Flat spectrum detector for cable tunnel, crack measuring method and storage medium

Abstract

The invention discloses a cable tunnel flat spectrum detector, a crack measuring method and a storage medium, and relates to the technical field of tunnel cracks, and the cable tunnel flat spectrum detector comprises a flat spectrum detection module, a signal processing module, a data storage module, a data comparison and analysis module and a display. A plurality of standard crack test pieces with different crack depths or lengths and frequency spectrum characteristic information of crack-free standard test pieces are pre-stored in the data storage module; the signal processing module compares the reference spectrum of the crack-free standard test piece with the spectrum detected by the flat spectrum detection module, screens out a newly added characteristic peak and a frequency deviation peak as characteristic peaks to be detected, and calculates spectrum characteristic information; and the data comparison and analysis module is used for matching the current spectrum characteristic information with the spectrum characteristic information of the standard crack test piece in the crack parameter database to obtain crack parameters. Traditional cable tunnel detection depends on local ultrasonic flaw detection, hysteresis exists, and early-stage tiny cracks are difficult to find; in order to overcome the hysteresis, cracks are found in a full-time monitoring mode through a flat spectrum detection module.

Description

Technical Field

[0001] This invention relates to the field of tunnel crack technology, specifically to a cable tunnel flat spectrum detector, a method for measuring cracks, and a storage medium. Background Technology

[0002] Traditional cable tunnel inspection relies on manual visual inspection or local ultrasonic testing. Existing detection technologies are lagging and difficult to detect early micro-cracks. To overcome this lag, there is an urgent need for a cable tunnel flat-spectrum detector with early warning capabilities and a method for measuring cracks. Summary of the Invention

[0003] To address the aforementioned technical shortcomings, the present invention aims to provide a cable tunnel flat spectrum detector with early warning capability, a method for measuring cracks, and a storage medium.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A cable tunnel flat spectrum detector includes a flat spectrum detection module, a signal processing module, a data storage module, and a data comparison and analysis module. The flat spectrum detection module includes a multi-band acoustic wave emission array and a piezoelectric sensor array; A multi-band acoustic wave emitting array is set at a preset position on or inside the surface of the concrete structure to be inspected, and a piezoelectric sensor array is set inside the cable tunnel flat spectrum detector. The multi-band acoustic wave emitting array excites acoustic waves, and the piezoelectric sensor array receives the reflected acoustic wave signals. The data storage module is used to record the detection data of the cable tunnel flat spectrum detector and is equipped with a crack parameter database. The crack parameter database contains spectral characteristic information of multiple standard cracked specimens with different crack depths or lengths and crack-free standard specimens without cracks, and stores crack parameters including crack depth and length. The signal processing module is used to filter the acoustic wave reflection signal received by the piezoelectric sensor array and use fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module is used to preprocess the spectrum; identify all peak points in the spectrum that exceed a preset threshold, record the center frequency f and amplitude A corresponding to the peak points; and by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, select the newly added characteristic peaks and frequency offset peaks as the characteristic peaks to be detected, and calculate the spectral characteristic information of the characteristic peaks to be detected. The data comparison and analysis module matches the current spectral characteristic information, harmonic amplitude ratio, and spectral characteristic information of standard crack specimens in the crack parameter database to obtain crack parameters. The spectral characteristics of the characteristic peak to be detected include at least the characteristic frequency, frequency band energy, and harmonic amplitude ratio.

[0005] Furthermore, the data comparison and analysis module matches the spectral feature information of the standard crack specimen using an Euclidean distance algorithm or a cosine similarity algorithm.

[0006] Furthermore, the preset threshold is set to 1.5-2 times the average amplitude of the spectrum. Furthermore, it also includes a GPS positioning module, which is used to collect coordinates of the installation location of the multi-band acoustic wave transmitting array.

[0007] Furthermore, it also includes an environmental sensing module, which measures the water pressure and humidity of the cable tunnel using a water pressure sensor and a humidity sensor.

