A tunnel lining health monitoring system and method based on acoustic emission

Abstract

This invention discloses a tunnel lining health monitoring system and method based on acoustic emission, belonging to the field of tunnel engineering health monitoring technology. The acoustic emission-based tunnel lining health monitoring system includes a signal acquisition system, a signal processing system, and a safety risk early warning system. The signal acquisition system includes an acoustic emission receiver matrix arranged at certain intervals on the tunnel lining. The signal processing system includes a transmission device for receiving signal waveforms and spectral characteristics, and a signal processor for processing signals based on the waveforms and spectral characteristics. The safety risk early warning system includes a display device and an alarm. The display device locates the signal source points determined by the signal processing system and displays the acoustic emission signal source points in a simplified lining model. The alarm sounds after the cumulative number of acoustic emission events reaches a threshold. This invention aims to solve the problems of limited monitoring space, low monitoring sensitivity, and untimely feedback of monitoring results in current tunnel health monitoring.

Description

Technical Field

[0001] This invention relates to the field of tunnel engineering health monitoring technology, and in particular to a tunnel lining health monitoring system and method based on acoustic emission. Background Technology

[0002] With the continuous emergence of mountain tunnels, secondary linings are experiencing more and more defects when facing more complex and variable geological conditions, resulting in a significant increase in engineering economic costs and safety risks. In tunnel construction and operation, timely and comprehensive acquisition of the health status information of secondary linings through monitoring and measurement methods is a prerequisite for adopting reasonable engineering countermeasures.

[0003] Current tunnel lining monitoring technology mainly focuses on monitoring stress and strain. It infers the mechanical state of the entire lining from discrete and isolated measuring points. The monitoring range is limited, and it cannot detect subtle changes inside the lining concrete. It lacks sensitivity and cannot provide timely feedback on the mechanical state of the lining concrete.

[0004] Acoustic emission monitoring, a type of microseismic monitoring, monitors the release and propagation of elastic waves within a medium to calculate source parameters such as the spatial location, energy, magnitude, and stress drop of acoustic emission events. Based on the activity characteristics of acoustic emission events, it infers the mechanical state and failure characteristics of the medium, revealing major damage areas and potential instability zones, thereby controlling and preventing sudden failure of the medium. Acoustic emission exhibits good sensitivity to the failure process of a medium; the evolution of its parameters and signals can effectively reflect the degree of concrete damage, providing precursory information for concrete failure that precedes stress and strain monitoring, and possessing the ability to predict and identify concrete failure.

[0005] Applying acoustic emission monitoring to tunnel lining safety monitoring allows for the inference of the time, spatial location, and scale of microcracks based on the emitted transient stress waves when microcracks appear and develop within the concrete. This enables the identification and assessment of the health status and risk level of the lining concrete. This provides a novel monitoring approach for concrete linings, enabling comprehensive and real-time monitoring of their health status. Summary of the Invention

[0006] To address the current problems of limited monitoring space, low monitoring sensitivity, and untimely feedback of monitoring results in tunnel health monitoring, this invention proposes a tunnel lining health monitoring system and method based on acoustic emission.

[0007] The technical solution adopted in this invention is as follows:

[0008] An acoustic emission-based tunnel lining health monitoring system includes a signal acquisition system, a signal processing system, and a safety risk early warning system.

[0009] The signal acquisition system includes an acoustic emission receiver matrix arranged at certain intervals on the tunnel lining, and signal transmission equipment connected to the acoustic emission receivers;

[0010] The signal processing system is connected to the signal acquisition system and includes a transmission device that receives signal waveforms and spectral characteristics, as well as a signal processor that performs signal processing based on the signal waveforms and spectral characteristics.

[0011] The safety risk early warning system is connected to the signal processing system. It includes a display device and an alarm. The display device locates the signal source point determined by the signal processing system and displays the acoustic emission signal source point in the simplified lining model. The alarm sounds an alarm after the cumulative number of acoustic emission events reaches a threshold.

[0012] Furthermore, the signal processing steps of the signal processing system are as follows:

[0013] Step 1: Conduct acoustic emission experiments on concrete in the laboratory to obtain the waveform and spectral characteristics of acoustic emission during the generation and development of microcracks inside the concrete.

[0014] Step 2: Based on the acoustic emission waveform and spectral characteristics of microcrack generation and development in concrete material obtained in the laboratory, the acoustic emission signal received by the transmission equipment is filtered to remove background noise and obtain the initial arrival time of the acoustic emission signal of different acoustic emission receivers in the acoustic emission receiver matrix.

[0015] Step 3: Based on the initial arrival time of the signal, the location of the acoustic emission source is determined by combining the Multi-Template Fast Traveling Algorithm (MSFM) for calculating the initial arrival travel time of the stress wave with narrowband extension technology.

[0016] Furthermore, the steps to determine the location of the acoustic emission source are as follows:

[0017] Step 3.1: The three-dimensional lining is simplified to a cylindrical surface with no thickness, and the acoustic emission source points are considered only in the two propagation dimensions of circumferential and longitudinal directions.

[0018] Step 3.2: Use the two-dimensional stress wave path function equation to describe the stress wave travel time at different locations in the lining;

[0019] Step 3.3: Discretize the two-dimensional equations by windward difference to obtain the equations.

[0020] Step 3.4: Perform circumferential and longitudinal difference operator calculations;

[0021] Step 3.5: Calculate the preliminary travel time values ​​of the 8 points surrounding the node based on the travel time values ​​of the adjacent nodes;

[0022] Step 3.6: Using narrowband extension, the initial arrival travel time of the stress wave at the other discrete nodes is calculated when any discrete node in the region is taken as the source point of the stress wave.

[0023] Furthermore, the two-dimensional stress path function equation is:

[0024]

[0025] Right now

[0026] In the formula: T is the time delay, representing the propagation time of the sound wave from the transmitting point to the receiving point; l is the circumferential coordinate; z is the longitudinal coordinate; α(l,z) represents the propagation speed of the sound wave at a certain point; s(l,z) represents the phase velocity of the sound wave. It represents the magnitude of the gradient at time t at coordinates (l, z).

