. The monitoring method according to claim 5, characterized in that: the method for calculating the forward modeling distribution of the flow field when the leakage source is in a static state comprises the following steps:

(1) adopting a CFD three-dimensional numerical simulation method at a tunnel section within 100m in the longitudinal direction away from the leakage source to respectively solve the tunnel gas leakage concentration distribution at different leakage source strengths and leakage source positions;

(2) adopting a simplified one-dimensional gas diffusion model in a tunnel section which is 100m away from a leakage source along the longitudinal direction, and respectively solving the tunnel gas leakage concentration distribution at different leakage source intensities and leakage source positions;

(3) and obtaining concentration parameters of the gas leakage process at different moments at the positions of the monitoring points calculated by the forward model when the leakage source is in a static state.

7. The monitoring method according to claim 6, wherein: the method for calculating the forward distribution of the flow field when the leakage source is in a uniform motion state comprises the following steps:

(1) regarding the continuously released leakage concentration field in the tunnel as a continuous instantaneous point source in a certain time sequence along the longitudinal length range of the tunnel, and when the length of the tunnel is L, the intensity of the continuously released leakage source in the tunnel is q ₀ Continuously released leakage sources are regarded as point sources of instant release at certain intervals delta x, and the driving speed of the tunnel is designed to be u ₀ Calculating the leakage of each point source as

(2) Respectively solving tunnel interior by adopting one-dimensional gas diffusion model

Point sources at time intervals u ₀ The longitudinal concentration distribution of the flow field after the delta x is released in sequence;

(3) and obtaining concentration parameters of the leakage source at different moments in the gas leakage process at the positions of the monitoring points calculated by the forward model when the leakage source is in a uniform motion state.

8. The monitoring method according to claim 7, wherein: the prior distribution function of the leak source intensity and the leak location is:

in the formula:

p(Y _k ) -a prior distribution of leak source intensities;

W _max -estimating an upper value of the parameter;

W _min -estimating a lower value of the parameter.

9. The monitoring method according to claim 8, wherein: the calculation formula of the step (4) is as follows:

wherein C _β A measured concentration value of the sensor is represented,

representing the sensor values, σ, calculated using a forward model _f·k Representing the standard deviation, sigma, of the concentration data calculated by the forward model _β·k Indicating the standard deviation of the concentration data measured with the sensor.

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