Blockage area positioning and analysis method and system for pipeline blockage detection

Abstract

The present invention discloses a method and system for positioning and analyzing a blocked area for pipeline blockage detection, including: collecting detection response signals emitted by a target pipeline detection robot based on a handheld terminal, analyzing and acquiring signals and determining an initial detection position; generating detection orientation guidance according to the initial position, and then continuously collecting signals according to the guidance until stable communication is established with the detection robot, and obtaining pipeline detection feedback information. The detection trajectory features are extracted through feedback information, and the detection route of the detection robot is generated and a 3D space trajectory map is established. Combined with the detection area map, the handheld terminal performs secondary positioning of the detection robot and generates positioning guidance information. The terminal further extracts detection image information, analyzes the pipeline blockage status and recommends construction plans, so as to realize rapid and accurate positioning and analysis of the blocked area in a complex pipeline environment, and assist in formulating the optimal treatment plan to improve detection and maintenance efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline blockage detection, and in particular to a blockage area positioning and analysis method and system applied to pipeline blockage detection. Background Art

[0002] In recent years, detection robots have been widely used, especially in long-distance or small-diameter pipelines. However, it is difficult for ground personnel to accurately locate the position and trajectory of the detection robot by relying solely on the physical contact of the detection robot along the pipeline to obtain information on the blockage location. In addition, existing detection methods generally lack detailed analysis of the specific conditions of the blockage (such as severity, type of material, etc.), resulting in a lack of pertinence in the formulation of subsequent treatment plans. At the same time, the signal strength and image information fed back by the detection robot have not been fully utilized, resulting in further limitations on detection efficiency and accuracy. When an underground pipeline is blocked, it is often difficult to determine the location of the blockage. When the pipeline robot crawls in the pipeline with a probe, it stops when it encounters a blockage. It is difficult to accurately know the position where the probe stops on the ground with traditional technology. When the position is inaccurate, excavating the ground will cause unnecessary waste, and due to pipeline layout problems, there may be other pipelines near the blocked pipeline, and direct drilling may cause pipeline damage.

[0003] Therefore, there is an urgent need for a comprehensive method that combines the signals sent by the detection robot, feedback information, and interaction with the ground terminal to quickly and accurately locate and analyze the blockage area in a complex pipeline environment, and assist in formulating the optimal treatment plan to improve the detection and maintenance efficiency. Summary of the invention

[0004] The present invention overcomes the defects of the prior art and provides a method and system for locating and analyzing a blockage area for pipeline blockage detection, an important purpose of which is to improve detection and maintenance efficiency.

[0005] To achieve the above-mentioned purpose, the present invention provides a first aspect of a blockage area positioning and analysis method for pipeline blockage detection, comprising:

[0006] The detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain initial detection position analysis information;

[0007] An initial detection orientation guide is generated according to the initial detection position analysis information, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information;

[0008] Extracting the detection trajectory characteristics of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory characteristics and establishing a 3D space trajectory map;

[0009] The detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D spatial trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information;

[0010] The handheld terminal extracts detection image information of the target pipeline detection robot when performing a detection task according to the pipeline detection feedback information, analyzes the pipeline blockage condition according to the detection image information, and recommends a construction plan.

[0011] In this solution, the detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain the initial detection position analysis information, which specifically includes:

[0012] A pipeline detection robot is placed in the pipeline area to be detected to detect pipeline blockage. Ground monitoring personnel use handheld terminals to collect detection response signals continuously emitted by the target pipeline detection robot during the detection task.

[0013] After the handheld terminal user selects the starting direction in the ground area, the signal receiving module of the handheld terminal collects the detection response signal on the ground. The detection response signal is the electromagnetic signal continuously emitted by the probe of the target pipeline robot;

[0014] The handheld terminal user adjusts the signal receiving direction to obtain detection response signals at different directions, obtains detection response signal collection information, extracts features from the detection response collection signals, and obtains detection response feature signals received at different directions;

[0015] Extracting a local maximum value and a local minimum value in the detection response characteristic signal, performing signal interpolation processing based on the local maximum value and the local minimum value, and constructing an upper envelope and a lower envelope of the detection response characteristic signal;

[0016] Based on the obtained upper envelope and lower envelope calculations including the mean, it is determined whether they are within a preset threshold range. If so, the corresponding local signal trend is removed from the original detection response characteristic signal to obtain a reconstructed detection response characteristic signal;

[0017] The envelope strengths of different directions are calculated according to the reconstructed detection response characteristic signal, the directions corresponding to the envelope strengths greater than a preset threshold are selected as candidate guidance directions, and the initial detection position analysis information is generated by combining the envelope strengths of all directions.

[0018] In this solution, the initial detection position analysis information is used to generate the initial detection orientation guidance, and the handheld terminal user continues to collect signals according to the initial detection orientation guidance until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information, specifically including:

[0019] Acquire initial detection position analysis information, generate a detection response signal strength distribution map at the current moment based on the initial detection position analysis information, extract candidate guidance directions from the initial detection position analysis information, and mark them in the detection response signal strength distribution map;

[0020] Extracting the detection response signal strength characteristics of the neighbor direction of the candidate guidance direction based on the detection response signal strength distribution diagram and taking the candidate guidance direction as a reference, and judging it with a preset threshold, if it is greater than the preset threshold, obtaining the detection response signal strength of the neighbor direction by using the initial detection position analysis information;

[0021] Extract the detection response signal strength of the candidate guidance direction, combine the detection response signal strength of the neighbor direction to generate the guidance direction optimization interval, preset the guidance direction interval and introduce it into the Bayesian inference network to analyze the detection response signal strength corresponding to each direction interval within the candidate guidance direction and the neighbor direction, and obtain the detection response signal strength inference information;

[0022] Based on the detection response signal strength inference information, a detection response signal strength gradient map of the guidance direction optimization interval is constructed, and the guidance direction interval with the largest signal strength is selected as the final guidance direction through the detection response signal strength gradient map to generate an initial detection direction guidance for push;

[0023] The handheld terminal user continues to collect signals according to the generated initial detection direction guidance, and monitors the communication channel in the guidance direction in real time to obtain communication channel monitoring information, and calculates the signal-to-noise ratio, packet loss rate and communication delay of each channel when establishing communication with the target pipeline detection robot according to the communication channel monitoring information, to obtain first analysis information;

[0024] Preset communication environment assessment rules, analyze the stability of the current communication environment using the communication environment assessment rules according to the first analysis information, and select a stable communication channel. If a stable communication environment cannot be established with the target pipeline detection robot, prompt the handheld terminal user to continue to move forward in the guided direction;

[0025] When the handheld terminal establishes a stable communication environment with the target pipeline detection robot, the handheld terminal sends a data transmission instruction to the target pipeline detection robot, and the target pipeline detection robot sends pipeline detection feedback information to the handheld terminal after receiving the data transmission instruction.

