Detection system for holes behind tunnel and detection method thereof

Abstract

The invention discloses a tunnel back cavity detection system and a detection method thereof, and relates to the field of cavity detection, and the method comprises the following steps: collecting tunnel signal data and tunnel visual image data, and building a tunnel frame model according to the tunnel visual image data; obtaining cavity information data according to the tunnel signal data and the tunnel frame model, and obtaining cavity characteristic data and cavity edge points according to the cavity information data; according to the cavity characteristic data, obtaining a cavity clearness factor and a cavity smoothness factor, and according to the cavity clearness factor and the cavity smoothness factor, obtaining a cavity subsidence factor; evaluating a cavity behind the tunnel according to the cavity subsidence factor to obtain a cavity defect evaluation value; the safety of the tunnel is improved.

Description

Technical Field

[0001] The invention relates to the field of cavity detection, in particular to a cavity detection system and a cavity detection method for a tunnel. Background Art

[0002] With the development of non-destructive testing technology, various methods based on electromagnetic waves, sound waves, micro-vibration, etc. are gradually applied to the detection of cavities behind tunnels. For example, geological radar, ultrasonic detection, infrared thermal imaging and other methods use the reflection and attenuation characteristics of waves in different media to detect cavities. These methods can not only reduce the downtime of tunnels, but also provide more accurate information inside the tunnel, thus improving the efficiency and accuracy of detection. In the existing technology, although non-destructive testing technology has great advantages, non-destructive testing technology alone may sometimes encounter limitations; for example, tunnel safety needs to be guaranteed in a timely manner, and the cavity behind the tunnel may be affected by the environment inside the tunnel, resulting in changes in the cavity state, which may in turn cause tunnel accidents; changes in the cavity state will cause changes in the stability of the tunnel structure, and the shutdown and large-scale maintenance caused by structural damage will reduce the service life of the tunnel and cause more serious tunnel accidents. These are problems we need to solve. To this end, a detection system and a detection method for the cavity behind the tunnel are now provided. Summary of the invention

[0003] In order to solve the above technical problems, the object of the present invention is to provide a method for detecting a cavity behind a tunnel, comprising the following steps: Step S1: collecting tunnel signal data and tunnel visual image data, and establishing a tunnel framework model according to the tunnel visual image data; Step S2: obtaining cavity information data according to the tunnel signal data and the tunnel framework model, and obtaining cavity characteristic data and cavity edge points according to the cavity information data; Step S3: obtaining a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtaining a hole sink factor according to the hole clarity factor and the hole smoothness factor; Step S4: Evaluate the cavity behind the tunnel according to the cavity factor to obtain a cavity defect evaluation value.

[0004] Furthermore, the process of collecting tunnel signal data and tunnel visual image data and establishing a tunnel framework model according to the tunnel visual image data includes: The tunnel signal data includes reflected signal waveform data and arrival time; the tunnel visible image data includes tunnel overall structure image data and image acquisition time; Set up a signal transmitting end and a tunnel collecting end; collect tunnel signal data through the signal transmitting end, and collect tunnel visible image data through the tunnel collecting end; According to the tunnel visual image data, tunnel characteristic data and tunnel dimension data are obtained; a tunnel physical model is established according to the tunnel dimension data, and model details of the tunnel physical model are constructed according to the tunnel characteristic data to obtain a tunnel framework model.

[0005] Furthermore, according to the tunnel signal data and the tunnel framework model, the process of obtaining the cavity information data includes: Obtain the propagation speed of the electromagnetic wave in the tunnel air, and obtain the depth of the cavity position according to the propagation speed and the arrival time; obtain the correction coefficient, and obtain the corrected depth of the cavity position according to the correction coefficient and the cavity position depth; According to the reflected signal waveform data of the tunnel signal data, the amplitude and phase of the reflected signal are obtained; an amplitude identification unit and a phase identification unit are set; the amplitude peak value and the phase of the reflected signal are respectively obtained by the amplitude identification unit and the phase identification unit; an amplitude peak change threshold and a phase change threshold are set; the amplitude peak value of the reflected signal is continuously obtained by the amplitude identification unit, and the hole amplitude signal data is obtained according to the amplitude peak change threshold and the amplitude peak value; the phase of the reflected signal is continuously obtained by the phase identification unit, and the hole phase signal data is obtained according to the phase change threshold and the phase; The cavity morphology data is obtained according to the cavity amplitude signal data and the cavity phase signal data, and the cavity range data is obtained according to the cavity position correction depth, the cavity morphology data and the tunnel frame model. The cavity amplitude signal data, the cavity phase signal data and the cavity range data are recorded as cavity information data.

