Pipeline inspection method and apparatus

Abstract

The application relates to the technical field of pipeline safety, and discloses a pipeline inspection method and device. The method comprises the following steps: determining a target inspection path of a to-be-detected pipeline; wherein the target inspection path is a periodic inspection path described by a first function; performing safety inspection based on the target inspection path to obtain a line inspection result of the to-be-detected pipeline; when the line inspection result indicates that a first abnormal situation exists, performing leakage tracing processing to obtain a leakage tracing result; wherein the first abnormal situation is used for describing a gas leakage safety accident of the to-be-detected pipeline; generating first emergency warning information based on the leakage tracing result to assist in carrying out emergency response and risk control of the to-be-detected pipeline. The method has the beneficial effect that the pipeline inspection is upgraded from a traditional manual or simple aerial photography mode to an intelligent and automatic leakage sensing and tracing mode, and safety accidents caused by pipeline leakage can be effectively prevented and reduced.

Description

Technical Field

[0001] This application relates to the field of pipeline safety technology, and in particular to a pipeline inspection method and apparatus. Background Technology

[0002] Pipeline transportation, as another major mode of transport besides road, rail, sea, and air transport, is unaffected by weather and other natural factors, enabling continuous delivery of pipeline media and exhibiting high reliability and stability. However, as pipelines operate over time, their integrity can be weakened by the characteristics of the transported media, the aging of their own structures, environmental corrosion, and the impact of human activities. This can lead to leaks of the transported media and potentially cause safety accidents such as explosions, fires, and poisoning, posing serious safety threats.

[0003] Pipeline operators typically manage pipeline patrols to promptly identify and control any anomalies along the pipeline route, serving as a crucial means of ensuring safe pipeline operation. Generally, production pipelines face complex equipment distribution within plant areas, while long-distance pipelines encounter harsh natural environments such as deserts, Gobi, and mountainous regions. Furthermore, the unique chemical properties of the transported media can potentially cause harm to human health. All these factors significantly complicate traditional manual pipeline patrol methods. In recent years, with the rapid development of science and technology, the application of intelligent equipment such as robots and drones in the oil, gas, and petrochemical fields has become increasingly widespread. In particular, drone-based intelligent inspection technology has played a significant role in production area inspections, pipeline reconnaissance, and emergency patrols, improving efficiency and reducing costs for enterprises.

[0004] However, current pipeline safety inspection methods have limitations such as low identification accuracy and slow response speed, and there is a need to further improve the efficiency of pipeline inspection. Summary of the Invention

[0005] This application aims to at least partially solve one of the technical problems in related technologies. To this end, this application proposes a pipeline inspection method and apparatus. The main technical solutions adopted in this application include:

[0006] Firstly, this application provides a pipeline inspection method, which includes: determining a target inspection path for the pipeline to be inspected; wherein the target inspection path is a periodic inspection path described by a first function; performing a safety inspection based on the target inspection path to obtain the inspection results of the pipeline to be inspected; when the inspection results indicate the presence of a first abnormality, performing leak tracing to obtain the leak tracing results; wherein the first abnormality is used to describe a gas leak safety accident in the pipeline to be inspected; and generating a first emergency warning message based on the leak tracing results to assist in emergency response and risk management of the pipeline to be inspected.

[0007] By using the first function model to plan periodic target inspection paths, the inspection coverage is expanded, and flexible control of the inspection paths is facilitated through parameter adjustments. Subsequently, safety inspections are performed based on the target inspection paths to comprehensively collect pipeline-related data, providing a reliable basis for risk identification. Then, upon identification of the first anomaly, leak tracing is immediately initiated to accurately and quickly determine the leak situation. Finally, based on the leak tracing results, a first emergency warning message is generated, which assists in rapid emergency response and risk management. This upgrades pipeline inspection from traditional manual or simple aerial photography to an intelligent and automated leak detection and tracing model, effectively preventing and reducing safety accidents caused by pipeline leaks.

[0008] Optionally, determining the target inspection path for the pipeline to be inspected includes: obtaining pipeline status parameters of the pipeline to be inspected; determining the regional risk level of the pipeline to be inspected based on the pipeline status parameters; wherein the regional risk level is used to describe the importance of the pipeline to be inspected in each sub-inspection area; determining the initial inspection path based on the regional risk level; and performing path correction processing based on environmental parameters and the initial inspection path to obtain the target inspection path.

[0009] First, comprehensive parameters reflecting the pipeline's condition were acquired, providing a data foundation for risk assessment. These parameters were then used to determine the regional risk level, clarifying the key areas for inspection. Next, an initial inspection path was generated based on the risk level, ensuring the inspection's relevance and comprehensiveness. Subsequently, the path was revised using real-time environmental parameters, enabling it to dynamically adapt to environmental changes and improve the probability of leak detection. Ultimately, this significantly improved the efficiency and reliability of pipeline inspections.

[0010] Optionally, the initial inspection path is determined based on the regional risk level, including: adjusting the first, second, and third parameters in the initial first function model using the regional risk level and the current inspection round to obtain the initial inspection path; wherein, the first parameter refers to the amplitude parameter used to control the inspection amplitude; the second parameter refers to the frequency parameter used to control the inspection frequency; and the third parameter refers to the phase parameter used to control the inspection coverage area.

[0011] This method, which adjusts the amplitude, frequency, and phase parameters in the initial first function model based on the regional risk level and the current inspection round, can generate an initial inspection path that matches the actual risk distribution of the pipeline and provides more comprehensive coverage. This not only meets the needs of differentiated risk management but also ensures the comprehensiveness of subsequent rounds of inspections.

[0012] Optionally, the first, second, and third parameters in the initial first function model are determined using the regional risk level and the current inspection round to obtain the initial inspection path. This includes: determining the first and second parameters in the initial first function model using the regional risk level to obtain the baseline inspection path; wherein the baseline inspection path corresponds to the baseline first function model; and adjusting the third parameter of the baseline first function model based on the current inspection round to obtain the initial inspection path.

[0013] By using regional risk levels to determine the first and second parameters, the baseline inspection path can adaptively adjust its coverage width and inspection density for different risk areas, thereby allocating more inspection resources to high-risk areas and improving inspection effectiveness. Adjusting the third parameter using the current inspection cycle ensures that all angles on both sides of the pipeline are covered after multiple inspections, avoiding missed inspections due to a fixed viewing angle.

[0014] Optionally, the initial inspection path corresponds to a theoretical first function model; path correction processing is performed based on environmental parameters and the initial inspection path to obtain the target inspection path, including: gas diffusion prediction based on environmental parameters to obtain the predicted diffusion result; and adjusting the fourth parameter in the theoretical first function model based on the predicted diffusion result to obtain the target inspection path; wherein, the fourth parameter refers to the offset parameter used to control the degree of deviation of the overall inspection path.

[0015] First, gas diffusion prediction based on environmental parameters allows for early identification of potential gas distribution areas, providing a basis for subsequent path correction. Then, by adjusting the fourth parameter, the inspection path is shifted towards higher-probability detection areas, significantly increasing the probability that the inspection equipment will detect leaking gas when a real leak occurs.

[0016] Optionally, a safety inspection is performed based on the target inspection path to obtain the inspection results of the pipeline to be inspected, including: during the safety inspection, the inspection path is checked based on real-time location parameters to obtain the inspection check results; the target inspection path is adjusted based on the inspection check results to obtain the actual inspection path; and a safety inspection is performed based on the actual inspection path to obtain the inspection results of the pipeline to be inspected.

[0017] By verifying the inspection path using real-time location parameters, flight deviations of the inspection equipment can be detected promptly, preventing missed inspection areas due to these deviations. Based on the verification results, the target inspection path is adjusted to obtain the actual inspection path, effectively and accurately correcting any deviations. Finally, the corrected path guides subsequent inspection processes, thereby improving the reliability and accuracy of the final line inspection results.

[0018] Optionally, the method further includes: when the pipeline inspection results indicate the presence of a second anomaly, performing pipeline threat identification processing to obtain a threat identification result; wherein the second anomaly is used to describe the structural anomaly risk of the pipeline under inspection; and generating a second emergency warning message based on the threat identification result to assist in carrying out preventive maintenance and risk intervention for the pipeline under inspection.

[0019] By analyzing image data from pipeline inspections, automated and real-time identification of pipeline structural anomalies and risks was achieved, enabling timely detection of potential risks related to pipeline structures. Subsequently, the identified anomalies were precisely classified and located, generating structured information that directly guides on-site intervention. Ultimately, this information guides maintenance units to conduct targeted preventative maintenance, proactively mitigating risks and reducing the probability of leaks caused by pipeline structural damage.

[0020] Optionally, leak tracing can be performed as follows: A target tracing area is determined based on gas diffusion data of the pipeline under test in the leak area; wherein, the target tracing area is a spatial search range described by a second function; iterative tracing and localization processing is performed within the target tracing area to obtain the leak tracing result. First, a target tracing area described by a quadratic function is determined based on the gas diffusion data, narrowing the search range of the leak point from a broad space to a specific planar area, greatly improving search efficiency. Next, iterative detection is performed within this area, continuously sensing the environment and updating the location, achieving dynamic tracking and gradual approach to the leak point. Finally, by integrating the localization results from multiple iterations, a precise leak point coordinate and its confidence interval are obtained. The entire process achieves automated tracing from area locking to precise point location, significantly improving the speed and accuracy of leak emergency response.

