Ultrasonic guided wave monitoring of pipe damage and probabilistic bend location system and method

Abstract

The present application belongs to the technical field of city pipeline facility safety monitoring, and discloses a pipeline damage ultrasonic guided wave monitoring and probabilistic bending positioning system and method. The piezoelectric sensor for excitation and the piezoelectric sensor for receiving are installed on the pipeline section to be detected and positioned, the received signals are transmitted to the local control system, the signals are preprocessed in the local control system, and then transmitted to the central control system through wireless transmission. The received signals and the non-damage received signals under the same working condition are compared, and the signal correlation coefficient is extracted. The damage probability function distribution obtained by the probabilistic bending positioning damage is used as the prior probability distribution and the likelihood function, respectively. Finally, the posterior probability distribution is obtained by Bayesian correction as the final positioning result. The method used in the present application can accurately realize the positioning of the damage on the pipeline wall, and has high precision.

Description

Technical Field

[0001] This invention belongs to the field of safety monitoring technology for urban underground pipeline facilities, specifically relating to a system and method for ultrasonic guided wave monitoring and probabilistic bending location of pipeline damage. Background Technology

[0002] In the process of modernization, various pipelines are widely used in oil and gas transportation, urban water supply and drainage systems, chemical industry, and power industry. However, due to the high-intensity loads and environmental influences during long-term service, the reliability of pipeline materials gradually decreases, and various types of damage, such as cracks and fissures, inevitably occur. Nevertheless, their operational safety and reliability are crucial for economic development and social stability, therefore, timely reliability monitoring of pipeline health is necessary.

[0003] Ultrasonic guided wave pipeline damage localization technology is a non-destructive testing technique based on the principle of ultrasonic wave propagation. It boasts advantages such as high sensitivity, high precision, and high efficiency, and is widely used in pipeline damage detection and localization. When a pipeline is damaged, the propagation of ultrasonic guided waves along the pipe wall is affected by the damage, carrying specific damage information during propagation. The guided wave signal changes according to the changes in damage conditions. When the pipeline is in a complex external environment or under complex operating conditions, the information reflecting the pipeline damage may change, resulting in errors and making it impossible to assess the true damage state of the pipeline. How to achieve low cost and high reliability while ensuring the accuracy of underground pipeline damage localization is a pressing problem that needs to be solved.

[0004] Existing research on ultrasonic guided wave damage detection for pipeline structures, such as patent application CN113567560A, describes a damage detection method for pipelines with auxiliary structures based on ultrasonic guided waves. This method can locate underground pipeline damage using ultrasonic guided waves by analyzing echoes. However, since the ultrasonic guided waves are attenuated or affected during the process of transmission and reception of echoes in the pipeline, and receiving direct waves can introduce the problem of random propagation paths, the difficulty of location is greatly increased. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a system and method for ultrasonic guided wave monitoring and probabilistic bending location of pipeline damage. By arranging piezoelectric sensors, the system processes the collected signals containing damage information and signals from healthy pipelines under the same operating conditions, extracts damage factors and time of flight, and uses a Bayesian correction algorithm to locate the damage point.

[0006] The ultrasonic guided wave monitoring and probabilistic bending localization system for pipeline damage described in this invention includes a pipeline wall excitation and receiving sensor system, a local control system, and a central control system.

[0007] The pipe wall excitation and receiving sensing system sequentially excites several excitation sensors installed at one end of the underground pipe, and collects signals by the same number of receiving sensors installed at the other end of the underground pipe, transmitting the received signals to the local control system.

[0008] The local control system receives excitation signals from the pipe wall and signals with damage information transmitted by the sensor system. It then transmits the signals with damage information, signals collected from healthy pipes under the same working conditions stored in the system before the damage occurred, and excitation signals to the central control system via wireless communication.

[0009] The central control system processes the three types of signals received using a probabilistic bending damage location method to locate the damage point in the pipeline; at the same time, it sends control signals to the local control system to start or stop the local control system.

[0010] Furthermore, the pipe wall excitation and reception sensing system includes an excitation sensor, a receiving sensor, and a signal amplification module;

[0011] On one end of each underground pipeline, several excitation sensors are installed along its circumference. The excitation sensors are activated sequentially, and the same number of receiving sensors installed along the circumference of the other end of the underground pipeline collect the signals and convert the guided wave signals into electrical signals.