[0008] A method for measuring cracks includes the following steps: when a cable tunnel flat spectrum detector moves along the tunnel axis, a multi-band acoustic wave emitting array excites acoustic waves towards the multi-band acoustic wave emitting array on the tunnel wall, and a piezoelectric sensor array receives the reflected acoustic wave signals; The signal processing module filters the acoustic wave reflection signal received by the piezoelectric sensor array and uses fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module preprocesses the spectrum; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, it selects the newly added characteristic peaks and frequency shift peaks as the characteristic peaks to be detected, and calculates the spectral characteristic information of the characteristic peaks to be detected. The data comparison and analysis module matches the current spectral feature information with the spectral feature information of standard crack specimens in the crack parameter database to obtain the crack parameters.

[0009] Furthermore, the signal processing module stores the geometric parameters of the crack in real time to the data storage module and synchronizes them to the cloud. The data comparison and analysis module calls historical data from the data storage module to perform trend comparison, and triggers an alert when the following conditions are detected: Yellow alert: Crack propagation rate > 0.1 mm / month and depth < 5 mm; Orange alert: Crack depth ≥ 5mm and water seepage ≤ 10L / min; Red alert: Crack depth ≥ 5mm and water seepage rate > 10L / min.

[0010] Furthermore, a computer-readable storage medium stores a plurality of instructions that can be read by a processor and executed using the aforementioned method.

[0011] The technical benefits achieved include: early warning capability: it can detect cracks as small as 0.3mm, improving sensitivity by 80% compared to traditional technologies; and quantitative analysis advantages: depth measurement error ≤ ±0.1mm, length error ≤ ±2cm. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the connection of the cable tunnel flat spectrum detector provided by the present invention. Detailed Implementation

[0014] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] See Figure 1 As shown, a cable tunnel flat spectrum detector includes a flat spectrum detection module, a signal processing module, a data storage module, and a data comparison and analysis module.

[0016] The flat-spectrum detection module includes a multi-band acoustic wave transmitting array and a piezoelectric sensor array. By emitting acoustic waves and receiving their reflected signals, it detects cracks in concrete structures.

[0017] A multi-band acoustic wave emitting array is positioned at a predetermined location on or inside the concrete structure to be inspected. A piezoelectric sensor array is housed inside the cable tunnel flat-spectrum detector. The multi-band acoustic wave emitting array excites sound waves, and the piezoelectric sensor array receives the reflected sound wave signals. This module primarily measures the propagation and reflection signals of sound waves excited by the multi-band acoustic wave emitting array within the concrete structure. These signals are captured by the piezoelectric sensor array in a three-dimensional arrangement.

[0018] The data storage module records the detection data from the cable tunnel flat-spectrum detector and includes a crack parameter database. The detection data includes storage of data such as detection time, crack parameters (depth, length), and environmental data (humidity, water pressure), as well as historical and current detection data extracted from the data storage module.

[0019] The crack parameter database in the data storage module contains spectral characteristic information for multiple crack depths, or spectral characteristic information for crack-free standard specimens, and stores crack parameters including crack depth and length. The standard cracked specimens and crack-free standard specimens have the same external dimensions, but the standard cracked specimens themselves have cracks of varying depths and lengths.

[0020] Specifically, the data storage module can encrypt storage devices (such as SD cards) and cloud servers. Installation locations include inside the testing equipment and in remote data centers. Data is encrypted and archived according to timestamps before storage, ensuring data security and traceability. Each test generates an independent data packet, facilitating subsequent data management and analysis. Simultaneously, it supports dual-channel storage via SD cards and the cloud, improving data reliability and accessibility.

[0021] The signal processing module directly processes the filtered signal from the flat spectrum detection module. It is used to filter the acoustic wave reflection signal received by the piezoelectric sensor array to remove environmental noise, and uses fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum.

[0022] The raw signal collected by the piezoelectric sensor array is first filtered to remove environmental noise. The time-domain signal is then converted into a frequency-domain signal using Fast Fourier Transform (FFT) technology. The spectrum after FFT is then windowed (e.g., Hanning window, Blackman window) to reduce false peaks caused by spectral leakage. Finally, the spectrum curve is smoothed by moving average filtering or wavelet thresholding to highlight the true crack characteristic peaks.

[0023] The signal processing module is also used to preprocess the spectrum to reduce false peaks caused by spectral leakage and smooth the spectral curve; identify all peak points in the spectrum that exceed a preset threshold, and record the center frequency f and amplitude A corresponding to the peak points; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, the module selects newly added characteristic peaks and frequency offset peaks as characteristic peaks to be detected, and calculates the spectral characteristic information of the characteristic peaks to be detected.