[0021] Optionally, iterative source tracing and localization processing is performed in the target source tracing area to obtain leakage source tracing results, including: determining the current source tracing starting point and determining the current source tracing path based on the current source tracing starting point and the target source tracing area; wherein, the current source tracing path is a leakage detection path described by a third function; performing leakage detection and source tracing localization based on the current source tracing path to obtain the current source tracing result; calculating based on the current source tracing path and the target source tracing area to obtain the next source tracing starting point, and using the next source tracing starting point as the new current source tracing starting point, repeating the above steps for determining the new current source tracing starting point, and determining the leakage source tracing result based on the current source tracing results obtained in each iteration when the iteration termination condition is met.

[0022] By determining the current source of leakage and constructing the current source path using a third function, the detection path is made to conform to the gas concentration gradient distribution, achieving a progressive detection from the regional boundary to the leak core. Subsequently, based on this path, environmental data and gas diffusion data are reused to determine the source tracing result. This allows the leak tracing process to adapt to environmental changes in real time, ensuring that the physical model (diffusion direction) used for each location analysis is up-to-date, thereby improving the environmental adaptability of the location. Finally, by integrating the location results obtained from multiple iterations, the error of a single measurement can be effectively smoothed, and a final result including a confidence interval can be provided, thus significantly improving the robustness and accuracy of leak point location.

[0023] Secondly, this application provides a pipeline inspection device, which includes:

[0024] The inspection path determination module is used to determine the target inspection path for the pipeline to be inspected; wherein, the target inspection path is a periodic inspection path described by the first function;

[0025] The pipeline inspection execution module is used to perform safety inspections based on the target inspection path in order to obtain the pipeline inspection results.

[0026] The leak tracing execution module is used to perform leak tracing processing when the pipeline inspection results show the presence of a first abnormality, in order to obtain the leak tracing results; wherein, the first abnormality is used to describe a gas leak accident in the pipeline to be inspected;

[0027] The emergency warning module is used to generate the first emergency warning information based on the leak tracing results, so as to assist in the emergency response and risk management of the pipeline to be inspected. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1a This is a flowchart of a pipeline inspection method according to an embodiment of this application;

[0030] Figure 1b This is a schematic diagram of a target inspection path provided according to an embodiment of this application;

[0031] Figure 2 Here is a flowchart of a pipeline inspection method according to yet another embodiment of this application;

[0032] Figure 3 This is a flowchart illustrating the determination of a target inspection path according to an embodiment of this application;

[0033] Figure 4a This is a flowchart for determining a target inspection path according to another embodiment of this application;

[0034] Figure 4b This is a schematic diagram of a target tracing area provided according to an embodiment of this application;

[0035] Figure 4c This is a schematic diagram of a data acquisition plane according to an embodiment of this application;

[0036] Figure 4d This is a schematic diagram illustrating the determination of a target tracing region according to an embodiment of this application;

[0037] Figure 4e This is a schematic diagram of the current tracing path provided according to one embodiment of this application;

[0038] Figure 4f This is a schematic diagram of iterative source tracing and localization according to an embodiment of this application;

[0039] Figure 5 This is a structural block diagram of a pipeline inspection device provided according to an embodiment of this application. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] Specifically, taking gas pipelines as an example, the pipeline inspection and management methods in related technologies still have the following limitations: Pipeline inspection and management based on UAV platforms mainly relies on UAVs equipped with image capture systems to monitor the surrounding environment of the pipeline and identify abnormal situations such as third-party construction or illegal encroachment that may damage the pipeline's integrity. Innovations in UAV path planning methods based on the above objectives mainly aim to improve the computational speed of path planning by enabling UAVs to complete target task point scanning, minimize inspection time, reduce energy consumption, and ensure safe flight and obstacle avoidance. However, there is currently no effective solution for using UAV path planning methods to identify whether leaks have occurred in the pipeline during the transportation of relevant media and to trace the source of leaks after confirmation.

[0042] Based on this, according to the embodiments of this application, a pipeline inspection method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0043] This embodiment provides a pipeline inspection method, such as Figure 1a As shown, the method includes the following steps:

[0044] S110. Determine the target inspection path for the pipeline to be inspected.

[0045] The target inspection path can be a spatial trajectory that instructs the inspection equipment to perform safety inspection tasks. Specifically, the target inspection path is a periodic inspection path described by a first function. For example, this first function can be a sine or cosine function; for example, please refer to [reference needed]. Figure 1bThe image shows a top view of the pipeline to be inspected: a coordinate system is established with the pipeline's central axis as the X-axis, the direction perpendicular to the central axis as the Y-axis, and the center of the cross-section at the pipeline's starting position as the origin. Assuming the pipeline is a straight line from west to east, the east-west direction can be used as the X-axis, with the eastward direction being the positive X-axis; the north-south direction can be used as the Y-axis, with the northward direction being the positive Y-axis. In this coordinate system, the target inspection path can be mathematically represented using a sine function model (y=Asin(wx+φ)+B). If a drone is used as the inspection device, its flight trajectory in the coordinate system (i.e., the target inspection path) can be presented as a periodic curve following this sine function, achieving wide-area coverage inspection along the pipeline's extension direction.

[0046] Understandably, the aforementioned sine function model contains four key parameters: amplitude parameter A, frequency parameter w, phase parameter φ, and offset parameter B. Amplitude parameter A controls the oscillation amplitude of the inspection path along the Y-axis, i.e., the width of the lateral inspection. Frequency parameter w controls the number of periodic oscillations of the inspection path per unit distance along the X-axis (pipeline direction), i.e., the inspection density. Phase parameter φ controls the starting position of the sine waveform, affecting the starting point of coverage for different pipe regions. Offset parameter B controls the overall translational amount of the entire inspection path along the Y-axis.

[0047] Specifically, the pipeline status parameters and gas characteristic parameters of the pipeline to be inspected can be obtained first. Based on these parameters, the pipeline is divided into areas and a risk level assessment is performed. Then, an initial inspection path is generated by combining the area risk level and the current inspection round. Finally, the initial inspection path is corrected based on real-time environmental parameters to obtain the target inspection path.

[0048] For example, taking the sine function model (y=Asin (wx+φ)+B) as an example, the determination of the amplitude parameter A and the frequency parameter w mainly depends on the regional risk level of each sub-inspection area. For instance, during the initial inspection, the regional risk level of each sub-inspection area can be determined by comprehensively using the Kent method to assess the pipeline condition parameters (such as whether the pipeline has cracks, dents, bends, and flanges that are prone to leakage, and the pipeline's service life) and gas characteristic parameters (such as the toxicity, flammability, explosiveness, and diffusion rate of the pipeline gas).

[0049] Subsequently, for sub-inspection areas with higher regional risk levels, the amplitude parameter A can be increased to expand the lateral coverage of the inspection, while the frequency parameter w can be increased to improve the inspection density and ensure that no potential risk points are missed. For sub-inspection areas with lower regional risk levels, the values ​​of A and w can be appropriately reduced to improve inspection efficiency while ensuring inspection effectiveness. For example, if a 200-meter-wide section of pipe in a sub-inspection area is a high-risk area, A can be set to 100 to ensure coverage of 100 meters on both sides of the pipe. If it is a low-risk area, A can be set to 50. In addition, during non-first-time inspections, A and w can be further increased and adjusted based on historical inspection data for sub-inspection areas with frequent anomalies to strengthen the inspection efforts.

[0050] The determination of the phase parameter φ is related to the current inspection cycle. For example, the phase φ can be set to 0 during the first inspection. In the next inspection, the phase parameter can be adjusted to π / 2, causing the sine curve to shift as a whole, covering areas not covered in the previous cycle. After multiple inspections, a multi-angle inspection of the pipeline's surrounding environment can be achieved.

[0051] The determination of the offset parameter B is related to real-time environmental parameters, especially wind direction and speed. Specifically, before the inspection begins, the diffusion direction after a gas leak can be predicted based on wind direction and speed data. For example, if the detected wind direction is from south to north, the gas leak will most likely diffuse northward. To increase the probability of detecting the leaked gas, the inspection path can be shifted entirely towards the diffusion direction (northward), i.e., the value of the offset parameter B can be adjusted. This specific value can be determined based on the wind speed and the predicted diffusion range to improve the accuracy of the inspection. However, it is important to note that the value of the offset parameter B should always be less than the value of the amplitude parameter A to avoid potential risk points on the other side of the pipeline not being covered due to the overall shift.

[0052] Understandably, a complete inspection task typically includes a forward inspection from the starting point to the end point, as well as a return inspection from the end point back to the starting point. Therefore, the target inspection path will also include a return inspection path. This return inspection path can also be planned using the periodic inspection path described by the first function.

[0053] Specifically, the return inspection path can share the same amplitude parameter A and frequency parameter w as the forward inspection path, but the phase parameter φ can be further adjusted. For better detection results, the phase parameter can preferably be set to be π phase different from the forward inspection path, so as to supplement the detection of areas not directly detected during the forward pipeline inspection during the return journey.