[0006] Furthermore, the process of obtaining the hole characteristic data and the hole edge points according to the hole information data includes: According to the hole amplitude signal data, the hole phase signal data and the hole range data, a hole amplitude signal segment and a hole phase signal segment are obtained; and the amplitude value of the hole amplitude signal segment and the phase value of the hole phase signal segment are obtained; according to the hole amplitude signal data and the amplitude value, an amplitude floating value is obtained, and according to the amplitude floating value, an amplitude reference value is obtained; according to the amplitude floating value and the amplitude reference value, amplitude characteristic data is obtained; according to the hole phase signal data and the phase value, a phase floating value is obtained, and according to the phase floating value, a phase reference value is obtained; according to the phase floating value and the phase reference value, phase characteristic data is obtained; according to the amplitude characteristic data and the phase characteristic data, hole characteristic data is obtained; The hole edge data is obtained according to the hole characteristic data and the hole range data, and the hole edge simulation image is obtained according to the hole edge data and the hole range data, and the hole edge point is obtained according to the hole edge simulation image.

[0007] Furthermore, according to the hole characteristic data, the process of obtaining the hole edge clarity factor and the hole edge sliding factor includes: According to the void characteristic data and the void edge points, a characteristic relationship is obtained; according to the characteristic relationship, the void characteristic data and the amplitude characteristic data, each amplitude integral peak range in the amplitude characteristic data is obtained, and according to the amplitude peak value and the amplitude integral peak range, the peak edge m and the peak edge n are obtained; according to the peak edge m and the peak edge n, the peak width value is obtained, and according to the amplitude peak value and the peak width value, the amplitude kurtosis is obtained; According to the amplitude characteristic data and the phase characteristic data, an amplitude characteristic mark and a phase characteristic mark are obtained; according to the amplitude characteristic mark and the reflected signal waveform data, an area of ​​the entire amplitude change in the reflected signal waveform data and an area formed by discontinuous points in the reflected signal waveform data are obtained; and according to the area formed by the discontinuous points in the reflected signal waveform data and the area of ​​the entire amplitude change in the reflected signal waveform data, an amplitude jump degree is obtained; According to the phase characteristic mark and the reflected signal waveform data, the area of ​​the overall phase change in the reflected signal waveform data and the area formed by the phase mutation in the reflected signal waveform data are obtained; according to the area formed by the phase mutation in the reflected signal waveform data and the area of ​​the overall phase change in the reflected signal waveform data, the phase jump abruptness is obtained; according to the amplitude jump abruptness, the phase jump abruptness and the amplitude kurtosis, the hole edge clarity factor is obtained; The reflected signal waveform data of the amplitude characteristic mark and the phase characteristic mark corresponding to the characteristic relationship are divided into several small signal windows through the characteristic relationship, and the obtained small signal windows are subjected to Fourier transform to obtain the frequency-time image, and the void edge slip factor is obtained according to the frequency-time image.

[0008] Furthermore, the process of evaluating the cavity behind the tunnel according to the cavity factor and obtaining the cavity defect evaluation value includes: According to the characteristic relationship and the collapse factor, the cavity defect assessment value is obtained; the cavity defect assessment value is marked to the corresponding position of the tunnel frame model to obtain the tunnel assessment model; the tunnel assessment model is sent to the tunnel engineering personnel to plan the reinforcement plan and preventive measures, and the tunnel is reinforced through the tunnel assessment model, reinforcement plan and preventive measures.