[0027] Furthermore, by discretizing the two-dimensional equations based on the windward difference, we can obtain the equations for the coordinates (l,z) and point number (i,j):

[0028]

[0029] In the formula, D represents the magnitude of the time gradient at grid point (i,j); n -l t i,j D n +l t i,j To simplify the backward and forward nth-order difference operators for discrete points (i,j) in the plane; D n -z t i,j D n +z t i,j This represents the effect of the nth-order difference operator along the longitudinal direction z at point (i,j) on time t; the max() operator is calculated based on the known and magnitude of the travel time values ​​of the points surrounding the calculated point;

[0030] The difference operator uses a first-order difference operator;

[0031] The circumferential difference operator is calculated as follows:

[0032]

[0033] The longitudinal difference operator is calculated as follows:

[0034]

[0035] In the formula, D n +l t, D n -l t represents the first-order difference operator forward and backward along the l direction; ti+1 This represents the time value at grid point (i+1,j); t i This represents the time value at grid point (i,j); Δl represents the grid spacing in the l direction; This represents the first-order difference operator forward and backward along the l direction; Δz represents the grid spacing in the z direction; t j+1 This represents the time value at grid point (i,j+1); t j This represents the time value at grid point (i,j); Δz represents the grid spacing in the z-direction.

[0036] The specific operation rules for the first order are as follows:

[0037]

[0038] In the formula, D1 -l t i,j D1 +l t i,j Let t represent the backward difference operator along the l direction from point (i-1,j) to point (i,j), and the forward difference operator from (i,j) to point (i+1,j); i,j This represents the travel time value at grid point (i,j); t i-1,j This represents the travel time value at grid point (i-1,j); t i+1,j This represents the travel time value at grid point (i+1,j).

[0039] Furthermore, by rotating the Cartesian coordinate system, the diagonal direction is incorporated into the propagation path calculation, which is the Multi-Template Fast Marching (MSFM) algorithm.

[0040] The initial travel time values ​​of the eight points surrounding node (i,j) are obtained based on the slowness calculation method, namely: the initial travel time values ​​of the four directly adjacent points and the four diagonally adjacent points;

[0041] The calculation formula is as follows:

[0042]

[0043] In the formula, t i,j This represents the travel time value at grid point (i,j), i.e., the initial travel time at that point; t i,j±1 This represents the travel time at grid point (i,j+1) or (i,j-1), where i is the adjacent point above or below; t i±1,j t represents the time taken at point (i+1,j) or (i-1,j), where (i+1,j) represents the time taken by the left and right adjacent points, respectively; i+1,j±1 This represents the time taken at point (i+1,j+1) or (i+1,j-1), where (i+1,j-1) represents the diagonally adjacent point to the upper right and lower right, respectively; t i-1,j±1This represents the time travel value at point (i-1, j+1) or (i-1, j-1), representing the diagonally adjacent points to the upper left and lower left, respectively; s i,j This represents the slowness at grid point (i,j); s i±1,j Indicates the slowness at adjacent points in the horizontal and vertical directions; s i±1,j±1 The value represents the slowness at diagonally adjacent points; h represents the step size used in the calculation, which is usually the spatial resolution of the grid and refers to the distance between two adjacent nodes.

[0044] Furthermore, the narrowband extension technique categorizes the nodes within the region that require time-travel calculations into the following three types:

[0045] Acceptance point: The point where the initial arrival and departure times have been confirmed;

[0046] Narrowband point: A point that is in direct contact with the receiver and whose time travel has already been calculated, but whose time travel will be updated in subsequent calculations with a certain probability;

[0047] The point of distance is the point where the travel time has not been calculated at all.

[0048] All the narrow band points together constitute the narrow band.

[0049] Furthermore, the signal processing system, based on the MSFM algorithm combined with narrowband extension, calculates the initial arrival travel time of each discrete node in the tunnel lining space when the position of each acoustic emission receiver in the acoustic emission receiver matrix is ​​taken as the stress wave source point.

[0050] The signal processing system, using the stress wave interchange theorem, obtains the time required for propagation from each discrete node to each acoustic emission receiver. Each acoustic emission receiver forms a travel time matrix T of size m×n. m×n ;

[0051] Element t in the matrix i,j Representing discrete node P i,j When the source is a receiver, the time required for the sound to propagate to the receiver is given. A total of u×v matrices can be formed, where u and v represent the number of receivers arranged circumferentially and longitudinally in the receiver matrix, respectively.

[0052] When microcracks appear and develop in concrete, the acoustic emission signals generated are received by acoustic emission receivers. First, based on the initial arrival time of the microseismic signals from each receiver, the two columns with the smallest initial arrival time in the circumferential direction and the two rows with the smallest initial arrival time in the longitudinal direction are selected, for a total of 4 acoustic emission receivers, to calculate the location of the acoustic emission signal source.

[0053] The calculation method is as follows:

[0054] First, the four acoustic transmitters and receivers are paired up to obtain a total of A combination;

[0055] Calculate the difference in first arrival time based on the first arrival time measured by the two acoustic transmitters and receivers in each combination;

[0056] Based on the duration matrix of the acoustic emission receiver, the set of nodes that reach the measured first arrival time difference for each pair of combinations is identified, resulting in a total of 6 node sets;

[0057] Find the intersection of the 6 node sets, which is considered as the source of the acoustic emission signal.

[0058] Furthermore, the spacing of the acoustic emission receiver matrix of the signal acquisition system should be precisely calculated to ensure that the positioning error of the acoustic emission signal is within the allowable range;

[0059] The specific calculation is performed using the following formula:

[0060] ε<ε lim

[0061] In the formula, ε represents the total acoustic emission positioning error; ε lim The determination will be made based on the specific conditions of the tunnel section being inspected and in accordance with the relevant standards.