[0012] The signal amplification module consists of a voltage amplification circuit, a microprocessor, a signal transceiver module, and a power supply module. The voltage amplification circuit amplifies the input guided wave signal with a small original amplitude to a maximum amplitude of 2V. The microprocessor transmits the amplified guided wave signal to the local control system. The power supply module is a battery that provides the electrical energy required by the voltage amplification circuit and the microprocessor.

[0013] Furthermore, the local control system includes an electronic switch, a signal storage module, and a wireless communication module;

[0014] The electronic switch is used to start and stop the signal transmission and reception of the excitation sensors in each pipe section, thereby achieving the orderliness of each waveguide path and thus realizing the serialization of the acquired signals.

[0015] The signal storage module encodes and stores the excitation signal, the signal collected by the receiving sensor, and the signal collected by the healthy pipeline under the same working conditions in an orderly manner, and realizes the transmission preparation under the command of the central control system.

[0016] The wireless communication module wirelessly transmits the guided wave data for each path.

[0017] Furthermore, the central control system includes a signal processing module, a damage factor extraction module, a time-of-flight extraction module, a probabilistic bending positioning module, and a Bayesian correction module.

[0018] The signal processing module is used to amplify the signal transmitted by the local control system, and perform a subtraction operation between the signal with damage information and the signal collected under the same working condition of the healthy pipeline to obtain a scattered signal, and replace the initial part of the scattered signal with the excitation signal.

[0019] The damage factor extraction module is used to obtain the damage factor of each excitation sensor to each receiving sensor path by using the signal with damage information and the signal collected under the same working conditions of the healthy pipeline.

[0020] The flight time extraction module is used to extract the flight time of each path after obtaining the signal envelope through Hilbert transform based on the excitation signal and scattering signal provided by the signal processing module.

[0021] The probabilistic bending positioning module is used to perform probabilistic bending imaging based on the effective paths in each sensor path and the damage factors extracted by the damage factor module, and obtain a pipeline damage reconstruction probability function graph; select several paths based on the flight time to perform bending elliptical trajectory positioning, and obtain a pipeline damage elliptical probability function graph from the positioning.

[0022] The Bayesian correction module is used to take the pipeline reconstruction damage probability function graph based on damage factor provided by the probabilistic bending location module as the prior probability, and the pipeline damage ellipse probability density graph based on time of flight provided by the probabilistic bending location module as the likelihood function. After Bayesian correction, a posterior probability function graph is obtained, and the point with the highest probability is taken as the damage location point.

[0023] A method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage, implemented based on the aforementioned system, includes the following steps:

[0024] Step 1: Collect the signals received by each receiving sensor in the pipeline through the pipeline wall excitation and receiving sensing system, and transmit the signal with damage information to the local control system.

[0025] Step 2: The local control system transmits the pipeline wall excitation signal, the receiving sensor signal, the signal collected under the same working condition, and the signal from the healthy pipeline together to the central control system.

[0026] Step 3: The central control system preprocesses the received signal containing damage information to obtain the received signal, the scattered signal, and the signal with the excitation signal added to the scattered signal under healthy and damaged conditions.

[0027] Step 4: The central control system extracts the damage factors from each excitation sensor to each receiving sensor path and extracts the flight time of each path from the preprocessed signal.

[0028] Step 5: Based on the extracted damage factors and flight time, the central control system calculates and generates the pipeline damage reconstruction probability function graph and the pipeline damage elliptic probability function graph through bending coordinate transformation, and then inputs the pipeline damage reconstruction probability function graph and the pipeline damage elliptic probability function graph into the Bayesian correction module as prior probability and likelihood function, respectively.

[0029] Step 6: The central control system calculates the corresponding posterior probability based on the input prior probability and likelihood function, and obtains the point with the highest probability in the posterior probability density distribution. This point is the damage point located by this method.

[0030] Furthermore, the specific operating mode of the pipe wall excitation and receiving sensing system is as follows:

[0031] 1) The central control system sends a start data acquisition command to the local control system;

[0032] 2) The local control system sends commands to the pipe wall excitation and receiving sensor system for signal acquisition;

[0033] 3) The pipe wall excitation and receiving sensor system performs signal preprocessing and transmits the preprocessed signal to the local controller;

[0034] 4) The local control system transmits the received conditioning signals to the central control system;

[0035] 5) The central control system sends an acknowledgment signal. After receiving the acknowledgment signal, the local control system sends a signal to shut down the excitation sensor to the pipe wall excitation and receiving sensor system, ends the data acquisition, and waits for the next data acquisition command.

