Method, device and equipment for safely monitoring load of embankment penetrating pipeline and medium

Abstract

The invention relates to an embankment penetrating pipeline load safety monitoring method and device, equipment and a medium. Determining a load type, a load size, a load action frequency, a load action position coordinate and a load action duration corresponding to the load sample as load identification data of the sub-detection sections; taking the load identification data of the sub detection sections as boundary conditions, and inputting the boundary conditions, pipeline parameters of the to-be-detected embankment penetrating pipeline, embankment body parameters and foundation parameters into a preset pipeline-embankment body-foundation three-dimensional coupling mechanical model, determining a stress value, a deformation value and a fatigue damage value corresponding to each sub-detection section in the to-be-detected embankment-penetrating pipeline; and according to the stress value, the deformation value and the fatigue damage value, determining a safety evaluation level corresponding to the sub-detection section of the to-be-detected embankment-penetrating pipeline. The damage to the integrity of the embankment body structure caused by traditional strain sensor arrangement is avoided, and real-time monitoring and recognition of the load are achieved.

Description

Methods, devices, equipment and media for monitoring the load safety of pipelines crossing dikes Technical Field

[0001] This application relates to the field of monitoring pipelines crossing dikes, and in particular to a method, device, electronic equipment and computer-readable storage medium for monitoring the load safety of pipelines crossing dikes. Background Technology

[0002] Pipelines crossing levees serve as crucial hubs for energy transportation across rivers, lakes, and seas, and are widely used for transporting crude oil, natural gas, and refined oil products across waterways. With the continuous improvement of my country's energy pipeline network, the number of pipelines crossing levees is constantly increasing, and their safe operation is directly related to the stability of energy supply and the ecological security of the basin. Pipelines crossing levees simultaneously bear multiple loads, including internal pipeline pressure, the weight of the levee itself, water erosion, wave impact, vehicles passing over the levee crest, landslides, human encroachment, and illegal construction. These loads are complex and exhibit randomness and suddenness.

[0003] Currently, most related studies focus on the impact of single loads on pipelines, lacking comprehensive safety assessment methods based on field-measured loads. This makes it difficult to effectively predict the structural damage risk of pipelines crossing embankments under complex loads. The safety monitoring technology for pipelines crossing embankments suffers from the following technical deficiencies:

[0004] Firstly, when using traditional strain sensors for monitoring, it is necessary to excavate the embankment and pipeline foundation to install the sensors, which not only damages the structural integrity of the embankment, but also makes construction difficult and costly, and makes it difficult to achieve continuous monitoring of the entire pipeline.

[0005] Secondly, existing distributed fiber optic sensing technology is mostly used for early warning of leaks in ordinary buried pipelines, and it does not carry out load identification and safety assessment for the special load environment of seepage in the embankment of pipelines crossing the embankment, thus failing to meet the special monitoring needs of pipelines crossing the embankment.

[0006] In summary, existing technologies for monitoring the load safety of pipelines crossing dikes require excavating the dike and pipeline foundations to install sensors. This not only damages the structural integrity of the dike but also presents significant construction difficulties, high costs, and challenges in effectively predicting the structural damage risk of pipelines under complex loads. Therefore, the applicant has made corresponding explorations to address these issues. Summary of the Invention

[0007] The purpose of this application is to solve the above-mentioned problems by providing a method, device, electronic equipment and computer-readable storage medium for monitoring the load safety of pipelines crossing dikes.

[0008] To achieve the various objectives of this application, the following technical solution is adopted:

[0009] A method for monitoring the load safety of a pipeline crossing a levee, proposed to meet one of the purposes of this application, includes:

[0010] The load-related vibration signals of each sub-testing section of the pipeline to be tested through the dike are collected. The sub-testing sections include the buried pipe section inside the dike, the transition section at the dike shoulder, and the extension section at the dike toe.

[0011] The average value of the load-related vibration signal within a preset time range is calculated and determined as the reference vibration signal. The load-related vibration signal is subjected to multi-layer noise reduction using a fourth-order Dobes wavelet basis. The load-related vibration signal after multi-layer noise reduction is compared with the reference vibration signal. The load-related vibration signal with an amplitude exceeding a preset percentage of the reference vibration signal is taken as the effective load vibration signal corresponding to the sub-detection segment.

[0012] Fourier transform is used to extract the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal to construct a load feature vector. The load feature vector is compared with each load sample in the preset load sample database. If the similarity of a certain load sample is the maximum value among all matching results and exceeds the preset similarity threshold, then the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample are determined as the load identification data of the sub-detection segment.

[0013] The load identification data of the sub-detection segment is used as the boundary condition. The boundary condition, the pipe parameters of the pipe to be detected through the dike, the dike parameters, and the foundation parameters are input into the preset three-dimensional coupled mechanical model of pipe-dike-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment.

[0014] Based on the stress value, the deformation value, and the fatigue damage value, the safety assessment level corresponding to the sub-inspection section of the pipeline under test is determined to complete the safety monitoring of the pipeline load.

[0015] Optionally, the step of performing multi-layer noise reduction on the load-related vibration signal using a fourth-order Dobessi wavelet basis, performing difference calculation between the multi-layer noise-reduced load-related vibration signal and the reference vibration signal, and taking the load-related vibration signal with an amplitude exceeding a preset percentage of the reference vibration signal as the effective load vibration signal corresponding to the sub-detection segment includes:

[0016] The load-related vibration signals of each sub-detection segment were subjected to five layers of noise reduction using a fourth-order Dobessi wavelet basis to obtain the noise-reduced load-related vibration signals.

[0017] The difference between the noise-reduced load-related vibration signal and the reference vibration signal is calculated, and signal segments with amplitudes exceeding 5% of the reference vibration signal are selected and identified as effective load vibration signals.

[0018] Optionally, the step of extracting the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal using Fourier transform to construct a load feature vector includes:

[0019] Fast Fourier Transform is performed on the effective load vibration signals corresponding to each sub-segment of the pipeline to be inspected to determine the signal spectrum corresponding to the effective load vibration signals.

[0020] The frequency component with the highest energy proportion in the signal spectrum is extracted as the main peak frequency feature parameter, the maximum energy value in the signal spectrum is taken as the energy peak feature parameter, and the bandwidth of the frequency range in the signal spectrum where the energy proportion exceeds a preset percentage of the total energy is taken as the spectrum width feature parameter.

[0021] The main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter are combined in sequence to construct the load characteristic vector corresponding to the sub-detection segment.

[0022] Optionally, the step of comparing the load feature vector with each load sample in a preset load sample database, and determining the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample as the load identification data of the sub-detection segment, includes:

[0023] The load feature vectors of each sub-segment of the pipeline to be inspected are compared with all load samples in the preset load sample database one by one to calculate the cosine similarity, so as to determine the similarity calculation results.

[0024] The highest similarity among all similarity calculation results is selected. If the highest similarity exceeds a preset similarity threshold, the load type, load size, and load frequency associated with the load sample corresponding to the highest similarity are determined as the load identification data corresponding to the sub-detection segment of the pipeline to be detected.

[0025] Optionally, the step of using the load identification data of the sub-detection segment as boundary conditions, and inputting the boundary conditions, the pipe parameters of the pipe to be detected crossing the embankment, the embankment parameters, and the foundation parameters into a preset three-dimensional coupled mechanical model of pipe-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment, includes:

[0026] Based on the finite element calculation results of the three-dimensional coupled mechanical model of pipeline-embankment-foundation, the set of nodes to be detected corresponding to each sub-segment of the pipeline crossing the embankment is located.

[0027] For each sub-detection segment corresponding to the set of nodes to be detected, the maximum values ​​of the circumferential stress, axial stress, and shear stress of the pipeline to be detected within the set of nodes to be detected are calculated. The first average value among the maximum values ​​of the circumferential stress, the axial stress, and the shear stress is taken as the stress value corresponding to the sub-detection segment.