[0062] Acoustic emission signal localization error includes model simplification error and travel time algorithm error; among which, the travel time algorithm error is the acoustic emission localization error caused by using the MSFM algorithm to calculate the initial arrival travel time of each point in the region and replacing the actual propagation path of the stress wave with discrete line segments.

[0063] The method for calculating acoustic emission positioning error is as follows:

[0064] ε = ε1 + ε2

[0065] In the formula, ε is the acoustic emission localization error; ε1 is the acoustic emission localization model simplification error; and ε2 is the acoustic emission localization algorithm error.

[0066] ε1=|l max -l' max |

[0067] In the formula, l max Within each simplified unit, the maximum circumferential distance between two points; l' max The actual circumferential distance corresponding to the above two locations, which results in the largest propagation distance error;

[0068] ε2=φl max

[0069] In the formula, φ represents the error rate of the positioning algorithm, which is related to the size of the discrete grid and the propagation distance; l max This represents the maximum circumferential distance between two points within each simplified unit.

[0070] Furthermore, the calculation process for the threshold is as follows:

[0071] The damage factor of concrete is proportional to the cumulative number of acoustic emission events, expressed as:

[0072] D = kN

[0073] In the formula, D is the concrete material damage factor; k is the proportionality coefficient determined based on indoor material tests; and N is the cumulative number of acoustic emission events.

[0074] D = 1 - E / E *

[0075] In the formula, E is the elastic modulus of the material under damaged conditions; E * This is the initial elastic modulus of the material;

[0076] Based on the load magnitude, distribution, and cross-sectional dimensions of the lining structure, the minimum elastic modulus required for the concrete material of the lining structure is determined, and then the threshold for the maximum number of acoustic emission events to ensure structural safety is calculated.

[0077] The beneficial effects of this invention are:

[0078] 1. The lining monitoring range is complete and the results are reliable.

[0079] Unlike traditional stress-strain monitoring that infers the stress state of the lining by measuring points on the inner surface of the lining, the acoustic emitter-receiver matrix set in this invention can receive acoustic emission signals from the entire lining, monitor the closure, generation and development of microcracks inside it, and directly monitor the state of the entire lining. The completeness and reliability of the monitoring are greatly improved compared with traditional monitoring methods.

[0080] 2. Improve the sensitivity of monitoring response

[0081] Subtle changes in the stress state of concrete during loading have little impact on the stress-strain state of the inner surface of the lining, making them difficult to detect with traditional monitoring methods. This invention can monitor the acoustic emission signals generated by the concrete material when the stress state changes, and incorporate these signals into a safety risk early warning system.

[0082] 3. The positioning accuracy is adjustable, meeting the monitoring accuracy requirements with minimal material cost.

[0083] Based on the engineering measures to be adopted for subsequent reinforcement and maintenance, the required positioning accuracy for potential risk points can be determined. By adjusting the receiver spacing in the receiver matrix and the stress wave first arrival travel time algorithm, the required monitoring accuracy can be achieved with fewer monitoring devices.

[0084] 4. Achieve real-time monitoring and early warning

[0085] Dynamic monitoring: The system can record acoustic emission events of concrete in real time. Once the corresponding threshold is reached, an early warning can be issued immediately to remind relevant personnel of potential safety hazards.

[0086] Real-time feedback: Through real-time analysis of acoustic emission signals, the monitoring system can quickly identify the deterioration of the lining structure, thus facilitating timely repair measures.

[0087] 5. Structural health diagnosis

[0088] Early identification: Acoustic emission technology can detect the deterioration of the lining before macroscopic cracks appear, enabling tunnel maintenance and management to shift from a passive to a proactive approach.

[0089] Traceability: The acoustic emission data recorded by the system can serve as a basis for subsequent analysis, helping engineers assess the health status and related properties of concrete materials.

[0090] 6. Optimize maintenance strategies

[0091] Information-guided decision-making: By analyzing acoustic emission data, engineers can make more reasonable assessments of the lining health, thereby optimizing maintenance and reinforcement strategies, improving structural safety, and reducing maintenance costs.

[0092] Material performance monitoring: Combining the requirement that concrete must maintain its modulus of elasticity after deterioration, the system can ensure that the performance of materials during use will not fall below the predetermined standard, thereby enhancing the safety of the structure.

[0093] 7. Reduce security risks

[0094] Preventive technology application: Acoustic emission monitoring systems can take preventive measures before problems occur, reducing the safety risks caused by tunnel collapses or other accidents, and ensuring the safety of engineering personnel and passing vehicles.

[0095] Enhanced construction management: By integrating monitoring data in real time, managers can better understand the construction status, formulate targeted measures, and improve construction safety and efficiency.

[0096] In summary, the acoustic emission-based tunnel lining health monitoring system not only improves monitoring accuracy and real-time early warning capabilities, but also provides strong support for health assessment and maintenance decisions of concrete structures, making significant contributions to ensuring the safety and durability of tunnels. Attached Figure Description

[0097] Figure 1 This is a layout diagram of the acoustic emission receiver matrix of the signal acquisition system of the present invention;

[0098] Figure 2 This is a simplified diagram of the three-dimensional lining process of the present invention;

[0099] Figure 3 This is a flowchart of the narrowband extension process of the present invention;

[0100] Figure 4 This is a diagram of the lining structure in a verification example of the present invention;

[0101] Figure 5 This is a simplified diagram of the three-dimensional lining in a verification example of the present invention;

[0102] In the diagram: 1 - Acoustic transmitter and receiver matrix. Detailed Implementation

[0103] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0104] Example 1

[0105] To address the current problems of limited monitoring space, low monitoring sensitivity, and untimely feedback of monitoring results in tunnel health monitoring, this invention proposes a tunnel lining health monitoring system based on acoustic emission. This system uses an acoustic emission receiver matrix to receive transient elastic waves emitted when internal microcracks appear and expand during concrete loading. Based on these waves, the system can infer the appearance and expansion of internal microcracks in the concrete, further deduce the health status of the concrete lining, and identify lining risk points.

