CN115773473B - Monitoring system and monitoring method for natural gas leakage in tunnel - Google Patents
Monitoring system and monitoring method for natural gas leakage in tunnel Download PDFInfo
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Abstract
本发明公开了一种隧道内天然气泄漏监测系统及监测方法，包括传感器、光缆、主机、报警装置和显示装置，传感器通过光缆与主机连接，主机分别和报警装置、显示装置相连，主机包括控制单元、泄漏源定位计算单元、泄漏源泄漏率反演计算单元和预警决策单元，泄漏源定位计算单元根据甲烷浓度数据对泄漏源位置进行定位，泄漏源泄漏率反演计算单元根据甲烷浓度数据对泄漏源泄漏率进行计算，预警决策单元根据甲烷浓度数据控制报警装置的启停，泄漏源定位结果和泄漏源泄漏率计算结果均输出至显示装置上。本发明实现高度自动化，由传感器自动检测，通过主机实时预警判断，效率高。在信息采集、运输、储存等环节均通过监测与预警系统进行，人为因素影响小。
The present invention discloses a natural gas leakage monitoring system and method in a tunnel, including a sensor, an optical cable, a host, an alarm device and a display device. The sensor is connected to the host through an optical cable, and the host is respectively connected to the alarm device and the display device. The host includes 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 locates 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 unit controls the start and stop of the alarm device according to the methane concentration data. The leakage source positioning result and the leakage source leakage rate calculation result are both output to the display device. The present invention realizes high automation, automatic detection by the sensor, real-time early warning judgment by the host, and high efficiency. Information collection, transportation, storage and other links are all carried out through the monitoring and early warning system, and the influence of human factors is small.
Description
Technical Field
The invention relates to a natural gas leakage monitoring system in a tunnel and a monitoring method of the natural gas leakage monitoring system in the tunnel.
Background
Compressed natural gas and liquefied natural gas tank cars are one of the common transportation modes of natural gas, and are also the motive fuels for many vehicles. In the process of passing through the tunnel, if leakage is caused by accidents such as high temperature (such as fire), impact, pipe fitting falling and the like, flammable and explosive gas clouds are formed in the tunnel space, the formed flammable and explosive gas clouds possibly cause hypoxia and suffocation of personnel and frostbite, and the formed flammable and explosive gas clouds encounter ignition sources, dangerous accidents such as steam cloud explosion and the like can possibly occur in the tunnel, and the generated high-temperature smoke and overpressure can cause serious injury to personnel and property.
However, only the tunnel passing through the gas stratum is required to monitor the gas concentration in the highway tunnel design rule in China at present, but no universal requirement is made for monitoring the inflammable and explosive gas of the highway tunnel, so that the methane monitoring system in the tunnel is very necessary.
Disclosure of Invention
The first aim of the invention is to provide a natural gas leakage monitoring system in the tunnel, which can effectively monitor and early warn natural gas in the tunnel, position accident sites and improve accident handling efficiency.
The first object of the present invention is achieved by the following technical measures: the utility model provides a natural gas leakage monitoring system in tunnel, its characterized in that includes sensor, optical cable, host computer, alarm device and the display device that are 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, leak source location calculation unit, leak source leakage rate inversion calculation unit and the early warning decision unit that are connected with it respectively, wherein, leak source location calculation unit is according to methane concentration data to leaking source position, leak source leakage rate inversion calculation unit is according to methane concentration data to leaking source leakage rate calculation, early warning decision unit is according to the start-stop of methane concentration data control alarm device, leak source location result and leak source leakage rate calculation result all output to display device.