[0026] In this solution, the detection trajectory characteristics of the target pipeline detection robot are extracted through the pipeline detection feedback information, and the detection route of the target pipeline detection robot is analyzed according to the detection trajectory characteristics and a 3D space trajectory map is established, which specifically includes:

[0027] Acquiring pipeline detection feedback information, wherein the pipeline detection feedback information includes detection image information and detection trajectory information when the target pipeline detection robot performs a pipeline blockage detection task;

[0028] Extracting features from the pipeline detection feedback information, extracting detection trajectory features of the target pipeline detection robot when performing the current detection task, performing spatial coordinate transformation according to the extracted detection trajectory features, and generating a detection trajectory data set of the target pipeline detection robot based on the transformed detection trajectory features;

[0029] Performing a registration operation on each detection trajectory data in the detection trajectory data set according to the corresponding spatial coordinates, performing a fitting operation on the registered detection trajectory data based on a least squares method to construct continuous detection trajectory data, and obtaining detection trajectory fitting data;

[0030] Extracting the detection dwell time characteristics of the target pipeline detection robot when performing the current detection task through the pipeline detection feedback information, and associating it with the detection trajectory fitting data;

[0031] A kernel density estimation method is introduced to perform density estimation on the detection dwell time of each trajectory point in the associated detection trajectory fitting data to obtain the probability density of each trajectory point, and the probability density of each trajectory point is converted into color information using a linear color mapping method;

[0032] The color information obtained after the conversion is used to construct a detection trajectory heat map of the target pipeline detection robot when performing the current detection task, and based on the color information of each trajectory point, the trajectory points greater than a preset threshold are marked in the detection trajectory heat map as potential blockage areas;

[0033] The 3D spatial trajectory map of the target pipeline robot when performing the current detection task is constructed by combining the detection trajectory heat map and the associated detection trajectory fitting data using 3D modeling technology.

[0034] In this solution, the detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D spatial trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information, which specifically includes:

[0035] The real-time position of the user of the handheld terminal is located by a positioning module of the handheld terminal to obtain real-time position features, and the real-time position features are spatially registered in a 3D spatial trajectory map to calibrate the real-time position of the user of the handheld terminal;

[0036] Taking the real-time position of the handheld terminal user as the starting point, the end point trajectory point of the target pipeline detection robot is obtained through the 3D spatial trajectory graph with the time series feature as the query tag, and the Euclidean distance between the two points is calculated using the Euclidean algorithm;

[0037] The shortest guidance distance between the handheld terminal user and the target pipeline detection robot is generated according to the calculated Euclidean distance, and a detection area map is obtained, where the detection area map is a ground map of the detection area, including building information, environmental information, and road information;

[0038] The shortest guidance distance is merged into the detection area map to define the actual position of the target pipeline detection robot on the ground and the straight-line distance and direction to the handheld terminal user;

[0039] The real-time position of the handheld terminal is taken as the starting point, and the actual position of the target pipeline detection robot on the ground is taken as the end point. The A* path planning algorithm is used to formulate the guidance route based on the road information of the detection area, and the detection position guidance information is generated and pushed.

[0040] In this solution, the handheld terminal extracts the detection image information of the target pipeline detection robot when performing the detection task according to the pipeline detection feedback information, and analyzes the pipeline blockage status according to the detection image information, specifically including:

[0041] Based on big data retrieval, image data of blockage conditions inside different pipelines are obtained, and blockage type marking and blockage condition assessment are performed to form a training data set, a blockage condition analysis model is constructed through a support vector machine, and the training data set is used to perform model training to obtain a desired blockage condition analysis model;

[0042] The handheld terminal obtains pipeline detection feedback information after establishing a stable communication environment with the target pipeline detection robot, and extracts detection image information when performing a pipeline blockage detection task through the pipeline detection feedback information;

[0043] Perform image preprocessing on the acquired detection image information, input the preprocessed detection image into the trained congestion condition analysis model, and introduce a weighted attention mechanism to weight the extracted detection image features to represent the importance, thereby obtaining congestion condition analysis information;

[0044] Acquire a 3D space trajectory map, extract potential congestion areas from the 3D space trajectory map, extract congestion condition characteristics of each potential congestion area using the congestion condition analysis information, including congestion type characteristics and congestion severity characteristics, determine whether each potential congestion area is an area to be treated, and obtain analysis information of the area to be treated;

[0045] The location information of each area to be treated is obtained from the 3D spatial trajectory map, and is marked in the detection area map. The congestion status characteristics of each area to be treated are used as priority weights, and the treatment priority is set to obtain the marked detection area map.

[0046] In this plan, the construction plan recommended specifically includes:

[0047] Obtaining an underground pipeline layout diagram of the detection area, wherein the underground pipeline layout diagram includes the distribution of underground pipelines in the target detection area; obtaining a marked detection area map, and extracting regional location information of the area to be treated based on the marked detection area map;

[0048] Determine the location of the pipeline with a blocked condition in the underground pipeline layout map by using the regional location information of the area to be treated, and extract the pipeline location features of the area near the blocked pipeline based on the underground pipeline layout map;

[0049] A two-dimensional plane map of the pipeline area that needs to be managed is constructed based on the location of the pipeline with a blocked condition and the location characteristics of the pipelines in the nearby area. The constructed two-dimensional plane map is meshed, and the pipeline meshes that need to be managed and the pipeline meshes that need to be avoided are defined to obtain a two-dimensional plane grid map.

[0050] In the two-dimensional plane grid map, a pipeline location grid with a blocked condition is defined as a starting point, a pipeline grid to be avoided is defined as an obstacle, and an improved ant colony algorithm is introduced to formulate a construction drilling route;

[0051] The PSO algorithm is used to carry out initial global planning with the pipeline location grid with blockage as the starting point. Several initial feasible drilling routes are output through iterative analysis. The initial feasible drilling routes are used as the enhanced variables of ant colony pheromone to improve the ant colony algorithm.

