Comprehensive identification and evaluation method for risk of pavement collapse induced by shallow methane gas leakage

Abstract

The invention relates to the technical field of comprehensive recognition and evaluation of pavement collapse risks, in particular to a comprehensive recognition and evaluation method for the risk of pavement collapse induced by methane shallow gas leakage. A fault tree and a T-S fuzzy number concept are introduced to express a logical relationship between events, a shallow gas leakage caused pavement collapse fault tree is constructed, a T-S fuzzy fault tree is adopted to evaluate the sensitivity and the importance degree of each factor, and environmental information of shallow gas leakage disasters is comprehensively counted. And an accurate risk identification index and risk assessment of shallow gas leakage are summarized.

Description

Technical Field

[0001] The invention relates to the technical field of comprehensive identification and assessment of road collapse risk, and in particular to a method for comprehensive identification and assessment of road collapse risk induced by shallow biogas leakage. Background Art

[0002] In engineering construction, shallow gas is a potential geological disaster. Geotechnical engineering problems caused by shallow gas often occur in engineering construction in soft soil areas and are a major cause of road collapse. In addition, since the main components of shallow gas are usually flammable gases, it may also cause fires or even explosions.

[0003] From the perspective of quantitative level, the safety and reliability evaluation methods of shallow gas leakage can be divided into: qualitative analysis, quantitative analysis and semi-qualitative and semi-quantitative analysis. The qualitative analysis method mainly evaluates the risk level of the disaster-causing factors based on experience. The classification of the risk level of the disaster-causing factors usually includes five levels: "very high", "very high", "medium", "low" and "very low". The qualitative method has the most direct engineering guidance significance and can judge and make decisions on the safety of a project simply and quickly, but there are certain errors. The quantitative analysis is based on the statistics of the incident cases of road collapse caused by shallow gas leakage, analyzes the factors of road collapse from multiple aspects and angles, and conducts a specific analysis of the weights of different factors. However, due to the lack of sufficient information support, quantitative analysis is usually difficult to achieve.

[0004] Therefore, there is an urgent need to invent a comprehensive identification and assessment method for the risk of road collapse induced by shallow biogas leakage. Summary of the invention

[0005] In view of the above problems, the present invention provides the following technical solutions: a comprehensive identification and assessment method for the risk of road collapse induced by shallow biogas leakage, the method comprising the following steps;

[0006] S1, determine the depth, location and distribution range of shallow gas;

[0007] S2, determine the shallow gas leakage rate;

[0008] S3, determine the pressure of shallow gas;

[0009] S4, determine the reserves of shallow gas;

[0010] S5, determine the genetic composition of shallow gas;

[0011] S6, introduces the TS fuzzy model, describes the failure probability of each component in the form of a TS fuzzy fault tree, considers the fault state more comprehensively, and decomposes and quantifies complex and uncertain problems by establishing TS fuzzy gates, thereby accurately identifying and evaluating the risk of road collapse.

[0012] Preferably, the specific steps in S1 above include:

[0013] S1.1: According to the different field sources between the gas-rich area in the shallow soil layer and the surrounding medium power supply point, a parallel electrical method test system is deployed. The acquisition methods of the parallel electrical method test system are divided into AM method and ABM method;

[0014] S1.2: Use a parallel electrical instrument to collect and measure the potential difference ΔU between the two points of the measuring electrodes M and N multiple times MN f, select the group with better data for analysis;

[0015] S1.3: Based on the collected potential difference data, calculate the resistivity ρ of the underground geological body, use software for analytical processing, perform resistivity inversion, output geoelectric information, and use software to generate maps.

[0016] Preferably, the specific steps in S2 above include:

[0017] S2.1: Deploy acoustic wave collection devices at places where shallow gas may leak, collect acoustic wave signals through multi-channel acoustic sensors, and use the spectrum area within a wide frequency band as the detection indicator;

[0018] S2.2: After wavelet transform, the wavelet coefficients of each scale can be obtained from the observed signal, so as to distinguish the useful signal with higher wavelet coefficient and the noise signal with lower wavelet coefficient. Then, the appropriate threshold function is selected adaptively to perform threshold denoising. The threshold is adjusted repeatedly until all noise signals are removed to obtain the estimated values ​​of the wavelet coefficients of each scale of the useful signal. Finally, the signal is reconstructed through inverse transform to obtain the useful sound signal.

[0019] S2.3: Use the acoustic solver to analyze the acoustic signal waveform and calculate the leakage gas flow velocity characteristics.