[0106] The acoustic emission-based tunnel lining health monitoring system includes a signal acquisition system, a signal processing system, and a safety risk early warning system. The specific composition and function of each system are as follows:

[0107] like Figure 1 As shown, the signal acquisition system includes an acoustic emission receiver matrix 1 arranged at certain intervals on the tunnel lining, and a signal transmission device connected to the acoustic emission receivers. The ring and longitudinal spacing of the acoustic emission receiver matrix is ​​controlled according to the error calculation method and reasonably arranged according to the internal force distribution of the lining. The acoustic emission receiver matrix is ​​mainly used to receive acoustic emission signals, record signal waveforms and spectral characteristics, and transmit them to the signal processing system by the transmission device.

[0108] The signal processing system is connected to the signal acquisition system and includes a transmission device for receiving signal waveforms and spectral characteristics, as well as a signal processor for processing the signal based on the waveforms and spectral characteristics. The signal processor processes the signal based on the waveforms and spectral characteristics to obtain the initial arrival time of each signal at different receivers in the receiver matrix. Furthermore, by combining the Multi-Template Fast Traveling (MSFM) algorithm with narrowband spread, the source point of the acoustic emission signal is determined.

[0109] The safety risk early warning system is connected to the signal processing system. It includes a display device and an alarm. The display device locates the acoustic emission signal source point in the simplified lining model based on the signal source point determined by the signal processing system. The signal processor determines the alarm threshold for the cumulative number of acoustic emission events based on the relationship between the cumulative number of acoustic emission events and the damage factor of concrete materials. When the cumulative number of acoustic emission events in the same discrete grid reaches the threshold, the signal processor, in conjunction with the alarm, issues an alarm.

[0110] Furthermore, the signal acquisition system, signal processing system, and safety risk early warning system of the acoustic emission-based tunnel lining health monitoring system are described in detail below:

[0111] The specific process of signal processing in a signal processing system is as follows:

[0112] Step 1: Conduct acoustic emission experiments on concrete in the laboratory to obtain the waveform and spectral characteristics of acoustic emission during the generation and development of microcracks inside the concrete.

[0113] Step 2: Based on the acoustic emission waveforms and spectral characteristics of microcrack generation and development in concrete materials obtained in the laboratory, the acoustic emission signals received by the transmission equipment are filtered to remove background noise; during the construction phase, construction noise is mainly filtered, and during the operation phase, passing vehicle noise is mainly filtered. After filtering the background noise, the initial arrival times of the acoustic emission signals from different acoustic emission receivers in the acoustic emission receiver matrix are obtained.

[0114] Step 3: Based on the initial arrival time of the signal, the location of the acoustic emission source is determined by combining the Multi-Template Fast Traveling Algorithm (MSFM) and narrowband extension to calculate the initial arrival travel time of the stress wave.

[0115] The steps to determine the location of the acoustic emission source are as follows:

[0116] Step 3.1, the purpose of lining health monitoring is to obtain the longitudinal and circumferential locations of potential damage points within the lining. Locating these risk points in the thickness direction is less significant for subsequent engineering treatment. Furthermore, considering that the lining thickness is negligible compared to its longitudinal and circumferential lengths, therefore, if... Figure 2 As shown, in this embodiment, the three-dimensional lining is simplified to a cylindrical surface with no thickness, and the acoustic emission source point only considers the two propagation dimensions of circumferential and longitudinal directions.

[0117] Step 3.2: Use the two-dimensional stress wave path function equation to describe the stress wave travel time at different locations in the lining;

[0118] The two-dimensional stress path function equation is:

[0119]

[0120] In the formula: T is the time delay, representing the propagation time of the sound wave from the transmitting point to the receiving point; l is the circumferential coordinate; z is the longitudinal coordinate; α(l,z) represents the propagation speed of the sound wave at a certain point; s(l,z) represents the phase velocity of the sound wave. It represents the magnitude of the gradient at time t at coordinates (l, z).

[0121] Step 3.3: Discretize the two-dimensional equations by windward difference to obtain the equations.

[0122] By discretizing the two-dimensional equations based on the windward difference, we can obtain the equations for the coordinates (l,z) and point number (i,j):

[0123]

[0124] In the formula, D represents the magnitude of the time gradient at grid point (i,j); n -l t i,j D n +l t i,j To simplify the backward and forward nth-order difference operators for discrete points (i,j) in the plane; D n -z t i,j D n +z t i,j This represents the effect of the nth-order difference operator along the longitudinal direction z at point (i,j) on time t; the max() operator is calculated based on the known and magnitude of the travel time values ​​of the points surrounding the calculated point.

[0125] Step 3.4: Perform circumferential and longitudinal difference operator calculations;

[0126] The difference operator uses a first-order difference operator;

[0127] The circumferential difference operator is calculated as follows:

[0128]

[0129] The longitudinal difference operator is calculated as follows:

[0130]

[0131] In the formula, D n +l t, D n -l t represents the first-order difference operator forward and backward along the l direction; t i+1 This represents the time value at grid point (i+1,j); t i This represents the time value at grid point (i,j); Δl represents the grid spacing in the l direction; This represents the first-order difference operator forward and backward along the l direction; Δz represents the grid spacing in the z direction; t j+1 This represents the time value at grid point (i,j+1); t j This represents the time value at grid point (i,j); Δz represents the grid spacing in the z-direction.

[0132] The specific operation rules for the first order are as follows:

[0133]

[0134] In the formula, D1 -l t i,j D1 +l t i,j Let t represent the backward difference operator along the l direction from point (i-1,j) to point (i,j), and the forward difference operator from (i,j) to point (i+1,j); i,j This represents the travel time value at grid point (i,j); t i-1,j This represents the travel time value at grid point (i-1,j); t i+1,j This represents the travel time value at grid point (i+1,j).

