Automatic detection and health assessment system and method for underground pipeline

Abstract

The invention discloses an automatic detection and health assessment system and method for an underground pipeline, and relates to the technical field of detection.The automatic detection and health assessment system comprises a data acquisition module, a data analysis module, a scheme making module, an early warning terminal and a database; whether the underground pipeline is healthy or not is judged, if not, the risk level of the underground pipeline is analyzed, early warning and maintenance are carried out at the same time, if yes, the damage speed of the underground pipeline is analyzed, if the damage speed is high, early warning and maintenance are carried out, and a maintainer with the highest maintenance level is selected for maintenance during maintenance, so that the inspection efficiency is guaranteed; the validity and integrity of data are guaranteed, and the judgment accuracy and the maintenance effect of the underground pipeline are also guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, and in particular to an automated detection and health assessment system and method for underground pipelines. Background Art

[0002] Pipelines in municipal infrastructure are the core of urban operations. With the acceleration of urbanization, underground pipelines, as the "lifeline" of the city, undertake important functions such as transporting water, gas, electricity, and communications. However, since underground pipelines have been buried underground for a long time, they are affected by various factors such as geological conditions, environmental factors, and years of use. They are prone to corrosion, leakage, and rupture, which not only affect the normal operation of the city but may also cause safety accidents.

[0003] The traditional automated detection and health assessment system and method for underground pipelines relies on manual inspection of various external parameters of underground pipelines and records them. Finally, the health status of the underground pipelines is analyzed based on the recorded data, and the maintenance technician repairs the underground pipelines based on the health status of the underground pipelines. Obviously, this automated detection and health assessment system and method for underground pipelines has at least the following shortcomings: 1. The traditional automated detection and health assessment system and method for underground pipelines relies on manual inspections and data recording. Manual inspections are inefficient, and omissions or errors may occur when recording data. The efficiency of inspections cannot be guaranteed, and the validity and integrity of data cannot be guaranteed.

[0004] 2. In actual situations, the internal parameters of underground pipelines will also affect the health of underground pipelines. Traditional automated detection and health assessment systems and methods for underground pipelines rely on various external parameters to determine whether the underground pipelines are healthy, and cannot guarantee the accuracy of the judgment.

[0005] 3. When repairing underground pipelines, the traditional automated detection and health assessment system and method randomly notifies a maintenance technician to perform maintenance on the pipeline, which cannot guarantee the maintenance effect of the underground pipeline. Summary of the Invention

[0006] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an automated detection and health assessment system and method for underground pipelines.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: First, the present invention provides an automated detection and health assessment system for underground pipelines, comprising the following modules: a data acquisition module, a data analysis module, a program formulation module, an early warning terminal and a database.

[0008] The data acquisition module is used by the intelligent robot to collect various external parameters and internal parameters of the underground pipeline according to the planned driving path.

[0009] The data analysis module includes a health analysis unit and a damage speed analysis unit.

[0010] The health analysis unit is used to obtain various external parameters and internal parameters of the underground pipeline, analyze whether the underground pipeline is healthy, and if unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute a maintenance and protection module.

[0011] The damage rate analysis unit block is used to obtain various environmental parameters of the underground pipeline when the underground pipeline is healthy, and analyze the damage rate of the underground pipeline in combination with various parameters of the underground pipeline. If the damage rate is fast, an early warning is issued and a maintenance and protection module is executed.

[0012] The maintenance and protection module is used to perform maintenance and protection based on the information of the underground pipeline.

[0013] The early warning terminal is used to issue an early warning when the underground pipeline is unhealthy or is rapidly damaged.

[0014] The database is used to store historical information of underground pipelines and information of each maintenance technician.

[0015] In a second aspect, the present invention provides an automated detection and health assessment method for underground pipelines, comprising the following steps: Step 1, data collection: the intelligent robot collects various external and internal parameters of the underground pipeline according to the planned driving path.

[0016] Step 2: Analyze pipeline health: Obtain the external and internal parameters of the underground pipeline and analyze whether the underground pipeline is healthy. If it is unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute the maintenance and protection module.