[0009] In another embodiment of the present invention, the present invention further discloses a detection system for a cavity behind a tunnel, comprising a management center, wherein the management center is communicatively connected to a tunnel signal acquisition module, a tunnel signal analysis module, a tunnel signal processing module, and a tunnel evaluation module: The tunnel signal acquisition module is used to collect tunnel signal data and tunnel visual image data, and establish a tunnel framework model according to the tunnel visual image data; The tunnel signal analysis module is used to obtain cavity information data according to the tunnel signal data and the tunnel framework model, and to obtain cavity characteristic data and cavity edge points according to the cavity information data; The tunnel signal processing module is used to obtain a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtain a hole sink factor according to the hole clarity factor and the hole smoothness factor; The tunnel assessment module is used to assess the cavity behind the tunnel according to the cavity factor to obtain a cavity defect assessment value.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: tunnel signal data and tunnel visible image data are collected, and a tunnel framework model is established according to the tunnel visible image data, so that engineering personnel can observe tunnel conditions and determine the subsequent cavity positions; cavity information data is obtained according to the tunnel signal data and the tunnel framework model, and cavity characteristic data is obtained according to the cavity information data, so that the approximate range of the cavity and the state of the cavity edge can be located; cavity clarity factor and cavity smoothness factor are obtained according to the cavity characteristic data, and a cavity sinking factor is obtained according to the cavity clarity factor and the cavity smoothness factor, so that the degree of influence of the cavity on the tunnel can be obtained and potential hidden dangers can be identified; the cavity behind the tunnel is evaluated according to the sinking factor, and the evaluation result is obtained, so that the influence of the cavity on the tunnel structure can be judged, which helps to take reinforcement and repair measures, ensure the long-term structural stability of the tunnel, effectively reduce the safety risks during the operation of the tunnel, avoid shutdown and large-scale maintenance due to structural damage, and thus extend the service life of the tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 This is a flow chart of a method for detecting a cavity behind a tunnel according to an embodiment of the present application.

[0012] Figure 2 This is a schematic diagram of a detection system for a cavity behind a tunnel according to an embodiment of the present application. DETAILED DESCRIPTION

[0013] like Figure 1 As shown, a method for detecting a cavity behind a tunnel comprises the following steps: Step S1: collecting tunnel signal data and tunnel visual image data, and establishing a tunnel framework model according to the tunnel visual image data; Step S2: obtaining cavity information data according to the tunnel signal data and the tunnel framework model, and obtaining cavity characteristic data and cavity edge points according to the cavity information data; Step S3: obtaining a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtaining a hole sink factor according to the hole clarity factor and the hole smoothness factor; Step S4: Evaluate the cavity behind the tunnel according to the cavity factor to obtain a cavity defect evaluation value.

[0014] It should be further explained that, in the specific implementation process, the process of collecting tunnel signal data and tunnel visible image data and establishing the tunnel framework model according to the tunnel visible image data is as follows: A signal transmitting end is provided, wherein the signal transmitting end is used to transmit electromagnetic waves into the tunnel and receive electromagnetic wave reflection signals; the tunnel signal data is the electromagnetic wave reflection signals received by the signal transmitting end; The tunnel signal data includes reflected signal waveform data and arrival time; The tunnel visible image data includes the tunnel overall structure image data and the image acquisition time; Setting a tunnel acquisition terminal, wherein the tunnel acquisition terminal is used to obtain tunnel visible image data; The signal transmitting end is used to collect tunnel signal data, and the tunnel visual image data is collected through the tunnel collecting end; The tunnel visible image data is analyzed by computer vision technology, and the tunnel overall structure image data of the tunnel visible image data is outlined to obtain tunnel characteristic data and tunnel size data; It should be further explained that, in the specific implementation process, the tunnel characteristic data refers to the shape and characteristic information of the tunnel, the tunnel dimension data refers to geometric parameters such as the length, height and width of the tunnel, and the arrival time refers to the time difference between the transmission of the electromagnetic wave signal and the reception of the transmission signal; A tunnel physical model is established according to the tunnel dimension data, and model details of the tunnel physical model are constructed according to the tunnel characteristic data to obtain a tunnel framework model.