[0028] The maximum values ​​of radial deformation, axial deformation, and lateral deformation of the pipeline crossing the dike within the set of nodes to be detected are statistically analyzed. The second average value among the maximum values ​​of radial deformation, axial deformation, and lateral deformation is taken as the deformation value corresponding to the sub-detection segment.

[0029] Based on Miner's linear cumulative damage theory, and combining the stress cycle number within the set of nodes to be tested with the fatigue life curve of the pipe, the fatigue damage increment of the sub-test segment under a single load is calculated. The fatigue damage value of the sub-test segment in the historical cumulative cycle is then superimposed to obtain the fatigue damage value corresponding to the sub-test segment.

[0030] Optionally, the step of determining the safety assessment level corresponding to the sub-inspection section of the pipeline to be inspected based on the stress value, the deformation value, and the fatigue damage value includes:

[0031] Obtain the stress value, deformation value, and fatigue damage value of each sub-segment of the pipeline to be inspected;

[0032] The first ratio between the stress value and the preset stress threshold, the second ratio between the deformation value and the preset deformation threshold, and the third ratio between the fatigue damage value and the preset fatigue damage threshold are calculated and determined.

[0033] If the first ratio, the second ratio, and the third ratio are all below 80%, then the sub-detection segment is determined to be at a safety level.

[0034] If any one of the first ratio, the second ratio, and the third ratio is between 80% and 100%, the sub-detection segment is determined to be at the warning level, and a risk warning report is generated.

[0035] If any one of the first ratio, the second ratio, and the third ratio reaches or exceeds 100%, the sub-detection segment is determined to be at a dangerous level, and an audible and visual alarm is triggered, and a danger alarm message is sent to the mobile terminal of the management personnel to complete the safety monitoring of the load on the pipeline crossing the embankment.

[0036] Optionally, the step of determining the safety assessment level corresponding to the sub-inspection section of the pipeline to be inspected based on the stress value, the deformation value, and the fatigue damage value includes:

[0037] Obtain the stress value, deformation value, and fatigue damage value of each sub-segment of the pipeline to be inspected;

[0038] The first ratio between the stress value and the preset stress threshold, the second ratio between the deformation value and the preset deformation threshold, and the third ratio between the fatigue damage value and the preset fatigue damage threshold are calculated and determined.

[0039] If the first ratio, the second ratio, and the third ratio are all below 80%, then the sub-detection segment is determined to be at a safety level.

[0040] If any one of the first ratio, the second ratio, and the third ratio is between 80% and 100%, the sub-detection segment is determined to be at the warning level, and a risk warning report is generated.

[0041] If any one of the first ratio, the second ratio, and the third ratio reaches or exceeds 100%, the sub-detection segment is determined to be at a dangerous level, and an audible and visual alarm is triggered, and a danger alarm message is sent to the mobile terminal of the management personnel to complete the safety monitoring of the load on the pipeline crossing the embankment.

[0042] Optionally, the pipeline parameters include the pipe material elastic modulus, pipe diameter, and pipe wall thickness; the embankment parameters include soil cohesion, internal friction angle, and compaction degree; and the foundation parameters include foundation bearing capacity and compression modulus.

[0043] The stress values ​​include circumferential stress, axial stress, and shear stress; the deformation values ​​include radial deformation, axial deformation, and transverse deformation.

[0044] A load safety monitoring device for a pipeline crossing a levee, provided for another purpose of this application, includes:

[0045] The vibration signal acquisition module is configured to acquire load-related vibration signals corresponding to each sub-detection section of the pipeline to be tested through the dike. The sub-detection section includes the buried pipe section inside the dike, the transition section at the dike shoulder, and the extension section at the dike toe.

[0046] The effective signal confirmation module is configured to calculate and determine the average value of the load-related vibration signal within a preset time range as the reference vibration signal, use a fourth-order Dobes wavelet basis to perform multi-layer noise reduction on the load-related vibration signal, perform difference calculation between the multi-layer noise-reduced load-related vibration signal and the reference vibration signal, and take the load-related vibration signal whose amplitude exceeds a preset percentage of the reference vibration signal as the effective load vibration signal corresponding to the sub-detection segment.

[0047] The load data determination module is configured to use Fourier transform to extract the main peak frequency characteristic parameters, energy peak characteristic parameters, and spectral width characteristic parameters from the effective load vibration signal to construct a load feature vector. The load feature vector is then compared with the similarity of each load sample in a preset load sample database. If the similarity of a certain load sample is the maximum value among all matching results and exceeds a preset similarity threshold, the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample are determined as the load identification data of the sub-detection segment.

[0048] The three-dimensional coupling module is configured to use the load identification data of the sub-detection segment as boundary conditions, and input the boundary conditions, the pipe parameters of the pipe to be detected through the embankment, the embankment parameters, and the foundation parameters into a preset three-dimensional coupled mechanical model of pipe-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment.

[0049] The safety monitoring module is configured to determine the safety assessment level of the sub-inspection section of the pipeline under test based on the stress value, the deformation value, and the fatigue damage value, so as to complete the safety monitoring of the pipeline load.

[0050] An electronic device provided for another purpose of this application includes a central processing unit and a memory, the central processing unit being configured to invoke and run a computer program stored in the memory to perform the steps of the method for monitoring the load safety of a pipeline crossing a dam as described in this application.

[0051] A computer-readable storage medium is provided for another purpose of this application, which stores, in the form of computer-readable instructions, a computer program implemented according to the method for monitoring the load safety of pipelines crossing embankments, which, when called by a computer, executes the steps included in the corresponding method.

[0052] Compared to existing technologies, this application addresses the problems of traditional methods for monitoring the load safety of pipelines crossing dikes, which require excavating both the dike and the pipeline foundation to install sensors. This not only damages the structural integrity of the dike but also presents significant construction difficulties and high costs. Furthermore, it struggles to effectively predict the structural damage risk of pipelines crossing dikes under complex loads. This application offers advantages including, but not limited to, the following:

[0053] Firstly, this application adopts a distributed fiber optic vibration sensor and pipeline laid in the same trench, eliminating the need for excavation of the dike and pipeline foundations. This avoids the structural integrity damage to the dike caused by traditional strain sensor deployment, ensuring that the core functions of flood control and seepage prevention of the dike remain unaffected. The sensor extends continuously along the pipeline axis, fully covering the buried pipe section inside the dike, the transition section at the dike shoulder, and the extension section outside the dike. This solves the monitoring blind spot problem caused by the traditional "point-based layout" and achieves continuous monitoring of the entire pipeline without blind spots. Simultaneously, the distributed fiber optic vibration sensor is a single-mode fiber optic vibration sensor based on phase-sensitive optical time-domain reflectometry technology, requiring no additional laying, significantly reducing construction difficulty and cost, and is particularly suitable for renovation projects of existing pipelines.

[0054] Secondly, this application combines Fast Fourier Transform to extract core feature parameters such as peak frequency and energy peak value, and compares them with similarity thresholds to achieve accurate identification of load type, size, and frequency of action. The system has a self-learning and updating function, which can expand the new load samples through on-site verification, effectively dealing with the complex, random, and sudden characteristics of loads on pipelines crossing embankments. In the signal preprocessing stage, techniques such as db4 wavelet basis multilayer noise reduction and 10 to 100 times adjustable amplification are used to improve the signal-to-noise ratio to over 20dB, successfully filtering environmental interference such as wind noise and water flow noise, ensuring that even weak load signals can be accurately captured, and realizing real-time monitoring and identification of loads.