[0135] Step 3.5: Calculate the preliminary travel time values ​​of the 8 points around the node based on the travel time values ​​of the adjacent nodes; in this embodiment, the diagonal direction is included in the propagation path calculation by rotating the rectangular coordinate system, i.e., the Multi-Template Fast Traveling Algorithm (MSFM);

[0136] The initial travel time values ​​of the eight points surrounding node (i,j) are obtained based on the slowness calculation method, namely: the initial travel time values ​​of the four directly adjacent points and the four diagonally adjacent points;

[0137] The calculation formula is as follows:

[0138]

[0139] In the formula, t i,j This represents the travel time value at grid point (i,j), i.e., the initial travel time at that point; t i,j±1This represents the travel time at grid point (i,j+1) or (i,j-1), where i is the adjacent point above or below; t i±1,j t represents the time taken at point (i+1,j) or (i-1,j), where (i+1,j) represents the time taken by the left and right adjacent points, respectively; i+1,j±1 This represents the time taken at point (i+1,j+1) or (i+1,j-1), where (i+1,j-1) represents the diagonally adjacent point to the upper right and lower right, respectively; t i-1,j±1 This represents the time travel value at point (i-1, j+1) or (i-1, j-1), representing the diagonally adjacent points to the upper left and lower left, respectively; s i,j This represents the slowness at grid point (i,j); s i±1,j Indicates the slowness at adjacent points in the horizontal and vertical directions; s i±1,j±1 The value represents the slowness at diagonally adjacent points; h represents the step size used in the calculation, which is usually the spatial resolution of the grid and refers to the distance between two adjacent nodes.

[0140] Step 3.6: Using narrowband extension, the initial arrival travel time of the stress wave at the other discrete nodes is calculated when any discrete node in the region is taken as the source point of the stress wave.

[0141] Narrowband extension technology divides the nodes within the region that need to have their travel times calculated into the following three types of nodes:

[0142] Acceptance point: The point where the initial arrival and departure times have been confirmed;

[0143] Narrowband point: A point that is in direct contact with the receiver and whose time travel has already been calculated, but whose time travel will be updated in subsequent calculations with a certain probability;

[0144] The point of distance is the point where the travel time has not been calculated at all.

[0145] Narrowband extension process as follows Figure 3 As shown, all the narrowband points constitute the narrowband.

[0146] The signal processing system, based on the MSFM algorithm combined with narrowband extension, calculates the initial arrival travel time of each discrete node in the tunnel lining space when the position of each acoustic emitter in the acoustic emitter-receiver matrix is ​​taken as the stress wave source point.

[0147] The signal processing system, using the stress wave interchange theorem, obtains the time required for propagation from each discrete node to each acoustic emission receiver. Each acoustic emission receiver forms a travel time matrix T of size m×n. m×n ;

[0148] Element t in the matrix i,j Representing discrete node P i,j When the source is a receiver, the time required for the sound to propagate to the receiver is given. A total of u×v matrices can be formed, where u and v represent the number of receivers arranged circumferentially and longitudinally in the receiver matrix, respectively.

[0149] When microcracks appear and develop in concrete, the acoustic emission signals generated are received by acoustic emission receivers. First, based on the initial arrival time of the microseismic signals from each receiver, the two columns with the smallest initial arrival time in the circumferential direction and the two rows with the smallest initial arrival time in the longitudinal direction are selected, for a total of 4 acoustic emission receivers, to calculate the location of the acoustic emission signal source.

[0150] The calculation method is as follows:

[0151] First, the four acoustic transmitters and receivers are paired up to obtain a total of A combination;

[0152] Calculate the difference in first arrival time based on the first arrival time measured by the two acoustic transmitters and receivers in each combination;

[0153] Based on the duration matrix of the acoustic emission receiver, the set of nodes that reach the measured first arrival time difference for each pair of combinations is identified, resulting in a total of 6 node sets;

[0154] Find the intersection of the 6 node sets, which is considered as the source of the acoustic emission signal.

[0155] Deployment of the signal acquisition system:

[0156] The signal acquisition system is deployed based on the signal processing of the signal processing system.

[0157] First, based on the specific circumstances of the tunnel project, including the stress characteristics of the lining and the reinforcement measures to be adopted later, the required positioning accuracy for monitoring should be determined, and the size of the discrete grid should be preliminarily determined according to the required positioning accuracy. Taking a positioning accuracy requirement of 1m as an example, to ensure the positioning accuracy is within 1m, the discrete grid size should not exceed 1m when calculating its travel time matrix. Based on the preliminarily determined discrete grid size, such as... Figure 2 As shown, the discrete simplified model.

[0158] To facilitate the calculation of travel time from each node to the receiver, the receiver should be placed on the nodes of the discrete grid. Based on the stress characteristics of the lining structure, the receiver should be placed in the lining parts with larger internal forces as much as possible to improve the positioning accuracy of the acoustic emission signal.

[0159] The spacing between receivers in the acoustic emission receiver matrix directly affects the positioning accuracy of acoustic emission events. The spacing of the receiver matrix should ensure that the positioning error meets the error requirements. After the acoustic emission receiver matrix, which is arranged according to the stress characteristics of the lining, is completed, its positioning accuracy should be verified according to the following formula:

[0160] ε<ε lim

[0161] In the formula, ε represents the total acoustic emission positioning error; ε limThe measurement range is determined based on the specific conditions of the tunnel section being inspected and in accordance with relevant standards, and is generally between 0.25m and 3m.

[0162] There are two main sources of acoustic emission signal positioning error:

[0163] ① Model simplification error: When simplifying the lining model, the mid-surface of the lining is used to replace the three-dimensional structure of the lining, and the actual three-dimensional propagation path of the acoustic emission signal is replaced by a two-dimensional curve in the surface, resulting in positioning error.