[0036] Furthermore, in step 3, the signal carrying damage information received by the sensor along a certain path is subtracted from the signal collected under the same operating conditions in the healthy pipeline to obtain the scattered signal of that path. The excitation signal is then used to replace the starting part of the scattered signal to prepare for the calculation of the time-of-flight extraction module.

[0037] Furthermore, in step 4, the expression for calculating the correlation coefficient of each path is as follows:

[0038] ,

[0039] Damage factor is ;in, The correlation coefficient is the desired value; k represents the k-th value of the signal under a certain path, and K is the maximum value of k. and These represent the k-th values ​​of the health signal and the damage signal, respectively. and They are and The average value;

[0040] The specific steps for calculating the flight time of each path are as follows: perform Hilbert transform on the scattered signal with the added excitation signal in step 3 and extract its envelope; the difference between the first peak of the received signal and the peak of the excitation signal is the flight time.

[0041] Furthermore, in step 5, the specific steps for generating the two surface damage probability functions for the two pipe walls are as follows:

[0042] Step 5-1: Unfold the pipe surface to achieve the transformation from curved coordinates to planar coordinates;

[0043] Step 5-2: Calculate the damage probability function based on the damage factor. For a specific excitation-receiver path, the spatial distribution of damage is a linearly decreasing elliptic weighted function, with the focus located at the excitation sensor and the receiving sensor along the path. The monitoring area is divided into a uniform grid, thereby estimating the probability of damage points appearing on each grid. Due to the special characteristic of the pipe being a hollow cylinder, when excitation is generated, the guided wave will inevitably have two paths from the excitation sensor to another point. When there are N excitation-receiver paths, the point... Probability of damage:

[0044] ,

[0045] ,

[0046] ;

[0047] in, The desired correlation coefficient; The value of the nth path is a point The probability of impact; The midpoint of the nth path The weighted distribution function; To determine a parameter of an ellipse, this parameter is compared with the ellipse's shape factor. Determine the spatial distribution of damage along the nth path; For point The distance to the excitation sensor along the nth path. For point The distance to the sensor receiving the nth path. Let n be the distance from the excitation sensor to the receiving sensor along the nth path. The coordinates of the excitation sensor for the nth path; Receive sensor coordinates for the nth path. The shape factor is the ellipse shape factor.

[0048] The shorter path from an excitation sensor to a receiving sensor in the pipeline is valid. Therefore, the lengths of the two paths are calculated, and the shorter path is taken as the valid path.

[0049] ,

[0050] Two-path D n1 and D n2 The lengths are respectively:

[0051] ,

[0052] ,

[0053] Where r is the outer radius of the pipe;

[0054] A shorter path from an excitation sensor to the damage point in the pipeline is effective. The effective path is:

[0055] ,

[0056] Two-path D sn1 and D sn2 The lengths are respectively:

[0057] ,

[0058] ;

[0059] The shortest path from the point of damage in the pipe to a receiving sensor is valid. The valid path is:

[0060] ,

[0061] Two-path D rn1 and D rn2 The lengths are respectively:

[0062] ,

[0063] ;

[0064] Step 5-3: Calculate the damage probability function based on flight time; Define the area around the damage point in the elliptical graph obtained by using the elliptical trajectory method based on the flight time of several paths. The probability of damage is proportional to the number of ellipses traversed in each unit. The probability of damage in other areas not around the damage point is set to 0. This gives the damage probability density map of the pipe wall based on the elliptical trajectory, which is used as the likelihood function.

[0065] The principle behind obtaining the ellipse diagram based on flight time is as follows:

[0066] ;

[0067] T represents flight time. Let be the group velocity of the guided wave in the pipe wall.

[0068] Furthermore, in step 6, the posterior probability is ;in, For prior probability, Let be the likelihood function, and the point with the highest probability of damage in the posterior probability is the damage point.

[0069] The beneficial effects of this invention are as follows:

[0070] 1) By transforming the coordinates of the curved surface, this invention makes the system and method fit the physical characteristics of the hollow cylinder and thin wall of the pipe, which is the basis for applying the damage location method to the pipe wall and improves the convenience and accuracy of damage location results observation.

[0071] 2) This invention proposes that the propagation of guided waves on the pipe wall has a path duality, and selects an effective path based on this characteristic for calculation and processing for tomographic imaging positioning and elliptical trajectory imaging positioning, which has good rationality and reliability.