[0017] Step 3: Analyze the damage rate: When the underground pipeline is healthy, obtain the various environmental parameters of the underground pipeline and analyze the damage rate of the underground pipeline in combination with the various parameters of the underground pipeline. If the damage rate is fast, issue an early warning and execute the maintenance and protection module.

[0018] Step 4: Maintenance and protection: Perform maintenance and protection based on the information of underground pipelines.

[0019] The beneficial effects of the present invention are: 1. An automated detection and health assessment system and method for underground pipelines, which uses robots to collect various external and internal parameters of underground pipelines and determine whether the underground pipelines are healthy. If they are unhealthy, the risk level of the underground pipelines is analyzed, and early warning and maintenance are carried out at the same time. If they are healthy, the damage rate of the underground pipelines is analyzed. If the damage rate is fast, early warning and maintenance are carried out. During maintenance, the maintenance technician with the highest maintenance level is selected to perform the maintenance, thereby ensuring the efficiency of inspections, the validity and integrity of the data, the accuracy of judgments and the maintenance effect of underground pipelines.

[0020] 2. The present invention uses an intelligent robot to collect various external and internal parameters of underground pipelines, plans the optimal driving route of the intelligent robot before collection, obtains a panoramic view of the robot's surrounding environment in real time during the collection process, and adjusts the optimal driving route, thereby ensuring the efficiency of inspection and the validity and integrity of the data.

[0021] 3. The present invention uses dual intelligent robots to simultaneously collect the external parameters and internal parameters of underground pipelines, and analyzes whether the underground pipelines are healthy based on the internal parameters and external parameters, thereby ensuring the accuracy of the judgment.

[0022] 4. When the underground pipeline is unhealthy, the present invention analyzes the risk level of the underground pipeline, analyzes the maintenance level of each maintenance master according to the risk level of the underground pipeline and the historical maintenance effect of each maintenance master, and compares them, and selects the maintenance master with the highest maintenance level to repair the underground pipeline, thereby ensuring the maintenance effect of the underground pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0025] Figure 2 The figure is a schematic flow chart of the steps for implementing the method of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] See also Figure 1 As shown, the present invention provides an automated detection and health assessment system for underground pipelines, comprising the following modules: a data acquisition module, a data analysis module, a program formulation module, an early warning terminal, and a database.

[0028] The data acquisition module is connected to the data analysis module, the data analysis module is connected to the program formulation module, the early warning terminal is connected to the data analysis module, and the database is connected to the data analysis module and the program formulation module.

[0029] The data acquisition module is used by the intelligent robot to collect various external parameters and internal parameters of the underground pipeline according to the planned driving path.

[0030] In a specific embodiment, the data acquisition module has the following specific process: S11, using a high-definition camera to capture a panoramic image of the detection area, and obtaining the positions of each obstacle and underground pipeline in the panoramic image, automatically planning several driving routes based on the positions of each obstacle and underground pipeline, and obtaining the coordinates of each turning point on each driving route, the coordinates of each turning point of the underground pipeline, the radius of the buffer area of each turning point of the underground pipeline and the shooting distance of the high-definition camera installed on the intelligent robot, analyzing the priority coefficient of each driving route, and comparing them, selecting the driving route with the largest priority coefficient, and using this driving route as the optimal driving route.

[0031] It should be noted that the panoramic image is input into the deep learning model. The deep learning model identifies the underground pipelines and obstacles in the panoramic image based on the panoramic images learned historically, and outputs their locations.

[0032] It should also be noted that the obstacles include discarded concrete blocks, bricks and wood.

[0033] Among them, the turning point refers to the bending point of the underground pipeline and the turning point of the driving route. The radius of the buffer area of each turning point of the underground pipeline and the shooting distance of the high-definition camera installed on the intelligent robot are obtained from the database.

[0034] S12. Use two intelligent robots to collect data simultaneously. One of the intelligent robots is called an external robot, and the other is called an internal robot. The external robot collects the external parameters of the underground pipeline according to the optimal driving path, and the internal robot collects the internal parameters of the underground pipeline according to the preset driving path.