[0054] However, in actual inspections, the final execution plan for the return-to-home inspection path may need to be adjusted based on the real-time status of the inspection equipment. Taking a drone as an example, when planning the return-to-home, its real-time battery level must first be determined. If the real-time battery level is sufficient, the theoretical return-to-home path with only phase adjustment can be used as the return-to-home inspection path. If the real-time battery level is very low, periodic inspections will not be performed, and the most basic return-to-home path, flying directly along the pipeline's central axis, will be used as the return-to-home inspection path to save energy.

[0055] If the real-time battery level falls between these two values, a hybrid path can be planned, which involves applying the theoretical return path in some high-risk sub-detection areas and the most basic return path in low-risk sub-detection areas.

[0056] For example, if the real-time power level is greater than the power required for the most basic return route, the characteristics of the pipeline gas can be further determined. If the pipeline gas is a low-risk gas that is non-flammable, non-explosive, and non-toxic, then the most basic return route can still be used as the return inspection route to improve return efficiency.

[0057] If the gas being transported is a high-risk gas, the system continues to assess whether the real-time battery level is greater than the theoretical return path's required battery level. If so, the theoretical return path is used as the return inspection path, and safety inspections continue during the return process. If not, a hybrid path is adopted: for pipe sections with higher regional risk levels, inspections are performed according to the theoretical return inspection path; for sub-inspection areas with lower regional risk levels, the most basic return path is used for rapid return, ensuring the effectiveness of inspections in key areas while guaranteeing the drone's smooth return.

[0058] Optionally, to enable pipeline inspections over longer distances, charging stations can be set up at intervals along the pipeline. The location of these charging stations can then be taken into account when planning the target inspection route. When the drone's battery is low, a route via the nearest charging station can be planned for relay charging, thus supporting continuous inspections over longer distances.

[0059] S120. Perform a safety inspection based on the target inspection path to obtain the inspection results of the pipeline to be inspected.

[0060] Safety inspection can refer to the process of controlling inspection equipment to fly along a target inspection path to collect comprehensive data on the pipeline. For example, this may include gas concentration data acquisition and image acquisition of the pipeline's surrounding environment.

[0061] Specifically, the inspection equipment uses modules to collect real-time gas concentration signals, environmental parameters (wind speed and direction), and surrounding environmental image data of each sub-inspection area of ​​the pipeline under inspection. The collected gas concentration signals are then processed in conjunction with the environmental parameters to obtain real-time gas concentration data. Finally, the real-time gas concentration data is integrated with the surrounding environmental image data to form the pipeline inspection result. This inspection result can refer to a basic dataset reflecting the relevant physical data and environmental images of the pipeline under inspection, which may include the collected real-time gas concentration data, pipeline image data captured during the inspection, and environmental parameters used for subsequent analysis.

[0062] For example, taking a drone as an inspection device, the drone can be equipped with a parameter measurement module and an image acquisition module. The parameter measurement module may include a TDLAS laser gas telemetry instrument, a temperature sensor, and a pressure sensor. The image acquisition module may include a multi-axis gimbal and a camera. During the safety inspection along the drone's target inspection path, the TDLAS laser gas telemetry instrument in the parameter measurement module is always vertically pointed towards the ground, collecting real-time gas concentration data for each sub-detection area of ​​the pipeline.

[0063] Meanwhile, the image acquisition module uses a multi-axis pan-tilt unit to capture pipeline images and their surrounding environment from multiple angles (front, top, and oblique top views, etc.) using imaging equipment, ensuring comprehensive capture of the pipeline structure and its surroundings. Understandably, ground personnel can view the real-time pipeline image data transmitted via the visual interface of the ground remote control and monitoring module.

[0064] Finally, the real-time gas concentration data, pipeline image data, and relevant environmental parameters are integrated to form the pipeline inspection results for subsequent analysis.

[0065] Optionally, performing a safety inspection based on the target inspection path to obtain the inspection results of the pipeline to be inspected may further include: during the safety inspection process, verifying the inspection path based on real-time location parameters to obtain the inspection verification results; adjusting the target inspection path based on the inspection verification results to obtain the actual inspection path; and performing a safety inspection based on the actual inspection path to obtain the inspection results of the pipeline to be inspected.

[0066] Real-time position parameters refer to the geographic coordinate data acquired by the inspection equipment during flight. Taking a drone as an example, real-time position parameters can refer to the latitude, longitude, and altitude data obtained by the drone through its GPS positioning module, which accurately determines the actual inspection location. Inspection path verification refers to the process of comparing and analyzing the real-time position parameters of the inspection equipment with the theoretical position parameters corresponding to the target inspection path to determine whether the inspection equipment has deviated from the target inspection path. The inspection verification result can be a set of data describing the degree and orientation of the deviation between the actual position and the theoretical position of the inspection equipment.

[0067] For example, taking a drone as an example, when the drone flies along the target inspection path, it can transmit its real-time position via GPS positioning module every preset time interval (e.g., 1 second) and convert it into real-time coordinates (x1, y1) in the aforementioned pipeline coordinate system. Then, the theoretical coordinates (x0, y0) in the target inspection path at that moment are retrieved, and the longitudinal deviation between the two is calculated (Δy = y1 - y0). If the deviation is less than a preset deviation threshold (e.g., 0.5 meters), it is determined that there is no significant deviation in the inspection path. If the deviation is greater than the preset threshold, the deviation direction (determined by the sign of the deviation) and the deviation distance are recorded to form the inspection verification result.

[0068] After obtaining the inspection and verification results, the target inspection path can be adjusted based on the inspection and verification results to obtain the actual inspection path.

[0069] Specifically, based on the deviation direction and deviation distance in the inspection and verification results, the offset parameter B corresponding to the target inspection path can be corrected to obtain an actual inspection path that conforms to the real-time flight status. This actual inspection path can refer to the inspection path actually executed by the inspection equipment after dynamically correcting the target inspection path.

[0070] For example, if the inspection results show that the UAV's current position deviates longitudinally from the target inspection path, the subsequent inspection path can be corrected in the opposite direction of the longitudinal deviation by adjusting the offset parameter B in the target inspection path (e.g., if actual northward deviation is detected, the offset parameter is adjusted to shift the subsequent path southward). This brings the UAV's flight trajectory closer to the target inspection path, ensuring that the error between the actual inspection path and the target path is within an acceptable threshold range. It should be noted that the above process of path verification and adjustment based on real-time position parameters is also applicable during the return inspection phase.

[0071] After obtaining the actual inspection path, a safety inspection can be performed based on the actual inspection path to obtain the inspection results of the pipeline to be inspected.

[0072] Specifically, the inspection equipment can be controlled to fly along the updated actual inspection path and simultaneously perform gas concentration detection and image acquisition tasks. Based on the acquired data, leakage risk and structural anomaly analysis can be performed, and finally, the inspection results can be generated.

[0073] By verifying the inspection path using real-time location parameters, flight deviations of the inspection equipment can be detected promptly, preventing missed inspection areas due to these deviations. Based on the verification results, the target inspection path is adjusted to obtain the actual inspection path, effectively and accurately correcting any deviations. Finally, the corrected path guides subsequent inspection processes, thereby improving the reliability and accuracy of the final line inspection results.

[0074] Optionally, during the safety inspection based on the target inspection path, the inspection speed can also be adjusted based on environmental parameters and gas characteristic parameters.

[0075] Among these, environmental parameters can refer to external environmental data such as wind speed and direction in the current inspection area. Gas characteristic parameters can refer to the inherent physicochemical properties of the pipeline gas itself, such as descriptive properties like density, and the degree of danger, such as toxicity, flammability, or explosiveness.

[0076] Understandably, environmental parameters and the descriptive properties of the gas determine its diffusion rate. Therefore, the diffusion rate of the pipeline gas can first be determined based on its descriptive properties and the environmental parameters acquired in real time during inspections. Then, the patrol speed of the inspection equipment can be dynamically adjusted based on the diffusion rate and the degree of hazard, ensuring that the inspection speed is compatible with the gas leak detection requirements.

[0077] For example, if the descriptive attribute indicates that the density of the pipeline gas is low and the current environmental parameters indicate that the wind speed is high, it means that the diffusion rate of the pipeline gas may be fast; if the descriptive attribute indicates that the density of the pipeline gas is high and the current environmental parameters indicate that the wind speed is low, it means that the diffusion rate of the pipeline gas may be slow.

[0078] Furthermore, the primary rule for adjusting the inspection speed depends on the gas's hazard level, i.e., its toxicity and subsequent flammability and explosiveness. The gas's diffusion rate is then considered. For example: if the pipeline gas diffuses rapidly and is highly hazardous (e.g., extremely toxic, highly flammable, and explosive), the inspection speed should be adjusted to the slowest setting regardless of the current wind speed to ensure maximum coverage of potential leak areas. If the pipeline gas is highly hazardous but diffuses slowly, the inspection speed should be adjusted to a slower setting to balance coverage with efficiency. If the pipeline gas diffuses rapidly but is not hazardous (non-toxic, non-flammable, and non-explosive), the inspection speed should be adjusted to a faster setting to balance detection effectiveness and efficiency. If the pipeline gas diffuses slowly and is not hazardous, the inspection speed should be adjusted to the fastest setting to maximize efficiency.

