Non-metallic drain pipe water filling rate detection method

Abstract

The application belongs to the technical field of water supply and drainage pipeline detection, and provides a non-metallic drainage pipe water filling rate detection method, which comprises the following steps: obtaining ground penetrating radar data of a non-metallic drainage pipeline; pre-processing the radar data to enhance the pipeline signal; detecting a pipeline vertex signal in a B-Scan image and extracting an A-Scan signal at the vertex; obtaining two-way travel time of the top and bottom of the pipeline according to the A-Scan signal, and calculating a virtual radius of the pipeline; and calculating the water filling rate of the pipeline according to the virtual pipe diameter calculation result and in combination with the real radius of the pipeline. The pipeline type is determined to be a full pipe or a non-full pipe in a non-destructive state, thereby providing an efficient and reliable detection means for the maintenance and management of underground pipelines.

Description

Technical Field

[0001] This invention belongs to the field of water supply and drainage pipeline testing technology, and particularly relates to a method for testing the water filling rate of non-metallic drainage pipes. Background Technology

[0002] Drainage pipes, as a crucial component of urban drainage systems, are fundamental structures ensuring water recycling and ecological safety. However, varying degrees of pollutant accumulation exist in urban drainage systems worldwide. When siltation occurs, the hydraulic state within the pipe gradually changes from free surface flow to pressurized flow as the flow rate increases, and the hydraulic bottleneck formed by siltation continuously raises the upstream water level. This obstruction effect results in a high water-filling rate upstream of the silted section due to backwater, while the downstream section experiences a relatively lower water-filling rate as the flow cross-section recovers. Because siltation has a direct and significant impact on the size of the flow cross-section within the pipe, research on drainage pipe siltation typically uses the water-filling rate as an indicator to quantify the degree of siltation.

[0003] Determining the liquid filling level of pipelines under complex conditions such as settlement is a challenge for supporting efficient pipeline maintenance and management and ensuring the safe and stable operation of urban underground pipe networks. Current methods for detecting pipeline water filling rates mainly use closed-circuit television (CCTV) or sonar, which have limitations in practical applications. Limited by lighting conditions and the pipe environment, CCTV cannot provide clear images in complex pipeline environments and requires maintaining a low water level within the pipeline to prevent the camera from being submerged. On the other hand, since sound waves can hardly propagate in air, sonar must operate in a liquid medium, meaning the pipeline must be full, and water flow can severely interfere with the sound signal, affecting accuracy. Neither method has the potential for intelligent detection and is difficult to implement in real-time monitoring of large-scale pipe networks. Ground-penetrating radar (GPR), as a non-destructive detection technology, has been widely used in the field of underground pipeline inspection in recent years. Electromagnetic flowmeters (GPR) offer advantages such as high detection speed, wide coverage, and ease of operation. By emitting high-frequency electromagnetic waves and receiving reflected signals, they acquire the electromagnetic properties of the underground medium, allowing for the determination of water level and sedimentation information without contacting the pipe's interior. This results in higher detection efficiency and a wider range of applications. For metal drainage pipes, water levels can be directly measured using common devices such as electromagnetic flowmeters and conductivity sensors. However, for non-metallic drainage pipes, the insulating materials cannot form a closed current loop, necessitating alternative methods such as acoustic and optical approaches. GPR detection of water levels in metal pipes relies on reflected signals, but non-metallic pipes are transparent to radar waves, resulting in relatively weak detection signals. This necessitates higher-frequency radar and solutions to signal attenuation issues. Currently, there is no research on using GPR to determine the water level of non-metallic pipes.