[0055] Thirdly, this application uses the measured loads on site as boundary conditions and combines the actual physical parameters of the pipeline, embankment, and foundation. It performs finite element calculations through a three-dimensional coupled mechanical model of pipeline-embankment-foundation. Compared with traditional assumed load analysis, this method can more realistically reflect the mechanical properties of the pipeline. The model adopts fine mesh division to accurately calculate circumferential stress, axial stress, shear stress, and various deformation values. Based on Miner's linear cumulative damage theory, it quantifies the cumulative amount of fatigue damage to establish a multi-level safety assessment for accurate classification. When an early warning is issued, it automatically generates an analysis report containing load information, calculation results including stress values, deformation values, and fatigue damage values, as well as the analysis report of the risk causes. In case of danger, it immediately triggers an audible and visual alarm and pushes an emergency notification containing coordinate information, effectively predicting structural damage risks and solving the problem of inaccurate assessment by traditional technologies. Attached Figure Description

[0056] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0057] Figure 1 is a flowchart illustrating the load safety monitoring method for pipelines crossing dikes in this embodiment of the present application;

[0058] Figure 2 is an exemplary architecture diagram of the load safety monitoring system for pipelines crossing dikes in this application embodiment;

[0059] Figure 3 is a flowchart of the vibration signal identification and analysis unit in the embodiment of this application;

[0060] Figure 4 is a schematic diagram of the three-dimensional coupled mechanical model of pipeline-embankment-foundation in an embodiment of this application;

[0061] Figure 5 is a schematic diagram of the load safety monitoring device for pipelines crossing dikes in an embodiment of this application.

[0062] Figure 6 is a schematic diagram of the structure of the computer device in the embodiment of this application. Detailed Implementation

[0063] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0064] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0065] Those skilled in the art will understand that although the various methods in this application are described based on the same concept and thus present commonality among them, they can be performed independently unless otherwise specified. Similarly, the various embodiments disclosed in this application are all based on the same inventive concept; therefore, concepts expressed in the same way, as well as concepts that are appropriately changed for convenience but are expressed differently, should be understood equivalently.

[0066] Unless otherwise expressly stated, the various embodiments disclosed in this application can be combined in a cross-cutting manner to flexibly construct new embodiments, as long as such combination does not depart from the inventive spirit of this application and can meet the needs of the prior art or solve a certain deficiency in the prior art. Those skilled in the art should be aware of such modifications.

[0067] Please refer to Figure 1. In one embodiment of the method for monitoring the load safety of pipelines crossing dikes according to this application, it includes:

[0068] Step S10: Collect load-related vibration signals corresponding to each sub-testing section of the pipeline to be tested through the dike, wherein the sub-testing section includes the buried pipe section inside the dike, the transition section of the dike shoulder, and the extension section outside the dike toe.

[0069] The distributed fiber optic vibration sensor in the embankment pipeline load safety monitoring system can collect load-related vibration signals corresponding to each sub-detection section of the pipeline to be tested. The sub-detection sections include the buried pipe section inside the embankment, the transition section at the embankment shoulder, and the extension section at the embankment toe.

[0070] Please refer to Figure 2. The method for monitoring the load safety of pipelines crossing dikes in this application can be implemented based on the pipeline load safety monitoring system shown in Figure 2. The pipeline load safety monitoring system includes a distributed optical fiber vibration sensor 1, a transmission optical cable 2, a distributed optical fiber vibration testing unit 3, a vibration signal identification and analysis unit 4, and a pipeline safety assessment unit 5, etc.

[0071] In some embodiments, the distributed fiber optic vibration sensor 1 is a single-mode fiber optic vibration sensor based on phase-sensitive optical time-domain reflectometry (PTZ) technology. The fiber core diameter is 9 / 125 μm, the vibration sensitivity is no more than 10 nm / √Hz, it is suitable for the 1 to 1000 Hz frequency band, and can operate stably in environments ranging from -40℃ to 85℃. The distributed fiber optic vibration sensor is laid in the same trench as the pipeline passing through the dike, extending along the pipeline axis and covering the entire pipeline, including the buried pipe section inside the dike, the transition section at the dike shoulder, and the extension section outside the dike. The extension section outside the dike needs to extend 5 to 10 meters beyond the dike toe to ensure the capture of the impact of external loads on the pipeline passing through the dike. The distributed fiber optic vibration sensor and the pipeline... The laying spacing of the pipeline under the dike is strictly controlled between 0.5 and 1m, with a deviation not exceeding ±0.1m, to avoid vibration signal attenuation caused by excessive spacing. The attenuation rate is controlled within 5%. Meanwhile, the distributed fiber optic vibration sensors can be deployed in two ways: one is to lay the distributed fiber optic vibration sensors separately, with the outer layer wrapped in a polyethylene protective sleeve with a wall thickness of not less than 2mm to prevent friction damage to the dike soil; the other is to directly utilize the redundant single-mode optical fiber in the communication optical cable laid in the same trench as the pipeline under the dike, reserving at least one core for sensing purposes, avoiding the need to lay additional sensors, thereby reducing project costs. This method is suitable for existing pipeline under the dike renovation projects.

[0072] In some embodiments, the transmission optical cable 2 is an armored single-mode optical cable with an armor layer of stainless steel tape, the thickness of which is not less than 0.3 mm. It possesses tensile strength of 1000 N or more, compressive strength (i.e., lateral pressure withstands 10 kN / 100 mm), and good corrosion resistance, capable of withstanding soil environments with a pH value between 3 and 11. This optical cable is used to connect distributed fiber optic vibration sensors and distributed fiber optic vibration testing units. The laying path of the transmission optical cable must avoid critical structures such as seepage barriers and intercepting trenches in the dike. If it is necessary to cross a seepage barrier, a PVC conduit with a diameter of not less than 50 mm should be used for protection and sealed to prevent seepage from the dike. The optical cable joints are spliced ​​using a fusion splicing method, with a splicing loss not exceeding 0.1 dB to ensure distortion-free transmission of load-related vibration signals.

[0073] In some embodiments, the distributed fiber optic vibration testing unit 3 is constructed based on a light source module, an optical coupler, a photodetector, and a data acquisition card. The light source module uses a 1550nm narrow-linewidth laser with a linewidth not exceeding 10kHz; the optical coupler has a coupling ratio of 50:50; the photodetector has a response bandwidth of 1GHz or higher; and the data acquisition card has a sampling rate of not less than 1MS / s. The distributed fiber optic vibration testing unit is entirely encapsulated in a waterproof and dustproof cabinet with an IP65 protection rating. It is installed in a monitoring station at least 10m away from the embankment to prevent flooding. The testing unit has real-time data acquisition, signal preprocessing, and data transmission functions. It can transmit data to the vibration signal identification and analysis unit via Ethernet (gigabit Ethernet port) or a 4G / 5G wireless module, with a data transmission rate of 100Mbps or higher and a latency of no more than 100ms to ensure real-time monitoring.

[0074] In some embodiments, the vibration signal identification and analysis unit 4 is composed of an industrial computer, signal processing software, and a load sample database. The industrial computer requires a CPU of at least Intel Core i7, at least 16GB of memory, and a hard disk capacity of at least 1TB SSD. The vibration signal identification and analysis unit 4 can be deployed at a local monitoring station or a remote monitoring center and can achieve data interaction through VPN.

[0075] Furthermore, referring to Figure 3, the vibration signal identification and analysis unit 4 is equipped with a signal preprocessing module, a signal spectrum analysis module, a sample comparison module, and a self-learning update module. It has the capability to operate continuously for 24 hours and supports multi-channel parallel data processing, capable of processing at least 8 fiber optic sensor signals simultaneously. First, the signal spectrum analysis module performs a fast Fourier transform on the load-related vibration signal to obtain the signal spectrum of the vibration signal, and extracts feature parameters from the signal spectrum, such as the main peak frequency, energy peak value, and spectral width. Next, the sample comparison module compares the feature parameters such as the main peak frequency, energy peak value, and spectral width with the pre-constructed load samples for similarity. If the similarity reaches or exceeds the similarity threshold, it is determined to be a successful match, and the corresponding load type, load size, and load application frequency are directly identified. If the similarity is lower than the similarity threshold, the self-learning update module is triggered to expand the sample space. This self-learning update module confirms the actual type and size of the new load by combining on-site video monitoring or manual inspection data, and then extracts features from the corresponding vibration signal spectrum to establish a new correspondence between "load type - load size - signal spectrum features". This relationship is automatically entered into the load sample database, and the parameters of the sample comparison algorithm are updated to ensure accurate identification of similar loads in the future.

