Method and system for analyzing and evaluating the repair effect of building or tunnel lining

Abstract

The present invention provides a method and system for analyzing and evaluating the repair effect of a building or tunnel lining. The method for analyzing and evaluating the repair effect of a building or tunnel lining includes: performing a first constant micro-vibration detection on a defect to obtain a first micro-vibration signal; after repairing the defect, performing a second constant micro-vibration detection to obtain a second micro-vibration signal; performing a third constant micro-vibration detection on a non-defective part to obtain a third micro-vibration signal; pre-processing and time-frequency transforming the first, second and third micro-vibration signals to obtain a first spectrum, a second spectrum and a third spectrum; calculating a spectral ratio restoration coefficient based on the first, second and third spectra; and evaluating the repair and management work based on the spectral ratio restoration coefficient. The system includes: a detection module, a data processing module, a calculation module and an evaluation module. The present invention has low technical difficulty, can quickly carry out analysis and evaluation work, is convenient and fast, does not require a lot of manpower and material resources, and is low-cost.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering, and in particular to a method and system for analyzing and evaluating the repair effect of a building or tunnel lining. Background Art

[0002] Tunnel lining is often used as a secondary support method for tunnel support, which plays an important role in maintaining the stability of tunnel surrounding rock and ensuring the safety of tunnel structure. In actual projects, the rear part of the lining often suffers from insufficient lining thickness, resulting in voids behind the wall or local cracks and deformations of the lining due to insufficient pouring and filling density or excessive ground pressure, which leads to the deterioration of the stability of the lining and causes certain safety hazards. Therefore, early detection and repair of insufficient lining thickness, voids behind the wall, deformation and cracking is one of the important tasks to maintain the stability of tunnel projects. Due to the strong concealment of tunnel projects, it is difficult to detect hidden dangers in tunnel lining structures, and it is difficult to intuitively evaluate the treatment effect. The effect of engineering repairs can be evaluated by detecting the spatial characteristics of related structures or from the later repair effects. The former often uses acoustic or electromagnetic detection technology to evaluate the back wall filling or wall repair of the lining structure, which cannot directly reflect the improvement of the mechanical properties of the lining structure itself by the repair project; while the latter often evaluates the observation of lining deformation, water seepage and other phenomena. This evaluation method not only cannot directly reflect the improvement of the mechanical properties of the structure, but also the evaluation results are superficial and take a long time. Similarly, there is a lack of effective evaluation methods in the repair of building defects. Summary of the invention

[0003] The purpose of the present invention is to solve at least one of the above-mentioned deficiencies in the prior art. For example, one of the purposes of the present invention is to achieve direct and rapid evaluation of tunnel lining structure repair work, and the second purpose is to improve the accuracy of tunnel lining structure repair work evaluation. The third purpose is to achieve reasonable and effective evaluation of the repair work of concrete structure (or concrete composite structure) buildings.

[0004] In order to achieve the above objectives, the present invention provides a method for analyzing and evaluating the repair effect of a tunnel lining.

[0005] The method may include the following steps: performing a first regular microvibration detection on a defective part of a tunnel lining to obtain a first microvibration signal; performing a second regular microvibration detection on a defective part of the tunnel lining to obtain a second microvibration signal after repairing the defective part of the tunnel lining; performing a third regular microvibration detection on a non-defective part of the tunnel lining to obtain a third microvibration signal; preprocessing and time-frequency transforming the first, second and third microvibration signals to obtain a first spectrum, a second spectrum and a third spectrum; calculating a spectral ratio restoration coefficient based on the first, second and third spectra; and evaluating the repair and management work of the tunnel lining based on the spectral ratio restoration coefficient.

[0006] Furthermore, the first, second and third micro-vibration signals may all include: at least one vibration time sequence.

[0007] Furthermore, the time period of each vibration time series is no less than 10 minutes, for example, 11, 15, 20 minutes, etc.

[0008] Further, the first, second and third vibration time sequences may each include a plurality of vibration time sequences.

[0009] Furthermore, the vibration time series is a micro-vibration discrete time series.

[0010] Furthermore, the time interval and duration of the vibration time series are the same.

[0011] Furthermore, the preprocessing may include: at least one of filtering out constant values, filtering out system errors and zero drift processing.