[0024] An adaptive thresholding method (with the threshold set at 1.5-2 times the average amplitude of the spectrum) is used to automatically identify all peak points in the spectrum that exceed the threshold, and record their center frequency (f) and amplitude (A) to calculate the harmonic amplitude ratio. Crack feature screening is also required: based on the acoustic properties of concrete, features related to cracks are screened from the identified peaks: by comparing the baseline spectrum of a crack-free standard specimen, new characteristic peaks (such as the 5kHz high-frequency peak generated by scattering from the crack interface) are screened; frequency shift peaks (such as the 10kHz fundamental frequency shifting left to 9.8kHz due to a decrease in structural stiffness) are screened; and characteristic peaks and frequency band energy are calculated (energy values ​​within a 500Hz bandwidth are calculated by integration) as auxiliary features.

[0025] The data comparison and analysis module matches the current spectral characteristic information, harmonic amplitude ratio, and spectral characteristic information of standard crack specimens in the crack parameter database to obtain crack parameters; The spectral characteristics of the characteristic peak to be detected include at least the characteristic frequency, frequency band energy, and harmonic amplitude ratio.

[0026] The raw signal acquired by the piezoelectric sensor is first filtered to remove environmental noise. Then, the time-domain signal is converted to a frequency-domain signal using Fast Fourier Transform (FFT) technology. The FFT spectrum is then "windowed" to reduce spurious peaks caused by spectral leakage. Simultaneously, in concrete without cracks, the spectrum of sound wave propagation exhibits a "continuous smooth peak," while cracks cause unique resonant frequency shifts or new characteristic peaks due to "sound wave reflection / scattering." Based on the acoustic properties of concrete, features related to cracks are screened from the identified peaks: new characteristic peaks are identified by comparing the spectrum with that of a standard specimen without cracks; frequency shift peaks are identified (e.g., a left shift of the 10kHz fundamental frequency to 9.8kHz due to a decrease in structural stiffness); and the half-maximum width (FWHM) and frequency band energy of the characteristic peaks are calculated as auxiliary features. Cable tunnels contain interference from cable heat dissipation noise, emergency light stray light, and humidity fluctuations, which traditional detection methods easily cause "signal confusion." Misjudgment or omission, while the newly added characteristic peaks and frequency shift peaks have "anti-interference specificity" and can exclude the influence of non-crack factors.

[0027] An adaptive thresholding method is also required to automatically identify all peak points in the spectrum that exceed the threshold and record their center frequency (f) and amplitude (A). The harmonic amplitude ratio is calculated using f and a. Crack parameters can be calculated using the harmonic amplitude ratio, combined with characteristic frequencies and frequency band energy. By comparing with standard specimens, the corresponding crack parameters can be output.

[0028] The Euclidean distance algorithm is preferred for calculating similarity. Let the eigenvector of a certain standard entry in the crack parameter database be X=(x1, x2, x3) (x1= characteristic frequency, x2= frequency band energy, x3= harmonic amplitude ratio); the harmonic amplitude ratio is calculated from the ratio of the center frequency (f) to the amplitude.

[0029] The on-site detection feature vector is Y=(y1, y2, y3), (y1= characteristic frequency, y2= frequency band energy, y3= harmonic amplitude ratio). Calculate the distance: d = √[(x1-y1)² + (x2-y2)² + (x3-y3)²], that is, d 2= [(x1-y1)²+(x2-y2)²+(x3-y3)²]; the smaller the d value, the higher the similarity.

[0030] Select the standard item with the smallest distance and output its corresponding crack parameters (e.g., depth = 0.3mm, length = 3mm).

[0031] Find the best matching standard specimen and directly output the corresponding crack parameters (e.g., a specimen with a depth of 0.3 mm and a length of 3 mm is matched).

[0032] In a preferred embodiment, a display is also included to show crack parameters. The display visually presents data at various time points.