[0072] 3) This invention utilizes the Bayesian method for damage localization. The Bayesian method modifies the two probability distributions obtained from the damage factor and the time of flight, respectively, to obtain the posterior probability distribution. Unlike single-method damage localization methods, Bayesian modification can further improve the reliability and accuracy of damage localization. Attached Figure Description

[0073] Figure 1 This is a schematic diagram of the ultrasonic guided wave sensing damage localization system of the present invention;

[0074] Figure 2 This is a schematic diagram of the sensor distribution on the pipeline;

[0075] Figure 3 This is a schematic diagram of a piezoelectric sensor structure;

[0076] Figure 4 This is a diagram of a signal processing circuit.

[0077] Figure 5 This is a signal amplifier circuit diagram;

[0078] Figure 6 This is the circuit connection diagram for the communication module;

[0079] Figure 7This is a diagram of a guided wave signal acquisition system;

[0080] Figure 8 This is a schematic diagram of the bending coordinate transformation process;

[0081] Figure 9 It is a guided wave signal diagram of a damaged pipeline carrying damage information and a guided wave signal diagram of a healthy pipeline under the same working conditions;

[0082] Figure 10 This is a schematic diagram illustrating the process of extracting specific flight times;

[0083] Figure 11 It is a damage probability function based on tomographic imaging;

[0084] Figure 12 This is a schematic diagram of damage localization using the elliptical trajectory method;

[0085] Figure 13 It is the number of ellipses that pass through the unit near the damage site in the elliptical trajectory method;

[0086] Figure 14 It is the posterior probability function for damage localization;

[0087] Figure 15 This is a diagram of the local control system architecture;

[0088] Figure 16 This is a schematic diagram of the damage localization method;

[0089] Figure 17 This is a complete flowchart of the method of the present invention. Detailed Implementation

[0090] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0091] The system described in this invention consists of three parts: a pipe wall excitation and receiving sensing system, a local control system, and a central control system. The overall structure is as follows: Figure 1 As shown.

[0092] The pipe wall excitation and reception sensing system includes piezoelectric sensors and a signal amplification module. Several excitation piezoelectric sensors are evenly spaced and installed around the perimeter of an underground pipe parallel to the pipe's cross-section. An equal number of receiving piezoelectric sensors are also evenly spaced and installed around the perimeter of the underground pipe, maintaining a certain distance from the excitation piezoelectric sensors. These sensors are used to transmit guided waves and receive guided waves carrying damage information after passing through a damaged area. The sensor distribution is as follows: Figure 2As shown, S1-S8 are excitation sensors, and R1-R8 are receiving sensors; the signal amplification module includes a voltage amplification circuit, a microprocessor, a signal transceiver module, and a power supply module; wherein, the voltage amplification circuit amplifies the input relatively weak guided wave signal to a suitable range; the microprocessor is a PIC, which transmits the amplified guided wave signal to the local control system; the power supply module is a battery, which supplies power to the voltage amplification circuit and the microprocessor respectively.

[0093] To achieve precise global location of damage to urban underground pipelines, it is necessary to control the excitation and reception sensors within the pipeline to collect signals. When a section of the pipeline is damaged, guided waves will be reflected at different angles as they pass through the damage, interfering with guided waves that do not pass through the damaged section. This results in a signal that is inconsistent with the signal received by healthy pipelines; that is, the signal carries damage information. By using receiving sensors evenly distributed around the pipeline to collect this signal, and analyzing the characteristics of the signals received by healthy pipelines (which do not carry damage information) and damaged pipelines, the damage to the pipeline can be located.

[0094] The piezoelectric sensor consists of an excitation piezoelectric sensor and a receiving piezoelectric sensor, both with identical structures. It uses a lead germanate titanate piezoelectric ceramic sheet (PZT). First, the unflanged silver electrode is thickened, then it is polished into an arc to fit the pipe surface, improving its adhesion. Finally, hot melt adhesive is applied to one side of the polished electrode to adhere it to the pipe surface. This ensures stable contact between the sensor and pipes of different materials. The sensor structure is as follows: Figure 3 As shown. Since piezoelectric sensors have the property of increasing amplitude closer to their resonant frequency, and the excitation signal frequency used in the experiment is 80kHz, a piezoelectric sensor with a frequency slightly greater than 80kHz can be selected to ensure the experimental signal has a suitable amplitude, such as a piezoelectric ceramic sheet with a frequency of 100kHz. In addition, piezoelectric sensors also have certain requirements regarding size and thickness. In this example, a PZT with a frequency of 100kHz, a diameter of 8mm, and a thickness of 2mm is selected as the excitation and receiving sensor.

[0095] If damage is known to exist in a certain section of underground pipeline, the excitation and receiving sensors of that section of pipeline are activated to accurately locate the damage point. The activation and deactivation of the piezoelectric sensors are controlled by the central control system.