[0164] ② Travel time algorithm error: The MSFM algorithm is used to calculate the initial arrival travel time of each point in the area, and the positioning error caused by replacing the actual propagation path of the stress wave with discrete line segments.

[0165] The method for calculating acoustic emission positioning error is as follows:

[0166] ε = ε1 + ε2

[0167] In the formula, ε is the acoustic emission localization error; ε1 is the acoustic emission localization model simplification error; and ε2 is the acoustic emission localization algorithm error.

[0168] Based on the sources of ε1 and ε2, the formula for calculating ε1 is given as follows:

[0169] ε1=|l max -l' max |

[0170] In the formula, l max Within each simplified unit, the maximum circumferential distance between two points; l' max This is the actual circumferential distance that corresponds to the positions of the two points mentioned above, resulting in the largest error in the propagation distance.

[0171] The formula for calculating ε² is given below:

[0172] ε2=φl max

[0173] In the formula, φ represents the error rate of the positioning algorithm, which is related to the size of the discrete grid and the propagation distance; l max This represents the maximum circumferential distance between two points within each simplified unit.

[0174] Alarms from the security risk warning system:

[0175] The signal processor determines the alarm threshold for the cumulative number of acoustic emission events based on the relationship between the cumulative number of acoustic emission events and the damage factor of concrete materials. When the cumulative number of acoustic emission events in the same discrete grid reaches the threshold, the signal processor, in conjunction with the alarm, issues an alarm.

[0176] Therefore, the threshold setting needs to be calculated, and the threshold calculation process is as follows:

[0177] The damage factor of concrete is proportional to the cumulative number of acoustic emission events, expressed as:

[0178] D = kN

[0179] In the formula, D is the concrete material damage factor; k is the proportionality coefficient determined based on indoor material tests; and N is the cumulative number of acoustic emission events.

[0180] D = 1 - E / E *

[0181] In the formula, E is the elastic modulus of the material under damaged conditions; E * This is the initial elastic modulus of the material;

[0182] Therefore, we get:

[0183] 1-E / E * =kN

[0184] Based on the load magnitude, distribution, and cross-sectional dimensions of the lining structure, the minimum elastic modulus required for the concrete material of the lining structure is determined, and then the threshold for the maximum number of acoustic emission events to ensure structural safety is calculated. Once the number of acoustic emissions located within the same grid reaches the threshold, the signal processor, in conjunction with the alarm, issues an alarm.

[0185] Example 2

[0186] Based on the acoustic emission-based tunnel lining health monitoring system provided in Embodiment 1, this embodiment also provides an acoustic emission-based tunnel lining health monitoring method, which includes the following steps:

[0187] Step 1, Design and Layout:

[0188] Determine the tunnel lining structure: Define the lining geometry inside the tunnel, identify key areas (such as the arch crown, arch shoulder, and arch foot), and determine the lining thickness and material properties.

[0189] Simplified model: The lining structure is simplified into a two-dimensional curved surface to facilitate subsequent numerical calculations and analysis.

[0190] Discretized mesh: According to design requirements, the two-dimensional surface is discretized according to a mesh size of 1m to facilitate the processing and analysis of acoustic emission signals.

[0191] Step 2, Receiver Setup:

[0192] Risk point identification: Based on the stress characteristics, a total of five acoustic emission receivers were set at the arch crown, arch shoulder and arch foot, these locations are potential risk points.

[0193] Acoustic emission receiver arrangement: After setting up the acoustic emission receivers in a circumferential manner according to the error calculation method to form an acoustic emission receiver matrix, the longitudinal spacing of the acoustic emission receiver matrix is ​​controlled according to the error calculation method; the acoustic emission receiver matrix is ​​arranged to ensure coverage of the entire tunnel.

[0194] Step 3, Signal Acquisition and Processing:

[0195] Acoustic emission signal acquisition: The signal processor collects acoustic emission events through transmission equipment and analyzes them using location and time data.

[0196] Travel time calculation: The signal processor uses the second-order MSFM algorithm to calculate the first arrival travel time of the signal at each node. Based on the known acoustic emission signal propagation speed of 4000m / s and distance, the propagation time and error of the signal are evaluated.

[0197] Step 4, Positioning accuracy analysis:

[0198] Error calculation: Calculate the positioning error according to the formula.

[0199] Verification error requirements: Check whether the overall error meets the following requirements.

[0200] Step 5, Concrete deterioration monitoring:

[0201] Concrete material properties: Determine the elastic modulus of concrete to ensure that it does not fall below 75% of the initial modulus after deterioration.

[0202] Acoustic emission event trigger alarm: Calculate the number N of acoustic emission events within the same discrete grid using data obtained from acoustic emission monitoring. If the number reaches N, issue an alarm and indicate the location of the risk point.

[0203] Step 6, Data Analysis and Reporting:

[0204] Risk point identification: Analyze the collected acoustic emission data and locate specific risk points to provide project managers with information for taking necessary maintenance or reinforcement measures.

[0205] Regular monitoring and assessment: Develop a regular monitoring plan to conduct long-term health monitoring and assessment of the lining structure in order to respond promptly to potential risks.

[0206] Furthermore, to verify the feasibility of the acoustic emission-based tunnel lining health monitoring system provided in Example 1 and the acoustic emission-based tunnel lining health monitoring method provided in Example 2, this example provides the following practical engineering verification:

[0207] Taking a tunnel in Yunnan Province as an example, its lining structure is as follows: Figure 4 As shown, the inner contour is a single-centered circle with a radius of 550cm and a lining thickness of 75cm.

[0208] Based on the specific engineering conditions of the tunnel, the accuracy of locating risk points that may cause cracks needs to be controlled within 1 meter. The three-dimensional lining structure should be designed as follows: Figure 5 The method shown is simplified to a two-dimensional curved surface structure, and the two-dimensional curved surface is discretized according to a grid size of 1m.