The invention can realize high automation, realizes real-time early warning judgment through the methane sensor and the host computer, and has high working efficiency. All links such as information acquisition, transportation, storage and the like are carried out through a monitoring and early warning system, no manual participation is needed, and the influence of human factors is small. The method can realize the early warning of natural gas leakage in the tunnel and the calculation of the position and the intensity of the leakage source, and meanwhile, the early warning of the natural gas leakage is carried out by utilizing the monitored methane concentration data, and the intensity and the position of the leakage source are inverted, so that the response time of accident disposal can be shortened, the early warning probability of the occurrence of the leakage accident is improved, and the pertinence and the effectiveness of the accident response measures are enhanced. The natural gas leakage source and leakage intensity are inverted by combining the monitored methane concentration data with a machine learning method, so that position and leakage intensity information can be provided for accident rescue and accident disposal, in addition, references can be provided for accident disposal measures, and a proper disaster relief scheme is provided by combining the calculated leakage source information.
The sensors 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, 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 the gas cloud of the leaked gas in the tunnel;
S2, carrying out a numerical experiment on the gas explosion result by using gas explosion result calculation software so as to quantify the maximum explosion overpressure value generated by gas explosion in the tunnel under different leakage time lengths;
S3, mapping the maximum explosion overpressure value under different gas cloud volumes to a gas cloud volume range corresponding to the maximum explosion overpressure 20KPa (human body light injury);
and S4, taking the distance of the combustible gas cloud in the tunnel length direction at the moment as the maximum distance between adjacent sensors.
The second object of the present invention is to provide a monitoring method of the above-mentioned monitoring system for natural gas leakage in a tunnel.
The second object of the present invention is achieved by the following technical measures: the monitoring method of the natural gas leakage monitoring system in the tunnel is characterized by comprising the following steps of:
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 methane concentration data is judged through the early warning decision unit to obtain a judging result;
S3, the alarm device responds to the judging result;
S4, a leakage source leakage rate inversion calculation unit in the host calculates the leakage source leakage rate, a leakage source positioning calculation unit calculates the leakage source leakage position, and a leakage source leakage rate calculation result and a leakage source positioning result are output to a display device.
In the step S2, the basis of the decision of the early warning decision unit is:
wherein: c i -methane concentration measured by the ith methane gas detector; LEL-lower explosion limit of methane gas, 5%.
In the step S4, the method specifically includes the steps of:
⑴ Calculating forward distribution of a flow field when the leakage source is in a static state, and obtaining concentration parameters of different moments in the gas leakage process at the positions of each monitoring point when the leakage source is in the static state;
⑵ Assuming that a leakage source in the tunnel is in a uniform motion state all the time 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;
⑶ Assuming that the prior distribution function of the leakage source intensity and the leakage position is a uniform distribution function within a certain range;
⑷ Calculating likelihood functions of observation concentration distribution under the condition that the prior distribution of the leakage source intensity is established according to the observation data of each sensor;
⑸ Combining prior distribution, predicted concentration and observation data, and calculating posterior distribution approximate solution of source item leakage rate parameters by using Bayes theorem;
⑹ And calculating the leakage rate and the leakage position of the leakage source to be the 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 uniform motion state.
The invention calculates the forward distribution of the flow field when the leakage source is in a static state, and comprises the following steps:
① Adopting a CFD three-dimensional numerical simulation method for tunnel sections within 100m from a leakage source along the longitudinal direction, and respectively solving tunnel gas leakage concentration distribution at different leakage source intensities and leakage source positions;
② Adopting a simplified one-dimensional gas diffusion model at tunnel sections which are 100m away from the leakage source along the longitudinal direction, and respectively solving the leakage concentration distribution of tunnel gas at different leakage source intensities and leakage source positions;
③ And when the leakage source is in a static state, acquiring concentration parameters of different moments in the gas leakage process at the positions of each monitoring point calculated by the forward model.