[0096] Because long-distance guided wave propagation attenuates the excitation signal emitted by the excitation sensor, the acquired raw guided wave signal from the pipeline is relatively weak. Therefore, a signal processing module is needed to amplify the raw signal, as shown in the functional diagram below. Figure 4As shown in the figure. When selecting an amplifier chip, the impact of the chip's own electrical noise on the overall circuit needs to be considered, as well as factors such as impedance matching, dynamic range, and amplification factor. In this embodiment, the Analog Devices MAX40089 is selected as the core amplifier chip, which meets the requirements for noise, linearity, and other specifications. The signal amplification circuit diagram is shown in the figure. Figure 5 As shown. The guided wave signal, after being preprocessed by the amplification circuit, is transmitted to the microprocessor. When selecting a microprocessor, factors such as digital-to-analog conversion performance and power consumption need to be considered. In this embodiment, a PIC is selected as the processor for the pipe wall excitation and receiving sensing system.

[0097] The specific steps of the working mode of the pipe wall excitation and receiving sensor system are as follows:

[0098] 1) The central control system sends a start data acquisition command to the local control system;

[0099] 2) The local control system sends commands to the pipe wall excitation and receiving sensor system for signal acquisition;

[0100] 3) The pipe wall excitation and receiving sensor system performs signal preprocessing and transmits the preprocessed signal to the local controller;

[0101] 4) The local control system transmits the received conditioning signals to the central control system;

[0102] 5) The central control system sends an acknowledgment signal. After receiving the acknowledgment signal, the local control system sends a signal to shut down the excitation sensor to the pipe wall excitation and receiving sensor system, ends the data acquisition, and waits for the next data acquisition command.

[0103] The structure of the local control system is as follows: Figure 15 As shown, it is used to process the data output from the pipe wall excitation and receiving sensor system, and wirelessly transmits it to the central control system, as well as bidirectionally transmitting control commands. The local control system uses an STM32 as the processor, and the guided wave signals from each excitation sensor are connected to different I / O ports. The connection of this I / O port is controlled by a virtual electronic switch to achieve serialized data acquisition.

[0104] Because a single signal acquisition of a certain pipe section generates numerous sets of signal data, it is necessary to expand the storage capacity of the local control system. The signal storage module first assigns a storage number to each excitation sensor, then associates this number with an expanded external storage unit to achieve sequential storage. Storage expansion methods generally include SD cards, EEPROMs, and Flash memory. This embodiment uses an SD card, communicating with the STM32 processor via the SDIO protocol to achieve sequential storage of the guided wave signals.

[0105] To enable wireless communication between the local control system and the central control system, a cable tie is first used to move the wireless communication module of the local control system to an open area on the ground. The GPRS protocol is used to wirelessly transmit the received signal data temporarily stored in the local control system. In this embodiment, the SIM800L is used as the communication chip. This chip has a wide frequency band of 850MHz-1900MHz and uses a serial port to communicate with the STM32 microprocessor. The wireless communication module circuit connection is as follows. Figure 6 As shown.

[0106] Central control system: Collects guided wave signals and excitation sensor numbers transmitted from the local control system, and controls the start and stop of the local control system by receiving confirmation signals, issuing start signals, and issuing stop signals. The control logic flow is as follows: Figure 7 As shown.

[0107] The signal processing flow of the central control system is as follows: Figure 16 As shown. First, as Figure 8 As shown, a surface space coordinate transformation is performed on the pipe. The undeveloped pipe is as follows: Figure 8 As shown in (a), the x-axis and y-axis correspond to the x-axis and y-axis of the plane coordinate system. The line connecting the origin of the plane coordinate system and the center of the pipe section is the o-axis. An angle parameter α is introduced, which is the angle between the line connecting the projection point of the point on the circle and the center of the circle and the o-axis. Figure 8 (b) represents the expanding pipe, with the x and y coordinates... Convert to coordinate system The coordinates of S0 in the x, y coordinate system are: After conversion Coordinates are The completed pipework is as follows: Figure 8 As shown in (c), after unfolding into a plane, let's assume that the number of pipe excitation sensors and receiving sensors is m, and... If a coordinate system is established with the origin as the coordinate system origin, the unfolded diagram is as follows: Figure 8 As shown in (d); where, The z-axis is the line connecting the centers of the two circles. Therefore, we can use... Represent all points on the pipeline, completing the planar coordinate conversion. Coordinate transformation.