[0020] Preferably, the specific steps in the above S3 include:

[0021] S3.1: Use an acoustic sensor to monitor and capture the acoustic waveform of leaking gas;

[0022] S3.2: Use wavelet analysis or empirical mode decomposition (EMD) algorithms to reduce the noise generated by other fluctuations in the fluid;

[0023] S3.3: Analyze the denoised acoustic signal, use the acoustic-pressure coupling method or various pattern recognition algorithms to identify leaks, and use the characteristics of the Lighthill equation and the finite element method to calculate the shallow air pressure.

[0024] Preferably, the specific steps in S4 above include:

[0025] S4.1: Select the AM method or ABM method according to the actual situation of the shallow soil site, and deploy a parallel electrical test system to generate a stable current field in the underground space;

[0026] S4.2: Use the parallel electrical instrument to collect data multiple times, and select the data with better results for data processing;

[0027] S4.3: Perform resistivity inversion based on the collected data and conduct a comprehensive analysis of the shallow gas reserves in the underground space.

[0028] Preferably, in the above S5, data of shallow gas composition and isotope variation are measured to analyze and identify the genesis components of the shallow gas.

[0029] Preferably, in the above S6, a trapezoidal membership function is used to represent the fuzzy possibility.

[0030] Preferably, the membership function F is expressed as: F = (FO, sl, ml, sr, mr), where F0 is the center of the fuzzy number support set, sl and sr are the left and right support radii, and ml and mr are the left and right fuzzy regions. The fault degree of the fuzzy number F described by the trapezoidal membership function is expressed as:

[0031]

[0032] Technical effects and advantages of the present invention:

[0033] 1. The present invention integrates various identification indicators and methods of shallow gas-induced road collapse, introduces the concepts of fault tree and TS fuzzy number to express the logical relationship between events, constructs a fault tree of road collapse caused by shallow gas leakage, uses TS fuzzy fault tree to evaluate the sensitivity and importance of various factors, comprehensively counts the environmental information of shallow gas leakage disasters, and summarizes accurate risk identification indicators and risk assessment of shallow gas leakage.

[0034] Other features and advantages of the present invention will be set forth in the following description, and in part will become apparent from the description, or may be understood through implementation of the present invention. The objects and other advantages of the present invention may be realized and obtained through the structures indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 It is a factor that shallow gas leakage in the present invention may cause road collapse;

[0037] Figure 2 It is a schematic diagram of the trapezoidal membership function in the present invention;

[0038] Figure 3 It is a schematic diagram of the fault tree of road collapse caused by shallow gas leakage in the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0041] Embodiment 1:

[0042] like Figures 1 to 3 As shown: A comprehensive identification and assessment method for the risk of road collapse induced by shallow biogas leakage, the method comprising the following steps;

[0043] S1, determine the depth, location and distribution range of shallow gas;

[0044] S2, determine the shallow gas leakage rate;

[0045] S3, determine the pressure of shallow gas;

[0046] S4, determine the reserves of shallow gas;

[0047] S5, determine the genetic composition of shallow gas;

[0048] S6, introduces the TS fuzzy model, describes the failure probability of each component in the form of a TS fuzzy fault tree, considers the fault state more comprehensively, and decomposes and quantifies complex and uncertain problems by establishing TS fuzzy gates, thereby accurately identifying and evaluating the risk of road collapse.

[0049] The specific steps in the above S1 include:

[0050] S1.1: According to the different field sources between the gas-rich area in the shallow soil layer and the surrounding medium power supply point, a parallel electrical method test system is deployed. The acquisition methods of the parallel electrical method test system are divided into AM method and ABM method;

[0051] S1.2: Use a parallel electrical instrument to collect and measure the potential difference ΔU between the two points of the measuring electrodes M and N multiple times MN f, select the group with better data for analysis;

[0052] S1.3: Based on the collected potential difference data, calculate the resistivity ρ of the underground geological body, use software for analytical processing, perform resistivity inversion, output geoelectric information, and use software to generate maps.

[0053] The specific steps in the above S2 include:

[0054] S2.1: Deploy acoustic wave collection devices at places where shallow gas may leak, collect acoustic wave signals through multi-channel acoustic sensors, and use the spectrum area within a wide frequency band as the detection indicator;

[0055] S2.2: After wavelet transform, the wavelet coefficients of each scale can be obtained from the observed signal, so as to distinguish the useful signal with higher wavelet coefficient and the noise signal with lower wavelet coefficient. Then, the appropriate threshold function is selected adaptively to perform threshold denoising. The threshold is adjusted repeatedly until all noise signals are removed to obtain the estimated values ​​of the wavelet coefficients of each scale of the useful signal. Finally, the signal is reconstructed through inverse transform to obtain the useful sound signal.