[0209] Based on the stress characteristics of the lining, the internal forces at the arch crown, arch shoulder, and arch foot are relatively large, which are the major risk points. Accordingly, five acoustic emission receivers are deployed in the circumferential direction at the arch crown, arch shoulder, and arch foot, forming an acoustic emission receiver matrix 1.

[0210] Based on the reinforcement measures to be adopted later, the acoustic emission signal positioning error ε should meet the following requirements:

[0211] ε<ε lim =1m

[0212] Based on the simplified discrete model and the preliminary circumferential arrangement of the acoustic emission receivers, the spacing between two adjacent circumferential acoustic emission receivers should satisfy the following:

[0213] l max =7m

[0214] l′ max =6.554m

[0215] ε1=|l max -l′ max |=0.446m

[0216] The second-order MSFM algorithm was used to calculate the initial arrival travel time of the signal at each node. Previous studies have shown that when the acoustic emission signal propagation speed is 4000 m / s, the propagation speed of the stress wave in concrete is 3000 to 5000 m / s, and the mesh size is 1 m, the error rate of the second-order MSFM algorithm in calculating the travel time is 0.14%.

[0217] but

[0218]

[0219] d represents the longitudinal spacing of the acoustic emission receiver matrix. When d = 100m, ε can be calculated to be 0.586m < ε. lim =1m, which meets the error requirement.

[0220] To ensure that the acoustic emission signals meet the positioning accuracy requirements in the later stage, after the acoustic emission receivers are arranged circumferentially as described above, the acoustic emission receiver matrix is ​​arranged longitudinally at equal intervals of 100m.

[0221] Based on the specific circumstances of this project, the engineering requirements stipulate that the elastic modulus of concrete materials after deterioration must not be lower than 75% of the initial elastic modulus, i.e., E ≥ 0.75E. * According to indoor experiments, the concrete material k = 1.84 × 10⁻⁴. Substituting this into the following formula:

[0222] 1-E / E * =kN

[0223] We can obtain N = 1358, which means that after the number of acoustic emission events located in the same discrete grid reaches 1358, an alarm is issued and the corresponding risk point location is given.

[0224] Through practical engineering verification, the acoustic emission-based tunnel lining health monitoring system and method can receive transient elastic waves emitted when internal microcracks appear and expand during concrete loading through an acoustic emission receiver matrix. Based on this, the occurrence and expansion of internal microcracks in the concrete can be inferred, further indicating the health status of the concrete lining and identifying lining risk points.

[0225] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A tunnel lining health monitoring system based on acoustic emission, characterized in that: The acoustic emission-based tunnel lining health monitoring system includes a signal acquisition system, a signal processing system, and a safety risk early warning system. The signal acquisition system includes an acoustic emission receiver matrix arranged at certain intervals on the tunnel lining, and signal transmission equipment connected to the acoustic emission receivers; The signal processing system is connected to the signal acquisition system and includes a transmission device that receives signal waveforms and spectral characteristics, as well as a signal processor that performs signal processing based on the signal waveforms and spectral characteristics. The safety risk early warning system is connected to the signal processing system. It includes a display device and an alarm. The display device locates the signal source point determined by the signal processing system and displays the acoustic emission signal source point in the simplified lining model. The alarm sounds an alarm after the cumulative number of acoustic emission events reaches a threshold. The signal processing steps of the signal processing system are as follows: Step 1: Conduct acoustic emission experiments on concrete in the laboratory to obtain the waveform and spectral characteristics of acoustic emission during the generation and development of microcracks inside the concrete. Step 2: Based on the acoustic emission waveform and spectral characteristics of microcrack generation and development in concrete material obtained in the laboratory, the acoustic emission signal received by the transmission equipment is filtered to remove background noise and obtain the initial arrival time of the acoustic emission signal of different acoustic emission receivers in the acoustic emission receiver matrix. Step 3: Based on the initial arrival time of the signal, and combined with the Multi-Template Fast Traveling Algorithm (MSFM) and narrowband extension for calculating the initial arrival travel time of the stress wave, determine the location of the acoustic emission source point; The steps to determine the location of the acoustic emission source are as follows: Step 3.1: The three-dimensional lining is simplified to a cylindrical surface with no thickness, and the acoustic emission source points are considered only in the two propagation dimensions of circumferential and longitudinal directions. Step 3.2: Use the two-dimensional stress wave path function equation to describe the stress wave travel time at different locations in the lining; Step 3.3: Discretize the two-dimensional equations by windward difference to obtain the equations. Step 3.4: Perform circumferential and longitudinal difference operator calculations; Step 3.5: Calculate the preliminary travel time values ​​of the 8 points surrounding the node based on the travel time values ​​of the adjacent nodes; Step 3.6: Using narrowband extension, the initial arrival travel time of the stress wave at the other discrete nodes is calculated when any discrete node in the region is taken as the source point of the stress wave.

2. The tunnel lining health monitoring system based on acoustic emission according to claim 1, characterized in that: The two-dimensional stress path function equation is: ； Right now ; In the formula: The time delay represents the propagation time of a sound wave from the transmitting point to the receiving point; Circular coordinates; The vertical axis; This indicates the speed at which a sound wave travels at a given point. Represents the phase velocity of sound waves; Representing time t in coordinates The magnitude of the gradient at that point.

3. The tunnel lining health monitoring system based on acoustic emission according to claim 2, characterized in that: The coordinates can be obtained by discretizing the two-dimensional equations by windward difference. The location number is The equation of the function at the location: ； In the formula, Indicates at grid points The magnitude of the time gradient at that point; , To simplify discrete points in the plane The backward and forward n-order difference operators; , Indicates at point Along the longitudinal direction The effect of the backward and forward nth-order difference operators on time t; The operator is determined based on the known information and magnitude of the travel time values ​​of the points surrounding the point being calculated; The difference operator uses a first-order difference operator; The circumferential difference operator is calculated as follows: ； The longitudinal difference operator is calculated as follows: ； In the formula, , Indicates along First-order difference operators that move forward and backward; Indicates at grid points The time value at that location; Indicates at grid points The time value at that location; express Grid spacing in the direction; , Indicates along First-order difference operators that move forward and backward; express Grid spacing in the direction; Indicates at grid points The time value at that location; Indicates at grid points The time value at that location; express Grid spacing in the direction; The specific operation rules for the first order are as follows: ； In the formula, , Indicates along Direction from point Time The backward difference operator, and from Time The forward difference operator; Indicates at grid points The travel time value at that location; Indicates at grid points The travel time value at that location; Indicates at grid points The time value at that location.