[0033] During operation, as the detector moves along the tunnel axis, the acoustic wave emission array radiates composite frequency acoustic waves towards the tunnel wall. The piezoelectric sensor receives the reflected signal, which is then filtered by an adaptive filtering unit to remove environmental noise interference. The signal processing module converts the time-domain signal into a frequency-domain feature spectrum and calculates the geometric parameters of the crack (depth accuracy ±0.1mm, length accuracy ±2cm) by matching the concrete acoustic parameters in the material database. The detection data is stored in real-time and synchronized to the cloud. The analysis module retrieves historical data for trend comparison and triggers an alert when the following conditions are detected: Yellow alert: Crack propagation rate > 0.1 mm / month and depth < 5 mm; Orange alert: Crack depth ≥ 5mm; Red alert: Through-cracks accompanied by water seepage >10L / min.

[0034] In a preferred embodiment, the spectral characteristic information of the characteristic peak to be detected includes at least the characteristic frequency and the frequency band energy; The data comparison and analysis module matches the spectral feature information of standard crack specimens using Euclidean distance algorithm or cosine similarity algorithm.

[0035] In a preferred embodiment, the preset threshold is set to 1.5-2 times the average amplitude of the spectrum. In a preferred embodiment, the GPS positioning module is used to acquire coordinates of the installation location of the multi-band acoustic wave transmitting array, and the display shows the coordinates of the crack. The detection data includes measurement data from the GPS positioning module.

[0036] It also includes an environmental sensing module, which measures the water pressure and humidity of the cable tunnel through water pressure and humidity sensors and displays the data on a monitor.

[0037] A method for measuring cracks using a cable tunnel flat spectrum detector includes the following steps: when the cable tunnel flat spectrum detector moves along the tunnel axis, a multi-band acoustic wave emitting array excites acoustic waves toward the multi-band acoustic wave emitting array on the tunnel wall, and a piezoelectric sensor array receives the reflected acoustic wave signal. The signal processing module filters the acoustic wave reflection signal received by the piezoelectric sensor array and uses fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module preprocesses the spectrum; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, it selects the newly added characteristic peaks and frequency shift peaks as the characteristic peaks to be detected, and calculates the spectral characteristic information of the characteristic peaks to be detected. The data comparison and analysis module matches the current spectral characteristic information, harmonic amplitude ratio, and spectral characteristic information of standard crack specimens in the crack parameter database to obtain crack parameters; The spectral characteristics of the characteristic peak to be detected include at least the characteristic frequency, frequency band energy, and harmonic amplitude ratio.

[0038] Furthermore, the signal processing module stores the geometric parameters of the crack in real time to the data storage module and synchronizes them to the cloud. The data comparison and analysis module calls historical data from the data storage module to perform trend comparison, and triggers an alert when the following conditions are detected: Yellow alert: Crack propagation rate > 0.1 mm / month and depth < 5 mm; Orange alert: Crack depth ≥ 5mm and water seepage ≤ 10L / min; Red alert: Crack depth ≥ 5mm and water seepage rate > 10L / min.

[0039] Furthermore, a maintenance priority list for production tunnels based on different levels of early warning is provided.

[0040] A computer-readable storage medium storing multiple instructions that can be read and executed by a processor: When the cable tunnel flat spectrum detector moves along the tunnel axis, the multi-band acoustic wave emitting array excites acoustic waves towards the tunnel wall multi-band acoustic wave emitting array, and the piezoelectric sensor array receives the acoustic wave reflection signal; The signal processing module filters the acoustic wave reflection signal received by the piezoelectric sensor array and uses fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module preprocesses the spectrum; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, it selects the newly added characteristic peaks and frequency shift peaks as the characteristic peaks to be detected, and calculates the spectral characteristic information of the characteristic peaks to be detected. The data comparison and analysis module matches the current spectral feature information with the spectral feature information of standard crack specimens in the crack parameter database to obtain the crack parameters.

[0041] The signal processing module stores the geometric parameters of the crack in real time to the data storage module and synchronizes them to the cloud. The data comparison and analysis module calls historical data from the data storage module to compare trends. An early warning is triggered when the following conditions are detected: Yellow warning: Crack propagation rate > 0.1 mm / month and depth < 5 mm; Orange alert: Crack depth ≥ 5mm and water seepage ≤ 10L / min; Red alert: Crack depth ≥ 5mm and water seepage rate > 10L / min.

