High-precision full-automatic AI pipeline detection system and method

Abstract

The invention discloses a high-precision full-automatic AI pipeline detection system and method, and belongs to the technical field of pipeline detection, and the high-precision full-automatic AI pipeline detection system comprises a data acquisition module, a data processing module, a pipeline detection module, an analysis management and control module and a data storage module. According to the invention, the problems of time and labor waste and low pipeline detection efficiency caused by semi-automatic inspection for operators in existing pipeline detection are solved, real-time pipeline data are collected and processed in a high-precision manner, high-precision pipeline characterization data are determined, and the pipeline characterization data are compared and detected based on standard pipeline data, so that the pipeline detection efficiency is improved. The method comprises the following steps: determining a full-automatic AI pipeline detection result, performing deep mining analysis on the full-automatic AI pipeline detection result based on a data mining technology, determining a pipeline intelligent management and control method, and performing intelligent management and control on the pipeline based on the pipeline intelligent management and control method, so that the pipeline detection is full-automatic, and the purpose of high-precision full-automatic AI detection of the pipeline can be achieved; time and labor are saved, and the pipeline detection efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline detection, and in particular to a high-precision fully-automated AI pipeline detection system and method. Background Art

[0002] A pipeline is a device connected by pipes, pipe connectors and valves for conveying gas, liquid or fluid with solid particles. Usually, the fluid flows from the high pressure part of the pipeline to the low pressure part after being pressurized by blowers, compressors, pumps and boilers. It can also be conveyed by the fluid's own pressure or gravity. Pipelines are widely used, mainly in water supply, drainage, heating, gas supply, long-distance transportation of oil and natural gas, agricultural irrigation, hydraulic engineering and various industrial devices.

[0003] When the pipeline is in use, it is necessary to conduct regular inspections on the pipeline to ensure the normal use of the pipeline. Existing pipeline inspections are mostly semi-automatic inspections by operators, which is time-consuming and labor-intensive, and the pipeline inspection efficiency is low. Summary of the invention

[0004] The purpose of the present invention is to provide a high-precision fully automated AI pipeline detection system and method. The pipeline detection is fully automated, which can achieve the purpose of high-precision fully automated AI pipeline detection, save time and labor, and improve pipeline detection efficiency, solving the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] High-precision fully automated AI pipeline inspection system, including:

[0007] The data acquisition module is used to collect real-time pipeline data. Based on a variety of sensors and AI smart cameras, various pipeline data of the pipeline in use are obtained in real time. Based on the various pipeline data obtained, the real-time pipeline data collected with high precision is determined;

[0008] The data processing module is used to process the collected pipeline real-time data, obtain the pipeline real-time data collected with high precision, and retrieve, group, sort and calculate the pipeline real-time data to determine the high-precision pipeline characterization data;

[0009] The pipeline detection module is used to perform fully automated AI detection on pipelines, obtain high-precision pipeline characterization data, index and retrieve pipeline standard data corresponding to the pipeline characterization data, perform comparative detection on the pipeline characterization data based on the pipeline standard data, and determine the fully automated AI pipeline detection results;

[0010] The analysis and control module is used to analyze the fully automated AI pipeline detection results and intelligently control the pipeline. The fully automated AI pipeline detection results are obtained. Based on data mining technology, the fully automated AI pipeline detection results are deeply mined and analyzed to determine the pipeline intelligent control method. Based on the pipeline intelligent control method, the pipeline is intelligently controlled.

[0011] The data storage module is used to store high-precision collected real-time pipeline data and various pipeline standard data, providing a reference and guidance basis for high-precision fully automated AI pipeline detection.

[0012] Preferably, the data acquisition module includes:

[0013] AI smart camera, used to obtain visual data of the pipeline when it is in use. It is installed around the pipeline and surrounds the pipeline in all directions to obtain visual data of the pipeline;

[0014] Ultrasonic flowmeter, used to obtain pipeline flow data when the pipeline is in use. It is installed on the pipeline and obtains pipeline flow data based on the fact that the propagation speed of ultrasonic waves in the flowing medium is equal to the vector sum of the average flow velocity of the measured medium and the speed of the sound wave in the stationary medium;

[0015] The pressure sensor is used to obtain the pipeline pressure data when the pipeline is in use. It is installed on the pipeline and converts the pressure signal into an available output electrical signal based on the pressure signal it senses and according to a certain rule, thereby obtaining the pipeline pressure data;

[0016] The temperature sensor is used to obtain the temperature data of the pipeline when the pipeline is in use. It is installed on the pipeline and converts the sensed temperature signal into a usable output signal to obtain the pipeline temperature data.