[0108] The initial guided wave signal is acquired by sequentially receiving guided wave signals carrying damage information (hereinafter referred to as damage signals) from the first excitation sensor. In a healthy state, the guided wave signal (hereinafter referred to as the health signal) emitted by the first excitation sensor and collected by each receiving sensor is... Similarly, the guided wave signals emitted by the nth excitation sensor and collected by each receiving sensor are respectively and In this specific embodiment, the collected health signals and damage signals are respectively as follows: Figure 9 (a) Figure 9 As shown in (b).

[0109] The correlation coefficient of each path is obtained based on health signals and injury signals. The formula for calculating the correlation coefficient of the scattered signal along a path by subtracting the healthy signal from the damaged signal along that path is as follows:

[0110] ;

[0111] in, and These represent the health signal and the damage signal in path k, respectively. and They are and The average value; correlation coefficient Indicates the similarity between damage signals and health signals. The smaller the similarity, the lower the probability that the damage occurred on the corresponding stimulus-reception path; conversely, The larger the value, the higher the similarity; the closer it is to 1, the lower the probability of damage on the stimulus-reception path. The correlation coefficients extracted for each path are shown in Table 1.

[0112] Table 1. Correlation coefficients of all simulation paths

[0113] .

[0114] The scattered signal is subjected to Hilbert transform to extract the damaged time-of-flight T. The specific process for extracting the time-of-flight is as follows: Figure 10 As shown. In this embodiment, the guided wave signal expression is:

[0115] ,

[0116] In the formula, A0 is the amplitude of the guided wave signal, and n p f is the number of peaks. c For the center frequency, its Hilbert transform is: .

[0117] like Figure 10 As shown, after obtaining the envelope of the guided wave signal using the Hilbert transform, the first peak is the peak of the excitation signal, and the second peak is the peak of the first scattered wave. The time difference between the two is the flight time of the scattered wave along the path. The flight times extracted for each path are shown in Table 2.

[0118] Table 2. Flight times for all simulated paths (unit: ×10) -4 s)

[0119]

[0120] The probability of damage occurring at each point on the pipe wall along each path is calculated based on the correlation coefficient and then superimposed to obtain a damage probability function graph. The specific formula is as follows:

[0121] ,

[0122] ,

[0123] ;

[0124] in, The value of the nth path is a point The probability of impact, For point The distance to the excitation sensor along the nth valid path. For point The distance to the receiving sensor along the nth valid path. Let n be the distance from the excitation sensor to the receiving sensor along the nth path. The ellipse shape factor is set to 1.005; the damage probability map is generated as follows. Figure 11 (a) The localization result after thresholding is shown in the figure below. Figure 11 As shown in (b).

[0125] The formula for calculating the location of damage based on flight time is: ,in, Let be the group velocity of the guided wave propagating in the pipe wall. Several paths are selected, and the damage location is determined based on the elliptical trajectory method. The results are as follows: Figure 12 As shown, where Figure 12 (a) is an ellipse generated by the elliptical trajectory method. Figure 12 (b) shows the comparison between the intersection point of the ellipse and the actual damage point. A damage probability function graph is generated from this damage location map using the definition method of this invention, as described in the following... Figure 13 As shown.

[0126] To implement Bayesian correction, the damage probability function obtained from tomography is used as the prior probability, and the damage probability function obtained based on the elliptical trajectory method is used as the likelihood function. The results are then superimposed to obtain the posterior probability function distribution map, as shown below. Figure 14 (a) is the distribution graph of the posterior probability function. Figure 14 (b) is Figure 14 (a) Magnified view of the damage point.

[0127] The actual damage location is compared with the theoretical damage locations obtained by various methods. Here, the distance d between the theoretical and actual values ​​of the parameter is used to measure the accuracy of the positioning. In this embodiment, the actual damage location is... Therefore, the expression for d is as follows:

[0128] ;

[0129] The d-values ​​of the tomographic imaging method, the elliptical trajectory positioning method, and the method of the present invention used in the embodiments are shown in Table 3.

[0130] Table 3 d-values ​​for each method

[0131]

[0132] Table 3 shows that the accuracy of this method is 76.13% higher than that of tomography and 66.67% higher than that of the elliptical trajectory method. Table 3 also shows that the accuracy of this method is 66.5% higher than that of tomography and 49.75% higher than that of the elliptical trajectory method. The results indicate that the system and method of this invention can accurately detect single damages on the pipe wall with high precision.

[0133] The above description is merely a preferred embodiment of the present invention and is not intended to further limit the present invention. All equivalent changes made based on the description and drawings of the present invention are within the protection scope of the present invention.