[0056] S2.3: Use the acoustic solver to analyze the acoustic signal waveform and calculate the leakage gas flow velocity characteristics.

[0057] The specific steps in the above S3 include:

[0058] S3.1: Use an acoustic sensor to monitor and capture the acoustic waveform of leaking gas;

[0059] S3.2: Use wavelet analysis or empirical mode decomposition (EMD) algorithms to reduce the noise generated by other fluctuations in the fluid;

[0060] S3.3: Analyze the denoised acoustic signal, use the acoustic-pressure coupling method or various pattern recognition algorithms to identify leaks, and use the characteristics of the Lighthill equation and the finite element method to calculate the shallow air pressure.

[0061] The specific steps in the above S4 include:

[0062] S4.1: Select the AM method or ABM method according to the actual situation of the shallow soil site, and deploy a parallel electrical test system to generate a stable current field in the underground space;

[0063] S4.2: Use the parallel electrical instrument to collect data multiple times, and select the data with better results for data processing;

[0064] S4.3: Perform resistivity inversion based on the collected data and conduct a comprehensive analysis of the shallow gas reserves in the underground space.

[0065] In the above S5, the data of the composition and isotope variation of the shallow gas are measured to analyze and identify the genesis components of the shallow gas.

[0066] In the above S6, a trapezoidal membership function is used to represent the fuzzy possibility.

[0067] The membership function F is expressed as: F = (F0, sl, ml, sr, mr), where FO is the center of the fuzzy number support set, sl and sr are the left and right support radii, and ml and mr are the left and right fuzzy regions. The fault degree of the fuzzy number F described by the trapezoidal membership function is expressed as:

[0068]

[0069] By establishing a suitable fault tree, the top event is determined to be shallow gas leakage that induces road collapse. Then, the direct factor that triggers the top event needs to be determined. Then, specific logic gates are given according to the logical relationship. The above steps are repeated until the bottom event. When establishing the fault tree of shallow gas leakage that induces road collapse, the following assumptions are made: only shallow gas leakage is considered as the cause of road collapse; the strata are evenly distributed and free of foreign matter, and the electrical, acoustic and other properties in the strata are similar. The influence of hardware facilities, operation and maintenance and other human and other factors on the properties of the road surface and roadbed are not considered. On this basis, the relevant disaster-causing factors and their connections are considered, and a fault tree of shallow gas leakage leading to road collapse is established for deductive analysis;

[0070] For the fault tree of road collapse caused by shallow gas leakage established above, considering the fault probability and the logical relationship between events, fuzzy numbers are used to describe the fault probability and fault degree, and the TS fuzzy model is used to describe the logical relationship between events. According to the fault tree of road collapse caused by shallow gas leakage, let M = (A1, A2, ..., A5), where A1, A2, ..., A5 represent the bottom events in the fault tree respectively, let M1, M2, ..., M4 correspond to the sudden change of shallow gas storage state, resulting in underground voids, shallow gas leakage, and road collapse, which are the outputs of TS fuzzy gates 1-4 respectively, assuming that the common fault levels of A1, A2, ..., A5 and M1, M2, M3 are (0, 0.5, 1), and the membership functions are sl = sr = O.1, ml = mr = 0.3, and the common fault level of M4 is (0, 1), and the membership functions are sl = sr = 0.25, ml = mr = 0.5. The fuzzy gate is obtained based on experience, and the detailed TS fuzzy gate rules for shallow damage under the action of expansive soil are formulated as follows;

[0071]

[0072]

[0073]

[0074] The sensitivity analysis of related disaster factors is shown by the importance of each bottom event in the fault tree. When the bottom events have different degrees of failure, the failure probability of the upper events of the system will change accordingly. Therefore, we measure the importance of the bottom events by the magnitude of the change in the failure probability of the top events, and analyze the sensitivity of related disaster factors.