[0035] It should be noted that the external parameters include temperature, displacement, and the number of defects on the outer wall of the pipeline.

[0036] It should also be noted that the internal parameters include the pressure inside the pipeline and the number of defects on the inner wall of the pipeline.

[0037] S13. When the external robot collects the external parameters of the underground pipeline according to the optimal driving path, the high-definition camera mounted on the external robot collects the surrounding environment image of the external robot in real time, and obtains the position of each obstacle in the surrounding environment image, and determines whether there are obstacles on the optimal driving route. If so, the optimal driving route is adjusted according to the position of the obstacle.

[0038] It should be noted that the RTT algorithm is used to adjust the optimal driving route. The process is as follows: first, the position of the intelligent robot is obtained through the Beidou navigation device carried on the intelligent robot, and this position is used as the starting point. Then the end point is determined, and the driving range is planned according to the starting point and the end point. Secondly, several sampling points are randomly obtained within the driving range, and there are no obstacles between each sampling point and the starting point. After that, the distance between each sampling point and the starting point is compared, and the sampling point with the smallest distance to the starting point is selected and used as the starting point. The next sampling point is obtained according to the above method until the sampling point is the end point. Finally, the starting point, the end point and each sampling point are connected to form a new driving route.

[0039] In the above, the analysis of the priority coefficient of each driving route is carried out as follows: the coordinates of each turning point on each driving route, the coordinates of each turning point of the underground pipeline, the radius of the buffer area of each turning point of the underground pipeline, and the shooting distance of the high-definition camera installed on the intelligent robot are obtained, and the distance between each turning point on each driving route and the corresponding turning points of the underground pipeline is calculated, and this is called the distance between each turning point on each driving route and its corresponding turning point. Then: In the formula represents the distance between the bth turning point and its corresponding turning point on the ath driving route, B b represents the radius of the buffer zone of the b-th turning point of the underground pipeline, C represents the shooting distance of the high-definition camera installed on the intelligent robot, C ≥ B b , α a represents the priority coefficient of the a-th driving route, e represents a natural constant, a represents the number of each driving route, a=1,2,3,...,c, c represents the total number of driving routes, b represents the number of each turning point, b=1,2,3,...,d, d represents the total number of turning points, and a, c, b and d are all positive integers.

[0040] The data analysis module includes a health analysis unit and a damage speed analysis unit.

[0041] The health analysis unit is used to obtain various external parameters and internal parameters of the underground pipeline, analyze whether the underground pipeline is healthy, and if unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute a maintenance and protection module.

[0042] In a specific embodiment, the health analysis unit has the following specific process: S21, obtaining the temperature, displacement, internal pressure, defects of the outer wall of the pipeline, and defects of the inner wall of the pipeline, and calculating the health coefficient of the underground pipeline. If the health coefficient of the underground pipeline is 1, it means that the underground pipeline is healthy. If the health coefficient of the underground pipeline is 0, it means that the underground pipeline is unhealthy, and an early warning is issued at this time.

[0043] S22. When the underground pipeline is unhealthy, the risk return value of the underground pipeline is calculated based on the temperature, displacement, internal pressure, defects on the outer wall of the pipeline, and defects on the inner wall of the pipeline. If the risk return value of the underground pipeline is 1, it means that the risk level of the underground pipeline is high. If the risk return value of the underground pipeline is 0, it means that the risk level of the underground pipeline is low.

[0044] In the above description, the health factor of the underground pipeline is calculated as follows: the temperature, displacement, internal pressure, number of defects of each defect on the outer wall of the pipeline, and number of defects of each defect on the inner wall of the pipeline are obtained, and normalized. Then: Where D represents temperature, E represents displacement, G represents pressure inside the tube, and F f represents the number of defects of the fth defect on the outer wall of the pipeline, F′ f′ represents the number of defects of the f′th defect on the inner wall of the pipeline, D′ represents the temperature standard range, G′ represents the pressure standard range inside the pipeline, and w f Represents the weight coefficient of the fth defect on the outer wall of the pipeline, w′ f′ represents the weight coefficient of the f′th defect on the inner wall of the pipeline, β represents the health coefficient of the underground pipeline, represents the preset defect index threshold, f represents the number of each defect on the outer wall of the pipeline, f = 1, 2, 3, ..., g, g represents the total number of defects on the outer wall of the pipeline, f′ represents the number of each defect on the inner wall of the pipeline, f′ = 1, 2, 3, ..., g′, g′ represents the total number of defects on the outer wall of the pipeline, and f, g, f′ and g′ are all positive integers.