[0012] Furthermore, correlation analysis is performed on multiple vibration time series in the first micro-vibration signal, and the one with the highest correlation with other vibration time series is selected as the first preferred time series s f (t i ) ; Perform correlation analysis on multiple vibration time series in the second micro-vibration signal, and select the one with the highest correlation with other vibration time series as the second preferred time series s r (t i ) ; The multiple vibration time series in the third micro-vibration signal are subjected to correlation analysis in pairs, and the time period with the highest correlation with other vibration time series is selected as the third preferred time series s d (t i ), t i is time, i=0, 1, 2, 3, ..., n; the first, second and third spectra are obtained by performing time-frequency conversion on the first, second and third preferred time series respectively.

[0013] Furthermore, the spectral ratio restoration coefficient is calculated using the following formula:

[0014] Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient,

[0015] Among them, s f (f j ),s r (f j ),s d (f j) are the first, second and third spectra respectively.

[0016] Furthermore, γ j Spectral ratio SR d-f (f j )Sure:

[0017]

[0018] Here, the upper limit m corresponds to the highest frequency obtained by the time-frequency transformation, which is determined by the time-frequency transformation method.

[0019] Furthermore, the first constant micro-vibration detection and the third constant micro-vibration detection are performed synchronously or asynchronously.

[0020] Furthermore, the step of performing a first regular micro-vibration detection may include: installing at least one vibration sensor at a defect in the tunnel lining, and performing at least one detection on each vibration sensor; the step of performing a second regular micro-vibration detection may include: after the repair, installing at least one vibration sensor at a defect in the tunnel lining, and performing at least one detection on each vibration sensor; the step of performing a third regular micro-vibration detection may include: installing at least one vibration sensor at a defect-free location in the tunnel lining, and performing at least one detection on each vibration sensor.

[0021] Furthermore, the number of defect-free parts of the tunnel lining is at least one, and the distance between the defect-free parts and the defective parts of the tunnel lining may be no less than 3D, where D is the width of the tunnel, for example, 4D, 6D, 8D, 10D, 12D, etc.

[0022] Furthermore, the design parameters of the non-defective parts and defective parts of the tunnel lining are consistent, and the engineering geological conditions are basically consistent.

[0023] Another aspect of the present invention provides a system for analyzing and evaluating the repair effect of a tunnel lining.

[0024] The system may include a detection module, a data processing module, a calculation module and an evaluation module; wherein the detection module can perform regular microvibration detection on the defects of the tunnel lining before repair, the defects of the tunnel lining after repair, and the defect-free parts of the tunnel lining, and obtain the first microvibration signal, the second microvibration signal and the third microvibration signal respectively; the data processing module can pre-process and perform time-frequency transformation on the first, second and third microvibration signals respectively, and obtain the first spectrum, the second spectrum and the third spectrum respectively; the calculation module can calculate the spectral ratio restoration coefficient according to the first, second and third spectra; the evaluation module can display the spectral ratio restoration coefficient; or the evaluation module can evaluate the repair effect of the tunnel lining according to the spectral ratio restoration coefficient, and display the evaluation result.

[0025] Further, the detection module may include at least one vibration sensor.

[0026] Furthermore, the operation of the detection module using a vibration sensor to perform constant micro-vibration detection can be the same as in the above-mentioned analysis and evaluation method of the tunnel lining repair effect. For example, the detection module performs constant micro-vibration detection on the defects of the tunnel lining before repair, including: installing at least one vibration sensor at the defect of the tunnel lining, and each vibration sensor performs at least one detection. The detection module performs constant micro-vibration detection on the defects of the tunnel lining after repair, including: installing at least one vibration sensor at the defect of the tunnel lining, and each vibration sensor performs at least one detection. The detection module performs constant micro-vibration detection on the defect-free parts of the tunnel lining, including: installing at least one vibration sensor at the defect-free parts of the tunnel lining, and each vibration sensor performs at least one detection.

[0027] Furthermore, the first micro-vibration signal, the second micro-vibration signal and the third micro-vibration signal may be the same as those in the above-mentioned tunnel lining repair effect analysis and evaluation method. For example, the first, second and third micro-vibration signals all include: at least one vibration time series.

[0028] Furthermore, the data processing module may include a preprocessing unit and a time-frequency conversion unit.