[0042] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0043] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0044] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0045] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0046] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0047] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0048] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A cable tunnel flat spectrum detector, characterized in that, It includes a spectrum detection module, a signal processing module, a data storage module, and a data comparison and analysis module. The flat spectrum detection module includes a multi-band acoustic wave emission array and a piezoelectric sensor array; A multi-band acoustic wave emitting array is set at a preset position on or inside the surface of the concrete structure to be inspected, and a piezoelectric sensor array is set inside the cable tunnel flat spectrum detector. The multi-band acoustic wave emitting array excites acoustic waves, and the piezoelectric sensor array receives the reflected acoustic wave signals. The data storage module is used to record the detection data of the cable tunnel flat spectrum detector and is equipped with a crack parameter database. The crack parameter database contains spectral characteristic information of multiple standard cracked specimens with different crack depths or lengths and crack-free standard specimens without cracks, and stores crack parameters including crack depth and length. The signal processing module is used to filter the acoustic wave reflection signal received by the piezoelectric sensor array and use fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module is used to preprocess the spectrum; identify peak points in the spectrum that exceed a preset threshold, record the center frequency f and amplitude A corresponding to the peak points to calculate the harmonic amplitude ratio; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, the newly added characteristic peaks and frequency shift peaks are selected as the characteristic peaks to be detected, and the spectral characteristic information of the characteristic peaks to be detected is calculated. The data comparison and analysis module matches the current spectral characteristic information, harmonic amplitude ratio, and spectral characteristic information of standard crack specimens in the crack parameter database to obtain crack parameters. The spectral characteristics of the characteristic peak to be detected include at least the characteristic frequency, frequency band energy, and harmonic amplitude ratio.

2. The cable tunnel flat spectrum detector according to claim 1, characterized in that, The data comparison and analysis module matches the spectral feature information of the standard crack specimen using the Euclidean distance algorithm or the cosine similarity algorithm.

3. The cable tunnel flat spectrum detector according to claim 1, characterized in that, The preset threshold is set to 1.5-2 times the average amplitude of the spectrum.

4. The cable tunnel flat spectrum detector according to claim 1, characterized in that, It also includes a GPS positioning module, which is used to collect coordinates of the installation location of the multi-band acoustic wave transmitting array.

5. A cable tunnel flat spectrum detector according to claim 1, characterized in that, It also includes an environmental sensing module, which measures the water pressure and humidity of the cable tunnel using a water pressure sensor and a humidity sensor.

6. The cable tunnel flat spectrum detector according to claim 1, characterized in that, The signal processing module reduces spurious peaks by applying a windowing process.

7. A cable tunnel flat spectrum detector according to claim 1, characterized in that, The signal processing module smooths the spectral curve by using moving average filtering or wavelet threshold denoising.

8. The method for measuring cracks in cable tunnels using a flat-spectrum detector according to any one of claims 1-7, characterized in that, Includes the following steps: When the cable tunnel flat spectrum detector moves along the tunnel axis, the multi-band acoustic wave emitting array excites acoustic waves towards the multi-band acoustic wave emitting array on the tunnel wall, and the piezoelectric sensor array receives the acoustic wave reflection signal. The signal processing module filters the acoustic wave reflection signal received by the piezoelectric sensor array and uses fast Fourier transform to convert the time domain signal into a frequency domain signal to obtain the spectrum. The signal processing module preprocesses the spectrum; by comparing the reference spectrum of the crack-free standard specimen in the crack parameter database with the current spectrum, it selects the newly added characteristic peaks and frequency offset peaks as the characteristic peaks to be detected, and calculates the spectral characteristic information of the characteristic peaks to be detected; it identifies the peak points in the spectrum that exceed the preset threshold, and records the center frequency f and amplitude A corresponding to the peak points to calculate the harmonic amplitude ratio; The data comparison and analysis module matches the current spectral characteristics, harmonic amplitude ratio, and spectral characteristics of standard crack specimens in the crack parameter database to obtain crack parameters.

9. The method for measuring cracks according to claim 8, characterized in that, The signal processing module stores the geometric parameters of the crack in real time to the data storage module and synchronizes them to the cloud. The data comparison and analysis module calls historical data from the data storage module to perform trend comparison and triggers an alert when the following conditions are detected: Yellow alert: Crack propagation rate > 0.1 mm / month and depth < 5 mm; Orange alert: Crack depth ≥ 5mm and water seepage ≤ 10L / min; Red alert: Crack depth ≥ 5mm and water seepage rate > 10L / min.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions, which can be read by a processor and executed according to any one of claims 8 to 9.

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