[0004] In summary, the existing technologies suffer from several problems: a lack of robust testing methods for complex pipeline environments; and the inability of existing water-filling rate testing methods to accurately measure the water level inside non-metallic drainage pipes. Therefore, further research is needed to explore new methods for detecting the water-filling rate of non-metallic pipelines, thereby improving the intelligence level of drainage pipeline operation and maintenance to meet the needs of urban infrastructure construction and pipeline maintenance. Summary of the Invention

[0005] This invention aims to address the challenge of detecting the water filling rate of non-metallic drainage pipes by proposing a new method that combines deep learning, signal processing, and underground exploration technologies. This method improves the existing water filling rate detection process, enhances detection accuracy and efficiency, and provides reliable technical support for urban infrastructure construction and management.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] This invention provides a method for detecting the water filling rate of non-metallic drainage pipes, comprising:

[0008] (1) Obtain ground-penetrating radar data of buried non-metallic pipelines;

[0009] (2) Perform image preprocessing on the B-Scan image in the ground penetrating radar data;

[0010] (3) Detect the pipe vertices in the B-Scan image after image preprocessing and extract the A-Scan signal at the vertices;

[0011] (4) Obtain the two-way travel time at the top and bottom of the pipe based on the A-Scan signal, and calculate the virtual radius of the pipe;

[0012] (5) Calculate the water filling rate of the pipe based on the virtual pipe diameter calculation results and the actual pipe radius.

[0013] Furthermore, the image preprocessing operation employs a nonlinear time gain algorithm;

[0014] Wherein, let the B-Scan image after background removal be... A-Scan of the number of channels and The matrix composed of the nth sampling points, for the nth sampling point The first line A-Scan signal For the first one The gain compensation calculation method for each sampling point is as follows:

[0015] ;

[0016] ;

[0017] In the formula, The signal after gain. for This is the gain coefficient. As the base for gain growth, The time gain increases exponentially with depth. This is the depth scaling factor, used to control the steepness of the gain curve. This is the baseline offset, used to suppress shallow layers (when... (When the noise level is low) Noise amplification; To limit the gain, avoid deep layers (when) (When the noise level is high) Noise overshoot.

[0018] Furthermore, the pipe vertex detection operation employs a symmetry algorithm, and the symmetry curve of the B-Scan image is represented as follows:

[0019] ;

[0020] In the formula, These are the x and y coordinate values ​​of the B-Scan image. For the pixel value at the corresponding coordinates, with the first... Using the column as the axis of symmetry, calculate the distance between the left and right sides. symmetry, It is the image width. It is the image height. It is the maximum column width used to calculate symmetry;

[0021] The pipeline signal appears as a hyperbola in the B-Scan image, and the minimum position where the symmetry curve changes abruptly is the vertex position of the pipeline hyperbola signal.

[0022] Furthermore, the virtual radius of the pipeline is expressed as:

[0023] ;

[0024] ;

[0025] In the formula, For the virtual radius of the pipeline, and The two-way travel time of the reflected signals from the top and bottom of the pipe are respectively. The speed at which electromagnetic waves propagate in water. The speed of light in a vacuum. is the relative permittivity of water.

[0026] Furthermore, the water filling rate is calculated from the virtual radius and the actual radius of the pipe;

[0027] by Indicates the actual radius of the pipe, in and These represent the electromagnetic wave propagation times for the gas phase and water phase in the pipe, respectively. Their sum is the reflected wave delay between the top and bottom of the pipe.

[0028] ;

[0029] ;

[0030] ;

[0031] In the formula, The water filling rate of the pipeline, according to the definition of the virtual radius of the pipeline, is expressed as:

[0032] .

[0033] The present invention has the following beneficial effects:

[0034] (1) This invention preprocesses non-metallic pipeline radar data using a nonlinear time gain algorithm; extracts the symmetry curve of pipeline signals using a symmetry algorithm; proposes the concept of pipeline virtual radius, and uses the virtual radius and real radius to realize the calculation of pipeline water filling rate under non-destructive state, reducing underground environment and external noise interference; it has high processing efficiency and provides reliable technical support for the operation and maintenance of urban underground pipe networks.