[0079] By dynamically adjusting the inspection speed based on environmental and gas characteristic parameters, and rationally allocating detection resources, the system avoids both missed leaks due to excessively fast inspection speeds and wasted efficiency due to excessively slow speeds, thus significantly improving the targeting and overall effectiveness of inspections.

[0080] S130. If the inspection results indicate the presence of a first abnormality, leakage source tracing shall be performed to obtain the leakage source tracing results.

[0081] The first abnormal situation can be used to describe a gas leak safety accident in the pipeline under inspection, that is, the pipeline inspection results indicate that there is a gas leak in the pipeline under inspection, and the location of the leak needs to be further confirmed.

[0082] Specifically, the real-time gas concentration data in the pipeline inspection results can be analyzed and processed to identify whether a gas leak safety incident exists. If the real-time gas concentration data in the pipeline inspection results continuously exceeds the safe concentration threshold, it can be determined that a first abnormal situation exists.

[0083] For example, if the pipeline is currently transporting a gas that should not exist in the atmosphere, and this gas is detected in a certain detection area, it indicates a gas leak, and the first anomaly can be identified. If the pipeline is currently transporting a gas that already exists in the atmosphere but at an extremely low concentration, and the real-time gas concentration data is found to significantly exceed the normal value, it also indicates a gas leak, and the first anomaly can be identified.

[0084] Furthermore, upon confirming the existence of the first anomaly, leakage tracing can be initiated immediately to obtain the leakage tracing results.

[0085] Among them, the leak tracing results can refer to data that can reflect the location of the gas leak point, that is, a data set containing the most likely coordinates of the leak point and its confidence range.

[0086] Specifically, when tracing leaks, a target tracing area is first determined based on real-time gas concentration data and ambient wind speed and direction in the potential leak area. This target tracing area can refer to a horizontal projection outline of a gas diffusion cloud fitted using models such as quadratic functions. Then, the inspection equipment is controlled within the target tracing area to plan a three-dimensional detection path that gradually narrows towards the pipeline. The inspection equipment flies along this path, continuously collecting real-time gas concentration data. Iterative algorithms are used to continuously correct the estimated location of the leak point, ultimately locking the leak point into a relatively small spatial area, and outputting the leak tracing results.

[0087] S140. Generate the first emergency warning information based on the leak source tracing results to assist in the emergency response and risk management of the pipeline to be inspected.

[0088] The first emergency warning information can refer to comprehensive information generated based on the leak tracing results, used to alert relevant personnel and guide emergency response. This information may include leak details such as the location of the leak point, the type of leaked gas, and the extent of the hazardous area, as well as emergency response suggestions and personnel evacuation arrangements.

[0089] Specifically, leak source tracing results including the leak location, collected actual environmental images, and relevant pipeline emergency management regulations can be integrated to generate a structured first emergency warning message. This message is then sent to the ground control center to assist in warning, emergency response, and evacuation efforts.

[0090] For example, the inspection equipment (such as a drone) can also be equipped with a warning unit (including a speaker and a light warning device). After generating the first emergency warning information, the drone can, on the one hand, play the warning broadcast repeatedly through the speaker, and on the other hand, emit a flashing warning signal through the light warning device to drive away irrelevant personnel within the danger zone around the leak area. On the other hand, the drone can send the first emergency warning information to the ground control center and pipeline emergency management department through the communication and information transmission module, assisting them in formulating a detailed emergency response plan and directing personnel to the scene, thereby achieving rapid control of the leak risk.

[0091] In the above implementation, using the first function model to plan periodic target inspection paths not only expands the inspection coverage but also facilitates flexible control of the inspection paths through parameter adjustments. Subsequently, safety inspections are performed based on the target inspection paths to comprehensively collect pipeline-related data, providing a reliable basis for risk identification. Then, upon identification of the first anomaly, leak tracing is immediately initiated to accurately and quickly determine the leak situation. Finally, based on the leak tracing results, a first emergency warning message is generated, which assists in rapid emergency response and risk management. This upgrades pipeline inspection from traditional manual or simple aerial photography to an intelligent and automated leak detection and tracing model, effectively preventing and reducing safety accidents caused by pipeline leaks.

[0092] In some implementation methods, please refer to Figure 2 The method also includes:

[0093] S210. If the pipeline inspection results indicate the presence of a second anomaly, pipeline threat identification processing shall be performed to obtain the threat identification results.

[0094] The second anomaly describes the structural anomaly risk of the pipeline under inspection. This means that the pipeline inspection results show abnormalities in the pipeline and its surroundings that may affect the pipeline's integrity, requiring further risk assessment. For example, structural anomaly risk can refer to the risk that pipeline operation safety is threatened due to damage to the pipeline's own structure or changes in the surrounding environment. This can include abnormal pipeline exposure, such as damage to the pipeline's protective layer or deep pits in the ground leading to pipeline exposure, as well as abnormal covering, such as buildings encroaching on the pipeline or foreign objects covering the pipeline.

[0095] Specifically, image analysis algorithms can be used to identify and analyze pipeline image data in the pipeline inspection results. That is, the collected pipeline image data is compared with the baseline image data in the pipeline status parameters. If abnormal exposure, abnormal coverage, or other discrepancies with the baseline status are identified, it can be determined that a second abnormality exists.

[0096] Furthermore, upon confirmation of a second anomaly, pipeline threat identification can be performed immediately to obtain the threat identification results.

[0097] Threat identification results can refer to comprehensive report data that provides a detailed description of the type, location, severity, and other attributes of the identified structural anomalies.

[0098] Specifically, when conducting pipeline threat identification and processing, the first step is to determine the image features and precise location information of abnormal situations based on pipeline image data and pipeline status parameters obtained from pipeline inspections. Then, by combining pipeline maintenance specifications and risk assessment standards, the type of abnormal situation and potential hazards are analyzed to form a structured threat identification result.

[0099] For example, consider the case where real-time pipeline image data from pipeline inspections shows the presence of large construction machinery operating in a specific inspection area. During pipeline threat identification, image recognition and spatial comparison are performed based on the pipeline image data and pipeline GIS (Geographic Information System) data from the pipeline status parameters. This identifies an anomaly of "mechanical operation" in the inspection area and obtains its precise geographic coordinates. Subsequently, information such as the anomaly type, precise location, on-site images, and a preliminary risk level assessed based on the relative distance between the machinery and the pipeline are integrated to form the threat identification result.

[0100] It is understandable that the automatic identification performed using image analysis algorithms may contain errors due to factors such as image quality, lighting conditions, or object occlusion. Therefore, after generating threat identification results, the relevant images and alarms can be pushed to ground personnel through the ground monitoring system for manual secondary verification to ultimately confirm the existence and severity of any anomalies, thereby ensuring the accuracy of the threat identification results.

[0101] S220. Generate a second emergency warning message based on the threat identification results to assist in carrying out preventive maintenance and risk intervention for the pipeline to be inspected.

[0102] The second emergency alert information can refer to comprehensive information generated based on threat identification results, used to alert relevant personnel and guide maintenance and handling. This information may include threat information such as the type of abnormal situation, precise location, and on-site images, as well as guidance information such as maintenance and handling suggestions.

[0103] Specifically, firstly, based on the type and location of anomalies in the threat identification results, combined with pipeline maintenance specifications, a structured second emergency warning message can be generated.

[0104] For example, the generated second emergency warning message can be pushed to the patrol personnel's user terminal. The specific content could be: Warning: Mechanical operations have been discovered at a certain location (specific coordinates), approximately 5 meters from the main pipeline. Upon receiving this message, maintenance personnel can promptly arrange for on-site verification and intervention based on this warning information, thereby preventing potential damage to the pipeline structure due to ongoing third-party activities and achieving early warning and proactive intervention for pipeline risks.

[0105] In the above implementation, by analyzing the image data from pipeline inspection results, automated and real-time identification of pipeline structural anomalies and risks is achieved, enabling timely detection of potential risks related to pipeline structures. Subsequently, the identified anomalies are precisely classified and located, generating structured information that directly guides on-site intervention. Ultimately, based on this information, the operation and maintenance unit is guided to carry out targeted preventative maintenance work, proactively mitigating risks and reducing the probability of leaks caused by pipeline structural damage.

[0106] In some implementations, the target inspection path for the pipeline to be inspected is determined; please refer to the appendix. Figure 3 ,include:

[0107] S310. Obtain the pipeline status parameters of the pipeline to be inspected.

[0108] Pipeline status parameters can be comprehensive data describing the overall condition of the pipeline under inspection, reflecting its structural condition, geographical distribution, and historical inspection data. Specifically, pipeline status parameters can include pipeline GIS data, pipeline internal inspection reports, integrity assessment reports, and historical inspection data. Pipeline GIS data, generated during the pipeline design and construction phases, includes pipeline location information and topographical features along the pipeline route, and typically remains unchanged throughout the pipeline's lifecycle. Pipeline internal inspection reports are data obtained by inspecting the pipeline's structure for corrosion, cracks, or other structural damage using internal detectors; these reports are not updated unless new internal inspections are conducted. Similarly, integrity assessment reports are generated during pipeline integrity management by evaluating the geographical location of high-consequence areas, high-risk areas, and areas requiring structural damage repair along the pipeline route; these reports are not updated unless new assessments are conducted. Historical inspection data primarily includes location information of frequently occurring anomalies recorded during previous inspections and is updated after each round of inspections. For example, pipeline status parameters can be directly retrieved from the pipeline operator's management information system or database.