[0017] Preferably, the data processing module includes:

[0018] Data retrieval unit, used to retrieve pipeline real-time data collected with high precision;

[0019] Acquire the pipeline real-time data collected with high precision, retrieve the pipeline real-time data collected with high precision based on the sequential retrieval method, filter out the pipeline real-time data that is useless for high-precision fully automated AI pipeline detection, and determine the pipeline real-time data that is useful for high-precision fully automated AI pipeline detection;

[0020] A data grouping unit, used for grouping the retrieved pipeline real-time data;

[0021] Obtain pipeline real-time data that is useful for high-precision fully automated AI pipeline detection, group the pipeline real-time data based on the principle of mutual exclusivity, determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group;

[0022] A data sorting unit, used for sorting the grouped pipeline real-time data;

[0023] Acquire pipeline real-time data groups with different attributes, and sort the pipeline real-time data placed in each group to determine pipeline real-time data with a certain order;

[0024] A data calculation unit, used for calculating the sorted pipeline real-time data;

[0025] Acquire real-time pipeline data with a certain order, perform edge computing on the real-time pipeline data, and determine high-precision pipeline characterization data.

[0026] Preferably, the pipeline detection module includes:

[0027] A data indexing unit, used to index pipeline standard data;

[0028] Acquire high-precision pipeline characterization data, and based on the pipeline characterization data, index pipeline standard data corresponding to the pipeline characterization data from various stored pipeline standard data;

[0029] A data retrieval unit, used to retrieve pipeline standard data;

[0030] Obtain the indexed pipeline standard data corresponding to the pipeline characterization data, and retrieve the pipeline standard data;

[0031] Comparative detection unit, used for fully automated AI detection of pipelines;

[0032] Obtain pipeline standard data and pipeline characterization data, perform comparative detection on pipeline characterization data based on pipeline standard data, and determine fully automated AI pipeline detection results.

[0033] Preferably, the analysis and control module includes:

[0034] Mining and analysis unit, used to analyze the detection results of the fully automated AI pipeline;

[0035] Obtain the fully automated AI pipeline inspection results, conduct in-depth mining and analysis on the fully automated AI pipeline inspection results based on data mining technology, and determine the intelligent pipeline management and control method;

[0036] Intelligent management and control unit, used for intelligent management and control of pipelines;

[0037] Obtain the pipeline intelligent control method, and perform intelligent control on the pipeline based on the pipeline intelligent control method.

[0038] Preferably, the data storage module includes:

[0039] Real-time storage unit, used to store high-precision collected pipeline real-time data, providing support for real-time viewing of pipeline real-time data;

[0040] The standard storage unit is used to store various pipeline standard data, providing a reference and guidance basis for high-precision fully automated AI pipeline detection.

[0041] According to another aspect of the present invention, a high-precision fully-automated AI pipeline detection method is provided, which is implemented based on the high-precision fully-automated AI pipeline detection system as described above, and includes the following steps:

[0042] S1: various pipeline data of the pipeline in use are acquired in real time through the data acquisition module, and high-precision real-time pipeline data acquired based on the acquired various pipeline data are determined, and the high-precision real-time pipeline data acquired are retrieved, grouped, sorted and calculated through the data processing module to determine high-precision pipeline characterization data;

[0043] S2: Perform fully automated AI inspection on the pipeline through the pipeline inspection module to obtain high-precision pipeline characterization data, index and retrieve the pipeline standard data corresponding to the pipeline characterization data, and perform comparative inspection on the pipeline characterization data based on the pipeline standard data to determine the fully automated AI pipeline inspection results;

[0044] S3: Analyze the fully automated AI pipeline detection results through the analysis and control module and intelligently control the pipeline, obtain the fully automated AI pipeline detection results, conduct in-depth mining and analysis on the fully automated AI pipeline detection results based on data mining technology, determine the pipeline intelligent control method, and intelligently control the pipeline based on the pipeline intelligent control method.

[0045] Preferably, in S1, the real-time pipeline data collected with high precision is retrieved, grouped, sorted and calculated by the data processing module to determine the high-precision pipeline characterization data, and the following operations are performed:

[0046] Obtain high-precision real-time pipeline data;

[0047] Based on the sequential retrieval method, the real-time pipeline data collected with high precision is retrieved;

[0048] Filter out the real-time pipeline data that is useless for high-precision fully automated AI pipeline detection, and determine the real-time pipeline data that is useful for high-precision fully automated AI pipeline detection;

[0049] Based on the principle of mutual exclusivity, the pipeline real-time data that is determined to be useful for high-precision fully automated AI pipeline detection is grouped;

[0050] Determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group;

[0051] Obtain pipeline real-time data groups with different attributes;

[0052] Sort the pipeline real-time data placed in each group to determine the pipeline real-time data with a certain order;

[0053] Acquire real-time pipeline data with a certain order, perform edge computing on the real-time pipeline data, and determine high-precision pipeline characterization data.