[0035] (2) This invention can be used to determine whether the water filling type of underground pipeline is full or not. It has excellent robustness and generalization ability and is suitable for practical engineering applications. Attached Figure Description

[0036] Figure 1 This is a flowchart of the calculation method of the present invention.

[0037] Figure 2 This is a visual flowchart of the calculation method of the present invention.

[0038] Figure 3 This is a schematic diagram of the result after image preprocessing of radar data in the embodiment.

[0039] Figure 4 This is a typical sample diagram of the symmetry curve in the embodiment.

[0040] Figure 5 This is a schematic diagram illustrating the propagation time of electromagnetic waves in the gas and water phases in the embodiment.

[0041] Figure 6 This is the calculated water filling rate result from the on-site pipeline test in the embodiment.

[0042] Figure 7This is the result of the water filling rate calculation from the forward simulation experiment in the embodiment. Detailed Implementation

[0043] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments are only specific illustrations of the invention and should not be regarded as limitations on the invention. The purpose of the embodiments is to enable those skilled in the art to better understand and reproduce the technical solution of the present invention. The scope of protection of the present invention should still be determined by the scope defined in the claims.

[0044] S101 uses ground-penetrating radar and simulation software to obtain ground-penetrating radar data of buried non-metallic pipelines.

[0045] Specifically, in the field pipeline test, ground-penetrating radar was used to collect data on the buried pipeline. The pipeline cover was the original soil, and the soil dielectric constant fluctuated depending on the rainfall. Full-pipe and non-full-pipe conditions were created by calculating the pipe section volume. In the simulation software, an underground pipeline model with all parameters identical except for the water filling rate and pipeline specifications was established, and two test groups with representative water filling rates were set up: a full-pipe group and a half-full-pipe group.

[0046] S102, perform image preprocessing on the B-Scan image in the ground penetrating radar data;

[0047] The image preprocessing operation employs a nonlinear time gain algorithm;

[0048] Wherein, let the B-Scan image after background removal be... A-Scan of the number of channels and The matrix composed of the nth sampling points, for the nth sampling point The first line A-Scan signal For the first one The gain compensation calculation method for each sampling point is as follows:

[0049] ;

[0050] ;

[0051] In the formula, The signal after gain. for This is the gain coefficient. As the base for gain growth, The time gain increases exponentially with depth. This is the depth scaling factor, used to control the steepness of the gain curve. This is the baseline offset, used to suppress shallow layers (when... (When the noise level is low) Noise amplification; To limit the gain, avoid deep layers (when) (When the noise level is high) Noise overshoot.

[0052] S103, Detect the pipe vertices in the B-Scan image after image preprocessing and extract the A-Scan signal at the vertices;

[0053] The pipe vertex detection operation employs a symmetry algorithm, and the symmetry curve of the B-Scan image is represented as follows:

[0054] ;

[0055] In the formula, These are the x and y coordinate values ​​of the B-Scan image. For the pixel value at the corresponding coordinates, with the first... Using the column as the axis of symmetry, calculate the distance between the left and right sides. symmetry, It is the image width. It is the image height. It is the maximum column width used to calculate symmetry;

[0056] The pipeline signal appears as a hyperbola in the B-Scan image, and the minimum position where the symmetry curve changes abruptly is the vertex position of the pipeline hyperbola signal.

[0057] S104. Based on the A-Scan signal, obtain the two-way travel time at the top and bottom of the pipe, and calculate the virtual radius of the pipe;

[0058] The virtual radius of the pipeline is represented as:

[0059] ;

[0060] ;

[0061] In the formula, For the virtual radius of the pipeline, and The two-way travel time of the reflected signals from the top and bottom of the pipe are respectively. The speed at which electromagnetic waves propagate in water. The speed of light in a vacuum. is the relative permittivity of water.

[0062] S105, calculate the water filling rate of the pipe based on the virtual pipe diameter calculation results and the actual pipe radius.