[0029] The preprocessing unit can preprocess the first, second and third micro-vibration signals. The preprocessing may include: at least one of filtering out constant values, filtering out system errors and zero drift processing, and / or correlation analysis selection.

[0030] The correlation analysis selection may include: performing correlation analysis on multiple vibration time series in the first micro-vibration signal, and selecting the one with the highest correlation with other vibration time series as the first preferred time series s f (t i ) ; Perform correlation analysis on multiple vibration time series in the second micro-vibration signal, and select the one with the highest correlation with other vibration time series as the second preferred time series s r (t i ) ; The multiple vibration time series in the third micro-vibration signal are subjected to correlation analysis in pairs, and the time period with the highest correlation with other vibration time series is selected as the third preferred time series s d (t i ), t i is time, i=0,1,2,3,…,n.

[0031] The time-frequency conversion unit can perform time-frequency conversion on the first, second and third preferred time series and obtain the first, second and third frequency spectra respectively.

[0032] Furthermore, the calculation module calculates the spectral ratio restoration coefficient using the following formula:

[0033] Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient,

[0034] Among them, s f (f j ),s r (f j ),s d (f j ) are the first, second and third spectra respectively.

[0035] Furthermore, γ j Spectral ratio SR d-f (f j )Sure:

[0036]

[0037] Here, the upper limit m corresponds to the highest frequency obtained by the time-frequency transformation, which is determined by the time-frequency transformation method.

[0038] Furthermore, the evaluation module can display the spectral ratio restoration coefficient simultaneously when displaying the evaluation result.

[0039] Furthermore, the number of defect-free parts of the tunnel lining is at least one, and the distance between the defect-free parts and the defective parts of the tunnel lining is not less than 3D, where D is the width of the tunnel.

[0040] Furthermore, the design parameters of the non-defective parts and defective parts of the tunnel lining are consistent, and the engineering geological conditions are basically consistent.

[0041] In another aspect, the present invention provides a method for analyzing and evaluating the effect of repairing building defects.

[0042] The building is a concrete or concrete composite structure, and the method may include the following steps: performing a first regular micro-vibration detection on a defective part of the building to obtain a first micro-vibration signal; after repairing the defective part of the building, performing a second regular micro-vibration detection to obtain a second micro-vibration signal; performing a third regular micro-vibration detection on a non-defective part of the building to obtain a third micro-vibration signal; preprocessing and time-frequency transforming the first, second and third micro-vibration signals to obtain a first spectrum, a second spectrum and a third spectrum; calculating a spectral ratio restoration coefficient based on the first, second and third spectra; and evaluating the repair effect of the building defects based on the spectral ratio restoration coefficient.

[0043] Furthermore, the building may include: a house, a bridge, a dam or a retaining wall.

[0044] Furthermore, the defects of the building may include: cracks in the main structure of the building.

[0045] Furthermore, the steps of performing the first, second and third constant micro-vibration detections may be the same as those in the above-mentioned method for analyzing and evaluating the repair effect of the tunnel lining.

[0046] Furthermore, microvibration detection can be achieved by causing the building to vibrate slightly through natural disturbances, traffic loads or artificial dynamic excitations.

[0047] Furthermore, the steps of preprocessing and time-frequency transformation may be the same as those in the above-mentioned method for analyzing and evaluating the repair effect of tunnel lining.

[0048] Furthermore, the step of calculating the spectral ratio restoration coefficient may be the same as that in the above-mentioned analysis and evaluation method of the tunnel lining repair effect.

[0049] Furthermore, the smaller the value of the spectral ratio restoration coefficient is, the better the restoration effect is, and the larger the value is, the worse the restoration effect is.

[0050] Furthermore, the step of evaluating the repair effect of building defects may be the same as the above-mentioned method for analyzing and evaluating the repair effect of tunnel lining.

[0051] Compared with the prior art, the beneficial effects of the present invention include at least one of the following:

[0052] (1) The present invention is based on the evaluation of the dynamic stiffness of the tunnel lining structure, that is, it essentially analyzes and evaluates the changes in the dynamic stiffness of the surrounding rock mass-lining structure system in space caused by defects and repair measures, which is a change from the past evaluation based on the degree of change in the structural appearance.