[0076] In some embodiments, the safety assessment unit 5 for pipelines crossing embankments consists of a server, mechanical analysis software, and a safety assessment module. The server's CPU requirement is no less than an Intel Xeon E3, its memory requirement is no less than 32GB, and it supports GPU acceleration. This unit can synchronize data with the vibration signal identification and analysis unit via a local area network or cloud platform. The unit has a built-in library of three-dimensional coupled mechanical models of pipeline-embankment-foundation, covering common pipe materials such as steel pipes, PE pipes, and ductile iron pipes, as well as common embankment soil types such as cohesive soil, sandy soil, and soft soil. It also stores safety threshold parameters from standards such as the "Design Code for Oil and Gas Pipeline Crossing Engineering" and the "Technical Specification for Safety Protection Facilities in Water Conservancy and Hydropower Engineering Construction".

[0077] Furthermore, please refer to Figure 4, which is a schematic diagram of the three-dimensional coupled mechanical model of the pipeline-embankment-foundation. The safety assessment unit 5 for the pipeline crossing the embankment conducts a safety analysis according to the following steps:

[0078] First, parameters are input, automatically retrieving pipe parameters such as pipe elastic modulus, diameter, and wall thickness; embankment parameters such as soil cohesion, internal friction angle, and compaction degree; and foundation parameters such as bearing capacity and compression modulus. If any parameters are missing, design drawing data or field test data, such as geological survey reports, can be imported through the system interface. Second, a three-dimensional coupled mechanical model of the pipe-embankment-foundation is generated based on the input parameters, using finite element mesh generation to ensure calculation accuracy. The pipe mesh size does not exceed 50mm, and the embankment and foundation mesh sizes do not exceed 200mm. Next, the identified load data is applied as boundary conditions to the model for mechanical calculations to obtain the stress, deformation, and fatigue damage values ​​of the pipe under load. The stress values ​​include radial deformation, axial deformation, and lateral deformation values, and the deformation values ​​include radial deformation, axial deformation, and lateral deformation values. Fatigue damage values ​​can be calculated based on Miner's linear cumulative damage theory under load.

[0079] Step S20: Calculate and determine the average value of the load-related vibration signal within a preset time range as the reference vibration signal, use the fourth-order Dobes wavelet basis to perform multi-layer noise reduction on the load-related vibration signal, perform difference calculation between the load-related vibration signal after multi-layer noise reduction and the reference vibration signal, and take the load-related vibration signal with an amplitude exceeding the preset percentage of the reference vibration signal as the effective load vibration signal corresponding to the sub-detection segment.

[0080] After collecting load-related vibration signals corresponding to each sub-segment of the pipeline to be inspected, the average value of the load-related vibration signals within a preset time range is calculated and determined as the reference vibration signal. A fourth-order Dobessi wavelet basis is used to perform multi-layer noise reduction on the load-related vibration signals. The difference between the multi-layer noise-reduced load-related vibration signals and the reference vibration signals is calculated. Load-related vibration signals with amplitudes exceeding a preset percentage of the reference vibration signals are taken as the effective load vibration signals corresponding to the sub-segment. The preset time range includes 24 hours, 48 ​​hours, or 72 hours, etc.; the preset percentage can be 5%, etc.

[0081] In some embodiments, the steps of performing multi-layer noise reduction on the load-related vibration signal using a fourth-order Dobessi wavelet basis, performing difference calculation between the multi-layer noise-reduced load-related vibration signal and the reference vibration signal, and taking the load-related vibration signal with an amplitude exceeding a preset percentage of the reference vibration signal as the effective load vibration signal corresponding to the sub-detection segment include:

[0082] Step S201: Use a fourth-order Dobessi wavelet basis to perform five-layer noise reduction on the load-related vibration signals of each sub-detection segment to obtain the noise-reduced load-related vibration signals.

[0083] Step S202: Perform a difference calculation between the noise-reduced load-related vibration signal and the reference vibration signal, filter out signal segments whose amplitude exceeds 5% of the reference vibration signal, and determine the signal segments as effective load vibration signals.

[0084] Specifically, in the distributed optical fiber vibration testing unit 3, a fourth-order Dobesi wavelet basis (db4 wavelet basis) can be used for wavelet denoising, with the number of decomposition layers set to 5. This process aims to remove the interference of environmental noise such as wind and water flow, significantly improving the signal-to-noise ratio and ensuring an improvement of more than 20dB. The advantage of wavelet denoising using the fourth-order Dobesi wavelet basis is that it can effectively preserve the characteristics of the signal while removing noise components, thereby making subsequent processing more accurate. This distributed optical fiber vibration testing unit has an adjustable signal amplification function with an amplification factor ranging from 10 to 100 times. This mechanism ensures that even weak vibration signals can be effectively identified. By appropriately amplifying the signal, the sensitivity of the monitoring system to small-amplitude vibrations is enhanced. The real-time acquired signal is compared with a reference signal under no-load conditions. The reference signal is determined by continuously collecting data for more than 24 hours between 2:00 AM and 4:00 AM and averaging the data. The load-related vibration signal after multi-layer noise reduction is then compared with the reference vibration signal. Only those load-related vibration signals whose amplitude exceeds a preset percentage of the reference vibration signal are retained as the effective load vibration signals corresponding to the sub-detection segment. The preset percentage can be adjusted according to the pipe material and embankment type, and is usually set to 5%. This operation aims to filter out invalid interference signals, significantly reducing the amount of data required for subsequent analysis, thereby improving the efficiency and accuracy of data processing.

[0085] Step S30: Use Fourier transform to extract the main peak frequency feature parameter, energy peak feature parameter, and spectrum width feature parameter from the effective load vibration signal to construct a load feature vector. Compare the load feature vector with each load sample in the preset load sample database. If the similarity of a certain load sample is the maximum value among all matching results and exceeds the preset similarity threshold, then the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample are determined as the load identification data of the sub-detection segment.

[0086] The average value of the load-related vibration signal within a preset time range is calculated as the reference vibration signal. A fourth-order Dobessi wavelet basis is used to perform multi-layer noise reduction on the load-related vibration signal. The difference between the multi-layer noise-reduced load-related vibration signal and the reference vibration signal is calculated. Load-related vibration signals with amplitudes exceeding a preset percentage of the reference vibration signal are taken as the effective load vibration signal corresponding to the sub-detection segment. Fourier transform is then used to extract the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal to construct a load feature vector. The load feature vector is compared with the similarity of each load sample in a preset load sample database. If the similarity of a load sample is the maximum value among all matching results and exceeds a preset similarity threshold, the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample are determined as the load identification data of the sub-detection segment. The preset similarity threshold includes 90% or 95%, etc.

[0087] In some embodiments, the step of extracting the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal using Fourier transform to construct a load feature vector includes:

[0088] Step S301: Perform fast Fourier transform processing on the effective load vibration signal corresponding to each sub-segment of the pipeline to be tested to determine the signal spectrum corresponding to the effective load vibration signal.

[0089] Step S302: Extract the frequency component with the highest energy proportion in the signal spectrum as the main peak frequency feature parameter, take the maximum energy value in the signal spectrum as the energy peak feature parameter, and take the bandwidth of the frequency range in the signal spectrum where the energy proportion exceeds a preset percentage of the total energy as the spectrum width feature parameter.

[0090] Step S303: Combine the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter in sequence to construct the load characteristic vector corresponding to the sub-detection segment.

[0091] In a further embodiment, the step of comparing the similarity of the load feature vector with each load sample in a preset load sample database, and determining the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to the load sample as the load identification data of the sub-detection segment, includes:

[0092] Step S3001: Perform cosine similarity calculation on the load feature vectors of each sub-segment of the pipeline to be inspected and all load samples in the preset load sample database to determine the similarity calculation results.

[0093] Step S3002: Filter out the highest similarity among all similarity calculation results. If the highest similarity exceeds the preset similarity threshold, then the load type, load size and load frequency associated with the load sample corresponding to the highest similarity are determined as the load identification data corresponding to the sub-detection section of the pipeline to be detected.