[0063] The water filling rate is calculated from the virtual radius and the actual radius of the pipe;

[0064] by Indicates the actual radius of the pipe, in and These represent the electromagnetic wave propagation times for the gas phase and water phase in the pipe, respectively. Their sum is the reflected wave delay between the top and bottom of the pipe.

[0065] ;

[0066] ;

[0067] ;

[0068] In the formula, The water filling rate of the pipeline, according to the definition of the virtual radius of the pipeline, is expressed as:

[0069] .

[0070] Example

[0071] S101 uses ground-penetrating radar and simulation software to obtain ground-penetrating radar data of buried non-metallic pipelines.

[0072] Specifically, in the field pipeline test, ground-penetrating radar was used to collect data on the buried pipeline. The pipeline cover was original soil with a dielectric constant ranging from 3 to 9, fluctuating depending on rainfall. The pipeline burial depth ranged from 0.5m to 0.9m. Full-pipe and partial-pipe conditions were created by calculating the pipe section volume, resulting in 20 sets of real data, 10 sets each for full-pipe and partial-pipe conditions. In the simulation software, an underground pipeline model was established with all parameters identical except for the water-filling rate and pipeline specifications. The pipeline burial depth ranged from 0.6m to 1.6m, and two test groups with representative water-filling rates—full-pipe and partial-pipe groups—were set up, resulting in 36 sets of forward simulation data, 18 sets each for full-pipe and partial-pipe conditions.

[0073] S102, perform image preprocessing on the B-Scan image in the ground penetrating radar data. The preprocessed B-Scan image is shown below. Figure 3 As shown;

[0074] The image preprocessing operation employs a nonlinear time gain algorithm, which dynamically adjusts the gain coefficient to balance shallow noise suppression and deep signal enhancement.

[0075] Wherein, let the B-Scan image after background removal be... A-Scan of the number of channels and The matrix composed of the nth sampling points, for the nth sampling point The first line A-Scan signal For the first one The gain compensation calculation method for each sampling point is as follows:

[0076] ;

[0077] ;

[0078] In the formula, The signal after gain. for This is the gain coefficient. As the base for gain growth, The time gain increases exponentially with depth. This is the depth scaling factor, used to control the steepness of the gain curve; it is set to 0.01. This is the baseline offset, used to suppress shallow layers (when... When the noise level is relatively low, the amplification is set to 0.5. To limit the gain, avoid deep layers (when) When the noise is large, take 25 for overshoot.

[0079] S103, Detect the pipe vertices in the B-Scan image after image preprocessing and extract the A-Scan signal at the vertices;

[0080] The pipe vertex detection operation employs a symmetry algorithm, and the symmetry curve of the B-Scan image is represented as follows:

[0081] ;

[0082] In the formula, These are the x and y coordinate values ​​of the B-Scan image. For the pixel value at the corresponding coordinates, with the first... Using the column as the axis of symmetry, calculate the distance between the left and right sides. symmetry, It is the image width. It is the image height. It is the maximum column width for calculating symmetry, taken as 1 / 10 of the image width;

[0083] The pipeline signal appears as a hyperbola in a B-Scan image. The minimum position where the symmetry curve abruptly changes is the vertex position of the pipeline hyperbola signal. Figure 4 As shown.

[0084] S104. Based on the A-Scan signal, obtain the two-way travel time at the top and bottom of the pipe, and calculate the virtual radius of the pipe;

[0085] The virtual radius of the pipeline is represented as:

[0086] ;

[0087] ;

[0088] In the formula, For the virtual radius of the pipeline, and The two-way travel time of the reflected signals from the top and bottom of the pipe are respectively. The speed at which electromagnetic waves propagate in water. Let be the speed of light in a vacuum, and take 3 × 10⁻⁶. 8 m / s, Let be the relative permittivity of water, taken as 80.

[0089] S105, calculate the water filling rate of the pipe based on the virtual pipe diameter calculation results and the actual pipe radius.