[0045] It should be noted that the standard temperature range and the standard pipe pressure range are set by the staff to determine whether the temperature and pipe pressure of the underground pipeline are normal.

[0046] It should also be noted that the number of defects on the outer wall of the underground pipeline and the number of defects on the inner wall of the pipeline in each healthy period in the history of the underground pipeline are obtained from the database, and the defect index of each healthy period in the history of the underground pipeline is calculated, and the average value is calculated, and the average value is used as the preset defect index threshold.

[0047] Among them, the weight coefficients of each defect on the outer wall of the pipeline and the weight coefficients of each defect on the inner wall of the pipeline are set by the staff according to the degree of impact of each defect on the outer wall of the pipeline and the weight coefficients of each defect on the inner wall of the pipeline on the health of the underground pipeline. The higher the degree of impact, the higher the weight coefficient is set, and the sum of the weight coefficients of each defect on the outer wall of the pipeline and the weight coefficients of each defect on the inner wall of the pipeline is 1.

[0048] It needs to be explained that the defects on the outer wall and the inner wall of the pipeline include corrosion, cracks, interface leakage and scaling.

[0049] In the above, the specific process of calculating the risk return value of the underground pipeline is as follows: the coordinates of each defect on the outer wall of the pipeline, the coordinates of each defect on the inner wall of the pipeline, and each key area of the underground pipeline are obtained, and whether each key area of the underground pipeline has defects is determined. Each key area with defects is called a damaged area. The temperature, displacement, pressure inside the pipe, the number of defects in each damaged area, and the total number of damaged areas are obtained and normalized. Then: Where H h represents the number of defects on the h-th damaged area, represents the preset risk factor threshold, h represents the number of each damaged area, h=1,2,3,...,i, i represents the total number of damaged locations, h and i are both positive integers, χ represents the risk return value of underground pipelines.

[0050] It should be noted that the key areas include the socket-and-spigot joints, pipe diameter change points and pipe diameter change points of each section of the underground pipeline.

[0051] It should also be noted that when the coordinates of each defect are obtained, if the coordinates of a defect are within a certain key area, it means that there is a defect in the key area.

[0052] The damage rate analysis unit block is used to obtain various environmental parameters of the underground pipeline when the underground pipeline is healthy, and analyze the damage rate of the underground pipeline in combination with various parameters of the underground pipeline. If the damage rate is fast, an early warning is issued and a maintenance and protection module is executed.

[0053] It should be noted that the parameters of underground pipelines include service life, pipe diameter, pipe length, pipe material, various external parameters and various internal parameters.

[0054] It should also be noted that the environmental parameters include soil moisture, soil pH, soil resistivity and temperature.

[0055] Among them, a capacitive soil moisture sensor mounted on the robot is used to obtain soil moisture, a glass electrode soil pH sensor is used to obtain soil pH, a four-electrode soil resistivity sensor is used to obtain soil resistivity, and a temperature sensor is used to obtain temperature.

[0056] In a specific embodiment, the damage rate analysis unit has the following specific process: S31, obtaining the various environmental parameters of the underground pipeline and the various parameters of the underground pipe in each historical healthy period of the underground pipeline from the database, and obtaining the various environmental parameters and various parameters of the underground pipeline at this time, analyzing the state similarity coefficient of the underground pipeline in each historical healthy period and the state of the underground pipeline at this time, and calling it the state similarity coefficient of each historical healthy period of the underground pipeline.