[0094] Specifically, the preprocessed effective load vibration signal is transmitted to the vibration signal identification and analysis unit 4. First, the signal spectrum analysis module performs a fast Fourier transform on the effective load vibration signal to obtain the signal spectrum, and extracts the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter, etc. Next, the sample comparison module compares these characteristic parameters with all load samples in the pre-built load sample database for similarity, and selects the highest similarity among all similarity calculation results. If the highest similarity exceeds 90%, the load sample corresponding to the highest similarity is associated with... The load type, load size, and load frequency are determined as the load identification data corresponding to the sub-segment of the pipeline to be inspected. If the highest similarity is less than 90%, the self-learning update module is triggered to expand the sample space. This self-learning update module confirms the actual type and size of the new load by combining on-site video monitoring or manual inspection data, and then extracts the features of the corresponding vibration signal spectrum to establish a new correspondence between "load type - load size - signal spectrum features". This relationship is automatically entered into the load sample database, and the parameters of the sample comparison algorithm are updated to ensure accurate identification of similar loads in the future.

[0095] Furthermore, the initial construction of the load sample database is divided into two stages: laboratory simulation and outdoor field testing. In the laboratory simulation stage, a 1:10 scale model of the pipeline-dike structure was built. Different types of loads were applied using a hydraulic loading device, and vibration signals were collected and their spectra analyzed to establish a basic sample database. In the outdoor field testing stage, an operational pipeline-dike structure was selected, and vibration signals and load data were simultaneously collected for typical load conditions to supplement and improve the sample database. This ensures that the sample space covers at least 15 load types for pipelines-dike structures, with each load type corresponding to 8 to 10 different load level spectrum samples. These load types include constant self-weight load of the dike structure, vehicle traffic load on the dike crest, pedestrian activity load on the dike crest, seepage impact load of the dike structure, river flow impact load, river water level change load, uniform foundation settlement load, uneven foundation settlement load, and temporary foundation surcharge load. The load includes the self-weight load of the pipeline medium, the pressure load of the pipeline medium, the temperature deformation load of the pipeline, the temporary load of flood control construction, the secondary impact load of earthquake, and the disturbance load of plants and animals. Among these, the constant self-weight load of the dike body represents the constant load of the weight of the dike soil acting on the buried pipe section inside the dike over a long period of time; the vehicle traffic load on the dike top represents the intermittent dynamic load brought by motor vehicles and engineering vehicles passing on the dike top; the pedestrian activity load on the dike top represents the small-amplitude intermittent dynamic load brought by pedestrians and small non-motorized vehicles on the dike top; and the seepage impact load of the dike body represents the long-term dynamic load of groundwater seepage inside the dike on the pipe wall; the river... The river flow impact load represents the seasonal dynamic load of the river flow on the pipeline extending beyond the embankment toe; the river level change load represents the dynamic load transmitted to the pipeline due to the pressure changes in the embankment caused by the rise and fall of the river level; the uniform foundation settlement load represents the slow, long-term load generated by the uniform settlement of the foundation soil on the pipeline; the uneven foundation settlement load represents the tensile, long-term load generated by the local settlement of the foundation soil on the pipeline; the temporary foundation surcharge load represents the short-term dynamic load brought about by the temporary stockpiling of building materials and earthwork above the foundation; and the pipeline medium self-weight load represents the load brought about by the weight of the medium itself transported inside the pipeline. Long-term constant load; pipeline medium pressure load represents the long-term dynamic load caused by the operating pressure of the medium transported inside the pipeline; pipeline temperature deformation load represents the periodic dynamic load caused by the thermal expansion and contraction of the pipeline due to changes in environmental / medium temperature; temporary load for flood control construction represents the short-term dynamic load caused by equipment and materials during flood control construction of the dike; secondary impact load from earthquakes represents the sudden dynamic load on the pipeline caused by the shaking of the dike and foundation due to earthquakes; plant and animal disturbance load represents the small-amplitude long-term load caused by the activity of plants and animals inside the dike (such as soil loosening caused by ant holes and rat holes).

[0096] Step S40: Use the load identification data of the sub-detection segment as boundary conditions, and input the boundary conditions, the pipe parameters of the pipe to be detected through the dike, the dike parameters, and the foundation parameters into the preset three-dimensional coupled mechanical model of pipe-dike-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment.

[0097] Fourier transform is used to extract the main peak frequency characteristic parameters, energy peak characteristic parameters, and spectral width characteristic parameters from the effective load vibration signal to construct a load feature vector. The load feature vector is then compared with the similarity of each load sample in a preset load sample database. If the similarity of a load sample is the maximum value among all matching results and exceeds a preset similarity threshold, then the load type, load size, load application frequency, load application location coordinates, and load application duration corresponding to that load sample are determined as the load identification data of the sub-detection segment. The load identification data of the sub-detection segment is then used as the boundary... The boundary conditions, pipe parameters of the pipeline to be tested crossing the embankment, embankment parameters, and foundation parameters are input into a preset three-dimensional coupled mechanical model of the pipeline-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-test segment. The pipe parameters include the pipe's elastic modulus, pipe diameter, pipe wall thickness, etc.; the embankment parameters include soil cohesion, internal friction angle, compaction degree, etc.; and the foundation parameters include foundation bearing capacity, compression modulus, etc. The stress values ​​include circumferential stress, axial stress, and shear stress; and the deformation values ​​include radial deformation, axial deformation, and lateral deformation.

[0098] In some embodiments, the circumferential stress refers to the tensile or compressive stress generated along the tangential direction of the pipe wall when the pipeline is subjected to internal pressure or external load. It is the core stress affecting the deformation and rupture risk of the pipeline diameter. The axial stress refers to the stress generated along the axis of the pipeline through the embankment (the direction of medium transportation). It is mainly caused by the internal pressure of the pipeline, temperature changes, foundation settlement or axial load, and directly affects the expansion and contraction deformation and axial stability of the pipeline. The shear stress refers to the stress formed when there is a relative sliding tendency between different sections inside the pipe wall under load. It is mostly caused by lateral loads (such as water flow impact, landslide thrust) or uneven settlement, and is prone to local shear failure of the pipeline.

[0099] In some embodiments, the axial deformation represents expansion or displacement along the pipe axis (i.e., the direction of medium transport); the radial deformation represents expansion or contraction along the radius of the pipe cross-section (e.g., pipe diameter increase or decrease due to internal pressure); and the lateral deformation represents lateral displacement (non-radial) perpendicular to the pipe axis, i.e., horizontal or vertical offset of the pipe within its cross-section perpendicular to the radius (e.g., lateral displacement of the pipe due to embankment landslide).

[0100] In some embodiments, the elastic modulus of the pipe material represents the ratio of stress to strain during the elastic deformation stage, reflecting the pipe material's ability to resist elastic deformation. For example, the elastic modulus of steel pipes is much higher than that of PE pipes, resulting in smaller deformation under the same load. It is a key parameter for calculating the axial and circumferential stress distribution of the pipe, directly affecting the accuracy of the mechanical response results. The pipe diameter represents the cross-sectional diameter of the pipe, a core dimensional parameter for calculating stress distribution under load. The larger the pipe diameter, the more pronounced the stress concentration effect on the pipe wall under the same load (such as internal pressure or the self-weight of the embankment). The pipe wall thickness represents the thickness of the pipe wall, directly related to the structural strength and deformation resistance of the pipe. The greater the wall thickness, the stronger the pipe's ability to resist circumferential and shear stresses, effectively reducing the risk of pipe wall rupture and excessive deformation caused by load.