[0052] The initial feasible drilling route is used to enhance the variable allocation of the initial pheromone of the ant colony, and the initial optimization parameters are set. The state transition probability of each path node is calculated, and the path is optimized through the state transition probability. The pheromone of each optimized path is updated until the optimization result meets the iteration termination condition and the final drilling route is generated.

[0053] The drilling endpoint feature is extracted according to the final drilling route, and based on the drilling endpoint feature, a drilling point is recommended on the map of the detected area after the marking, and a drilling plan is generated corresponding to the final drilling route for push.

[0054] A second aspect of the present invention provides a system for locating and analyzing a blocked area for detecting a pipeline blockage. The system comprises: a memory and a processor. The memory contains a program for locating and analyzing a blocked area for detecting a pipeline blockage. When the program for locating and analyzing a blocked area for detecting a pipeline blockage is executed by the processor, the following steps are implemented:

[0055] The detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain initial detection position analysis information;

[0056] An initial detection orientation guide is generated according to the initial detection position analysis information, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information;

[0057] Extracting the detection trajectory characteristics of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory characteristics and establishing a 3D space trajectory map;

[0058] The detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D spatial trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information;

[0059] The handheld terminal extracts detection image information of the target pipeline detection robot when performing a detection task according to the pipeline detection feedback information, analyzes the pipeline blockage condition according to the detection image information, and recommends a construction plan.

[0060] The present invention discloses a method and system for positioning and analyzing a blocked area for pipeline blockage detection, including: collecting detection response signals emitted by a target pipeline detection robot based on a handheld terminal, analyzing and acquiring signals and determining an initial detection position; generating detection orientation guidance according to the initial position, and then continuously collecting signals according to the guidance until stable communication is established with the detection robot, and obtaining pipeline detection feedback information. The detection trajectory features are extracted through feedback information, and the detection route of the detection robot is generated and a 3D space trajectory map is established. Combined with the detection area map, the handheld terminal performs secondary positioning of the detection robot and generates positioning guidance information. The terminal further extracts detection image information, analyzes the pipeline blockage status and recommends construction plans, so as to realize rapid and accurate positioning and analysis of the blocked area in a complex pipeline environment, and assist in formulating the optimal treatment plan to improve detection and maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments or exemplary embodiments of the present invention, the drawings required for use in the embodiments or exemplary descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained according to the drawings without paying creative work.

[0062] Figure 1 A flow chart of a method for locating and analyzing a blocked area for pipeline blockage detection provided by an embodiment of the present invention;

[0063] Figure 2 A flow chart of a method for assisting drilling in a blocked area for detecting pipeline blockage provided by an embodiment of the present invention;

[0064] Figure 3 A block diagram of a blockage area positioning and analysis system for pipeline blockage detection provided by an embodiment of the present invention;

[0065] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0066] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0067] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0068] Figure 1 A flow chart of a method for locating and analyzing a blocked area for pipeline blockage detection provided by an embodiment of the present invention;

[0069] like Figure 1 As shown, the present invention provides a flow chart of a method for locating and analyzing a blocked area for pipeline blockage detection, comprising:

[0070] S102, collecting a detection response signal emitted by the target pipeline detection robot when performing detection based on the handheld terminal, analyzing the detection position of the target pipeline detection robot according to the acquired detection response signal, and obtaining initial detection position analysis information;

[0071] S104, generating an initial detection orientation guide according to the initial detection position analysis information, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information;

[0072] S106, extracting detection trajectory features of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory features and establishing a 3D space trajectory map;

[0073] S108, obtaining a detection area map, the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D space trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information;

[0074] S110, the handheld terminal extracts detection image information of the target pipeline detection robot when performing a detection task according to the pipeline detection feedback information, analyzes the pipeline blockage status according to the detection image information, and recommends a construction plan.

[0075] It should be noted that the present invention provides a method and system for positioning and analyzing a blocked area for pipeline blockage detection. The handheld terminal collects the response signal emitted by the pipeline detection robot, analyzes the initial detection position and generates orientation guidance to help the handheld terminal user adjust the signal collection direction. After establishing stable communication with the detection robot through continuous signal collection, the handheld terminal receives the detection feedback information, extracts the trajectory characteristics of the robot moving in the pipeline, and further generates a 3D space trajectory map. Combined with the generated 3D trajectory map and the detection area map, the handheld terminal performs secondary positioning of the detection robot and generates accurate detection position guidance information to guide user operations. At the same time, by extracting the image information of the detection feedback, analyzing the blockage condition inside the pipeline, evaluating the type and severity of the blockage, and recommending a specific construction treatment plan based on the detection results, the accurate positioning and efficient treatment of the blocked area can be achieved.

[0076] Further, in a preferred embodiment of the present application, the detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain the initial detection position analysis information, which specifically includes:

[0077] A pipeline detection robot is placed in the pipeline area to be detected to detect pipeline blockage. Ground monitoring personnel use handheld terminals to collect detection response signals continuously emitted by the target pipeline detection robot during the detection task.

[0078] After the handheld terminal user selects the starting direction in the ground area, the signal receiving module of the handheld terminal collects the detection response signal on the ground. The detection response signal is the electromagnetic signal continuously emitted by the probe of the target pipeline robot;

[0079] The handheld terminal user adjusts the signal receiving direction to obtain detection response signals at different directions, obtains detection response signal collection information, extracts features from the detection response collection signals, and obtains detection response feature signals received at different directions;

[0080] Extracting a local maximum value and a local minimum value in the detection response characteristic signal, performing signal interpolation processing based on the local maximum value and the local minimum value, and constructing an upper envelope and a lower envelope of the detection response characteristic signal;

[0081] Based on the obtained upper envelope and lower envelope calculations including the mean, it is determined whether they are within a preset threshold range. If so, the corresponding local signal trend is removed from the original detection response characteristic signal to obtain a reconstructed detection response characteristic signal;

[0082] The envelope strengths of different directions are calculated according to the reconstructed detection response characteristic signal, the directions corresponding to the envelope strengths greater than a preset threshold are selected as candidate guidance directions, and the initial detection position analysis information is generated by combining the envelope strengths of all directions.