[0053] (2) The present invention has low technical difficulty, is convenient and fast, and only requires one set of detection system to carry out analysis and evaluation work, does not require a lot of manpower and material resources, and has low cost.

[0054] (3) The present invention can not only carry out detection work at the construction site, but also generate evaluation results in real time and form an evaluation report. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The above and other objects and / or features of the present invention will become more apparent through the following description in conjunction with the accompanying drawings, in which:

[0056] Figure 1 A schematic diagram of the tunnel lining microvibration signal acquisition of the present invention is shown.

[0057] Figure 2A schematic flow chart of tunnel lining microvibration signal processing according to the present invention is shown. DETAILED DESCRIPTION

[0058] Hereinafter, the analysis and evaluation method and system for the repair effect of a building or tunnel lining of the present invention will be described in detail in conjunction with exemplary embodiments.

[0059] It should be noted that “first”, “second”, “third”, etc. are only for the convenience of description and distinction, and should not be understood as indicating or implying relative importance. “upper”, “lower”, “front”, “back”, “left”, “right”, “inner”, “outer”, etc. are only for the convenience of description and to constitute a relative orientation or position relationship, and should not indicate or imply that the referred component must have such a specific orientation or position.

[0060] As a common geotechnical engineering structure, the design, construction and operation of tunnels are closely related to geological environmental conditions. The safety and mechanical stability of the tunnel structure itself are closely related to the design and construction of the lining. The requirements for the strength and mechanical stiffness of the lining are often not the higher the better, but should be adapted to factors such as engineering technical conditions, engineering geological environment, and engineering construction level.

[0061] The evaluation of the effect of tunnel lining repair and reinforcement work by the present invention is achieved based on the regional and spatiotemporal variability of the dynamic properties of the lining structure; that is, the detection and analysis of the dynamic properties of the lining structure under certain conditions is the key to the present invention.

[0062] Under the dynamic excitation caused by natural disturbance or traffic load, the tunnel structure produces micro-vibration for a long time. Based on this, the present invention proposes a method for inverting the dynamic characteristics of the tunnel lining structure-surrounding rock interaction through the analysis of micro-vibration signals, so as to make a scientific evaluation of the repair work of tunnel defects.

[0063] The types of tunnel lining defects targeted by the present invention may include: deformation, cracking, and damage of the lining, insufficient lining pouring and filling, voids behind the lining wall, poor geological structure behind the lining wall, and weak lining.

[0064] Exemplary Embodiment 1

[0065] This exemplary embodiment provides a method for analyzing and evaluating the repair effect of a tunnel lining. Figure 1 A schematic diagram of the tunnel lining microvibration signal acquisition of the present invention is shown. Figure 2 A schematic flow chart of tunnel lining microvibration signal processing according to the present invention is shown.

[0066] The process of the analysis and evaluation method of the tunnel lining repair effect of the present invention is as follows: Figure 2As shown in the figure, the whole process includes multiple steps such as on-site detection, time-frequency transformation and calculation of spectral ratio restoration coefficients.

[0067] Specifically, the method may include the following steps:

[0068] S10: In order to analyze and evaluate the repair work of the defective part of the tunnel lining, it is necessary to perform micro-vibration detection at least three times at two locations. For example, the first constant micro-vibration detection is performed on the defective part of the tunnel lining (before repair) (e.g. Figure 2 After the defects of the tunnel lining are repaired, the second constant micro-vibration detection is performed (such as Figure 2 Test II in the above), obtain the second micro-vibration signal, that is, obtain at least a discrete time series; perform the third constant micro-vibration detection on the defect-free part of the tunnel lining (such as Figure 2 In the test III), the third micro-vibration signal is obtained, that is, at least a discrete time series is obtained.

[0069] In this embodiment, the above three tests do not need to be performed synchronously. Further, when conditions are met, the first constant micro-vibration detection and the third constant micro-vibration detection can perform synchronous data collection.

[0070] In this embodiment, the step of performing the first constant micro-vibration detection may include: before repairing, installing at least one vibration sensor at the defect of the tunnel lining, each vibration sensor performs at least one detection, and obtains at least one discrete time series.