[0101] The soil cohesion refers to the internal cohesion between soil particles in the embankment, and is a core indicator of soil resistance to shear failure. Higher cohesion results in stronger overall soil integrity, making local collapse or sliding less likely during load transfer, thus reducing additional stress on the pipeline caused by embankment instability. The internal friction angle refers to the friction angle between soil particles, reflecting the soil's shear strength. A larger internal friction angle indicates stronger resistance to shear deformation, resulting in a more uniform pressure distribution of the embankment's self-weight load on the pipeline, reducing the risk of excessive local stress on the pipeline. The compaction degree refers to the ratio of the compacted dry density to the maximum dry density of the embankment soil, directly affecting the structural integrity and bearing capacity of the embankment. Higher compaction degree results in better soil density and smaller deformation, avoiding pulling and squeezing effects on the pipeline due to uneven embankment settlement, and is a fundamental condition for ensuring the accuracy of load identification by the monitoring system.

[0102] The bearing capacity of the foundation represents the maximum load strength that the foundation soil can withstand, reflecting the foundation's ability to support the pipeline and embankment. A higher bearing capacity results in less settlement under the same load, preventing pipeline deformation and breakage due to excessive foundation settlement. The compression modulus represents the compressive deformation characteristics of the foundation soil under pressure. A higher compression modulus indicates less compressive deformation of the soil under load. This parameter directly affects the calculation results of the pipeline's vertical displacement; a lower compression modulus results in greater foundation settlement and more significant tensile loads on the pipeline.

[0103] In a further embodiment, the vibration signal identification and analysis unit 4, after identifying the load identification data of each sub-segment in the pipeline to be inspected, including load type, load magnitude, load frequency, load location coordinates, and load duration, transmits the data to the pipeline safety assessment unit 5. The pipeline safety assessment unit 5 then performs a safety analysis according to the following steps:

[0104] First, parameter input is performed. The system automatically retrieves pipe parameters (including pipe elastic modulus, pipe diameter, and pipe wall thickness), embankment parameters (including soil cohesion, internal friction angle, and compaction degree), and foundation parameters (including bearing capacity and compression modulus) for the sub-segment of the pipeline to be inspected. If any parameters are missing, design drawing data or field inspection data, such as geological survey reports, can be imported through the system interface. Second, a three-dimensional coupled mechanical model of the pipeline-embankment-foundation is generated based on the input parameters. Finite element mesh generation is used to ensure calculation accuracy; the pipeline mesh size does not exceed 50cm, and the embankment and foundation mesh sizes do not exceed 200cm. Next, the identified load data is applied as boundary conditions to the model for mechanical calculations to obtain the stress, deformation, and fatigue damage values ​​of the pipeline under load. The stress values ​​include radial, axial, and lateral deformation values, and the deformation values ​​include radial, axial, and lateral deformation values. Fatigue damage values ​​can be calculated based on Miner's linear cumulative damage theory under load.

[0105] In some embodiments, the step of using the load identification data of the sub-detection segment as boundary conditions, and inputting the boundary conditions, the pipe parameters of the pipe to be detected crossing the embankment, the embankment parameters, and the foundation parameters into a preset three-dimensional coupled mechanical model of pipe-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment includes:

[0106] Step S401: Based on the finite element calculation results of the three-dimensional coupled mechanical model of pipeline-embankment-foundation, locate the set of nodes to be detected corresponding to each sub-detection segment of the pipeline crossing the embankment.

[0107] Specifically, the finite element calculation results represent the quantified mechanical response values ​​of all nodes to be tested in the pipeline, embankment, and foundation constructed by the model under the corresponding load boundary conditions. These values ​​include the circumferential stress, axial stress, shear stress, radial deformation value, axial deformation value, and lateral deformation value of each node to be tested. The results also include the spatial coordinate information and structural partition information of all nodes to be tested. The set of nodes to be tested represents the subset of nodes that perfectly match a certain sub-segment of the pipeline crossing the embankment, selected from all nodes to be tested in the finite element calculation results.

[0108] Step S402: For each sub-detection segment corresponding to the set of nodes to be detected, calculate the maximum values ​​of the circumferential stress, axial stress and shear stress of the pipeline to be detected within the set of nodes to be detected, and take the first average value among the maximum values ​​of the circumferential stress, the maximum values ​​of the axial stress and the maximum values ​​of the shear stress as the stress value corresponding to the sub-detection segment.

[0109] Step S403: Calculate the maximum values ​​of radial deformation, axial deformation, and lateral deformation of the pipeline to be inspected within the set of nodes to be inspected, and take the second average value among the maximum values ​​of radial deformation, axial deformation, and lateral deformation as the deformation value corresponding to the sub-inspection segment.

[0110] Step S404: Based on Miner's linear cumulative damage theory, and combining the stress cycle number within the set of nodes to be tested with the fatigue life curve of the pipe, calculate the fatigue damage increment of the sub-test segment under a single load, and superimpose the fatigue damage value of the sub-test segment in the historical cumulative cycle to obtain the fatigue damage value corresponding to the sub-test segment.

[0111] Step S50: Determine the safety assessment level corresponding to the sub-inspection section of the pipeline to be inspected based on the stress value, the deformation value, and the fatigue damage value, so as to complete the safety monitoring of the pipeline load.

[0112] Using the load identification data of the sub-detection segment as boundary conditions, the boundary conditions, the pipeline parameters of the pipeline to be detected crossing the embankment, the embankment parameters, and the foundation parameters are input into a preset three-dimensional coupled mechanical model of pipeline-embankment-foundation. After determining the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment, the safety assessment level corresponding to the sub-detection segment of the pipeline to be detected crossing the embankment is determined based on the stress value, deformation value, and fatigue damage value, so as to complete the safety monitoring of the load of the pipeline crossing the embankment.

[0113] In some embodiments, the step of determining the safety assessment level corresponding to the sub-inspection section of the pipeline under inspection based on the stress value, the deformation value, and the fatigue damage value includes:

[0114] Step S501: Obtain the stress value, deformation value, and fatigue damage value corresponding to each sub-segment of the pipeline to be inspected.

[0115] Step S502: Calculate and determine the first ratio between the stress value and the preset stress threshold, the second ratio between the deformation value and the preset deformation threshold, and the third ratio between the fatigue damage value and the preset fatigue damage threshold;

[0116] Step S503: If the first ratio, the second ratio, and the third ratio are all below 80%, then the sub-detection segment is determined to be a safe level.

[0117] Step S50: If any one of the first ratio, the second ratio, and the third ratio is between 80% and 100%, the sub-detection segment is determined to be a warning level, and a risk warning report is generated.

[0118] Step S504: If any one of the first ratio, the second ratio, and the third ratio reaches or exceeds 100%, the sub-detection segment is determined to be at a dangerous level, and an audible and visual alarm is triggered, and a danger alarm message is sent to the mobile terminal of the management personnel to complete the safety monitoring of the load on the pipeline crossing the embankment.

[0119] Specifically, the system calculates and determines a first ratio between the stress value and a preset stress threshold, a second ratio between the deformation value and a preset deformation threshold, and a third ratio between the fatigue damage value and a preset fatigue damage threshold. If all three ratios are below 80%, the sub-detection segment is classified as "safe." If any one of these ratios is between 80% and 100%, the sub-detection segment is classified as "warning level," and a risk warning report is generated. The report includes load information, calculation results for stress, deformation, and fatigue damage values, and the cause of the risk. If any one of these ratios reaches or exceeds 100%, the sub-detection segment is classified as "danger level," and the system immediately triggers an audible and visual alarm, sends a danger alarm message to the administrator's mobile app and email, and marks the location coordinates of the danger in the sub-detection segment to guide emergency response.

[0120] In some embodiments, sensor protection is optimized as follows: In sections of the dike where erosion is severe, such as the toe of the dike and the upstream slope, the distributed fiber optic vibration sensor needs to be additionally wrapped with a wire mesh protective sleeve. The wire diameter should be no less than 2 mm, and the mesh size should be no greater than 10 mm. Simultaneously, the sensor should be fixed with concrete of C25 strength, with a wrapping thickness of no less than 50 mm, to prevent damage to the sensor from impacts by rocks during water erosion.