[0109] S320. Determine the regional risk level of the pipeline to be inspected based on pipeline condition parameters.

[0110] Among them, the regional risk level can be used to describe the importance of the pipeline to be inspected in each sub-inspection area, that is, a quantitative indicator that comprehensively reflects the possibility of various risks to the pipeline.

[0111] For example, based on pipeline inspection reports, integrity assessment reports, and historical inspection data in the pipeline condition parameters, sub-inspection areas with structural damage (i.e., cracks, gaps, and corrosion) or frequent historical anomalies can be identified first, and the severity of the potential consequences of leakage can be assessed. Then, risk assessment methods such as the Kent method are used to score each sub-inspection area to obtain its risk score. Subsequently, based on the score, different risk level intervals are defined to determine the regional risk level of each sub-inspection area.

[0112] For example, assuming all sub-inspection areas initially have the same base score (0 points), if the pipeline inspection report shows structural defects such as corrosion cracks in the sub-inspection area, different damage scores are assigned based on the severity of the defects (reflected by depth and length). If the integrity assessment report classifies the sub-inspection area as a high-risk or high-consequence area, a corresponding risk score can be assigned. If historical inspection data shows that the number of abnormal situations in this sub-inspection area is higher than in other sub-inspection areas during previous inspections, different historical scores are assigned based on the different frequencies of abnormal situations. Furthermore, regional factors surrounding the pipeline can be considered. For example, if the pipeline is located in a densely populated area (with more than 100 households within 200 meters on both sides of the pipeline's centerline), a corresponding regional score is assigned. Then, all the above-mentioned bonus points are accumulated to obtain the risk score for the sub-inspection area. Finally, low-risk, medium-risk, and high-risk score ranges are set for the pipeline; for example, 0-3 points for low risk, 4-7 points for medium risk, and 8-10 points for high risk.

[0113] Furthermore, when determining the regional risk level of a pipeline to be inspected, in addition to considering the influence of pipeline condition parameters, the gas characteristic parameters of the transported gas are also taken into account. These gas characteristic parameters refer to the inherent physicochemical properties of the transported gas itself, such as descriptive properties like density, and the degree of hazard, such as toxicity, flammability, or explosiveness. These parameters can be obtained from a pre-set gas property knowledge base based on the type of transported medium. Specifically, different hazard coefficients can be assigned to gases of different hazard levels. For example, when transporting non-toxic and non-flammable gases, the hazard coefficient can be 1.0; when transporting flammable or toxic gases, the hazard coefficient can be set to 1.5; and when transporting flammable, explosive, and highly toxic gases, the hazard coefficient can be set to 2.0 or higher. Subsequently, when calculating the total risk score of a sub-inspection area, the original score calculated based on the pipeline condition parameters can be multiplied by the gas hazard coefficient to obtain the corrected final risk score. Finally, a comprehensive calculation is performed to obtain the regional risk level of each sub-inspection area.

[0114] S330. Determine the initial inspection route based on the regional risk level.

[0115] The initial inspection path can refer to a periodic inspection path that is only adapted to the pipeline's own structure and risk distribution, i.e., the initial flight trajectory that does not take into account real-time environmental parameter correction.

[0116] Specifically, the initial inspection path can be determined based on the regional risk level by adjusting the first, second, and third parameters in the initial first function model using the regional risk level and the current inspection round.

[0117] The initial first function model can refer to the most basic mathematical model used to describe the periodic inspection path, preferably a sine function model with adjustable parameters.

[0118] The first parameter can refer to the amplitude parameter used to control the inspection amplitude. The second parameter can refer to the frequency parameter used to control the inspection frequency. The third parameter can refer to the phase parameter used to control the inspection coverage area.

[0119] For example, taking the sine function model (y=Asin (wx+φ)+B) as an example, the first parameter can be the amplitude A, which is used to control the oscillation amplitude of the inspection path in the direction perpendicular to the pipeline; the second parameter can be the angular frequency w, which is used to control the number of inspection cycles per unit distance along the pipeline; and the third parameter can be the phase φ, which is used to control the starting position of the sine curve.

[0120] Specifically, the initial inspection path is obtained by determining the first, second, and third parameters of the initial first function model using the regional risk level and the current inspection round. This can be achieved as follows: First, the first and second parameters of the initial first function model are determined using the regional risk level to obtain the baseline inspection path. Then, the third parameter of the baseline first function model is adjusted based on the current inspection round to obtain the initial inspection path.

[0121] Specifically, for sub-detection areas with different risk levels, the first parameter (amplitude parameter A) and the second parameter (frequency parameter w) in the initial first function model can be assigned values ​​based on the area's risk level and the distribution information of anomalies in historical inspection data, thereby forming a baseline inspection path. This baseline inspection path can refer to a basic inspection path that only adapts to the area's risk level, and this baseline path corresponds to a baseline first function model. The baseline first function model can refer to the function model obtained by assigning values ​​to the first and second parameters based on the initial first function model.

[0122] It should be noted that when describing the second parameter (frequency parameter w), using the scan period T is more intuitive and in line with engineering practices. The scan period T reflects how many meters the drone travels along the pipe direction (positive X-axis) to complete one full left-right swing. For example, assuming the first parameter (amplitude parameter A) in the initial first function model is 50 meters by default, and the default scan period T is 100 meters, then for sub-detection areas with high risk levels, to ensure full coverage without missed detections, the first parameter (amplitude parameter A) can be increased to expand the longitudinal inspection coverage width. For example, A can be set to the maximum safe distance that needs to be covered on both sides of the pipe to be inspected (e.g., 200 meters). Simultaneously, the second parameter (frequency parameter w) can be increased to improve the lateral inspection density, for example, by setting the scan period T to 20 meters. For sub-detection areas with medium risk levels, a moderate number of first and second parameters can be used to balance inspection effectiveness and efficiency. For example, A can be set to 50%-70% of the maximum safe distance (e.g., 100 to 140 meters), and the scan period T can be set to 50 meters.

[0123] For sub-detection areas with low regional risk levels, the first parameter can be reduced to narrow the coverage width, for example, setting A to less than 30% of the maximum safe distance (e.g., within 60 meters); at the same time, the second parameter can be reduced to decrease the density, for example, setting the scanning period T to 80 meters.

[0124] During non-initial inspections, if historical inspection data shows frequent anomalies in a certain sub-detection area, the first and second parameters of that area can be further increased based on the corresponding risk level to strengthen the inspection efforts, ultimately forming a baseline inspection path and a corresponding baseline first function model. For example, if within a certain statistical period (e.g., the past month), the number of valid anomalies (e.g., gas concentration warnings or structural anomaly identification) recorded in the same sub-detection area exceeds a preset threshold (e.g., 3 times), then the sub-detection area is determined to have frequent anomalies. Regardless of its original regional risk level, the first parameter A can be further increased (e.g., by 20%), and the scanning period T can be further reduced (e.g., by 30%) to implement enhanced inspections and form a baseline inspection path.

[0125] Furthermore, after obtaining the baseline inspection path, the third parameter of the baseline first function model can be adjusted based on the current inspection round to obtain the initial inspection path.

[0126] The current inspection round can refer to the sequence number of this round of inspection in the previous rounds of inspection, that is, in a complete inspection, which round of inspection task is currently being performed on the same pipeline.

[0127] Specifically, after determining the current inspection cycle, the third parameter (phase parameter φ) can be adjusted based on the current inspection cycle. The specific value of the adjustment can be flexibly determined, with the standard of maximizing the coverage of undetected areas.

[0128] For example, if the current inspection round is the first round, the third parameter (phase parameter φ) of the baseline first function model can be set to 0. In this case, the inspection path starts to swing from the initial position on one side of the pipeline centerline. If the current inspection round is the second round, φ can be set to π / 2, causing the sinusoidal waveform of the inspection path to shift by π / 2 phase, covering areas not covered in the first inspection. If it is the third round of inspection, π / 2 can be added again based on the previous round, and so on.

[0129] By using regional risk levels to determine the first and second parameters, the baseline inspection path can adaptively adjust its coverage width and inspection density for different risk areas, thereby allocating more inspection resources to high-risk areas and improving inspection effectiveness. Adjusting the third parameter using the current inspection cycle ensures that all angles on both sides of the pipeline are covered after multiple inspections, avoiding missed inspections due to a fixed viewing angle.

[0130] Furthermore, this method of adjusting the amplitude, frequency, and phase parameters in the initial first function model by utilizing the regional risk level and the current inspection round can generate an initial inspection path that matches the actual risk distribution of the pipeline and provides more comprehensive coverage. This not only meets the needs of differentiated risk management but also ensures the comprehensiveness of subsequent multiple rounds of inspections.

[0131] S340. Based on environmental parameters and the initial inspection path, perform path correction processing to obtain the target inspection path.

[0132] The initial inspection path corresponds to a theoretical first function model. This theoretical first function model can refer to a mathematical expression describing the initial inspection path.

[0133] It should be noted that the initial first function model, the baseline first function model, and the theoretical first function model mentioned above are essentially different names for the same sine function model at different adjustment stages. Their core mathematical forms are consistent, only the parameter values ​​are different.