[0071] The step of performing a second regular micro-vibration detection may include: after the repair, installing at least one vibration sensor at the defect of the tunnel lining, each vibration sensor performing at least one detection, and obtaining at least one discrete time series.

[0072] The step of performing the third constant micro-vibration detection may include: installing at least one vibration sensor at a defect-free location of the tunnel lining, each vibration sensor performing at least one detection, and obtaining at least one discrete time series.

[0073] In this embodiment, the vibration sensor may be an acceleration sensor or a velocity sensor. Further, a velocity sensor may be used. At the same time, since the acceleration and velocity signals have different sensitivities to the stiffness response of the surrounding rock-lining system, the present invention may convert the acceleration into a velocity signal before processing.

[0074] In this embodiment, when collecting micro-vibration signals, the vibration sensor body is directly rigidly connected to the main lining structure, and the installation mode, method, basic parameter settings, and data collection frequency are consistent (time interval Δt is consistent).

[0075] In this embodiment, the number of defect-free locations of the tunnel lining is at least one, for example, 1, 2, 3, etc.

[0076] In this embodiment, if Figure 1 As shown in the figure, the distance between the defect-free part and the defective or weak part of each tunnel lining is not less than 3D, where D is the width of the tunnel. This can avoid the local defects or weaknesses of the lining from having a significant impact on the vibration spectrum characteristics of the lining without defects, so that the vibration response characteristics of the lining without defects can represent the dynamic response characteristics of the intact lining.

[0077] In this embodiment, the design parameters of the non-defective parts and defective parts of the tunnel lining are consistent, and the engineering geological conditions are basically consistent, so that the time-frequency characteristics of the lining micro-vibration are referenceable.

[0078] In this embodiment, the first, second and third micro-vibration signals may all include: a plurality of vibration time sequences. For example, the first micro-vibration signal includes the A1th vibration time sequence, the A2th vibration time sequence, ..., etc.; the second micro-vibration signal includes the B1th vibration time sequence, the B2th vibration time sequence, ..., etc.; the third micro-vibration signal includes the C1th vibration time sequence, the C2th vibration time sequence, ..., etc.

[0079] The above vibration time series is a discrete time series with equal time intervals. In order to eliminate the influence of accidental dynamic disturbance events on the micro-vibration signal, in principle, discrete time series of multiple time periods can be monitored and obtained.

[0080] The duration of the micro-vibration discrete time series in each of the above time periods may be no less than 10 minutes. Sufficient duration facilitates the selection of relatively stable signal periods, which can reduce the impact of accidental disturbances on spectral characteristics.

[0081] S20: preprocessing and time-frequency transforming the first, second and third micro-vibration signals to obtain a first spectrum, a second spectrum and a third spectrum.

[0082] In this embodiment, the preprocessing includes: at least one of filtering out constant values, filtering out system errors and zero drift processing, and / or correlation analysis selection.

[0083] The correlation analysis selection includes: performing correlation analysis on multiple vibration time series obtained by multiple detections in the first micro-vibration signal, and selecting the time series with the highest correlation with other time series as the first preferred time series s f (t i ) ; The multiple vibration time series obtained by multiple detections of the second micro-vibration signal are subjected to correlation analysis in pairs, and the time series with the highest correlation with other time series is selected as the second preferred time series s r (ti ) ; The multiple vibration time series obtained by multiple detections in the third micro-vibration signal are subjected to correlation analysis in pairs, and the time series with the highest correlation with other time series is selected as the third preferred time series s d (t i ), t i is time, i=0,1,2,3,…,n. Among them, the time interval and duration of all discrete time series are the same.

[0084] In this embodiment, the time-frequency transformation includes: obtaining a corresponding vibration spectrum through discrete time-frequency transformation, as shown below:

[0085]

[0086]

[0087]

[0088] Where: t i is time, s; t i =iΔt, Δt is the data collection time interval set during micro-vibration detection, i=0,1,2...,n; f j is the frequency, Hz, j=0,1,2...,m.

[0089] s f (f i ),s r (f i ),s d (f i ) are the first spectrum, the second spectrum and the third spectrum respectively. The first, second and third spectrum are the spectrums of the micro-vibration signals at the lining defect (before repair), the lining defect (after repair) and the lining without defect respectively.