[0057] S32. Compare the status similarity coefficients of each historical healthy period of the underground pipeline, select the historical healthy period of the underground pipeline with the highest status similarity coefficient, and obtain the duration of the underground pipeline in the historical healthy period from the database. Use this duration as the healthy duration of the underground pipeline at this time and compare it with the preset duration threshold. If the healthy duration of the underground pipeline at this time is lower than the preset duration threshold, it means that the underground pipeline is damaged quickly. If the healthy duration of the underground pipeline at this time is higher than the preset duration threshold, it means that the underground pipeline is damaged slowly.

[0058] It should be noted that the preset time threshold is set by the staff based on the historical health status of the underground pipeline and is used to judge the damage speed of the underground pipeline.

[0059] In the above, the similarity coefficient between the status of the underground pipeline in each healthy period in history and the status of the underground pipeline at this time is analyzed. The specific process is as follows: the environmental parameters and parameters of the underground pipeline in each healthy period in history are obtained from the database, and the environmental parameters and parameters of the underground pipeline at this time are obtained. Then: Where I j Represents the jth environmental parameter value of the underground pipeline at this time, represents the jth environmental parameter value in the lth health period of the underground pipeline history, J m Represents the mth parameter value of the underground pipeline at this time, represents the mth parameter value in the lth healthy period of the underground pipeline history, δ l represents the similarity coefficient between the status of the lth healthy period in history and the status of the underground pipeline at this time, l represents the number of each good health status of the underground pipeline in history, l = 1, 2, 3, ..., p, p represents the total number of good health status of the underground pipeline in history, j represents the number of each environmental parameter, j = 1, 2, 3, ..., k, k represents the total number of environmental parameters, m represents the number of each parameter, m = 1, 2, 3, ..., n, n represents the total number of parameters, l, p, j, k, m and n are all positive integers.

[0060] The maintenance and protection module is used to perform maintenance and protection based on the information of the underground pipeline.

[0061] It should be noted that the information of underground pipelines includes risk return values, various environmental parameters, and various parameters of underground pipelines.

[0062] In a specific embodiment, the maintenance protection module has the following specific process: S41. When the underground pipeline is unhealthy, the risk return value of the underground pipeline during each maintenance by each maintenance master is obtained from the database, and compared with the risk return value of the underground pipeline at this time. If the risk return value of the underground pipeline during a certain maintenance by a maintenance master is the same as the risk return value of the underground pipeline at this time, then this maintenance is called target maintenance. In this way, the target maintenance of each maintenance master is obtained, and the usage time of the underground pipeline after each target maintenance is obtained, and input into the maintenance level model, and the maintenance level of each maintenance master is output. The maintenance level of each maintenance master is compared, and the maintenance master with the highest maintenance level is selected, and the maintenance master is notified to perform maintenance.

[0063] It should be noted that the maintenance level model: In the formula represents the time the p-th maintenance technician uses the underground pipeline after the q-th target maintenance. ε p represents the maintenance level of the p-th maintenance technician, p represents the number of each maintenance technician, p = 1, 2, 3, ..., s, s represents the total number of maintenance technicians, q represents the number of each target maintenance, q = 1, 2, 3, ..., r, r represents the total number of target maintenance, and p, q, s and r are all positive integers.

[0064] S42. When the underground pipeline is damaged quickly, the environmental parameters and parameters of the underground pipeline at this time are input into the deep learning model. The deep learning model outputs a pipeline protection plan based on the environmental parameters and parameters of the underground pipeline, and notifies the staff to protect the underground pipeline according to the pipeline protection plan.

[0065] It should be noted that the environmental parameters, parameters and protection methods of the underground pipelines in each historical protection plan are obtained and input into the established deep learning model. The deep learning model learns the environmental parameters of the underground pipelines and the relationship between the parameters and the protection methods based on the information input each time. After the learning is completed, the environmental parameters and parameters of the underground pipelines are input into the deep learning model. The deep learning model outputs a protection plan based on the learned environmental parameters and the relationship between the parameters and the protection methods, as well as the environmental parameters and parameters of the underground pipelines at this time.

[0066] The early warning terminal is used to issue an early warning when the underground pipeline is unhealthy or is rapidly damaged.