[0015] It should be further explained that, in the specific implementation process, the process of obtaining the cavity information data according to the tunnel signal data and the tunnel framework model, and obtaining the cavity characteristic data and the cavity edge point according to the cavity information data is as follows: Obtain the propagation speed of the electromagnetic wave in the tunnel air, multiply the obtained propagation speed by the arrival time, and calculate the ratio of the obtained product calculation result to 2 to obtain the depth of the cavity position; obtain the correction coefficient of the current tunnel depth through the "Code for Design of Building Foundations", and multiply the correction coefficient by the cavity position depth to obtain the corrected depth of the cavity position; According to the reflected signal waveform data of the tunnel signal data, the amplitude and phase of the reflected signal are obtained; an amplitude identification unit and a phase identification unit are set, the amplitude identification unit moves with the reflected signal waveform data, and is used to continuously identify the amplitude peak value in the reflected signal waveform data, and the phase identification unit moves with the reflected signal waveform data, and is used to continuously identify the phase in the reflected signal waveform data; the amplitude peak value and the phase of the reflected signal are respectively obtained by the amplitude identification unit and the phase identification unit; an amplitude peak value change threshold and a phase change threshold are set; and the amplitude peak value analysis and the phase analysis are respectively performed on the reflected signal waveform data by the amplitude identification unit and the phase identification unit; It should be further explained that, in the specific implementation process, the specific process of performing amplitude peak analysis and phase analysis on the reflected signal waveform data respectively by the amplitude recognition unit and the phase recognition unit includes: continuously acquiring the amplitude peak of the reflected signal by the amplitude recognition unit, judging the difference between adjacent amplitude peaks according to the amplitude peak change threshold, and when the difference between adjacent amplitude peaks is greater than the amplitude peak change threshold, obtaining the width area of ​​the amplitude peak, which is recorded as the hole amplitude signal data; continuously acquiring the phase of the reflected signal by the phase recognition unit, judging the difference between adjacent phases according to the phase change threshold, and when the difference between adjacent phases is greater than the phase change threshold, obtaining the change area of ​​adjacent phases, which is recorded as the hole phase signal data; The cavity amplitude signal data and the cavity phase signal data are analyzed by three-dimensional imaging technology to obtain cavity morphology data, and the cavity is marked at the corresponding position of the tunnel frame model according to the cavity position correction depth and the cavity morphology data to obtain cavity range data, and the cavity amplitude signal data, the cavity phase signal data and the cavity range data are recorded as cavity information data; And according to the cavity information data, cavity characteristic data and cavity edge points are obtained; It should be further explained that, in the specific implementation process, the specific process of obtaining the hole characteristic data according to the hole information data is as follows: the hole range data is analyzed according to the hole amplitude signal data and the hole phase signal data of the hole information data, and the hole amplitude signal data is divided into several segments of data, which are recorded as hole amplitude signal segments; the hole phase signal data is divided into several segments of data, which are recorded as hole phase signal segments; and the amplitude values ​​of the hole amplitude signal segments and the phase values ​​of the hole phase signal segments are obtained; according to the order of the hole amplitude signal data, the obtained adjacent amplitude values ​​are difference calculated to obtain the amplitude floating value, and the obtained amplitude floating value is calculated. The values ​​are averaged to obtain an amplitude reference value; when the amplitude floating value is greater than the amplitude reference value, a hole amplitude signal segment corresponding to the amplitude floating value is obtained, and the obtained hole amplitude signal segment is recorded as amplitude characteristic data; according to the order of the hole phase signal data, the obtained adjacent phase values ​​are differenced to obtain a phase floating value, and the obtained phase floating value is averaged to obtain a phase reference value; when the phase floating value is greater than the phase reference value, a hole phase signal segment corresponding to the phase floating value is obtained, and the obtained hole phase signal segment is recorded as phase characteristic data; and the amplitude characteristic data and the phase characteristic data are recorded as hole characteristic data; Through three-dimensional imaging technology, the hole range data is analyzed according to the hole characteristic data to obtain the hole edge data, and the hole edge data is marked within the hole range data to obtain the hole edge simulation image, and the hole edge simulation image is divided into several images, which are recorded as hole edge points, and the hole edge points are associated with each other.