[0083] It should be noted that a pipeline detection robot is placed in the pipeline area to be detected to perform the pipeline blockage detection task. During the operation of the detection robot, the probe will continuously emit electromagnetic signals, and the handheld terminal on the ground will continuously receive the electromagnetic signals emitted by the probe. The closer the handheld terminal is to the probe, the stronger the signal. The position where the signal is strongest is the position of the probe. The handheld terminal will display the signal strength. When the handheld terminal faces different directions, the signal strength will also change significantly. Based on this, the position of the probe relative to the handheld terminal can be judged. The monitoring personnel select a starting direction in the ground area and use the handheld terminal to adjust the direction of signal reception to obtain detection response signal data from different directions. Based on these signal data, the handheld terminal extracts features from the collected detection response signals and generates detection response feature signal data from different directions. The local maximum and local minimum values ​​of the signal are further extracted from these data, and the signal is interpolated based on these extreme points to generate the corresponding upper and lower envelopes. By analyzing the upper and lower envelopes of the signal, the envelope mean of the signal is calculated, and it is determined whether the mean falls within the preset threshold range. If the signal envelope mean meets the threshold condition, the corresponding local signal trend is removed from the original detection response signal to generate an optimized reconstructed detection response characteristic signal that reflects the truly effective directional characteristics. Subsequently, the envelope strengths of different directions are calculated based on the optimized reconstructed signal, and the directions with envelope strengths greater than the preset threshold are selected as candidate guidance directions. Finally, by combining the envelope strength information of all candidate directions, the handheld terminal generates analysis information of the initial detection position, providing a reliable basis for subsequent detection operations.

[0084] Further, in a preferred embodiment of the present application, the initial detection position analysis information is used to generate an initial detection orientation guide, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information, specifically including:

[0085] Acquire initial detection position analysis information, generate a detection response signal strength distribution map at the current moment based on the initial detection position analysis information, extract candidate guidance directions from the initial detection position analysis information, and mark them in the detection response signal strength distribution map;

[0086] Extracting the detection response signal strength characteristics of the neighbor direction of the candidate guidance direction based on the detection response signal strength distribution diagram and taking the candidate guidance direction as a reference, and judging it with a preset threshold, if it is greater than the preset threshold, obtaining the detection response signal strength of the neighbor direction by using the initial detection position analysis information;

[0087] Extract the detection response signal strength of the candidate guidance direction, combine the detection response signal strength of the neighbor direction to generate the guidance direction optimization interval, preset the guidance direction interval and introduce it into the Bayesian inference network to analyze the detection response signal strength corresponding to each direction interval within the candidate guidance direction and the neighbor direction, and obtain the detection response signal strength inference information;

[0088] Based on the detection response signal strength inference information, a detection response signal strength gradient map of the guidance direction optimization interval is constructed, and the guidance direction interval with the largest signal strength is selected as the final guidance direction through the detection response signal strength gradient map to generate an initial detection direction guidance for push;

[0089] The handheld terminal user continues to collect signals according to the generated initial detection direction guidance, and monitors the communication channel in the guidance direction in real time to obtain communication channel monitoring information, and calculates the signal-to-noise ratio, packet loss rate and communication delay of each channel when establishing communication with the target pipeline detection robot according to the communication channel monitoring information, to obtain first analysis information;

[0090] Preset communication environment assessment rules, analyze the stability of the current communication environment using the communication environment assessment rules according to the first analysis information, and select a stable communication channel. If a stable communication environment cannot be established with the target pipeline detection robot, prompt the handheld terminal user to continue to move forward in the guided direction;

[0091] When the handheld terminal establishes a stable communication environment with the target pipeline detection robot, the handheld terminal sends a data transmission instruction to the target pipeline detection robot, and the target pipeline detection robot sends pipeline detection feedback information to the handheld terminal after receiving the data transmission instruction.

[0092] It should be noted that the handheld terminal extracts the detection response signal strength characteristics in the neighbor direction based on the candidate guidance direction according to the detection response signal strength distribution map. If the strength characteristic value is greater than the preset threshold, the detection response signal strength in the neighbor direction is further obtained based on the initial detection position analysis information. Subsequently, the system comprehensively analyzes the detection response signal strength of the candidate guidance direction and the neighbor direction, generates an optimized guidance direction interval, and ensures that the signal strength characteristics can cover the target detection area with higher accuracy. The direction interval is preset, and the direction interval and its strength characteristics are imported into the Bayesian inference network. The Bayesian inference network is used to analyze the signal strength distribution characteristics between the candidate guidance direction and its neighbor direction, and determine the reliability and credibility of the signal strength in each direction interval through probabilistic inference, so as to generate more accurate detection response signal strength inference information. Then, based on the inference results, a detection response signal strength gradient map covering the optimized interval is constructed to intuitively display the signal change trend in each direction interval. In the gradient map, the direction interval with the largest signal strength is selected as the final guidance direction, and the initial detection azimuth guidance information is generated accordingly, which is pushed to the handheld terminal user in real time to provide direction guidance for its further detection operation. The user of the handheld terminal continues to move and collect signals according to the generated initial detection direction guidance, and in the process monitors the communication channel status in the guidance direction in real time to obtain communication channel monitoring information. This information includes key parameters such as the current signal-to-noise ratio, data packet loss rate, and communication delay of each channel to evaluate the communication quality. If a stable communication environment cannot be established with the target pipeline detection robot, the system will prompt the user of the handheld terminal to continue moving in the guidance direction and adjust the position to optimize the signal reception conditions. Once the handheld terminal successfully establishes a stable communication environment with the pipeline detection robot, it will send data transmission instructions to the detection robot. After receiving the instructions, the detection robot will send real-time pipeline detection feedback information to the handheld terminal, including specific images and related data of the detection area.

[0093] Further, in a preferred embodiment of the present application, the detection trajectory characteristics of the target pipeline detection robot are extracted through the pipeline detection feedback information, and the detection route of the target pipeline detection robot is analyzed according to the detection trajectory characteristics and a 3D space trajectory map is established, which specifically includes:

[0094] Acquiring pipeline detection feedback information, wherein the pipeline detection feedback information includes detection image information and detection trajectory information when the target pipeline detection robot performs a pipeline blockage detection task;

[0095] Extracting features from the pipeline detection feedback information, extracting detection trajectory features of the target pipeline detection robot when performing the current detection task, performing spatial coordinate transformation according to the extracted detection trajectory features, and generating a detection trajectory data set of the target pipeline detection robot based on the transformed detection trajectory features;

[0096] Performing a registration operation on each detection trajectory data in the detection trajectory data set according to the corresponding spatial coordinates, performing a fitting operation on the registered detection trajectory data based on a least squares method to construct continuous detection trajectory data, and obtaining detection trajectory fitting data;

[0097] Extracting the detection dwell time characteristics of the target pipeline detection robot when performing the current detection task through the pipeline detection feedback information, and associating it with the detection trajectory fitting data;

[0098] A kernel density estimation method is introduced to perform density estimation on the detection dwell time of each trajectory point in the associated detection trajectory fitting data to obtain the probability density of each trajectory point, and the probability density of each trajectory point is converted into color information using a linear color mapping method;

[0099] The color information obtained after the conversion is used to construct a detection trajectory heat map of the target pipeline detection robot when performing the current detection task, and based on the color information of each trajectory point, the trajectory points greater than a preset threshold are marked in the detection trajectory heat map as potential blockage areas;

[0100] The 3D spatial trajectory map of the target pipeline robot when performing the current detection task is constructed by combining the detection trajectory heat map and the associated detection trajectory fitting data using 3D modeling technology.