[0067] The database is used to store historical information of underground pipelines and information of each maintenance technician.

[0068] It should be noted that the historical information of underground pipelines includes historical risk return values, various environmental parameters and various parameters of underground pipelines in various historical health periods.

[0069] It should also be noted that the information of each maintenance master includes the risk return value of the underground pipeline during each maintenance and the length of time the underground pipeline is used after each maintenance.

[0070] See also Figure 2 As shown, the present invention provides an automated detection and health assessment method for underground pipelines, comprising the following steps: Step 1, data collection: the intelligent robot collects various external parameters and internal parameters of the underground pipeline according to the planned driving path.

[0071] Step 2: Analyze pipeline health: Obtain the external and internal parameters of the underground pipeline and analyze whether the underground pipeline is healthy. If it is unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute the maintenance and protection module.

[0072] Step 3: Analyze the damage rate: When the underground pipeline is healthy, obtain the various environmental parameters of the underground pipeline and analyze the damage rate of the underground pipeline in combination with the various parameters of the underground pipeline. If the damage rate is fast, issue an early warning and execute the maintenance and protection module.

[0073] Step 4: Maintenance and protection: Perform maintenance and protection based on the information of underground pipelines.

[0074] In the embodiment of the present invention, a robot collects various external and internal parameters of underground pipelines and determines whether the underground pipelines are healthy. If they are unhealthy, the risk level of the underground pipelines is analyzed, and early warning and repairs are performed at the same time. If they are healthy, the damage speed of the underground pipelines is analyzed. If the damage speed is fast, early warning and repairs are performed. During maintenance, the maintenance technician with the highest maintenance level is selected to perform the maintenance, thereby ensuring the efficiency of the inspection, the validity and integrity of the data, the accuracy of the judgment, and the maintenance effect of the underground pipelines.

[0075] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. An automated detection and health assessment system for underground pipelines, characterized in that: Includes the following modules: The data acquisition module is used by the intelligent robot to collect various external and internal parameters of the underground pipeline according to the planned driving path; The data analysis module includes a health analysis unit and a damage rate analysis unit: The health analysis unit is used to obtain various external and internal parameters of the underground pipeline, analyze whether the underground pipeline is healthy, and if unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute a maintenance and protection module; The damage rate analysis unit block is used to obtain various environmental parameters of the underground pipeline when the underground pipeline is healthy, and analyze the damage rate of the underground pipeline in combination with various parameters of the underground pipeline. If the damage rate is fast, an early warning is issued and a maintenance and protection module is executed; The maintenance and protection module is used to perform maintenance and protection based on the information of underground pipelines; The early warning terminal is used to issue early warnings when underground pipelines are unhealthy or are rapidly deteriorating; The database is used to store historical information of underground pipelines and information of each maintenance master.

2. The automated detection and health assessment system for underground pipelines according to claim 1, characterized in that: The data acquisition module has the following specific process: S11. Use a high-definition camera to capture a panoramic image of the inspection area, and obtain the locations of each obstacle and underground pipeline in the panoramic image. Automatically plan several driving routes based on the locations of each obstacle and underground pipeline, and obtain the coordinates of each turning point on each driving route, the coordinates of each turning point of each underground pipeline, the radius of the buffer area of each turning point of the underground pipeline, and the shooting distance of the high-definition camera installed on the intelligent robot. Analyze and compare the priority coefficients of each driving route, select the driving route with the largest priority coefficient, and determine the optimal driving route. S12. Using two intelligent robots to collect data simultaneously, one of which is called an external robot and the other is called an internal robot. The external robot collects external parameters of the underground pipeline along an optimal driving path, and the internal robot collects internal parameters of the underground pipeline along a preset driving path. S13. When the external robot collects the external parameters of the underground pipeline according to the optimal driving path, the high-definition camera mounted on the external robot collects the surrounding environment image of the external robot in real time, and obtains the position of each obstacle in the surrounding environment image, and determines whether there are obstacles on the optimal driving route. If so, the optimal driving route is adjusted according to the position of the obstacle.