[0016] It should be further explained that, in the specific implementation process, the process of obtaining the hole edge clear factor and the hole edge sliding factor according to the hole characteristic data, and obtaining the hole sink factor according to the hole edge clear factor and the hole edge sliding factor is as follows: Through three-dimensional imaging technology, the cavity characteristic data is converted into image data and compared with the cavity edge points for similarity. If the obtained image data is completely consistent with the data in the cavity edge points, the cavity characteristic data is feature-associated with the cavity edge points to obtain a feature relationship. Through the characteristic relationship and the amplitude characteristic data of the void characteristic data corresponding to the characteristic relationship, the amplitude full peak ranges in the amplitude characteristic data are obtained, and two points are found on the signal curve of the amplitude full peak range according to half of the amplitude peak value, and the coordinates of the two points are marked as peak edge m and peak edge n; the peak edge m and the peak edge n are calculated by difference and absolute value to obtain the peak width value, and the amplitude peak value and the peak width value are calculated by ratio to obtain the amplitude kurtosis; According to the amplitude characteristic data and the phase characteristic data, the amplitude characteristic data and the phase characteristic data are marked at corresponding positions in the reflected signal waveform data to obtain the amplitude characteristic mark and the phase characteristic mark, and the amplitude change is analyzed in the reflected signal waveform data according to the amplitude characteristic mark to obtain the overall area of ​​the amplitude change in the reflected signal waveform data and the area formed by the discontinuous points in the reflected signal waveform data, and the ratio of the area formed by the discontinuous points in the reflected signal waveform data to the overall area of ​​the amplitude change in the reflected signal waveform data is calculated to obtain the amplitude jump degree; And according to the phase characteristic mark, the phase change situation is analyzed in the reflected signal waveform data, the overall area of ​​the phase change in the reflected signal waveform data and the area formed by the phase mutation in the reflected signal waveform data are obtained, and the area formed by the phase mutation in the reflected signal waveform data and the overall area of ​​the phase change in the reflected signal waveform data are calculated to obtain the phase jump abruptness; the amplitude jump abruptness, the phase jump abruptness and the amplitude kurtosis are multiplied to obtain the void edge clarity factor; It should be further explained that, in the specific implementation process, the area of ​​the overall amplitude change in the reflected signal waveform data refers to the area enclosed by the signal curve corresponding to all the amplitude change situations reflected by the amplitude characteristic mark in the reflected signal waveform data and the horizontal axis, the area formed by the discontinuous points in the reflected signal waveform data refers to the total area enclosed by all discontinuous points in the signal curve corresponding to all the amplitude change situations reflected by the amplitude characteristic mark in the reflected signal waveform data and the horizontal axis, the area of ​​the overall phase change in the reflected signal waveform data refers to the area enclosed by the signal curve corresponding to all the phase change situations reflected by the phase characteristic mark in the reflected signal waveform data and the horizontal axis, and the area formed by the phase mutation in the reflected signal waveform data refers to the area enclosed by the signal curve corresponding to the phase flip reflected by the phase characteristic mark in the reflected signal waveform data and the horizontal axis; The reflected signal waveform data of the amplitude characteristic mark and the phase characteristic mark corresponding to the characteristic relationship are divided into a number of small signal windows through the characteristic relationship, and the obtained small signal windows are subjected to Fourier transform to obtain a frequency-time image, and the frequency values ​​in the obtained frequency-time image are subjected to variance calculation to obtain the void edge slip factor; The tunnel sweep coefficient is set, and the tunnel sweep coefficient is related to the humidity in the tunnel. The tunnel sweep coefficient, the void edge factor, and the void edge sliding factor are multiplied to obtain the sinking factor, and the sinking factor refers to the data of the void edge point corresponding to the characteristic relationship.

[0017] It should be further explained that, in the specific implementation process, the cavity behind the tunnel is evaluated according to the cavity factor, and the process of obtaining the cavity defect evaluation value is as follows: According to the characteristic relationship and the collapse factor, the edges of each cavity are analyzed as a whole, and the collapse factor of each cavity is numerically integrated to obtain the cavity defect assessment value; the cavity defect assessment value is marked to the corresponding position of the tunnel frame model to obtain the tunnel assessment model; the tunnel assessment model is sent to tunnel engineering personnel to plan reinforcement plans and preventive measures, and the tunnel is reinforced through the tunnel assessment model, reinforcement plan and preventive measures.