The invention calculates the forward distribution of the flow field when the leakage source is in a uniform motion state, and comprises the following steps:
① The continuously released leakage concentration field in the tunnel is regarded as a continuous instant point source within a range along the longitudinal length of the tunnel under a certain time sequence, when the tunnel length is L, the continuously released leakage source intensity in the tunnel is q 0, the continuously released leakage source is regarded as an instant released point source at intervals of a certain distance deltax, the running speed of the tunnel is u 0, and the leakage quantity of each point source is calculated
② Respectively solving the inside of the tunnel by adopting a one-dimensional gas diffusion modelThe longitudinal concentration distribution of the flow field is sequentially released by the point sources at the time interval delta x/u 0;
③ And when the leakage source is in a uniform motion state, concentration parameters of different moments in the gas leakage process at the positions of each monitoring point calculated by the forward model are obtained.
The prior distribution function of the leakage source intensity and the leakage position is as follows:
Wherein:
p (Y k) -a priori distribution of leak source intensities;
w max -upper limit of estimated parameters;
W min -lower limit of estimation parameters.
The calculation formula of step ⑷ in the present invention is:
where C β represents the measured concentration value of the sensor, Representing the sensor value calculated using the forward model, σ f·k representing the standard deviation of the concentration data calculated using the forward model, and σ β·k representing the standard deviation of the concentration data measured using the sensor.
Compared with the prior art, the invention has the following remarkable effects:
⑴ The invention can realize high automation, realizes real-time early warning judgment through the methane sensor and the host computer, and has high working efficiency. All links such as information acquisition, transportation, storage and the like are carried out through a monitoring and early warning system, no manual participation is needed, and the influence of human factors is small.
⑵ The method can realize the early warning of natural gas leakage in the tunnel and the calculation of the position and the intensity of the leakage source, and meanwhile, the early warning of the natural gas leakage is carried out by utilizing the monitored methane concentration data, and the intensity and the position of the leakage source are inverted, so that the response time of accident disposal can be shortened, the early warning probability of the occurrence of the leakage accident is improved, and the pertinence and the effectiveness of the accident response measures are enhanced.
⑶ The invention uses the monitored methane concentration data to invert the natural gas leakage source and the leakage intensity by combining a machine learning method, can provide position and leakage intensity information for accident rescue and accident disposal, can provide reference for accident disposal measures, and provides a proper disaster relief scheme by combining the calculated leakage source information.
Drawings
The invention will now be described in further detail with reference to the drawings and to specific examples.
FIG. 1 is a schematic diagram of the composition and structure of a system for monitoring natural gas leakage in a tunnel according to the present invention;
FIG. 2 is a flow chart of the monitoring method of the present invention;
FIG. 3 is a flow chart of leak location and leak rate inversion of the present invention;
FIG. 4 is a graph showing the concentration distribution of the gas cloud obtained by numerical calculation according to the present invention;
FIG. 5 is a schematic diagram of the concentration calculation result of each measuring point obtained by calculating the constant motion leakage source by the forward model;
FIG. 6 is a schematic diagram of the calculation result of the concentration of each measuring point obtained by three-dimensional simulation calculation of the constant motion leakage source;
FIG. 7 is a schematic diagram of the leak source position inversion result of the leak source of the present invention in a stationary state;
FIG. 8 is a schematic diagram of the inversion result of the leakage source intensity of the leakage source in a uniform motion state.
Detailed Description
The invention discloses a natural gas leakage monitoring system in a tunnel, which is shown in fig. 1, and comprises a sensor 1 for collecting methane concentration, an optical cable 2, a host computer 3, an alarm device 4 and a display device (not shown in the figure), wherein the sensor 1 is distributed on the inner wall of the tunnel at intervals along the length direction of the tunnel, the host computer 3 and the alarm device 4 are arranged in a cabinet 5, the sensor 1 is a plurality of and is connected with the host computer 3 through the optical cable 2, the host computer 3 is respectively connected with the alarm device 4 and the display device, the host computer 3 comprises a control unit, a leakage source positioning calculation unit, a leakage source leakage rate inversion calculation unit and an early warning decision unit which are respectively connected with the control unit, the leakage source positioning calculation unit positions the leakage source according to 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 output to the display device.