[0090] The water filling rate is calculated from the virtual radius and the actual radius of the pipe;

[0091] by Indicates the actual radius of the pipe, in and These represent the electromagnetic wave propagation times corresponding to the gas phase and water phase in the pipeline, respectively. Figure 5 As shown, the sum of the two is the reflected wave delay between the top and bottom of the pipe:

[0092] ;

[0093] ;

[0094] ;

[0095] In the formula, The water filling rate of the pipeline, according to the definition of the virtual radius of the pipeline, is expressed as:

[0096] .

[0097] The water filling rate was calculated using data from field pipeline tests using the method of this invention, and the results are as follows: Figure 6 As shown in the figure. The water filling rate of all experimental groups was calculated accurately. The water filling rate of the forward simulation test data was calculated using the method of this invention, and the results are as follows. Figure 7 As shown, the water filling rate of all test groups was calculated accurately. Therefore, this invention can accurately detect the water filling rate of drainage pipes without damage, providing reliable technical support for urban infrastructure construction and management.

[0098] 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.

[0099] It should be noted that any technical features not described in detail in this invention can be implemented using any existing technology.

Claims

1. A method for detecting the water filling rate of a non-metallic drainage pipe, characterized in that, include: (1) Obtain ground-penetrating radar data of buried non-metallic pipelines; (2) Perform image preprocessing on the B-Scan image in the ground penetrating radar data; (3) Detect the pipe vertices in the B-Scan image after image preprocessing and extract the A-Scan signal at the vertices; (4) Based on the A-Scan signal, obtain the two-way travel time at the top and bottom of the pipe, and calculate the virtual radius of the pipe, which is expressed as: ； ； In the formula, r vir Let v be the virtual radius of the pipe, t1 and t2 be the two-way travel times of the reflected signals at the top and bottom of the pipe, respectively. w Let ε be the speed of electromagnetic waves in water, c be the speed of light in a vacuum, and ε be the speed of electromagnetic waves in water. r is the relative permittivity of water; (5) Calculate the water filling rate of the pipe based on the virtual pipe diameter calculation results and the actual pipe radius; With r real Let Δt1 and Δt2 represent the electromagnetic wave propagation times for the gas and water phases in the pipe, respectively. The sum of these two values ​​represents the reflected wave delay between the top and bottom of the pipe. ； ； ； In the formula, K is the water filling rate of the pipe. According to the definition of the virtual radius of the pipe, the water filling rate is expressed as: 。 2. The method for detecting the water filling rate of a non-metallic drainage pipe according to claim 1, characterized in that, The image preprocessing operation employs a nonlinear time gain algorithm; Here, the background-removed B-Scan image is a matrix consisting of T channels of A-Scan and N sampling points. For the t-th A-Scan signal in the t-th row... The gain compensation calculation method for the nth sampling point is as follows: ； ； In the formula, Here, y(n) is the amplified signal, y(n) is the gain coefficient, a is the gain growth base, when a>1, the gain increases exponentially with depth, D is the depth scaling factor, used to control the steepness of the gain curve, B is the baseline offset, used to suppress the amplification of shallow noise when n is small, and U is the upper limit of gain, to avoid overshoot of deep noise when n is large.

3. The method for detecting the water filling rate of a non-metallic drainage pipe according to claim 1, characterized in that, The pipe vertex detection operation employs a symmetry algorithm, and the symmetry curve of the B-Scan image is represented as follows: ； In the formula, (i,j) are the horizontal and vertical coordinate values ​​of the B-Scan image, f(i,j) are the pixel values ​​at the corresponding coordinates, the symmetry is calculated with the j-th column as the axis of symmetry and the distance between the left and right sides is m, w is the image width, h is the image height, and k is the maximum column width for calculating the symmetry. The pipeline signal appears as a hyperbola in the B-Scan image, and the minimum position where the symmetry curve changes abruptly is the vertex position of the pipeline hyperbola signal.

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