4. The tunnel lining health monitoring system based on acoustic emission according to claim 3, characterized in that: By rotating the Cartesian coordinate system, the diagonal direction is included in the propagation path calculation, which is the Multi-Template Fast Traveling Algorithm (MSFM). Nodes are obtained based on the slowness calculation method. Preliminary travel times for the surrounding 8 points, namely: the preliminary travel times for the four directly adjacent points and the four diagonally adjacent points; The calculation formula is as follows: ； In the formula, Indicates at grid points The travel time value at that point, i.e., the initial travel time at that point; Indicates at grid points or The travel time values ​​at each point represent the points directly above and below them; Indicates at point or The travel time values ​​at each point represent the left and right adjacent points, respectively; Indicates at point or The travel time values ​​at each point represent the diagonally adjacent points to the upper right and lower right, respectively. Indicates at point or The travel time values ​​at each point represent the diagonally adjacent points at the top left and bottom left, respectively. Indicates at grid points The slowness at that point; Indicates the slowness at adjacent points in the horizontal and vertical directions; Indicates the slowness at diagonally adjacent points; This indicates the step size used in the calculation, which is usually the spatial resolution of the grid and refers to the distance between two adjacent nodes.

5. The tunnel lining health monitoring system based on acoustic emission according to claim 1, characterized in that: Narrowband extension technology divides the nodes within the region that need to have their travel times calculated into the following three types of nodes: Acceptance point: The point where the initial arrival and departure times have been confirmed; Narrowband point: A point that is in direct contact with the receiver and whose time travel has already been calculated, but whose time travel will be updated in subsequent calculations with a certain probability; The point of distance is the point where the travel time has not been calculated at all. All the narrow band points together constitute the narrow band.

6. The tunnel lining health monitoring system based on acoustic emission according to claim 1, characterized in that: The signal processing system, based on the MSFM algorithm combined with narrowband extension, calculates the initial arrival travel time of each discrete node in the tunnel lining space when the position of each acoustic emitter in the acoustic emitter-receiver matrix is ​​taken as the stress wave source point. The signal processing system, using the stress wave interchange theorem, obtains the time required for propagation from each discrete node to each acoustic emitter / receiver. Each acoustic emitter / receiver forms a signal of size m. travel duration matrix of n ; Elements in the matrix Represents discrete nodes When the source is a sound source, the time required for the sound to propagate to the sound transmitter and receiver; a total of u can be formed. There are matrices, where u and v represent the number of receivers arranged circumferentially and vertically in the receiver matrix, respectively; When microcracks appear and develop in concrete, the acoustic emission signals generated are received by acoustic emission receivers. First, based on the initial arrival time of the microseismic signals from each receiver, the two columns with the smallest initial arrival time in the circumferential direction and the two rows with the smallest initial arrival time in the longitudinal direction are selected, for a total of 4 acoustic emission receivers, to calculate the location of the acoustic emission signal source. The calculation method is as follows: First, the four acoustic transmitters and receivers are paired up to obtain a total of =6 combinations; Calculate the difference in first arrival time based on the first arrival time measured by the two acoustic transmitters and receivers in each combination; Based on the duration matrix of the acoustic emission receiver, the set of nodes that reach the measured first arrival time difference for each pair of combinations is identified, resulting in a total of 6 node sets; Find the intersection of the 6 node sets, which is considered as the source of the acoustic emission signal.

7. The tunnel lining health monitoring system based on acoustic emission according to claim 1, characterized in that: The spacing of the acoustic emission receiver matrix of the signal acquisition system should be precisely calculated to ensure that the positioning error of the acoustic emission signal is within the allowable range. The specific calculation is performed using the following formula: ； In the formula, This represents the total positioning error of acoustic emission. The determination will be made based on the specific conditions of the tunnel section being inspected and in accordance with the relevant standards. Acoustic emission signal localization error includes model simplification error and travel time algorithm error; among which, the travel time algorithm error is the acoustic emission localization error caused by using the MSFM algorithm to calculate the initial arrival travel time of each point in the region and replacing the actual propagation path of the stress wave with discrete line segments. The method for calculating acoustic emission positioning error is as follows: ； In the formula, This refers to acoustic emission positioning error; To simplify the error of the acoustic emission localization model; This refers to the error in the acoustic emission localization algorithm. ； In the formula, The maximum circumferential distance between two points within each simplified unit; The actual circumferential distance corresponding to the above two locations, which results in the largest propagation distance error; ； In the formula, The error rate of the positioning algorithm is related to the size of the discrete grid and the propagation distance. This represents the maximum circumferential distance between two points within each simplified unit.

8. The tunnel lining health monitoring system based on acoustic emission according to claim 1, characterized in that: The threshold is calculated as follows: The damage factor of concrete is proportional to the cumulative number of acoustic emission events, expressed as: ； In the formula, Damage factors for concrete materials; This is a proportionality coefficient determined based on indoor material testing; The cumulative number of acoustic emission events; ； In the formula, This represents the elastic modulus of the material under damaged conditions. This is the initial elastic modulus of the material; Based on the load magnitude, distribution, and cross-sectional dimensions of the lining structure, the minimum elastic modulus required for the concrete material of the lining structure is determined, and then the threshold for the maximum number of acoustic emission events to ensure structural safety is calculated.

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