As shown in fig. 2, the system for monitoring natural gas leakage in the tunnel is installed, specifically:
1. Determining a sensor arrangement pitch in a longitudinal direction:
(1) Modeling is carried out according to tunnel structure data, the length (X) width (Y) height (Z) of a highway tunnel numerical experiment model in the embodiment is 200m multiplied by 6m respectively, and a gas leakage diffusion numerical simulation software is used for carrying out numerical simulation on a compressed natural gas leakage diffusion process in the tunnel so as to obtain a distribution form of gas and cloud of leakage gas in the tunnel.
(2) According to the gas cloud concentration distribution at different moments obtained by natural gas leakage and diffusion numerical simulation, numerical experiments are carried out on gas explosion results by using gas explosion result calculation software, the calculation results are shown in fig. 4, and numerical experiments are carried out on the gas explosion results by using the gas explosion result calculation software so as to quantify the maximum explosion overpressure value generated by gas explosion in tunnels under different leakage time lengths.
(3) And mapping the maximum explosion overpressure value under different gas cloud volumes to a gas cloud volume range corresponding to the maximum explosion overpressure of 20KPa (human light injury).
(4) Taking the distance of the combustible gas cloud in the tunnel length direction at this time as the arrangement pitch of the methane concentration sensors, assuming that the arrangement pitch of the methane concentration sensors obtained in the present case is 20m, 9 methane concentration sensors are total in the present embodiment model.
2. And arranging the monitoring system according to the arrangement interval of the sensors in the longitudinal direction, and monitoring the data in real time.
The monitoring method of the natural gas leakage monitoring system in the tunnel specifically comprises the following steps:
S1, when methane gas generated by tank wagon leakage diffuses in a tunnel, a sensor monitors real-time methane concentration data, and the methane concentration data is transmitted to a host through an optical cable;
s2, the host receives the methane concentration data, and the methane concentration data is judged through the early warning decision unit to obtain a judging result; the basis of the judgment of the early warning decision unit is as follows:
wherein: 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 judging result;
S4, a leakage source leakage rate inversion calculation unit in the host calculates the leakage source leakage rate, a leakage source positioning calculation unit calculates the leakage source leakage position, and a leakage source leakage rate calculation result and a leakage source positioning result are output to the display device.
As shown in fig. 3, calculating the leak source leak rate and the leak source leak location specifically includes:
⑴ Calculating forward distribution of a flow field when the leakage source is in a static state, and obtaining concentration parameters of different moments in the gas leakage process at the positions of each monitoring point when the leakage source is in the static state;
in this example, the leak source intensities were calculated to be respectively 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, and the leak positions were forward distribution of stationary leak source flow fields every 5m in the tunnel space.
① Adopting a CFD three-dimensional numerical simulation method for tunnel sections within 100m from a leakage source along the longitudinal direction, and respectively solving tunnel gas leakage concentration distribution at different leakage source intensities and leakage source positions;
② Adopting a simplified one-dimensional gas diffusion model at tunnel sections which are 100m away from a leakage source along the longitudinal direction, adopting a time front and center difference method to calculate an equation, and programming to solve the tunnel gas leakage concentration distribution at different leakage source intensities and leakage source positions;
③ And when the leakage source is in a static state, extracting concentration parameters in the gas leakage process at the positions of monitoring points calculated by the forward model, wherein each measuring point records data once every 20s, and the leakage duration is 600s.
⑵ Assuming that a leakage source in the tunnel is in a uniform motion state all the time 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;
in this embodiment, when the intensities of the leakage sources in the tunnel are calculated to be 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, respectively, the flow field forward distribution when the leakage sources are in a motion state is calculated assuming that the leakage sources are in a uniform motion state from the beginning of entering the tunnel to the beginning of exiting the tunnel.