Claims

1. A method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage, characterized in that, This is achieved based on the aforementioned ultrasonic guided wave monitoring and probabilistic bending location system for pipeline damage. The system includes a pipeline wall excitation and receiving sensor system, a local control system, and a central control system. The pipe wall excitation and receiving sensing system uses several excitation sensors installed at one end of the underground pipe to excite the pipe in sequence, and the same number of receiving sensors installed at the other end of the underground pipe to collect the signals and transmit the received signals to the local control system. The local control system receives excitation signals from the pipe wall and signals with damage information transmitted by the sensor system. It then transmits the signals with damage information, signals collected from healthy pipes under the same working conditions stored in the system before the damage occurred, and excitation signals to the central control system via wireless communication. The central control system processes the three types of signals received using a probabilistic bending damage location method to locate the pipeline damage point; at the same time, it sends control signals to the local control system to start or stop the local control system. The method includes the following steps: Step 1: Collect the signals received by each receiving sensor in the pipeline through the pipeline wall excitation and receiving sensing system, and transmit the signal with damage information to the local control system. Step 2: The local control system transmits the signals from the pipe wall excitation and receiving sensor system, the excitation signal, and the signals collected under the same working conditions of the healthy pipe to the central control system. Step 3: The central control system preprocesses the received signal containing damage information to obtain the received signal, the scattered signal, and the signal with the excitation signal added to the scattered signal under healthy and damaged conditions. Step 4: The central control system extracts the damage factors and flight times of each path from each excitation sensor to each receiving sensor from the preprocessed signal. Step 5: Based on the extracted damage factors and flight time, the central control system calculates and generates the pipeline damage reconstruction probability function graph and the pipeline damage elliptic probability function graph through bending coordinate transformation, and then inputs the pipeline damage reconstruction probability function graph and the pipeline damage elliptic probability function graph into the Bayesian correction module as prior probability and likelihood function, respectively. Step 6: The central control system calculates the corresponding posterior probability based on the input prior probability and likelihood function, and obtains the point with the highest probability in the posterior probability density distribution. This point is the damage point located by this method. In step 5, the specific steps for generating the surface damage probability functions for the two pipe walls are as follows: Step 5-1: Unfold the pipe surface to achieve the transformation from curved coordinates to planar coordinates; Step 5-2: Calculate the damage probability function based on the damage factor. For a specific excitation-receiver path, the spatial distribution of damage is a linearly decreasing elliptic weighted function, with the focus located at the excitation sensor and the receiving sensor along the path. The monitoring area is divided into a uniform grid, thereby estimating the probability of damage points appearing on each grid. Due to the special characteristic of the pipe being a hollow cylinder, when excitation is generated, the guided wave will inevitably have two paths from the excitation sensor to another point. When there are N excitation-receiver paths, the point... Probability of damage: ， ， ； in, The desired correlation coefficient; The value of the nth path is a point The probability of impact; The midpoint of the nth path The weighted distribution function; To determine a parameter of an ellipse, this parameter is compared with the ellipse's shape factor. Determine the spatial distribution of damage along the nth path; For point The distance to the excitation sensor along the nth path. For point The distance to the sensor receiving the nth path. Let n be the distance from the excitation sensor to the receiving sensor along the nth path. The coordinates of the excitation sensor for the nth path; Receive sensor coordinates for the nth path. The shape factor is the ellipse shape factor. The shorter path from an excitation sensor to a receiving sensor in the pipeline is valid. Therefore, the lengths of the two paths are calculated, and the shorter path is taken as the valid path. ， Two-path D n1 and D n2 The lengths are respectively: ， ； Where r is the outer radius of the pipe; A shorter path from an excitation sensor to the damage point in the pipeline is effective. The effective path is: ， Two-path D sn1 and D sn2 The lengths are respectively: ， ； The shortest path from the point of damage in the pipe to a receiving sensor is valid. The valid path is: ， Two-path D rn1 and D rn2 The lengths are respectively: ， ； Step 5-3: Calculate the damage probability function based on flight time; Define the area around the damage point in the elliptical graph obtained by using the elliptical trajectory method based on the flight time of several paths. The probability of damage is proportional to the number of ellipses traversed in each unit. The probability of damage in other areas not around the damage point is set to 0. This gives the damage probability density map of the pipe wall based on the elliptical trajectory, which is used as the likelihood function. The principle behind obtaining the ellipse diagram based on flight time is as follows: ； T represents flight time. Let be the group velocity of the guided wave in the pipe wall.

2. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, The pipe wall excitation and receiving sensing system includes an excitation sensor, a receiving sensor, and a signal amplification module; On one end of each underground pipeline, several excitation sensors are installed along its circumference. The excitation sensors are activated sequentially, and the same number of receiving sensors installed along the circumference of the other end of the underground pipeline collect the signals and convert the guided wave signals into electrical signals. The signal amplification module includes a voltage amplification circuit, a microprocessor, a signal transceiver module, and a power supply module. The voltage amplification circuit amplifies the input guided wave signal with a small original amplitude to a maximum amplitude of 2V. The microprocessor transmits the amplified guided wave signal to the local control system. The power supply module is a battery that provides the power required by the voltage amplification circuit and the microprocessor.

3. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, The local control system includes an electronic switch, a signal storage module, and a wireless communication module; The electronic switch is used to start and stop the signal transmission and reception of the excitation sensors in each pipe section, thereby achieving the orderliness of each waveguide path and thus realizing the serialization of the acquired signals. The signal storage module encodes and stores the excitation signal, the signal collected by the receiving sensor, and the signal collected by the healthy pipeline under the same working conditions in an orderly manner, and realizes the transmission preparation under the command of the central control system. The wireless communication module wirelessly transmits the guided wave data for each path.

4. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, The central control system includes a signal processing module, a damage factor extraction module, a time-of-flight extraction module, a probabilistic bending positioning module, and a Bayesian correction module. The signal processing module is used to amplify the signal transmitted by the local control system, and perform a subtraction operation between the signal with damage information and the signal collected under the same working condition of the healthy pipeline to obtain a scattered signal, and replace the initial part of the scattered signal with the excitation signal. The damage factor extraction module is used to obtain the damage factor of each excitation sensor to each receiving sensor path by using the signal with damage information and the signal collected under the same working conditions of the healthy pipeline. The flight time extraction module is used to extract the flight time of each path after obtaining the signal envelope through Hilbert transform based on the excitation signal and scattering signal provided by the signal processing module. The probabilistic bending positioning module is used to perform probabilistic bending imaging based on the effective paths in each sensor path and the damage factors extracted by the damage factor module, and obtain a pipeline damage reconstruction probability function graph; select several paths based on the flight time to perform bending elliptical trajectory positioning, and obtain a pipeline damage elliptical probability function graph from the positioning. The Bayesian correction module is used to take the pipeline reconstruction damage probability function graph based on damage factor provided by the probabilistic bending location module as the prior probability, and the pipeline damage ellipse probability density graph based on time of flight provided by the probabilistic bending location module as the likelihood function. After Bayesian correction, a posterior probability function graph is obtained, and the point with the highest probability is taken as the damage location point.

5. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, The specific operating mode of the pipe wall excitation and receiving sensing system is as follows: 1) The central control system sends a start data acquisition command to the local control system; 2) The local control system sends commands to the pipe wall excitation and receiving sensor system for signal acquisition; 3) The pipe wall excitation and receiving sensor system performs signal preprocessing and transmits the preprocessed signal to the local controller; 4) The local control system transmits the received conditioning signals to the central control system; 5) The central control system sends an acknowledgment signal. After receiving the acknowledgment signal, the local control system sends a signal to shut down the excitation sensor to the pipe wall excitation and receiving sensor system, ends the data acquisition, and waits for the next data acquisition command.

6. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, In step 3, the signal carrying damage information received by the sensor along a certain path is subtracted from the signal collected under the same operating conditions in the healthy pipeline to obtain the scattered signal of that path. The excitation signal is then used to replace the starting part of the scattered signal to prepare for the calculation of the time-of-flight extraction module.

7. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, In step 4, the expression for calculating the correlation coefficient of each path is as follows: ， Damage factor is ;in, The correlation coefficient is the desired value; k represents the k-th value of the signal under a certain path, and K is the maximum value of k. and These represent the k-th values ​​of the health signal and the damage signal, respectively. and They are and The average value; The specific steps for calculating the flight time of each path are as follows: perform Hilbert transform on the scattered signal with the added excitation signal in step 3 and extract its envelope; the difference between the first peak of the received signal and the peak of the excitation signal is the flight time.

8. The method for ultrasonic guided wave monitoring and probabilistic bending localization of pipeline damage according to claim 1, characterized in that, In step 6, the posterior probability is ;in, For prior probability, Let be the likelihood function, and the point with the highest probability of damage in the posterior probability is the damage point.

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