[0121] In some embodiments, remote monitoring and control: the safety assessment unit for pipelines crossing embankments supports remote access via web and mobile app. Managers can view load identification results, safety assessment levels, and historical data curves in real time, and can also remotely adjust system parameters, such as vibration signal mutation threshold and load sample space similarity threshold, without the need for on-site operation, thereby improving management efficiency.

[0122] In some embodiments, data backup and redundancy are implemented: both the distributed fiber optic vibration testing unit and the vibration signal identification and analysis unit adopt a dual-machine hot standby mode. When the main device fails, the backup device can automatically switch over within 10 seconds to ensure that no data is lost. In addition, the system regularly backs up monitoring data to the local hard drive and cloud server, using encrypted transmission and the AES-256 encryption algorithm, and retains at least one year of historical data for subsequent traceability and analysis.

[0123] As can be seen from the above embodiments, compared with the prior art, this application addresses the problems of traditional methods for monitoring the load safety of pipelines crossing dikes, which require excavating the dike and pipeline foundation to install sensors. This not only damages the structural integrity of the dike but also results in high construction difficulty and cost, and makes it difficult to effectively predict the structural damage risk of pipelines crossing dikes under complex loads. This application has, but is not limited to, the following beneficial effects:

[0124] Firstly, this application adopts a distributed fiber optic vibration sensor and pipeline laid in the same trench, eliminating the need for excavation of the dike and pipeline foundations. This avoids the structural integrity damage to the dike caused by traditional strain sensor deployment, ensuring that the core functions of flood control and seepage prevention of the dike remain unaffected. The sensor extends continuously along the pipeline axis, fully covering the buried pipe section inside the dike, the transition section at the dike shoulder, and the extension section outside the dike. This solves the monitoring blind spot problem caused by the traditional "point-based layout" and achieves continuous monitoring of the entire pipeline without blind spots. Simultaneously, the distributed fiber optic vibration sensor is a single-mode fiber optic vibration sensor based on phase-sensitive optical time-domain reflectometry technology, requiring no additional laying, significantly reducing construction difficulty and cost, and is particularly suitable for renovation projects of existing pipelines.

[0125] Secondly, this application combines Fast Fourier Transform to extract core feature parameters such as peak frequency and energy peak value, and compares them with similarity thresholds to achieve accurate identification of load type, size, and frequency of action. The system has a self-learning and updating function, which can expand the new load samples through on-site verification, effectively dealing with the complex, random, and sudden characteristics of loads on pipelines crossing embankments. In the signal preprocessing stage, techniques such as db4 wavelet basis multilayer noise reduction and 10 to 100 times adjustable amplification are used to improve the signal-to-noise ratio to over 20dB, successfully filtering environmental interference such as wind noise and water flow noise, ensuring that even weak load signals can be accurately captured, and realizing real-time monitoring and identification of loads.

[0126] Thirdly, this application uses the measured loads on site as boundary conditions and combines the actual physical parameters of the pipeline, embankment, and foundation. It performs finite element calculations through a three-dimensional coupled mechanical model of pipeline-embankment-foundation. Compared with traditional assumed load analysis, this method can more realistically reflect the mechanical properties of the pipeline. The model adopts fine mesh division to accurately calculate circumferential stress, axial stress, shear stress, and various deformation values. Based on Miner's linear cumulative damage theory, it quantifies the cumulative amount of fatigue damage to establish a multi-level safety assessment for accurate classification. When an early warning is issued, it automatically generates an analysis report containing load information, calculation results including stress values, deformation values, and fatigue damage values, as well as the analysis report of the risk causes. In case of danger, it immediately triggers an audible and visual alarm and pushes an emergency notification containing coordinate information, effectively predicting structural damage risks and solving the problem of inaccurate assessment by traditional technologies.

[0127] Please refer to Figure 5. A load safety monitoring device for a pipeline crossing a dam, provided for one of the purposes of this application, includes a vibration signal acquisition module 1100, an effective signal confirmation module 1200, a load data determination module 1300, a three-dimensional coupling module 1400, and a safety monitoring module 1500. The vibration signal acquisition module 1100 is configured to acquire load-related vibration signals corresponding to each sub-detection segment of the pipeline to be tested through the dike. The sub-detection segments include the buried pipe segment inside the dike, the dike shoulder transition segment, and the dike toe extension segment. The effective signal confirmation module 1200 is configured to calculate and determine the average value of the load-related vibration signals within a preset time range as the reference vibration signal, perform multi-layer noise reduction on the load-related vibration signals using a fourth-order Dobes wavelet basis, perform difference calculation between the multi-layer noise-reduced load-related vibration signals and the reference vibration signal, and determine the load-related vibration signals whose amplitude exceeds a preset percentage of the reference vibration signal as the effective load vibration signals corresponding to the sub-detection segments. The load data determination module 1300 is configured to extract the main peak frequency characteristic parameters, energy peak characteristic parameters, and spectral width characteristic parameters from the effective load vibration signals using Fourier transform to construct a load feature vector, and then compare the load feature vector with... The similarity of each load sample in the preset load sample database is compared. If the similarity of a certain load sample is the maximum value among all matching results and exceeds the preset similarity threshold, the load type, load size, load frequency, load location coordinates, and load duration corresponding to the load sample are determined as the load identification data of the sub-detection segment. The three-dimensional coupling module 1400 is configured to use the load identification data of the sub-detection segment as boundary conditions, and input the boundary conditions, the pipeline parameters of the pipeline to be detected, the embankment parameters, and the foundation parameters into the preset pipeline-embankment-foundation three-dimensional coupled mechanical model to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment. The safety monitoring module 1500 is configured to determine the safety assessment level corresponding to the sub-detection segment of the pipeline to be detected based on the stress value, the deformation value, and the fatigue damage value, so as to complete the safety monitoring of the pipeline load.

[0128] Based on any embodiment of this application, referring to Figure 6, another embodiment of this application also provides an electronic device, which can be implemented by a computer device. As shown in Figure 6, this is a schematic diagram of the internal structure of the computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium stores an operating system, a database, and computer-readable instructions. The database may store a sequence of control information. When the computer-readable instructions are executed by the processor, the processor can implement a method for monitoring the load safety of a pipeline crossing a dam. The processor of the computer device provides computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute the method for monitoring the load safety of a pipeline crossing a dam as described in this application. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that the structure shown in Figure 6 is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the computer device to which the solution of this application is applied. Specific computer devices may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0129] In this embodiment, the processor executes the specific functions of each module in Figure 5, and the memory stores the program code and various types of data required to execute the above modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all modules in the dam-crossing pipeline load safety monitoring device of this application, and the server can call the server's program code and data to execute the functions of all modules.

[0130] This application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the load safety monitoring method for pipelines crossing dikes as described in any embodiment of this application.

[0131] This application also provides a computer program product, including a computer program / instructions that, when executed by one or more processors, implement the steps of the method for monitoring the load safety of pipelines crossing embankments as described in any embodiment of this application.

[0132] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0133] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for monitoring the load safety of pipelines crossing embankments, characterized in that, include: Load-related vibration signals are collected for each sub-segment of the pipeline to be inspected across the dike. Each sub-segment includes the buried pipe section within the dike, the transition section at the dike shoulder, and the extension section at the dike toe. The average value of the load-related vibration signals within a preset time range is calculated as the reference vibration signal. A fourth-order Dobese wavelet basis is used to perform multi-layer noise reduction on the load-related vibration signals. The difference between the multi-layer noise-reduced load-related vibration signals and the reference vibration signal is calculated. Load-related vibration signals with amplitudes exceeding a preset percentage of the reference vibration signal are taken as the effective load vibration signals corresponding to the sub-segment. Fourier transform is used to extract the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signals. A load feature vector is constructed, and the similarity of the load feature vector with each load sample in a preset load sample database is compared. If the similarity of a certain load sample is the maximum value among all matching results and exceeds a preset similarity threshold, then the load type, load size, load frequency, load location coordinates, and load duration corresponding to the load sample are determined as the load identification data of the sub-detection segment. The load identification data of the sub-detection segment is used as boundary conditions. The boundary conditions, the pipe parameters of the pipeline to be detected, the embankment parameters, and the foundation parameters are input into a preset three-dimensional coupled mechanical model of pipeline-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment. Based on the stress value, the deformation value, and the fatigue damage value, the safety assessment level corresponding to the sub-inspection section of the pipeline under test is determined to complete the safety monitoring of the pipeline load.