① Regarding a continuously released leakage concentration field in a tunnel as a continuous instant point source within a range of the longitudinal length of the tunnel under a certain time sequence, regarding the continuously released leakage source as a point source at intervals of 5m when the length of the tunnel is 200m and the strength of the continuously released leakage source in the tunnel is 0.1kg/s, and calculating the leakage quantity of each point source as Deltax/u 0·q0 = 0.03kg when the speed of a travelling crane in the tunnel is 60 km/h;
② And (3) respectively solving longitudinal concentration distribution of the flow field after 39 point sources are released in the tunnel by adopting a one-dimensional gas diffusion model, wherein the leakage duration is 60s, and recording data every 1s, wherein when the leakage source intensity is 0.9kg/s, the calculation result is shown in figure 5.
③ And when the leakage source is in a uniform motion state, concentration parameters of different moments in the gas leakage process at the positions of each monitoring point calculated by the forward model are obtained.
And obtaining concentration distribution of each measuring point at each moment by adopting a three-dimensional numerical experiment method, and taking the concentration distribution as a sensor measurement concentration value calculated by inversion. For a static leakage source in a tunnel, the leakage concentration in the tunnel is 0.26kg/s, and the position of the leakage source is 50m; for the in-tunnel moving state leakage source, the leakage concentration was 0.77kg/s, and the calculation result is shown in FIG. 6.
⑶ Assuming that the prior distribution function of the leakage source intensity and the leakage position is a uniform distribution function within a certain range;
The calculation formula is as follows:
Wherein:
p (Y k) -a priori distribution of leak source intensities;
w max -upper limit of estimated parameters;
W min -lower limit of estimation parameters.
When the leakage source is in a static state, the prior distribution of the leakage source strength is compliant with U [0,1], and the prior distribution of the leakage source position is compliant with U [0, 200]; when the leakage source is in a uniform motion state, the prior distribution of the leakage source intensity is compliant with U [0,1].
⑷ According to the observation data of each sensor, calculating a likelihood function of the observation concentration distribution under the condition that the prior distribution of the leakage source intensity is established, wherein the calculation formula is as follows:
Namely:
Wherein the method comprises the steps of The j-th measured concentration value representing the i-th sensor,The j-th measured concentration value of the i-th sensor calculated by using the forward model is represented, sigma is the standard deviation between the calculated concentration and the measured concentration of the forward model, the error is set to be the same order of magnitude as the measured concentration, and the standard deviation is assumed to be the same as the measured concentration.
⑸ The posterior distribution approximation solution of the source term leak rate parameter, p (Y k|β)＝(p(Yk)p(β|Yk))/(p (β)), is calculated using bayesian theorem in combination with the prior distribution, the predicted concentration and the observed data, where p (Y k) is the prior distribution and p (β|y k) is the likelihood function.
⑹ And (3) performing curve fitting according to the calculated probability values at each leakage source intensity and position, and taking the maximum probability value of the fitted curve as an inversion result. For a stationary leakage source, the leakage source position inversion result is shown in FIG. 7, the leakage source position inversion result is 39.95m, the error is 10.05m, the leakage source intensity inversion result is 0.17kg/s, and the error is 0.07kg/s; and for the leakage source in a uniform motion state, obtaining the leakage source intensity corresponding to the probability maximum value after fitting, wherein the error is 0.064kg/s, and the leakage source intensity inversion result is shown in figure 8.
The embodiments of the present invention are not limited thereto, and the present invention may be modified, substituted or altered in various other forms according to the general knowledge and conventional means of the art, which fall within the scope of the claims of the present invention.
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| 街道天然气管道泄漏扩散的数值模拟分析;黄小美;张婧;周阳;张琼雅;;煤气与热力;20160215(02);全文 * |
| 隧道内液化天然气管道泄漏爆炸过程的数值模拟;马世海;黄平;代鹏飞;李想;;科技导报;20110808(22);全文 * |
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