[0090] Among them, various commonly used time-frequency transformation algorithms can be used to perform the above-mentioned time-frequency transformation, such as FFT, HHT, WT, ST, etc. No matter which time-frequency transformation method is used, the same method should always be used in the above process.

[0091] S30: Calculate a spectrum ratio restoration coefficient according to the first, second and third spectra.

[0092] Specifically, this step may include:

[0093] S31: Calculate the spectral ratio SR of the lining defect after repair relative to that before repair r-f (f j ) and the spectrum ratio SR when the lining is intact relative to the defect d-f (f j ).

[0094]

[0095] S32: By spectrum ratio SR r-f (f j ) and SR d-f (f j ) Calculate the restoration coefficient (i.e., spectral ratio restoration coefficient) R for lining defect repair D .

[0096] Among them, R D is the spectral ratio restoration coefficient.

[0097] Among them, γ j is the frequency-based weight coefficient, which can be obtained from the spectral ratio SR d-f (f j )Sure:

[0098]

[0099] Here, the upper limit m corresponds to the highest frequency obtained by the time-frequency transformation, which is determined by the time-frequency transformation method.

[0100] S40: Evaluate the tunnel lining repair and treatment based on the spectral ratio restoration coefficient.

[0101] Among them, R D The smaller the value, the better the repair effect. D The larger the value, the worse the repair effect. For example, the tunnel lining repair evaluation work can be carried out based on the following table.

[0102] Table 1 Evaluation of tunnel lining repair based on spectral ratio restoration coefficient

[0103]

[0104]

[0105] Exemplary Embodiment 2

[0106] This exemplary embodiment provides a method for analyzing and evaluating the repair effect of a tunnel lining.

[0107] The method used in this exemplary embodiment is basically the same as the method in the above exemplary embodiment, except that multiple detections are performed, and the acquired data can be evaluated multiple times, and finally multiple restoration coefficients R are obtained. D , and using multiple R D , analyze and evaluate the tunnel lining repair effect, thereby improving the accuracy of the evaluation work.

[0108] Exemplary Embodiment 3

[0109] This exemplary embodiment provides a system for analyzing and evaluating the repair effect of a tunnel lining.

[0110] The system may include a detection module, a data processing module, a calculation module and an evaluation module.

[0111] Among them, the detection module can perform regular micro-vibration detection on the tunnel lining defects before repair, the tunnel lining defects after repair, and the tunnel lining defect-free area, and obtain the first micro-vibration signal, the second micro-vibration signal and the third micro-vibration signal respectively.

[0112] The data processing module can perform preprocessing and time-frequency transformation on the first, second and third micro-vibration signals respectively, and obtain a first spectrum, a second spectrum and a third spectrum respectively.

[0113] The calculation module can calculate the spectrum ratio restoration coefficient according to the first, second and third spectra.

[0114] The evaluation module can display the spectral ratio restoration coefficient; or, the evaluation module can evaluate the repair effect of the tunnel lining according to the spectral ratio restoration coefficient and display the evaluation result.

[0115] In this embodiment, the detection module may include at least one vibration sensor. The vibration sensor may be an acceleration sensor or a velocity sensor. Further, a velocity sensor may be used.

[0116] Further, the operation of the detection module performing constant micro-vibration detection using the vibration sensor may be the same as that in the first exemplary embodiment.

[0117] In this embodiment, the first micro-vibration signal, the second micro-vibration signal and the third micro-vibration signal may be the same as those in exemplary embodiment 1. For example, the first micro-vibration signal includes an A1th vibration time sequence, an A2th vibration time sequence, ..., etc.; the second micro-vibration signal includes a B1th vibration time sequence, a B2th vibration time sequence, ..., etc.; the third micro-vibration signal includes a C1th vibration time sequence, a C2th vibration time sequence, ..., etc.

[0118] In this embodiment, the data processing module may include a preprocessing unit and a time-frequency conversion unit.

[0119] The preprocessing unit can preprocess the first, second and third micro-vibration signals. The preprocessing may include: at least one of filtering out constant values, filtering out system errors and zero drift processing, and / or correlation analysis selection.