2. The method for monitoring the load safety of pipelines crossing dikes according to claim 1, characterized in that, The steps of performing multi-layer noise reduction on the load-related vibration signal using a fourth-order Dobesi wavelet basis, performing difference calculation on the multi-layer noise-reduced load-related vibration signal and the reference vibration signal, and taking the load-related vibration signal with an amplitude exceeding a preset percentage of the reference vibration signal as the effective load vibration signal corresponding to the sub-detection segment, include: performing five-layer noise reduction on the load-related vibration signal of each sub-detection segment using a fourth-order Dobesi wavelet basis to obtain a noise-reduced load-related vibration signal; performing difference calculation on the noise-reduced load-related vibration signal and the reference vibration signal, filtering out signal segments with an amplitude exceeding 5% of the reference vibration signal, and determining the signal segments as effective load vibration signals.

3. The method for monitoring the load safety of pipelines crossing embankments according to claim 1, characterized in that, The steps of extracting the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal using Fourier transform to construct a load feature vector include: performing fast Fourier transform processing on the effective load vibration signal corresponding to each sub-detection segment of the pipeline to be tested to determine the signal spectrum corresponding to the effective load vibration signal; extracting the frequency component with the highest energy proportion in the signal spectrum as the main peak frequency characteristic parameter, taking the maximum energy value in the signal spectrum as the energy peak characteristic parameter, and taking the bandwidth of the frequency range in the signal spectrum where the energy proportion exceeds a preset percentage of the total energy as the spectral width characteristic parameter; and combining the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter in sequence to construct the load feature vector corresponding to the sub-detection segment.

4. The method for monitoring the load safety of pipelines crossing dikes according to claim 1, characterized in that, The step of comparing the load feature vector with each load sample in the preset load sample database for similarity, and determining the load type, load size, load frequency, load position coordinates, and load duration corresponding to the load sample as the load identification data of the sub-detection segment if the similarity of a certain load sample is the maximum value among all matching results and exceeds the preset similarity threshold, includes: performing cosine similarity calculation on the load feature vector of each sub-detection segment of the pipeline to be detected with all load samples in the preset load sample database to determine the similarity calculation result; filtering out the highest similarity among all similarity calculation results; if the highest similarity exceeds the preset similarity threshold, determining the load type, load size, and load frequency associated with the load sample corresponding to the highest similarity as the load identification data corresponding to the sub-detection segment of the pipeline to be detected.

5. The method for monitoring the load safety of pipelines crossing dikes according to claim 1, characterized in that, Using the load identification data of the sub-detection segment as boundary conditions, the boundary conditions, pipe parameters of the pipeline to be tested, embankment parameters, and foundation parameters are input into a preset three-dimensional coupled mechanical model of pipeline-embankment-foundation to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment. This includes: using the finite element calculation results of the pipeline-embankment-foundation three-dimensional coupled mechanical model to locate the set of nodes to be tested corresponding to each sub-detection segment of the pipeline to be tested; for each set of nodes to be tested corresponding to a sub-detection segment, the maximum values ​​of the circumferential stress, axial stress, and shear stress of the pipeline to be tested within the set of nodes to be tested are calculated; and the maximum values ​​of the circumferential stress, axial stress, and shear stress of the pipeline to be tested are calculated. The first average value between the maximum stress and the maximum shear stress is taken as the stress value corresponding to the sub-detection segment. The maximum values ​​of radial deformation, axial deformation, and transverse deformation of the pipeline to be tested within the set of nodes to be tested are statistically analyzed, and the second average value between these three values ​​is taken as the deformation value corresponding to the sub-detection segment. Based on Miner's linear cumulative damage theory, and combined with the stress cycle number and pipe fatigue life curve within the set of nodes to be tested, the fatigue damage increment of the sub-detection segment under a single load is calculated. The fatigue damage values ​​of the sub-detection segment in the historical cumulative cycle are then superimposed to obtain the fatigue damage value corresponding to the sub-detection segment.

6. The method for monitoring the load safety of pipelines crossing dikes according to claim 5, characterized in that, The step of determining the safety assessment level of a sub-inspection section of the pipeline under test based on the stress value, deformation value, and fatigue damage value includes: acquiring the stress value, deformation value, and fatigue damage value corresponding to each sub-inspection section of the pipeline under test; calculating and determining a first ratio between the stress value and a preset stress threshold, a second ratio between the deformation value and a preset deformation threshold, and a third ratio between the fatigue damage value and a preset fatigue damage threshold; if the first ratio, the second ratio, and the third ratio are all below 80%, the sub-inspection section is determined to be at a safe level; if any one of the first ratio, the second ratio, and the third ratio is between 80% and 100%, the sub-inspection section is determined to be at a warning level, and a risk warning report is generated; if any one of the first ratio, the second ratio, and the third ratio reaches or exceeds 100%, the sub-inspection section is determined to be at a dangerous level, and an audible and visual alarm is triggered, and a danger alarm message is sent to the mobile terminal of the management personnel to complete the safety monitoring of the pipeline load.

7. The method for monitoring the load safety of pipelines crossing dikes according to any one of claims 1 to 6, characterized in that, The pipeline parameters include the pipe's elastic modulus, pipe diameter, and pipe wall thickness; the embankment parameters include soil cohesion, internal friction angle, and compaction degree; the foundation parameters include foundation bearing capacity and compression modulus; the stress values ​​include circumferential stress, axial stress, and shear stress; and the deformation values ​​include radial deformation, axial deformation, and lateral deformation.

8. A load safety monitoring device for pipelines crossing embankments, characterized in that, The system includes: a vibration signal acquisition module, configured to acquire load-related vibration signals corresponding to each sub-detection segment of the pipeline to be inspected across the embankment, wherein the sub-detection segment includes the buried pipe segment inside the embankment, the transition segment at the embankment shoulder, and the extension segment at the embankment toe; an effective signal confirmation module, configured to calculate and determine the average value of the load-related vibration signals within a preset time range as the reference vibration signal, perform multi-layer noise reduction on the load-related vibration signals using a fourth-order Dobes wavelet basis, perform difference calculation between the multi-layer noise-reduced load-related vibration signals and the reference vibration signal, and determine the load-related vibration signals whose amplitude exceeds a preset percentage of the reference vibration signal as the effective load vibration signals corresponding to the sub-detection segment; and a load data determination module, configured to extract the main peak frequency characteristic parameter, energy peak characteristic parameter, and spectral width characteristic parameter from the effective load vibration signal using Fourier transform to construct a load feature vector, and compare the load feature vector with a preset... The system compares the similarity of each load sample in the load sample database. If the similarity of a certain load sample is the maximum value among all matching results and exceeds a preset similarity threshold, then the load type, load size, load frequency, load location coordinates, and load duration corresponding to the load sample are determined as the load identification data of the sub-detection segment. The three-dimensional coupling module is configured to use the load identification data of the sub-detection segment as boundary conditions, and input the boundary conditions, the pipeline parameters of the pipeline to be detected, the embankment parameters, and the foundation parameters into a preset pipeline-embankment-foundation three-dimensional coupled mechanical model to determine the stress value, deformation value, and fatigue damage value corresponding to the sub-detection segment. The safety monitoring module is configured to determine the safety assessment level corresponding to the sub-detection segment of the pipeline to be detected based on the stress value, the deformation value, and the fatigue damage value, so as to complete the safety monitoring of the pipeline load.

9. An electronic device comprising a central processing unit and a memory, characterized in that, The central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implemented according to any one of claims 1 to 7, which, when invoked by a computer, executes the steps included in the corresponding method.

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