3. The automated detection and health assessment system for underground pipelines according to claim 2, characterized in that: The specific process of analyzing the priority coefficient of each driving route is as follows: Obtain the coordinates of each turning point on each driving route, the coordinates of each turning point of each underground pipeline, the radius of the buffer area of each turning point of the underground pipeline, and the shooting distance of the high-definition camera installed on the intelligent robot, and calculate the distance between each turning point on each driving route and the corresponding turning points of the underground pipeline. This is called the distance between each turning point on each driving route and its corresponding turning point. Then: In the formula represents the distance between the bth turning point and its corresponding turning point on the ath driving route, B b represents the radius of the buffer zone of the b-th turning point of the underground pipeline, C represents the shooting distance of the high-definition camera installed on the intelligent robot, C ≥ B b , α a represents the priority coefficient of the a-th driving route, e represents a natural constant, a represents the number of each driving route, a=1,2,3,...,c, c represents the total number of driving routes, b represents the number of each turning point, b=1,2,3,...,d, d represents the total number of turning points, and a, c, b and d are all positive integers.

4. The automated detection and health assessment system for underground pipelines according to claim 1, characterized in that: The health analysis unit has the following specific process: S21. Obtain the temperature, displacement, internal pressure, and defects on the outer and inner walls of the underground pipelines, and calculate the health coefficient of the underground pipelines. If the health coefficient of the underground pipelines is 1, it indicates that the underground pipelines are healthy. If the health coefficient of the underground pipelines is 0, it indicates that the underground pipelines are unhealthy, and an early warning is issued. S22. When the underground pipeline is unhealthy, the risk return value of the underground pipeline is calculated based on the temperature, displacement, internal pressure, defects on the outer wall of the pipeline, and defects on the inner wall of the pipeline. If the risk return value of the underground pipeline is 1, it means that the risk level of the underground pipeline is high. If the risk return value of the underground pipeline is 0, it means that the risk level of the underground pipeline is low.

5. The automated detection and health assessment system for underground pipelines according to claim 4, characterized in that: The specific process of calculating the health factor of underground pipes is as follows: Obtain the temperature, displacement, internal pressure of the underground pipeline, the number of defects of each defect on the outer wall of the pipeline, and the number of defects of each defect on the inner wall of the pipeline, and perform normalization processing, then: Where D represents temperature, E represents displacement, G represents pressure inside the tube, and F f represents the number of defects of the fth defect on the outer wall of the pipeline, F f ″ represents the number of defects of the f′th defect on the inner wall of the pipeline, D′ represents the temperature standard range, G′ represents the pressure standard range inside the pipeline, w f Represents the weight coefficient of the fth defect on the outer wall of the pipeline, w′ f′ represents the weight coefficient of the f′th defect on the inner wall of the pipeline, β represents the health coefficient of the underground pipeline, represents the preset defect index threshold, f represents the number of each defect on the outer wall of the pipeline, f = 1, 2, 3, ..., g, g represents the total number of defects on the outer wall of the pipeline, f′ represents the number of each defect on the inner wall of the pipeline, f′ = 1, 2, 3, ..., g′, g′ represents the total number of defects on the outer wall of the pipeline, and f, g, f′ and g′ are all positive integers.

6. The automated detection and health assessment system for underground pipelines according to claim 5, characterized in that: The specific process of calculating the risk return value of underground pipelines is as follows: Obtain the coordinates of each defect on the outer wall of the pipeline, the coordinates of each defect on the inner wall of the pipeline, and each key area of the underground pipeline, and determine whether each key area of the underground pipeline has defects. The key areas with defects are called damaged areas. Obtain the temperature, displacement, pressure inside the pipe, the number of defects in each damaged area, and the total number of damaged areas, and perform normalization processing. Then: Where H h represents the number of defects on the h-th damaged area, represents the preset risk factor threshold, h represents the number of each damaged area, h=1,2,3,...,i, i represents the total number of damaged locations, h and i are both positive integers, χ represents the risk return value of underground pipelines.