[0101] It should be noted that the detection image information and detection trajectory information of the detection robot during the execution of the task are extracted from the obtained pipeline detection feedback information. The detection trajectory information contains the detailed position record of the robot when it moves in the pipeline. The detection trajectory features are extracted and converted into a standard three-dimensional spatial coordinate format to generate the detection trajectory data set of the target pipeline detection robot. Each trajectory data in the detection trajectory data set is registered according to its corresponding spatial coordinates to calibrate the relative deviation between different positions of the robot. The calibrated trajectory data is fitted by the least squares method to construct a continuous and smooth detection trajectory. The continuity and accuracy of the trajectory are further enhanced, providing more intuitive and reliable basic data for subsequent blockage area analysis. At the same time, the detection residence time characteristics of each point of the target robot when performing the task are extracted from the pipeline detection feedback information, and these time characteristics are associated with the trajectory fitting data. It should be understood that the longer the robot stays at a certain position during the pipeline detection process, the greater the difficulty of passing through, which means that there may be a blockage. The kernel density estimation method is introduced to perform density estimation on the detection residence time of each trajectory point after association. Kernel density estimation provides the probability density of the detection residence time distribution of each trajectory point, and these probability density values ​​are converted into corresponding color information through linear color mapping. The color information intuitively reflects the importance and blockage possibility of each trajectory point. Using the generated color information, a detection trajectory heat map of the current detection task of the target pipeline robot is constructed. Different color areas in the heat map represent different probability densities. Trajectory points with higher density correspond to possible blockage areas. Trajectory points greater than the threshold in the heat map are marked as potential blockage areas. Finally, the detection trajectory heat map is combined with the associated trajectory fitting data, and 3D modeling technology is used to construct a 3D spatial trajectory map in the pipeline. The three-dimensional trajectory path of the detection robot when performing the task is displayed, providing clear and intuitive spatial distribution and blockage area information.

[0102] Further, in a preferred embodiment of the present application, the detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D space trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information, which specifically includes:

[0103] The real-time position of the user of the handheld terminal is located by a positioning module of the handheld terminal to obtain real-time position features, and the real-time position features are spatially registered in a 3D spatial trajectory map to calibrate the real-time position of the user of the handheld terminal;

[0104] Taking the real-time position of the handheld terminal user as the starting point, the end point trajectory point of the target pipeline detection robot is obtained through the 3D spatial trajectory graph with the time series feature as the query tag, and the Euclidean distance between the two points is calculated using the Euclidean algorithm;

[0105] The shortest guidance distance between the handheld terminal user and the target pipeline detection robot is generated according to the calculated Euclidean distance, and a detection area map is obtained, where the detection area map is a ground map of the detection area, including building information, environmental information, and road information;

[0106] The shortest guidance distance is merged into the detection area map to define the actual position of the target pipeline detection robot on the ground and the straight-line distance and direction to the handheld terminal user;

[0107] The real-time position of the handheld terminal is taken as the starting point, and the actual position of the target pipeline detection robot on the ground is taken as the end point. The A* path planning algorithm is used to formulate the guidance route based on the road information of the detection area, and the detection position guidance information is generated and pushed.

[0108] It should be noted that the real-time position of the handheld terminal user is accurately located through the positioning module of the handheld terminal, and a real-time position feature reflecting the user's current position is generated. The real-time position feature is spatially aligned with the 3D spatial trajectory map, so that the user's position is calibrated in the three-dimensional coordinate system of the trajectory map, ensuring that the ground positioning data is highly consistent with the data of the robot's activity trajectory in the pipeline, and providing a real-time reference position. Using the calibrated real-time position of the handheld terminal user as the starting point, the terminal trajectory point of the target pipeline detection robot is locked from the 3D spatial trajectory map using the time series feature as the query tag. Then, the straight-line distance between the user's position and the robot's terminal trajectory point, that is, the Euclidean distance between the two points, is calculated by the Euclidean algorithm. The shortest straight-line distance obtained is further combined with the detection area map, which is a two-dimensional representation of the ground environment, including information such as building layout, road network, and obstacle distribution, so as to clarify the actual position of the target robot on the ground, as well as its straight-line distance and direction with the handheld terminal user. The real-time position of the handheld terminal is used as the starting point of the path, and the actual ground position corresponding to the target pipeline detection robot is used as the end point of the path. Combined with the road information in the detection area map, the A* path planning algorithm is used to generate the optimized path. As a classic path planning method, the A* algorithm efficiently calculates the optimal path from the starting point to the end point in the ground environment by comprehensively considering the geometric information of the road network and the distribution of obstacles. The generated path combines the shortest guidance distance and the surrounding ground environment information to form the detection position guidance information. Finally, the handheld terminal pushes the best guidance route to the user to show the shortest path from the user to the actual ground position of the detection robot, and provides a specific direction of travel. Through real-time path updates and direction guidance, users can quickly reach the target point, effectively shorten the detection time, and improve the efficiency of task execution.