[0075] According to the TS fuzzy fault tree and fault gate of road collapse caused by shallow gas leakage, the importance of each bottom event A1, A2, ..., A5 is analyzed. The failure probability of a certain bottom event is changed while other conditions remain unchanged, and the degree of change of the failure probability of the top event is calculated. Then, the sensitivity of each related disaster factor is calculated. Assuming that the failure state of other bottom events is 0.2, the failure state of the target bottom event changes step by step from 0 to 1 with a gradient of 0.1;

[0076] As the fault state of the bottom event increases, the fault probability of the top event increases, but different bottom events have different impacts on the top event, that is, the corresponding sensitivities to the disaster factors are different. The sensitivity analysis of each disaster factor is as follows:

[0077] The cause, composition, and empirical distribution of bottom event A5 have the greatest impact, followed by the burial depth, location, and distribution range of A1, and finally the leakage rate of A2, the gas pressure of A3, and the reserves of A4 have the same impact.

[0078] According to its importance, the following relationship can be obtained:

[0079] A5>A1>A2=A3=A4.

[0080] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein, and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A comprehensive identification and assessment method for the risk of road collapse induced by shallow biogas leakage, characterized by: The method comprises the following steps: S1, determine the depth, location and distribution range of shallow gas; S2, determine the shallow gas leakage rate; S3, determine the pressure of shallow gas; S4, determine the reserves of shallow gas; S5, determine the genetic composition of shallow gas; S6, introduces the TS fuzzy model, describes the failure probability of each component in the form of a TS fuzzy fault tree, considers the fault state more comprehensively, and decomposes and quantifies complex and uncertain problems by establishing TS fuzzy gates, thereby accurately identifying and evaluating the risk of road collapse.

2. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 1 is characterized by: The specific steps in the above S1 include: S1.1: According to the different field sources between the gas-rich area in the shallow soil layer and the power supply point in the surrounding medium, a parallel electrical method test system is deployed. The acquisition methods of the parallel electrical method test system are divided into AM method and ABM method; S1.2: Use a parallel electrical instrument to collect and measure the potential difference ΔU between the two points of the measuring electrodes M and N multiple times MN f, select the group with better data for analysis; S1.3: Based on the collected potential difference data, calculate the resistivity ρ of the underground geological body, use software for analytical processing, perform resistivity inversion, output geoelectric information, and use software to generate maps.

3. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 1 is characterized by: The specific steps in the above S2 include: S2.1: Deploy acoustic wave collection devices at places where shallow gas may leak, collect acoustic wave signals through multi-channel acoustic sensors, and use the spectrum area within a wide frequency band as a detection indicator; S2.2: After wavelet transform, the wavelet coefficients of each scale can be obtained from the observed signal, so as to distinguish the useful signal with higher wavelet coefficient and the noise signal with lower wavelet coefficient. Then, the appropriate threshold function is selected adaptively to perform threshold denoising. The threshold is adjusted repeatedly until all noise signals are removed to obtain the estimated values ​​of the wavelet coefficients of each scale of the useful signal. Finally, the signal is reconstructed through inverse transform to obtain the useful sound signal. S2.3: Use the acoustic solver to analyze the acoustic signal waveform and calculate the leakage gas flow velocity characteristics.

4. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 1 is characterized by: The specific steps in the above S3 include: S3.1: Use an acoustic sensor to monitor and capture the acoustic waveform of leaking gas; S3.2: Use wavelet analysis or empirical mode decomposition (EMD) algorithms to reduce the noise generated by other fluctuations in the fluid; S3.3: Analyze the denoised acoustic signal, use the acoustic-pressure coupling method or various pattern recognition algorithms to identify leaks, and use the characteristics of the Lighthill equation and the finite element method to calculate the shallow air pressure.

5. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 1, characterized in that: The specific steps in the above S4 include: S4.1: Select the AM method or ABM method according to the actual situation of the shallow soil site, and deploy a parallel electrical test system to generate a stable current field in the underground space; S4.2: Use the parallel electrical instrument to collect data multiple times, and select the data with better results for data processing; S4.3: Perform resistivity inversion based on the collected data and conduct a comprehensive analysis of the shallow gas reserves in the underground space.

6. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 1, characterized in that: In the above S5, the data of shallow gas composition and isotope variation are measured to analyze and identify the genesis components of shallow gas.

7. The method for comprehensive identification and assessment of road subsidence risk induced by shallow biogas leakage according to claim 1, characterized in that: In the above S6, a trapezoidal membership function is used to represent the fuzzy possibility.

8. The method for comprehensive identification and assessment of the risk of road collapse induced by shallow biogas leakage according to claim 7, characterized in that: The membership function F is expressed as: F = (F0, sl, ml, Sr, mr), where F0 is the center of the fuzzy number support set, Sl and Sr are the left and right support radii, ml and mr are the left and right fuzzy areas, and the fault degree of the fuzzy number F described by the trapezoidal membership function is expressed as:

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