[0018] like Figure 2 As shown, in another embodiment of the present invention, the present invention further discloses a detection system for a cavity behind a tunnel, including a management center, wherein the management center is communicatively connected to a tunnel signal acquisition module, a tunnel signal analysis module, a tunnel signal processing module, and a tunnel evaluation module: The tunnel signal acquisition module is used to collect tunnel signal data and tunnel visual image data, and establish a tunnel framework model according to the tunnel visual image data; The tunnel signal analysis module is used to obtain cavity information data according to the tunnel signal data and the tunnel framework model, and to obtain cavity characteristic data and cavity edge points according to the cavity information data; The tunnel signal processing module is used to obtain a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtain a hole sink factor according to the hole clarity factor and the hole smoothness factor; The tunnel assessment module is used to assess the cavity behind the tunnel according to the cavity factor to obtain a cavity defect assessment value.

[0019] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for detecting a cavity behind a tunnel, characterized in that: The following steps are involved: Step S1: collecting tunnel signal data and tunnel visual image data, and establishing a tunnel framework model according to the tunnel visual image data; Step S2: obtaining cavity information data according to the tunnel signal data and the tunnel framework model, and obtaining cavity characteristic data and cavity edge points according to the cavity information data; Step S3: obtaining a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtaining a hole sink factor according to the hole clarity factor and the hole smoothness factor; Step S4: Evaluate the cavity behind the tunnel according to the cavity factor to obtain a cavity defect evaluation value.

2. A method for detecting a cavity behind a tunnel according to claim 1, characterized in that: The process of collecting tunnel signal data and tunnel visual image data and establishing a tunnel framework model based on the tunnel visual image data includes: The tunnel signal data includes reflected signal waveform data and arrival time; the tunnel visible image data includes tunnel overall structure image data and image acquisition time; Set up a signal transmitting end and a tunnel collecting end; collect tunnel signal data through the signal transmitting end, and collect tunnel visible image data through the tunnel collecting end; According to the tunnel visual image data, tunnel characteristic data and tunnel dimension data are obtained; a tunnel physical model is established according to the tunnel dimension data, and model details of the tunnel physical model are constructed according to the tunnel characteristic data to obtain a tunnel framework model.

3. A method for detecting a cavity behind a tunnel according to claim 2, characterized in that: According to the tunnel signal data and the tunnel framework model, the process of obtaining the cavity information data includes: Obtain the propagation speed of the electromagnetic wave in the tunnel air, and obtain the depth of the cavity position according to the propagation speed and the arrival time; obtain the correction coefficient, and obtain the corrected depth of the cavity position according to the correction coefficient and the cavity position depth; According to the reflected signal waveform data of the tunnel signal data, the amplitude and phase of the reflected signal are obtained; an amplitude identification unit and a phase identification unit are set; the amplitude peak value and the phase of the reflected signal are respectively obtained by the amplitude identification unit and the phase identification unit; an amplitude peak change threshold and a phase change threshold are set; the amplitude peak value of the reflected signal is continuously obtained by the amplitude identification unit, and the hole amplitude signal data is obtained according to the amplitude peak change threshold and the amplitude peak value; the phase of the reflected signal is continuously obtained by the phase identification unit, and the hole phase signal data is obtained according to the phase change threshold and the phase; The cavity morphology data is obtained according to the cavity amplitude signal data and the cavity phase signal data, and the cavity range data is obtained according to the cavity position correction depth, the cavity morphology data and the tunnel frame model. The cavity amplitude signal data, the cavity phase signal data and the cavity range data are recorded as cavity information data.

4. A method for detecting a cavity behind a tunnel according to claim 3, characterized in that: According to the void information data, the process of obtaining void characteristic data and void edge points includes: According to the hole amplitude signal data, the hole phase signal data and the hole range data, a hole amplitude signal segment and a hole phase signal segment are obtained; and the amplitude value of the hole amplitude signal segment and the phase value of the hole phase signal segment are obtained; according to the hole amplitude signal data and the amplitude value, an amplitude floating value is obtained, and according to the amplitude floating value, an amplitude reference value is obtained; according to the amplitude floating value and the amplitude reference value, amplitude characteristic data is obtained; according to the hole phase signal data and the phase value, a phase floating value is obtained, and according to the phase floating value, a phase reference value is obtained; according to the phase floating value and the phase reference value, phase characteristic data is obtained; according to the amplitude characteristic data and the phase characteristic data, hole characteristic data is obtained; The hole edge data is obtained according to the hole characteristic data and the hole range data, and the hole edge simulation image is obtained according to the hole edge data and the hole range data, and the hole edge point is obtained according to the hole edge simulation image.