[0109] Further, in a preferred embodiment of the present application, the handheld terminal extracts detection image information of the target pipeline detection robot when performing a detection task according to the pipeline detection feedback information, and analyzes the pipeline blockage condition according to the detection image information, specifically including:

[0110] Based on big data retrieval, image data of blockage conditions inside different pipelines are obtained, and blockage type marking and blockage condition assessment are performed to form a training data set, a blockage condition analysis model is constructed through a support vector machine, and the training data set is used to perform model training to obtain a desired blockage condition analysis model;

[0111] The handheld terminal obtains pipeline detection feedback information after establishing a stable communication environment with the target pipeline detection robot, and extracts detection image information when performing a pipeline blockage detection task through the pipeline detection feedback information;

[0112] Perform image preprocessing on the acquired detection image information, input the preprocessed detection image into the trained congestion condition analysis model, and introduce a weighted attention mechanism to weight the extracted detection image features to represent the importance, thereby obtaining congestion condition analysis information;

[0113] Acquire a 3D space trajectory map, extract potential congestion areas from the 3D space trajectory map, extract congestion condition characteristics of each potential congestion area using the congestion condition analysis information, including congestion type characteristics and congestion severity characteristics, determine whether each potential congestion area is an area to be treated, and obtain analysis information of the area to be treated;

[0114] The location information of each area to be treated is obtained from the 3D spatial trajectory map, and is marked in the detection area map. The congestion status characteristics of each area to be treated are used as priority weights, and the treatment priority is set to obtain the marked detection area map.

[0115] It should be noted that the image data about the blockage conditions inside different pipelines are collected by using big data retrieval technology, and these image data are analyzed and annotated to clarify the specific blockage types and blockage degrees involved, forming a training data set for blockage condition analysis. The blockage condition analysis model is established by support vector machine (SVM), and the model is fully trained using the constructed training data set to optimize its parameters and weights, so as to obtain an efficient analysis model that can accurately analyze the blockage condition in the actual blockage detection task. When the handheld terminal successfully establishes a stable communication environment with the target pipeline detection robot, the detection image information captured during the blockage detection task is extracted from the pipeline detection feedback information sent back by the robot. Subsequently, the preprocessed detection image data is input into the trained blockage condition analysis model. In order to further improve the analysis accuracy, the model uses a weighted attention mechanism to weight the features extracted from the detection image. In this way, the important features that characterize the blockage condition, such as the key areas of the blockage type and the severity of the blockage, are highlighted, and finally the blockage condition analysis information is obtained. Subsequently, according to the obtained 3D spatial trajectory map, the potential blockage area identified is extracted from it. Using the blockage analysis information, a detailed blockage feature assessment is conducted for each potential blockage area, including blockage type characteristics such as material properties (sediment, tree roots, etc.) and blockage severity characteristics such as blockage area ratio or flow blockage. By analyzing these characteristics, it is determined which potential blockage areas need to be treated first, and the screened treatment area information is integrated into the analysis information of the areas to be treated. Next, the precise locations of all areas to be treated are extracted from the 3D spatial trajectory map, and these location information is projected onto the ground map of the detection area for annotation. In order to further optimize the efficiency of the treatment work, the blockage condition characteristics of each area to be treated (such as blockage type and severity) are set as priority weights, and the treatment priority of each area is calculated and intuitively presented in the marked detection area map. In addition, the location of the area to be treated is clearly displayed, and the basis for the order of treatment is provided, providing comprehensive guidance information for subsequent cleaning decisions.

[0116] Figure 2 A flow chart of a method for assisting drilling in a blocked area for detecting pipeline blockage provided by an embodiment of the present invention;

[0117] like Figure 2 As shown, the present invention provides a flow chart of a method for assisting drilling in a blocked area for pipeline blockage detection, comprising:

[0118] S202, determining the location of the pipeline with a blockage in the underground pipeline layout map based on the regional location information of the area to be treated, and extracting the pipeline location features of the area near the blocked pipeline based on the underground pipeline layout map;

[0119] S204, constructing a two-dimensional plane map of the pipeline area to be treated based on the location of the pipeline with the blocked condition and the location characteristics of the pipelines in the nearby area, dividing the constructed two-dimensional plane map into grids, and defining the pipeline grids to be treated and the pipeline grids to be avoided, to obtain a two-dimensional plane grid map;

[0120] S206, defining the pipeline location grid with a blocked condition as the starting point in the two-dimensional plane grid map, defining the pipeline grid to be avoided as an obstacle, and introducing an improved ant colony algorithm to formulate a construction drilling route;

[0121] S208, using the PSO algorithm to perform initial global planning with the pipeline location grid where the blockage occurs as the starting point, outputting several initial feasible drilling routes through iterative analysis, and using the initial feasible drilling routes as enhanced variables of the ant colony pheromone to improve the ant colony algorithm;

[0122] S210, performing enhanced variable allocation on the initial pheromone of the ant colony through the initial feasible drilling route, setting the initial optimization parameters, calculating the state transition probability of each path node, performing path optimization through the state transition probability, and updating the pheromone of each optimized path until the optimization result meets the iteration termination condition, thereby generating the final drilling route;

[0123] S212, extracting drilling endpoint features according to the final drilling route, recommending drilling points on the marked detection area map based on the drilling endpoint features, and generating a drilling plan corresponding to the final drilling route for push.

[0124] It should be noted that the specific location of the pipeline with a blockage is determined in the underground pipeline layout map through the location information of the area to be treated, and the location features of other pipelines around the blocked pipeline are extracted according to the layout map. These features include the arrangement direction, spatial distribution and relative position relationship of the nearby pipelines with the blocked pipeline, forming a two-dimensional plane map of the pipeline area to be treated. The constructed two-dimensional plane map is gridded, and each grid is defined as a unit with clear attributes. For example, the grid of the pipeline to be treated represents the location of the pipeline with a blockage, and the grid of the pipeline to be avoided represents the pipeline area to be avoided during construction, thereby generating a clear two-dimensional plane grid map. In the two-dimensional plane grid map, the grid position representing the blocked pipeline is defined as the starting point, and the grid of the pipeline to be avoided is regarded as an obstacle in the planning. The improved traditional ant colony algorithm is used for drilling route analysis. The particle swarm optimization algorithm is used to perform global planning with the blocked pipeline grid as the starting point, and a set of initial feasible drilling routes are generated through multiple iterative analysis. This improves the coverage of the solution and provides a better initial pheromone distribution basis for the ant colony algorithm. Subsequently, the results of these initial feasible drilling routes are used as enhanced variables of pheromones and assigned to the initial pheromones of the ant colony algorithm. At the same time, optimization parameters are set to adjust the distribution weight of pheromones and control the path search behavior of ants. In the operation of the improved ant colony algorithm, the state transition probability of each grid path node is calculated based on the initial pheromones and the set parameters, thereby optimizing the path selection. Through multiple path iterations and pheromone updates, the algorithm can continuously improve the ability to distinguish between the advantages and disadvantages of each path, and finally lock the best drilling route. When the preset iteration termination conditions are met, the final construction drilling route is generated. Finally, according to the generated final drilling route, the drilling end point features are further extracted, including the specific location of the end point, the surrounding environment, and the actual operability of the drilling point. Based on the characteristics of the drilling end point, suitable drilling points are recommended, and the complete drilling plan is planned in detail in combination with the final drilling route and pushed to the construction personnel, providing accurate operation guidance for pipeline dredging, while effectively avoiding risks and improving construction efficiency.