7. The automated detection and health assessment system for underground pipelines according to claim 1, characterized in that: The damage speed analysis unit has the following specific process: S31. Obtaining from the database the environmental parameters and parameters of the underground pipeline during each historical healthy period of the underground pipeline, and obtaining the environmental parameters and parameters of the underground pipeline at this time, analyzing the similarity coefficient between the state of the underground pipeline during each historical healthy period and the state of the underground pipeline at this time, and referring to the similarity coefficient as the state similarity coefficient of each historical healthy period of the underground pipeline; S32. Compare the status similarity coefficients of each historical healthy period of the underground pipeline, select the historical healthy period of the underground pipeline with the highest status similarity coefficient, and obtain the duration of the underground pipeline in the historical healthy period from the database. Use this duration as the healthy duration of the underground pipeline at this time and compare it with the preset duration threshold. If the healthy duration of the underground pipeline at this time is lower than the preset duration threshold, it means that the underground pipeline is damaged quickly. If the healthy duration of the underground pipeline at this time is higher than the preset duration threshold, it means that the underground pipeline is damaged slowly.

8. The automated detection and health assessment system for underground pipelines according to claim 7, characterized in that: The specific process of analyzing the similarity coefficient between the status of the underground pipeline in each healthy period in history and the status of the underground pipeline at this time is as follows: Obtain the environmental parameters and parameters of the underground pipelines in each historical health period of the underground pipelines from the database, and obtain the environmental parameters and parameters of the underground pipelines at this time, then: Where I j Represents the jth environmental parameter value of the underground pipeline at this time, represents the jth environmental parameter value in the lth health period of the underground pipeline history, J m Represents the mth parameter value of the underground pipeline at this time, represents the mth parameter value in the lth healthy period of the underground pipeline history, δ l represents the similarity coefficient between the status of the lth healthy period in history and the status of the underground pipeline at this time, l represents the number of each good health status of the underground pipeline in history, l = 1, 2, 3, ..., p, p represents the total number of good health status of the underground pipeline in history, j represents the number of each environmental parameter, j = 1, 2, 3, ..., k, k represents the total number of environmental parameters, m represents the number of each parameter, m = 1, 2, 3, ..., n, n represents the total number of parameters, l, p, j, k, m and n are all positive integers.

9. The automated detection and health assessment system for underground pipelines according to claim 1, characterized in that: The specific process of the maintenance and protection module is as follows: S41. When the underground pipeline is unhealthy, the risk return value of the underground pipeline during each maintenance by each maintenance technician is obtained from the database and compared with the risk return value of the underground pipeline at this time. If the risk return value of the underground pipeline during a maintenance by a maintenance technician is the same as the risk return value of the underground pipeline at this time, then the maintenance is called the target maintenance. In this way, the target maintenance of each maintenance technician is obtained, and the usage time of the underground pipeline after each target maintenance is obtained. The maintenance level of each maintenance technician is output, and the maintenance level of each maintenance technician is compared. The maintenance technician with the highest maintenance level is selected and notified to perform the maintenance. S42. When the underground pipeline is damaged quickly, the environmental parameters and parameters of the underground pipeline at this time are input into the deep learning model. The deep learning model outputs a pipeline protection plan based on the environmental parameters and parameters of the underground pipeline, and notifies the staff to protect the underground pipeline according to the pipeline protection plan.

10. A method for implementing the automated detection and health assessment system for underground pipelines according to any one of claims 1 to 9, characterized in that: include: Step 1: Data collection: The intelligent robot collects the external and internal parameters of the underground pipeline according to the planned driving path; Step 2: Analyze pipeline health: Obtain the external and internal parameters of the underground pipeline to analyze whether the underground pipeline is healthy. If it is unhealthy, analyze the risk level of the underground pipeline, issue an early warning, and execute the maintenance and protection module; Step 3: Analyze the damage rate: When the underground pipeline is healthy, obtain the various environmental parameters of the underground pipeline and analyze the damage rate of the underground pipeline in combination with the various parameters of the underground pipeline. If the damage rate is fast, issue an early warning and execute the maintenance and protection module; Step 4: Maintenance and protection: Perform maintenance and protection based on the information of underground pipelines.

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