5. A method for detecting a cavity behind a tunnel according to claim 4, characterized in that: According to the cavity characteristic data, the process of obtaining the cavity edge clarity factor and the cavity edge sliding factor includes: According to the void characteristic data and the void edge points, a characteristic relationship is obtained; according to the characteristic relationship, the void characteristic data and the amplitude characteristic data, each amplitude integral peak range in the amplitude characteristic data is obtained, and according to the amplitude peak value and the amplitude integral peak range, the peak edge m and the peak edge n are obtained; according to the peak edge m and the peak edge n, the peak width value is obtained, and according to the amplitude peak value and the peak width value, the amplitude kurtosis is obtained; According to the amplitude characteristic data and the phase characteristic data, an amplitude characteristic mark and a phase characteristic mark are obtained; according to the amplitude characteristic mark and the reflected signal waveform data, an area of ​​the entire amplitude change in the reflected signal waveform data and an area formed by discontinuous points in the reflected signal waveform data are obtained; and according to the area formed by the discontinuous points in the reflected signal waveform data and the area of ​​the entire amplitude change in the reflected signal waveform data, an amplitude jump degree is obtained; According to the phase characteristic mark and the reflected signal waveform data, the area of ​​the overall phase change in the reflected signal waveform data and the area formed by the phase mutation in the reflected signal waveform data are obtained; according to the area formed by the phase mutation in the reflected signal waveform data and the area of ​​the overall phase change in the reflected signal waveform data, the phase jump abruptness is obtained; according to the amplitude jump abruptness, the phase jump abruptness and the amplitude kurtosis, the hole edge clarity factor is obtained; The reflected signal waveform data of the amplitude characteristic mark and the phase characteristic mark corresponding to the characteristic relationship are divided into several small signal windows through the characteristic relationship, and the obtained small signal windows are subjected to Fourier transform to obtain the frequency-time image, and the void edge slip factor is obtained according to the frequency-time image.

6. A method for detecting a cavity behind a tunnel according to claim 5, characterized in that: According to the void edge clearing factor and the void edge sliding factor, the process of obtaining the sinkhole factor includes: Set the tunnel sweep coefficient, and obtain the sinkhole factor based on the tunnel sweep coefficient, the void edge clearance factor, and the void edge sliding factor.

7. A method for detecting a cavity behind a tunnel according to claim 6, characterized in that: The process of evaluating the cavity behind the tunnel according to the cavity factor and obtaining the cavity defect evaluation value includes: According to the characteristic relationship and the collapse factor, the cavity defect assessment value is obtained; the cavity defect assessment value is marked to the corresponding position of the tunnel frame model to obtain the tunnel assessment model; the tunnel assessment model is sent to the tunnel engineering personnel to plan the reinforcement plan and preventive measures, and the tunnel is reinforced through the tunnel assessment model, reinforcement plan and preventive measures.

8. A detection system for a cavity behind a tunnel, specifically applied to a detection method for a cavity behind a tunnel as claimed in any one of claims 1 to 7, comprising a management center, characterized in that: The management center is communicatively connected to a tunnel signal acquisition module, a tunnel signal analysis module, a tunnel signal processing module and a tunnel evaluation module: The tunnel signal acquisition module is used to collect tunnel signal data and tunnel visual image data, and establish a tunnel framework model according to the tunnel visual image data; The tunnel signal analysis module is used to obtain cavity information data according to the tunnel signal data and the tunnel framework model, and to obtain cavity characteristic data and cavity edge points according to the cavity information data; The tunnel signal processing module is used to obtain a hole clarity factor and a hole smoothness factor according to the hole characteristic data, and obtain a hole sink factor according to the hole clarity factor and the hole smoothness factor; The tunnel assessment module is used to assess the cavity behind the tunnel according to the cavity factor to obtain a cavity defect assessment value.

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