[0125] Figure 3 A system 3 for locating and analyzing a blocked area for detecting a pipeline blockage is provided in one embodiment of the present invention. The system comprises: a memory 31 and a processor 32. The memory 31 contains a program for locating and analyzing a blocked area for detecting a pipeline blockage. When the program for locating and analyzing a blocked area for detecting a pipeline blockage is executed by the processor 32, the following steps are implemented:

[0126] The detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain initial detection position analysis information;

[0127] An initial detection orientation guide is generated according to the initial detection position analysis information, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information;

[0128] Extracting the detection trajectory characteristics of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory characteristics and establishing a 3D space trajectory map;

[0129] The detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D spatial trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information;

[0130] The handheld terminal extracts detection image information of the target pipeline detection robot when performing a detection task according to the pipeline detection feedback information, analyzes the pipeline blockage condition according to the detection image information, and recommends a construction plan.

[0131] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0132] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0133] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0134] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0135] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0136] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for locating and analyzing a blocked area for pipeline blockage detection, characterized in that: include: The detection response signal emitted by the target pipeline detection robot during detection is collected based on the handheld terminal, and the detection position of the target pipeline detection robot is analyzed according to the acquired detection response signal to obtain initial detection position analysis information; An initial detection orientation guide is generated according to the initial detection position analysis information, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information; Extracting the detection trajectory characteristics of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory characteristics and establishing a 3D space trajectory map; The detection area map is obtained, and the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D spatial trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information; The handheld terminal extracts detection image information of the target pipeline detection robot when performing the detection task according to the pipeline detection feedback information, analyzes the pipeline blockage condition according to the detection image information, and recommends a construction plan; The initial detection position analysis information is used to generate an initial detection orientation guide, and the handheld terminal user continues to collect signals according to the initial detection orientation guide until a stable communication environment is established with the target pipeline detection robot to obtain pipeline detection feedback information, which specifically includes: Acquire initial detection position analysis information, generate a detection response signal strength distribution map at the current moment based on the initial detection position analysis information, extract candidate guidance directions from the initial detection position analysis information, and mark them in the detection response signal strength distribution map; Extracting the detection response signal strength characteristics of the neighbor direction of the candidate guidance direction based on the detection response signal strength distribution diagram and taking the candidate guidance direction as a reference, and judging it with a preset threshold, if it is greater than the preset threshold, obtaining the detection response signal strength of the neighbor direction by using the initial detection position analysis information; Extract the detection response signal strength of the candidate guidance direction, combine the detection response signal strength of the neighbor direction to generate the guidance direction optimization interval, preset the guidance direction interval and introduce it into the Bayesian inference network to analyze the detection response signal strength corresponding to each direction interval within the candidate guidance direction and the neighbor direction, and obtain the detection response signal strength inference information; Based on the detection response signal strength inference information, a detection response signal strength gradient map of the guidance direction optimization interval is constructed, and the guidance direction interval with the largest signal strength is selected as the final guidance direction through the detection response signal strength gradient map to generate an initial detection direction guidance for push; The handheld terminal user continues to collect signals according to the generated initial detection direction guidance, and monitors the communication channel in the guidance direction in real time to obtain communication channel monitoring information, and calculates the signal-to-noise ratio, packet loss rate and communication delay of each channel when establishing communication with the target pipeline detection robot according to the communication channel monitoring information, to obtain first analysis information; A communication environment assessment rule is preset, and the stability of the current communication environment is analyzed using the communication environment assessment rule according to the first analysis information, and a stable communication channel is selected. If a stable communication environment cannot be established with the target pipeline detection robot, the handheld terminal user is prompted to continue to move forward in the guided direction; When the handheld terminal establishes a stable communication environment with the target pipeline detection robot, the handheld terminal sends a data transmission instruction to the target pipeline detection robot, and the target pipeline detection robot sends pipeline detection feedback information to the handheld terminal after receiving the data transmission instruction; The method of extracting the detection trajectory characteristics of the target pipeline detection robot through the pipeline detection feedback information, analyzing the detection route of the target pipeline detection robot according to the detection trajectory characteristics and establishing a 3D space trajectory map specifically includes: Acquiring pipeline detection feedback information, wherein the pipeline detection feedback information includes detection image information and detection trajectory information when the target pipeline detection robot performs a pipeline blockage detection task; Extracting features from the pipeline detection feedback information, extracting detection trajectory features of the target pipeline detection robot when performing the current detection task, performing spatial coordinate transformation according to the extracted detection trajectory features, and generating a detection trajectory data set of the target pipeline detection robot based on the transformed detection trajectory features; Performing a registration operation on each detection trajectory data in the detection trajectory data set according to the corresponding spatial coordinates, performing a fitting operation on the registered detection trajectory data based on a least squares method to construct continuous detection trajectory data, and obtaining detection trajectory fitting data; Extracting the detection dwell time characteristics of the target pipeline detection robot when performing the current detection task through the pipeline detection feedback information, and associating it with the detection trajectory fitting data; A kernel density estimation method is introduced to perform density estimation on the detection dwell time of each trajectory point in the associated detection trajectory fitting data to obtain the probability density of each trajectory point, and the probability density of each trajectory point is converted into color information using a linear color mapping method; The color information obtained after the conversion is used to construct a detection trajectory heat map of the target pipeline detection robot when performing the current detection task, and based on the color information of each trajectory point, the trajectory points greater than a preset threshold are marked in the detection trajectory heat map as potential blockage areas; Combining the detection trajectory heat map and the associated detection trajectory fitting data, the 3D modeling technology is used to construct a 3D spatial trajectory map of the target pipeline robot when performing the current detection task; The acquisition of the detection area map, the handheld terminal performs secondary positioning of the target pipeline detection robot according to the 3D space trajectory map, and performs detection position guidance in combination with the detection area map to obtain detection position guidance information, specifically including: The real-time position of the user of the handheld terminal is located by the positioning module of the handheld terminal to obtain the real-time position feature, and the real-time position feature is spatially registered in the 3D space trajectory map to calibrate the real-time position of the user of the handheld terminal; Taking the real-time position of the handheld terminal user as the starting point, the end point trajectory point of the target pipeline detection robot is obtained through the 3D spatial trajectory graph with the time series feature as the query tag, and the Euclidean distance between the two points is calculated using the Euclidean algorithm; The shortest guidance distance between the handheld terminal user and the target pipeline detection robot is generated according to the calculated Euclidean distance, and a detection area map is obtained, where the detection area map is a ground map of the detection area, including building information, environmental information, and road information; The shortest guidance distance is merged into the detection area map to define the actual position of the target pipeline detection robot on the ground and the straight-line distance and direction to the handheld terminal user; The real-time position of the handheld terminal is taken as the starting point, and the actual position of the target pipeline detection robot on the ground is taken as the end point. The A* path planning algorithm is used to formulate the guidance route based on the road information of the detection area, and the detection position guidance information is generated and pushed.