[0134] Specifically, the path correction process based on environmental parameters and the initial inspection path to obtain the target inspection path may include the following steps: First, gas diffusion prediction is performed based on environmental parameters to obtain the predicted diffusion result. Then, the fourth parameter in the theoretical first function model is adjusted based on the predicted diffusion result to obtain the target inspection path.

[0135] Among them, the predicted diffusion results can refer to data describing the possible distribution of pipeline gas in the atmosphere after a leak.

[0136] For example, environmental parameters (such as wind direction and speed) can be collected in real time through the parameter measurement module of the inspection equipment. Then, combined with the molecular diffusion rate in the gas characteristic parameters, the data is input into a pre-trained model. Because the model has been pre-learned on the diffusion law of gas under different wind directions and speeds, it can output predicted diffusion results such as the diffusion direction and diffusion range after a gas leak. For example, if the current wind direction is westerly and the wind speed is relatively high, the output predicted diffusion results may include that the gas mainly diffuses to the east and the diffusion range is relatively wide.

[0137] It should be noted that the neural network model here is only an intelligent algorithm tool for predicting the distribution characteristics of gas molecules, and does not refer to a specific model structure. Any intelligent model with this prediction function can be used.

[0138] After obtaining the predicted diffusion results, the fourth parameter in the theoretical first function model can be adjusted based on the predicted diffusion results to obtain the target inspection path.

[0139] The fourth parameter can be an offset parameter used to control the degree of deviation of the overall inspection path. For example, taking the sine function model (y=Asin (wx+φ)+B) as an example, the fourth parameter can be the offset parameter B, the magnitude of which determines the distance of the overall inspection path from the central axis of the pipeline, and the positive or negative value determines the direction of the offset.

[0140] For example, taking east as the positive direction of the Y-axis, if the predicted diffusion results show that the gas leak will mainly diffuse eastward, then to improve the detection probability of the leaked gas, the entire inspection path needs to be shifted eastward. This means assigning a positive value to the fourth parameter (offset parameter B) in the theoretical first function model, causing the path to shift eastward, thus obtaining the target inspection path. Furthermore, the specific value of the fourth parameter can be determined based on the wind speed and the diffusion range. For instance, firstly, the current wind speed level (e.g., light, moderate, or strong wind) can be determined based on different wind speeds using a preset mapping relationship or empirical data table. Then, different wind speed weights are assigned to different wind speed levels (e.g., light wind 0.8, moderate wind 1.0, strong wind 1.2). Next, the corresponding weight is multiplied by the diffusion range shown in the predicted diffusion results (e.g., the predicted gas cloud centerline deviating from the pipeline centerline by 50 meters, 100 meters, or 150 meters) to obtain a suggested offset, which is then used as the value for the fourth parameter B. It is important to note that the absolute value of the fourth parameter (offset parameter B) is always less than the absolute value of the first parameter (amplitude parameter A) to avoid potential risk points on the other side of the pipeline not being covered due to overall offset, thus ensuring the comprehensiveness of the inspection.

[0141] First, gas diffusion prediction based on environmental parameters allows for early identification of potential gas distribution areas, providing a basis for subsequent path correction. Then, by adjusting the fourth parameter, the inspection path is shifted towards higher-probability detection areas, significantly increasing the probability that the inspection equipment will detect leaking gas when a real leak occurs.

[0142] In the above implementation, parameters comprehensively reflecting the pipeline's condition are first acquired, providing a data foundation for risk assessment. These parameters are then used to determine the regional risk level, clarifying the key areas for inspection. Next, an initial inspection path is generated based on the risk level, ensuring the targeted and comprehensive nature of the inspection. Subsequently, the path is revised in conjunction with real-time environmental parameters, enabling the inspection path to dynamically adapt to environmental changes and improve the probability of leak detection. Ultimately, this significantly improves the efficiency and reliability of pipeline inspection.

[0143] In some implementation methods, please refer to the appendix. Figure 4a Leakage tracing and source investigation will be conducted in the following ways:

[0144] S410. Determine the target source area based on the gas diffusion data of the pipeline under test in the leak area.

[0145] Among them, gas diffusion data can refer to real-time gas concentration data collected in the suspected leak area, that is, a data set consisting of gas concentration values ​​at different locations in the area.

[0146] The target tracing area can refer to a search area used for centralized leak point location, which can be a spatial search range described by a second function. This second function can be a quadratic function.

[0147] Furthermore, to facilitate leak source tracing analysis, a new source tracing coordinate system can be established when determining the target source area. The origin of this coordinate system can be set at a representative concentration reference point, with its y-axis parallel to the current wind direction and its x-axis perpendicular to the wind direction. It should be noted that this source tracing coordinate system is a dynamically established local reference system specifically for this leak source tracing analysis, independent of the global pipeline coordinate system previously used to describe the pipeline's geometric location and plan inspection routes. Its coordinate axis directions will flexibly change with real-time environmental parameters (wind direction).

[0148] For example, taking the second function as a quadratic function that opens upwards, the target tracing region can be referred to... Figure 4b As shown in the figure, this is a top view of the pipeline to be inspected. Assuming the current wind direction is perpendicular to the pipeline's central axis, a tracing coordinate system can be established by using the wind direction at the current location of the inspection device as the y-axis (positive along the wind direction) and the direction perpendicular to the wind direction as the x-axis (positive along the pipeline's extension direction). Within this coordinate system, a quadratic function model (y=ax) can be used...2 +c) The projection profile of the gas diffusion cloud on the horizontal plane is mathematically represented. The area defined by this profile is the target source tracing area, which can be used to determine the approximate spatial range of the leak point.

[0149] Specifically, the initial contour parameters of the leak area can first be determined based on environmental parameters and gas diffusion data; then the initial contour parameters are corrected to obtain the target contour parameters; and finally, the target source area is determined based on the target contour parameters.

[0150] The initial profile parameters can refer to a set of data points that roughly describe the gas diffusion range; that is, key point data that characterizes the gas concentration distribution features obtained through preliminary scanning on a specific data acquisition plane. It is important to note that the data acquisition plane here can refer to a virtual plane parallel to the ground. For example... Figure 4c As shown in the figure, the diagram shows a side view of the pipe to be inspected. This plane is parallel to the ground (i.e., the XY plane), as indicated by the black arrow in the figure.

[0151] Specifically, during the inspection process, the inspection equipment collects gas concentration data in real time and compares it with a preset detection threshold to determine the initial profile parameters. This detection threshold depends on the accuracy of the detection instrument and the type of gas being transported. If the gas being transported is a gas not present in the atmosphere, then the detection threshold can be set to 0.

[0152] For example, assuming the inspection equipment is conducting inspections along an actual inspection path, when the equipment detects that the gas concentration data changes from below the detection threshold to above the threshold for the first time, it can adjust its flight direction in real time to be perpendicular to the wind direction at the current location. Subsequently, the equipment flies back and forth in a straight line along this direction, analyzing the real-time collected gas concentration data. During this back-and-forth flight, the coordinates of the two positions where the gas concentration data falls from above the detection threshold back below the threshold are recorded as the first boundary point C1 and the second boundary point C2, respectively. Next, all gas concentration data collected between C1 and C2 are retrieved, and the point with the highest concentration value is determined as the highest concentration point C0. Finally, the coordinate data of these three points are integrated and recorded as initial contour parameters.

[0153] The source tracing coordinate system can then be determined based on the initial profile parameters. For example, the projection of the current wind direction onto the ground can be used as the y-axis of the source tracing coordinate system, and the direction perpendicular to the current wind direction (i.e., the flight direction during reciprocating flight) can be used as the x-axis. The source tracing coordinate system x0C0y0 can be established in real time with the highest concentration point C0 as the origin.

[0154] Furthermore, the initial contour parameters can be modified to obtain the target contour parameters. These target contour parameters can refer to the core parameters used to construct the second function. Taking a quadratic function as an example, the target contour parameters could be the vertex coordinates and width of a parabola.

[0155] For example, taking the projection of the current wind direction onto the ground as perpendicular to the pipe direction as an example, please refer to... Figure 4d First, the straight-line distances C0C1 and C0C2 between the highest concentration point C0 and the two boundary points C1 and C2 can be compared. The distance with the larger absolute value (taking C0C1 as an example) is determined as the parabola width data. Then, extending along the negative y-axis of the source tracing coordinate system, the intersection point P of the straight line passing through the highest concentration point C0 and parallel to the wind direction with the central axis of the pipeline (x-axis) is found. This intersection point can be determined as the vertex of the quadratic function model and can be used as the initial assumed position for subsequent source tracing. Finally, the coordinates of vertex P and the parabola width (C0C1) are used as target contour parameters to complete the correction of the initial contour parameters.

[0156] Finally, the target tracing region is determined based on the target contour parameters. For example, the coordinates of the vertex coordinates (coordinates of P) and the coordinates of the boundary points (coordinates of C1) corresponding to the width data (C0C1) in the target contour parameters can be transformed from the original pipeline coordinate system to the tracing coordinate system. Then, the transformed coordinate values ​​are substituted into a quadratic function model to fit a unique quadratic function curve (y=ax). 2 +c), the area defined by this curve can be used as the target tracing area.