[0120] The correlation analysis and selection by the preprocessing module may include:

[0121] The multiple vibration time series obtained by multiple detections in the first micro-vibration signal are subjected to correlation analysis in pairs, and the time series with the highest correlation with other time series is selected as the first preferred time series s f (t i ) ; The multiple vibration time series obtained by multiple detections of the second micro-vibration signal are subjected to correlation analysis in pairs, and the time series with the highest correlation with other time series is selected as the second preferred time series s r (t i ) ; The multiple vibration time series obtained by multiple detections in the third micro-vibration signal are subjected to correlation analysis in pairs, and the time series with the highest correlation with other time series is selected as the third preferred time series s d (t i ), t i is time, i=0,1,2,3,…,n. Among them, the time interval and duration of all discrete time series are the same.

[0122] The time-frequency conversion unit can perform time-frequency conversion on the first, second and third preferred time series and obtain the first, second and third frequency spectra respectively.

[0123] In this embodiment, the calculation module calculates the spectral ratio restoration coefficient using the following formula:

[0124] Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient,

[0125]

[0126] s f (f j ),s r (f j ),s d (f j ) are the first, second and third spectra respectively.

[0127] In this embodiment, the evaluation module can be based on R D Among them, R D The smaller the value, the better the repair effect. D The larger the value, the worse the repair effect. For example, the tunnel lining repair evaluation can be performed based on Table 1 in Exemplary Embodiment 1.

[0128] Example 4

[0129] This exemplary embodiment provides a method for analyzing and evaluating the effect of repairing building defects.

[0130] The building is a concrete or concrete composite structure. The method may include the following steps:

[0131] A first constant micro-vibration detection is performed on defective parts of a building to obtain a first micro-vibration signal; after the defective parts of the building are repaired, a second constant micro-vibration detection is performed to obtain a second micro-vibration signal; a third constant micro-vibration detection is performed on non-defective parts of the building to obtain a third micro-vibration signal; the first, second and third micro-vibration signals are preprocessed and time-frequency transformed to obtain a first spectrum, a second spectrum and a third spectrum; a spectral ratio restoration coefficient is calculated based on the first, second and third spectra; and the repair effect of the building defects is evaluated based on the spectral ratio restoration coefficient.

[0132] In this embodiment, the buildings may include: houses, bridges, dams, retaining walls, etc.

[0133] In this embodiment, the defects of the building may include cracks in major structures such as beams, columns, load-bearing walls, and floor panels.

[0134] Furthermore, microvibration detection can be achieved by causing the building to vibrate slightly through natural disturbances, traffic loads or artificial dynamic excitations.

[0135] In this embodiment, the steps of performing the first, second and third constant micro-vibration detections may be the same as those in Exemplary Embodiment 1.

[0136] In this embodiment, the steps of preprocessing and time-frequency transformation may be the same as those in exemplary embodiment 1.

[0137] In this embodiment, the step of calculating the spectral ratio restoration coefficient may be the same as that in exemplary embodiment 1.

[0138] In this embodiment, R D The smaller the value, the better the repair effect. D The larger the value, the worse the repair effect.

[0139] In this embodiment, in the step of evaluating the restoration effect, the value of the spectral ratio restoration coefficient can be matched with the restoration degree according to the specific type of the building.

[0140] Although the present invention has been described above in conjunction with the exemplary embodiments and the accompanying drawings, it should be apparent to those skilled in the art that various modifications may be made to the above-described embodiments without departing from the spirit and scope of the claims.

Claims

1. A method for analyzing and evaluating the effect of tunnel lining repair, characterized in that: The method comprises the following steps: Performing a first constant micro-vibration detection on a defective part of a tunnel lining to obtain a first micro-vibration signal; After repairing the defects of the tunnel lining, a second constant micro-vibration detection is performed to obtain a second micro-vibration signal; Conduct a third constant micro-vibration test on the defect-free part of the tunnel lining to obtain a third micro-vibration signal; Preprocessing and time-frequency transforming the first, second and third micro-vibration signals to obtain a first spectrum, a second spectrum and a third spectrum; According to the first, second and third spectra, a spectrum ratio restoration coefficient is calculated; the spectrum ratio restoration coefficient is calculated using the following formula: Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient; Among them, s f (f j ),s r (f j ),s d (f j ) are the first, second and third spectra respectively; The repair and treatment work of the tunnel lining is evaluated based on the spectral ratio restoration coefficient.

2. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 1 is characterized in that: The preprocessing includes: at least one of filtering out constant values, filtering out system errors and zero drift processing.

3. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 1 is characterized in that: The first, second and third micro-vibration signals all include: at least one vibration time series, and the duration of each vibration time series is not less than 10 minutes.

4. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 2 is characterized in that: The first, second and third vibration time sequences all include a plurality of vibration time sequences, and the vibration time sequences are micro-vibration discrete time sequences; The pre-processing comprises the steps of: The multiple vibration time series in the first micro-vibration signal are subjected to correlation analysis two by two, and the one with the highest correlation with other vibration time series is selected as the first preferred time series s f (t i ), t i is time, i=0,1,2,3,…,n; The multiple vibration time series in the second micro-vibration signal are subjected to correlation analysis two by two, and the one with the highest correlation with other vibration time series is selected as the second preferred time series s r (t i ); The multiple vibration time series in the third micro-vibration signal are subjected to correlation analysis two by two, and the time period with the highest correlation with other vibration time series is selected as the third preferred time series s d (t i ); The first, second and third frequency spectra are obtained by performing time-frequency conversion on the first, second and third preferred time series respectively.

5. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 1, characterized in that: The first constant micro-vibration detection and the third constant micro-vibration detection are performed synchronously or asynchronously.

6. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 1 is characterized in that: The step of performing the first constant micro-vibration detection comprises: installing at least one vibration sensor at the defect of the tunnel lining, and each vibration sensor performs at least one detection; The step of performing the second constant micro-vibration detection comprises: after the repair, installing at least one vibration sensor at the defect of the tunnel lining, and performing at least one detection on each vibration sensor; The step of performing the third constant micro-vibration detection includes: installing at least one vibration sensor at a defect-free location of the tunnel lining, and performing at least one detection on each vibration sensor.

7. The method for analyzing and evaluating the repair effect of a tunnel lining according to claim 6, characterized in that: The number of defect-free parts of the tunnel lining is at least one, and the distance between the defect-free parts and the defective parts of the tunnel lining is not less than 3D, where D is the width of the tunnel; The design parameters of the non-defective parts and defective parts of the tunnel lining are consistent, and the engineering geological conditions are basically consistent.

8. A tunnel lining repair effect analysis and evaluation system, characterized in that: The system includes a detection module, a data processing module, a calculation module and an evaluation module; wherein, The detection module can perform constant micro-vibration detection on the defective parts of the tunnel lining before repair, the defective parts of the tunnel lining after repair, and the defect-free parts of the tunnel lining, and obtain the first micro-vibration signal, the second micro-vibration signal, and the third micro-vibration signal respectively; The data processing module can pre-process and perform time-frequency transformation on the first, second and third micro-vibration signals respectively, and obtain a first spectrum, a second spectrum and a third spectrum respectively; The calculation module can calculate the spectral ratio restoration coefficient according to the first, second and third spectra; the spectral ratio restoration coefficient is calculated using the following formula: Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient; Among them, s f (f j ),s r (f j ),s d (f j ) are the first, second and third spectra respectively; The evaluation module can display the spectral ratio restoration coefficient; or, the evaluation module can evaluate the repair effect of the tunnel lining according to the spectral ratio restoration coefficient and display the evaluation result.

9. A method for analyzing and evaluating the effect of building defect repair, characterized in that: The building is a concrete or concrete composite structure, and the method comprises the following steps: Performing a first constant micro-vibration detection on a defective part of the building to obtain a first micro-vibration signal; After repairing the defective part of the building, a second constant micro-vibration detection is performed to obtain a second micro-vibration signal; Performing a third constant micro-vibration detection on a non-defective part of the building to obtain a third micro-vibration signal; Preprocessing and time-frequency transforming the first, second and third micro-vibration signals to obtain a first spectrum, a second spectrum and a third spectrum; According to the first, second and third spectra, a spectrum ratio restoration coefficient is calculated; the spectrum ratio restoration coefficient is calculated using the following formula: Among them, R D is the spectral ratio restoration coefficient, γ j is the frequency-based weight coefficient; Among them, s f (f j ),s r (f j ),s d (f j ) are the first, second and third spectra respectively; The repair effect of the building defects is evaluated according to the spectral ratio restoration coefficient.

Images