2. The method for locating and analyzing a blocked area for pipeline blockage detection according to claim 1, characterized in that: The method of collecting the detection response signal emitted by the target pipeline detection robot when performing detection based on the handheld terminal, analyzing the detection position of the target pipeline detection robot according to the acquired detection response signal, and obtaining the initial detection position analysis information specifically includes: A pipeline detection robot is placed in the pipeline area to be detected to detect pipeline blockage. Ground monitoring personnel use handheld terminals to collect detection response signals continuously emitted by the target pipeline detection robot during the detection task. After the handheld terminal user selects the starting direction in the ground area, the signal receiving module of the handheld terminal collects the detection response signal on the ground. The detection response signal is the electromagnetic signal continuously emitted by the probe of the target pipeline robot; The handheld terminal user adjusts the signal receiving direction to obtain detection response signals at different directions, obtains detection response signal collection information, extracts features from the detection response signal collection information, and obtains detection response feature signals received at different directions; Extracting a local maximum value and a local minimum value in the detection response characteristic signal, performing signal interpolation processing based on the local maximum value and the local minimum value, and constructing an upper envelope and a lower envelope of the detection response characteristic signal; Based on the obtained upper envelope and lower envelope calculations including the mean, it is determined whether they are within a preset threshold range. If so, the corresponding local signal trend is removed from the original detection response characteristic signal to obtain a reconstructed detection response characteristic signal; The envelope strengths of different directions are calculated according to the reconstructed detection response characteristic signal, the directions corresponding to the envelope strengths greater than a preset threshold are selected as candidate guidance directions, and the initial detection position analysis information is generated by combining the envelope strengths of all directions.

3. The method for locating and analyzing a blocked area for pipeline blockage detection according to claim 1, characterized in that: The handheld terminal extracts detection image information when the target pipeline detection robot performs a detection task according to the pipeline detection feedback information, and analyzes the pipeline blockage condition according to the detection image information, specifically including: Based on big data retrieval, image data of blockage conditions inside different pipelines are obtained, and blockage type marking and blockage condition assessment are performed to form a training data set, a blockage condition analysis model is constructed through a support vector machine, and the training data set is used to perform model training to obtain a desired blockage condition analysis model; The handheld terminal obtains pipeline detection feedback information after establishing a stable communication environment with the target pipeline detection robot, and extracts detection image information when performing a pipeline blockage detection task through the pipeline detection feedback information; Perform image preprocessing on the acquired detection image information, input the preprocessed detection image into the trained congestion condition analysis model, and introduce a weighted attention mechanism to weight the extracted detection image features to represent the importance, thereby obtaining congestion condition analysis information; Acquire a 3D space trajectory map, extract potential congestion areas from the 3D space trajectory map, extract congestion condition characteristics of each potential congestion area using the congestion condition analysis information, including congestion type characteristics and congestion severity characteristics, determine whether each potential congestion area is an area to be treated, and obtain analysis information of the area to be treated; The location information of each area to be treated is obtained from the 3D spatial trajectory map, and is marked in the detection area map. The congestion status characteristics of each area to be treated are used as priority weights, and the treatment priority is set to obtain the marked detection area map.

4. The method for locating and analyzing a blocked area for pipeline blockage detection according to claim 1, characterized in that: The construction plan recommendation specifically includes: Obtaining an underground pipeline layout diagram of the detection area, wherein the underground pipeline layout diagram includes the distribution of underground pipelines in the target detection area; obtaining a marked detection area map, and extracting regional location information of the area to be treated based on the marked detection area map; Determine the location of the pipeline with a blocked condition in the underground pipeline layout map by using the regional location information of the area to be treated, and extract the pipeline location features of the area near the blocked pipeline based on the underground pipeline layout map; A two-dimensional plane map of the pipeline area that needs to be managed is constructed based on the location of the pipeline with a blocked condition and the location characteristics of the pipelines in the nearby area. The constructed two-dimensional plane map is meshed, and the pipeline meshes that need to be managed and the pipeline meshes that need to be avoided are defined to obtain a two-dimensional plane grid map. In the two-dimensional plane grid map, a pipeline location grid with a blocked condition is defined as a starting point, a pipeline grid to be avoided is defined as an obstacle, and an improved ant colony algorithm is introduced to formulate a construction drilling route; The PSO algorithm is used to carry out initial global planning with the pipeline location grid with blockage as the starting point. Several initial feasible drilling routes are output through iterative analysis. The initial feasible drilling routes are used as the enhanced variables of ant colony pheromone to improve the ant colony algorithm. The initial feasible drilling route is used to enhance the variable allocation of the initial pheromone of the ant colony, and the initial optimization parameters are set. The state transition probability of each path node is calculated, and the path is optimized through the state transition probability. The pheromone of each optimized path is updated until the optimization result meets the iteration termination condition and the final drilling route is generated. The drilling endpoint feature is extracted according to the final drilling route, and based on the drilling endpoint feature, a drilling point is recommended on the map of the detected area after the marking, and a drilling plan is generated corresponding to the final drilling route for push.

5. A blockage area positioning and analysis system for pipeline blockage detection, characterized in that: The system includes: a memory and a processor, wherein the memory contains a blockage area positioning and analysis method program applied to pipeline blockage detection, and when the blockage area positioning and analysis method program applied to pipeline blockage detection is executed by the processor, the blockage area positioning and analysis method steps applied to pipeline blockage detection as described in any one of claims 1 to 4 are implemented.

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