[0157] By using a quadratic function model to quantify the target source area, a large-scale gas diffusion area can be transformed into a precise mathematical model, avoiding blind searching during the leak point location process and significantly improving the source tracing efficiency. At the same time, key concentration points are extracted based on real-time wind direction in environmental parameters, ensuring that the model parameters fit the actual gas diffusion characteristics and laying a precise foundation for subsequent iterative location.

[0158] S420. Perform iterative source tracing and location processing in the target source tracing area to obtain the leakage source tracing results.

[0159] Specifically, this can be achieved as follows: First, determine the current source tracing starting point, and determine the current source tracing path based on the current source tracing starting point and the target source tracing area; perform leak detection and source tracing location based on the current source tracing path to obtain the current source tracing result; perform calculations based on the current source tracing path and the target source tracing area to obtain the next source tracing starting point, and use the next source tracing starting point as the new current source tracing starting point. Repeat the above steps, and when the iteration termination condition is met, determine the leak source tracing result based on the current source tracing result obtained in each iteration.

[0160] Here, the current tracing starting point can refer to the starting point of a certain tracing path detection during the iteration process. Specifically, it can be dynamically determined based on the boundary of the target tracing area and the real-time position of the inspection equipment. For example, please continue to refer to... Figure 4d If the real-time position of the inspection equipment is closer to the boundary point that determines the width of the parabola (such as C1), then that boundary point can be directly used as the current tracing starting point. If the real-time position of the inspection equipment is closer to another boundary point (such as C2), then the symmetrical point of the boundary point that determines the width of the parabola (such as C1) can be taken as the current tracing starting point (i.e., point C3 in the figure), so as to improve the detection efficiency while ensuring the detection accuracy.

[0161] The current tracing path can refer to the spatial trajectory of the inspection equipment during a single iteration, as it flies to collect data and perform positioning calculations. This trajectory curves towards the pipe being inspected. Specifically, it can be a leak detection path described by a third function. This third function can be an exponential function. For example, its form could be: (d<0) enables progressive detection from the regional boundary to the center, which fits the gas concentration gradient distribution characteristics.

[0162] For example, please refer to Figure 4e Assuming the target source tracing area has been defined in S410 using a quadratic function model (y=ax²+c), and the current inspection equipment is close to the boundary point C2, then the point C3, which is symmetrical to C1 about the highest concentration point C0, can be selected as the current source tracing starting point. A third function is then established in the current source tracing coordinate system with the highest concentration point C0 as the origin. In this example, the expression of the third function can be: d < 0. Then, by solving the system of equations between this function and the quadratic function model of the target source tracing region, we can obtain the unique intersection point Q1 on the boundary of the target source tracing region. The exponential function portion of the curve from the current source tracing starting point C3 to the intersection point Q1 (the red curve in the figure) represents the current source tracing path. This path extends from the region boundary towards the pipeline, accurately covering the area of ​​concentration gradient change.

[0163] Subsequently, the control and inspection equipment flies along the current source tracing path, collecting gas concentration data (i.e., gas diffusion data) in real time during flight and recording the coordinate information of each point. Then, based on the real-time collected gas concentration data, a new source tracing coordinate system and a new quadratic function are reconstructed.

[0164] For example, please refer to Figure 4f Similarly, the point C with the highest gas concentration detected on the current tracing path can be identified. 01This serves as the origin of the new source tracing coordinate system. Simultaneously, the average wind direction within this flight segment is calculated. This average wind direction can be obtained by averaging instantaneous wind direction data collected at preset time intervals (e.g., 1 second) as the inspection equipment flies along the current source tracing path. Subsequently, the direction of this average wind direction is used as the positive direction of the y-axis of the new source tracing coordinate system to establish the x-axis of the new source tracing coordinate system. 01 C 01 y 01 .

[0165] Subsequently, new gas diffusion boundary points are determined using data collected along the current tracing path. Due to the uneven distribution of actual gas clouds, within the detection range of the current tracing path, the point where the gas concentration data first falls from above the detection threshold to below the threshold is extracted as the new boundary point C. 11 The point where the value falls back from above the detection threshold to below the detection threshold is taken as the new boundary point C. 21 Then the new boundary point C will be... 11 And C 21 Coordinate transformation to the new coordinate system x 01 C 01 y 01 Next, substitute the transformed coordinate values ​​into the quadratic function equation to solve for the new quadratic function (y=a1x). 2 +c1). The vertex coordinates P1 of this new quadratic function model are the estimated location of the leak point in the current iteration, which can be recorded as the current source tracing result.

[0166] Next, calculations are performed based on the current tracing path and the target tracing area to determine the next tracing starting point. The next tracing starting point can refer to the starting point of the tracing operation immediately following the current detection round. For example, the intersection point Q1 obtained by combining the current tracing path with the quadratic function of the target tracing area can be directly determined as the next tracing starting point. This intersection point Q1 is located on the boundary of the target tracing area and is closer to the pipeline's central axis, enabling gradual convergence of the tracing path and improving positioning accuracy.

[0167] The next tracing starting point is then used as the new current tracing starting point, and the above process is repeated until the iteration termination condition is met. This iteration termination condition can refer to a preset standard used to determine whether the tracing and positioning process can end. For example, it can be that the iteration terminates when the horizontal distance between the inspection equipment and the pipeline centerline is less than a certain preset threshold (e.g., 5 meters), or when the range of vertex coordinate changes obtained from multiple consecutive iterations is less than the tolerance (determined based on the detection accuracy).

[0168] Finally, using the source-tracing coordinate system reconstructed through each iteration, the source-tracing results obtained from each iteration are transformed to the original coordinate system, so as to map the vertex coordinates of each source-tracing coordinate system to the planar projection coordinates in the original coordinate system. These coordinate points will be concentrated in a small interval due to iteration convergence. Finally, the mean of this interval is used as the precise coordinates of the leak point, and this interval is used as the confidence range of the leak point, integrating them to form the leak source-tracing result.

[0169] Alternatively, gas diffusion data can be used for source tracing to obtain the current source tracing results, or this can be achieved through another simplified method.

[0170] For example, the first step is to determine the current source tracing starting point and construct the current source tracing path. Then, when detecting and locating leaks along this path, it's unnecessary to reconstruct the coordinate system and quadratic function. Instead, the point of highest gas concentration is identified, and a ray is drawn directly from this point in the opposite direction of the current wind direction. The intersection of this ray and the pipeline's central axis is directly used as the current source tracing result (a point coordinate). Then, combined with a new exponential function equation, the next source tracing starting point is determined. Subsequent iterations follow a similar process. Finally, all source tracing results are collected, and the maximum and minimum X-coordinate values ​​are extracted to form the coordinate range of the leak point, which is then integrated into the leak source tracing result. However, this method only limits the leak point to the pipeline's central axis, while the method described above, which reconstructs the source tracing coordinate system and quadratic function, extends the leak point's location to the pipeline surface. Therefore, the reconstruction detection method has higher accuracy and reliability.

[0171] By determining the current source of leakage and constructing the current source path using a third function, the detection path is made to conform to the gas concentration gradient distribution, achieving a progressive detection from the regional boundary to the leak core. Subsequently, based on this path, environmental data and gas diffusion data are reused to determine the source tracing result. This allows the leak tracing process to adapt to environmental changes in real time, ensuring that the physical model (diffusion direction) used for each location analysis is up-to-date, thereby improving the environmental adaptability of the location. Finally, by integrating the location results obtained from multiple iterations, the error of a single measurement can be effectively smoothed, and a final result including a confidence interval can be provided, thus significantly improving the robustness and accuracy of leak point location.

[0172] In the above implementation, a target source tracing area described by a quadratic function is first determined based on gas diffusion data, narrowing the search range of the leak point from a vast space to a specific planar area, greatly improving search efficiency. Next, iterative detection is performed within this area, continuously sensing the environment and updating the location, achieving dynamic tracking and gradual approach to the leak point. Finally, by integrating the location results from multiple iterations, a precise coordinate of the leak point and its confidence interval are obtained. The entire process achieves automated source tracing from area locking to precise point location, significantly improving the speed and accuracy of leak emergency response.

[0173] It should be understood that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart above may include multiple steps or stages, which are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0174] This specification also provides a pipeline inspection device 500, such as... Figure 5 As shown, it includes: an inspection path determination module 510, a line inspection execution module 520, a leak tracing execution module 530, and an emergency alarm module 540, wherein:

[0175] The inspection path determination module 510 is used to determine the target inspection path of the pipeline to be inspected; wherein, the target inspection path is a periodic inspection path described by the first function.

[0176] The pipeline inspection execution module 520 is used to perform safety inspections based on the target inspection path to obtain the pipeline inspection results.

[0177] The leak tracing execution module 530 is used to perform leak tracing processing when the pipeline inspection results show that there is a first abnormal situation, so as to obtain the leak tracing result; wherein, the first abnormal situation is used to describe a gas leak safety accident in the pipeline to be inspected.

[0178] The emergency warning module 540 is used to generate the first emergency warning information based on the leak tracing results, so as to assist in the emergency response and risk management of the pipeline to be inspected.

[0179] In some implementations, the inspection path determination module 510 is also used to acquire pipeline status parameters of the pipeline to be inspected; determine the regional risk level of the pipeline to be inspected based on the pipeline status parameters; wherein the regional risk level is used to describe the importance of the pipeline to be inspected in each sub-inspection area; determine the initial inspection path based on the regional risk level; and perform path correction processing based on environmental parameters and the initial inspection path to obtain the target inspection path.

[0180] In some implementations, the inspection path determination module 510 is further used to adjust the first parameter, the second parameter, and the third parameter in the initial first function model using the regional risk level and the current inspection round to obtain the initial inspection path; wherein, the first parameter refers to the amplitude parameter used to control the inspection amplitude; the second parameter refers to the frequency parameter used to control the inspection frequency; and the third parameter refers to the phase parameter used to control the inspection coverage area.

[0181] In some implementations, the inspection path determination module 510 is further used to determine the first and second parameters in the initial first function model using the regional risk level to obtain a baseline inspection path; wherein the baseline inspection path corresponds to a baseline first function model; and the third parameter of the baseline first function model is adjusted based on the current inspection round to obtain the initial inspection path.

[0182] In some implementations, the initial inspection path corresponds to a theoretical first function model; the inspection path determination module 510 is also used to predict gas diffusion based on environmental parameters to obtain the predicted diffusion result; and to adjust the fourth parameter in the theoretical first function model based on the predicted diffusion result to obtain the target inspection path; wherein, the fourth parameter refers to the offset parameter used to control the degree of deviation of the overall inspection path.

[0183] In some implementations, the pipeline inspection execution module 520 is also used to verify the inspection path based on real-time location parameters during the safety inspection process to obtain the inspection verification result; adjust the target inspection path based on the inspection verification result to obtain the actual inspection path; and perform a safety inspection based on the actual inspection path to obtain the pipeline inspection result of the pipeline to be inspected.

[0184] In some embodiments, a pipeline inspection device 500 further includes a pipeline threat identification module, which is used to perform pipeline threat identification processing when the pipeline inspection results indicate the presence of a second anomaly, so as to obtain a threat identification result; wherein, the second anomaly is used to describe the structural anomaly risk of the pipeline to be inspected; and a second emergency warning message is generated based on the threat identification result to assist in carrying out preventive maintenance and risk intervention of the pipeline to be inspected.

[0185] In some implementations, the leak tracing execution module 530 is further configured to determine a target tracing area based on gas diffusion data of the pipeline to be detected in the leak area; wherein, the target tracing area is a spatial search range described by a second function; and iterative tracing and positioning processing is performed in the target tracing area to obtain the leak tracing result.

[0186] In some implementations, the leak tracing execution module 530 is further configured to determine the current tracing starting point and, based on the current tracing starting point and the target tracing area, determine the current tracing path; wherein, the current tracing path is a leak detection path described by a third function; leak detection and tracing location are performed based on the current tracing path to obtain the current tracing result; calculations are performed based on the current tracing path and the target tracing area to obtain the next tracing starting point, and the next tracing starting point is used as the new current tracing starting point. The steps for determining the new current tracing starting point are repeated, and, if the iteration termination condition is met, the leak tracing result is determined based on the current tracing result obtained in each iteration. Specific limitations regarding a pipeline inspection device can be found in the limitations of a pipeline inspection method described above, and will not be repeated here. Each module in the above pipeline inspection device can be implemented entirely or partially through software, hardware, or a combination thereof. Each module can be embedded in hardware or independently of the processor in a computer device, or stored in software in the memory of a computer device, so that the processor can call and execute the operations corresponding to each module.

[0187] In this embodiment, a pipeline inspection device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0188] The devices, modules, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices. For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0189] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0190] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0191] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0192] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0193] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0194] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0195] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0196] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0197] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0198] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method of inspecting a pipeline, characterized by, The method includes: Determine the target inspection path for the pipeline to be inspected; wherein, the target inspection path is a periodic inspection path described by a sine function; determining the target inspection path for the pipeline to be inspected includes: Obtain the pipe status parameters of the pipe to be detected; The regional risk level of the pipeline to be inspected is determined based on the pipeline status parameters; wherein, the regional risk level is used to describe the degree of importance of the pipeline to be inspected in each sub-inspection area. The first and second parameters in the initial first function model y=Asin(wx+φ)+B are determined using the regional risk level to obtain the benchmark inspection path; wherein, the benchmark inspection path corresponds to the benchmark first function model; wherein, the first parameter refers to the amplitude parameter used to control the inspection amplitude; and the second parameter refers to the frequency parameter used to control the inspection frequency. The third parameter of the baseline first function model is adjusted based on the current inspection cycle to obtain the initial inspection path; wherein, the initial inspection path corresponds to the theoretical first function model; the third parameter refers to the phase parameter used to control the inspection coverage area; Gas diffusion is predicted based on environmental parameters to obtain the predicted diffusion results; Based on the predicted diffusion results, the fourth parameter in the theoretical first function model is adjusted to obtain the target inspection path; wherein, the fourth parameter refers to the offset parameter used to control the degree of deviation of the overall inspection path; the target inspection path includes a forward inspection path and a return inspection path; the return inspection path and the forward inspection path share the same amplitude parameter and frequency parameter; the phase difference between the return inspection path and the forward inspection path is π. The inspection equipment performs safety inspections using the target inspection path as its flight trajectory to obtain the inspection results of the pipeline to be inspected. If the pipeline inspection results indicate the presence of a first anomaly, leakage tracing is performed to obtain the leakage tracing results; wherein, the first anomaly is used to describe a gas leakage safety accident in the pipeline under inspection; Based on the leak tracing results, a first emergency warning message is generated to assist in emergency response and risk management of the pipeline to be inspected.

2. The method according to claim 1, characterized in that, The inspection equipment performs safety inspections using the target inspection path as its flight trajectory to obtain the inspection results of the pipeline to be inspected, including: During the security inspection process, the inspection path is checked based on real-time location parameters to obtain the inspection results. The target inspection path is adjusted based on the inspection and verification results to obtain the actual inspection path. A safety inspection is performed based on the actual inspection path to obtain the inspection results of the pipeline to be inspected.

3. The method according to claim 1, characterized in that, The method further includes: When the pipeline inspection results indicate the presence of a second anomaly, pipeline threat identification processing is performed to obtain a threat identification result; wherein, the second anomaly is used to describe the risk of structural anomalies in the pipeline under inspection. Based on the threat identification results, a second emergency warning message is generated to assist in the preventive maintenance and risk intervention of the pipeline to be inspected.

4. The method according to claim 1, characterized in that, The leak tracing process is performed in the following manner: The target source area is determined based on the gas diffusion data of the pipeline under test in the leak area; wherein, the target source area is a spatial search range described by a second function; Iterative source tracing and location processing is performed in the target source tracing area to obtain the leakage source tracing result.

5. The method according to claim 4, characterized in that, The iterative source tracing and localization process performed in the target source tracing area to obtain the leak source tracing result includes: Determine the current source tracing starting point, and determine the current source tracing path based on the current source tracing starting point and the target source tracing area; wherein, the current source tracing path is a leakage detection path described by a third function; Based on the current tracing path, leakage detection and tracing are performed to obtain the current tracing result; The next tracing starting point is calculated based on the current tracing path and the target tracing area. This next tracing starting point is then used as the new current tracing starting point. The above steps are repeated. When the iteration termination condition is met, the leakage tracing result is determined based on the current tracing result obtained in each iteration.

6. A pipeline inspection device, characterized in that, The device includes: The inspection path determination module is used to determine the target inspection path for the pipeline to be inspected; wherein, the target inspection path is a periodic inspection path described by a sine function; determining the target inspection path for the pipeline to be inspected includes: Obtain the pipe status parameters of the pipe to be detected; The regional risk level of the pipeline to be inspected is determined based on the pipeline status parameters; wherein, the regional risk level is used to describe the degree of importance of the pipeline to be inspected in each sub-inspection area. The first and second parameters in the initial first function model y=Asin(wx+φ)+B are determined using the regional risk level to obtain the benchmark inspection path; wherein, the benchmark inspection path corresponds to the benchmark first function model; wherein, the first parameter refers to the amplitude parameter used to control the inspection amplitude; and the second parameter refers to the frequency parameter used to control the inspection frequency. The third parameter of the baseline first function model is adjusted based on the current inspection cycle to obtain the initial inspection path; wherein, the initial inspection path corresponds to the theoretical first function model; the third parameter refers to the phase parameter used to control the inspection coverage area; Gas diffusion is predicted based on environmental parameters to obtain the predicted diffusion results; Based on the predicted diffusion results, the fourth parameter in the theoretical first function model is adjusted to obtain the target inspection path; wherein, the fourth parameter refers to the offset parameter used to control the degree of deviation of the overall inspection path; the target inspection path includes a forward inspection path and a return inspection path; the return inspection path and the forward inspection path share the same amplitude parameter and frequency parameter; the phase difference between the return inspection path and the forward inspection path is π. The pipeline inspection execution module is used to control the inspection equipment to perform a safety inspection using the target inspection path as the flight trajectory, so as to obtain the pipeline inspection results of the pipeline to be inspected. The leak tracing execution module is used to perform leak tracing processing when the pipeline inspection results indicate the presence of a first abnormality, so as to obtain the leak tracing result; wherein, the first abnormality is used to describe a gas leak safety accident in the pipeline to be inspected; The emergency warning module is used to generate a first emergency warning message based on the leak tracing results, so as to assist in the emergency response and risk management of the pipeline to be inspected.

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