[0054] Preferably, in S2, the pipeline is subjected to fully automated AI detection by the pipeline detection module, and the following operations are performed:

[0055] Obtain high-precision pipeline characterization data;

[0056] Based on the pipeline characterization data, pipeline standard data corresponding to the pipeline characterization data is indexed from various stored pipeline standard data;

[0057] Retrieve the indexed pipeline standard data;

[0058] Based on pipeline standard data, the pipeline characterization data is compared and tested to determine the fully automated AI pipeline inspection results;

[0059] If the pipeline characterization data is within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be qualified for the pipeline inspection;

[0060] In the case where the pipeline characterization data is not within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be a pipeline inspection failure.

[0061] Preferably, in S3, the fully automated AI pipeline detection results are analyzed and the pipeline is intelligently controlled by the analysis and control module, and the following operations are performed:

[0062] Get fully automated AI pipeline detection results;

[0063] Based on data mining technology, the fully automated AI pipeline inspection results are deeply mined and analyzed to determine the intelligent pipeline management and control method;

[0064] If the pipeline inspection is qualified, the determined pipeline intelligent management and control method is to continue to carry out high-precision fully automated AI inspection of the pipeline;

[0065] In the case of pipeline inspection failure, the determined pipeline intelligent management and control method is to respond to the pipeline alarm in time, and upload the pipeline fault situation to the pipeline maintenance personnel, guide the pipeline maintenance personnel to go and repair the pipeline fault.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] The high-precision fully-automated AI pipeline detection system and method of the present invention acquires various pipeline data of the pipeline in use in real time based on multiple sensors and AI smart cameras, determines the pipeline real-time data collected with high precision based on the acquired various pipeline data, and retrieves, groups, sorts and calculates the pipeline real-time data collected with high precision to determine the high-precision pipeline characterization data, performs comparative detection on the pipeline characterization data based on pipeline standard data, determines the fully-automated AI pipeline detection result, performs in-depth mining and analysis on the fully-automated AI pipeline detection result based on data mining technology, determines the pipeline intelligent management and control method, and performs intelligent management and control on the pipeline based on the pipeline intelligent management and control method. The pipeline detection is fully automated, which can achieve the purpose of high-precision fully-automated AI detection of the pipeline, save time and labor, and improve the efficiency of pipeline detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is a module schematic diagram of the high-precision fully automated AI pipeline detection system of the present invention;

[0069] Figure 2 Flow chart of the high-precision fully-automated AI pipeline detection method of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0071] In order to solve the existing pipeline inspection, most operators perform semi-automatic inspections, which is time-consuming and labor-intensive, and the pipeline inspection efficiency is low. Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0072] The high-precision fully-automated AI pipeline inspection system includes data acquisition module, data processing module, pipeline inspection module, analysis and control module and data storage module.

[0073] Among them, the data acquisition module is used to collect real-time pipeline data;

[0074] Based on multiple sensors and AI smart cameras, various pipeline data of the pipeline in use status are obtained in real time, and based on the various pipeline data obtained, high-precision real-time pipeline data is determined.

[0075] It should be noted that the data acquisition module includes:

[0076] AI smart camera, used to obtain visual data of the pipeline when it is in use. It is installed around the pipeline and surrounds the pipeline in all directions to obtain visual data of the pipeline;

[0077] Ultrasonic flowmeter, used to obtain pipeline flow data when the pipeline is in use. It is installed on the pipeline and obtains pipeline flow data based on the fact that the propagation speed of ultrasonic waves in the flowing medium is equal to the vector sum of the average flow velocity of the measured medium and the speed of the sound wave in the stationary medium;

[0078] The pressure sensor is used to obtain the pipeline pressure data when the pipeline is in use. It is installed on the pipeline and converts the pressure signal into an available output electrical signal based on the pressure signal it senses and according to a certain rule, thereby obtaining the pipeline pressure data;

[0079] The temperature sensor is used to obtain the temperature data of the pipeline when the pipeline is in use. It is installed on the pipeline and converts the sensed temperature signal into a usable output signal to obtain the pipeline temperature data.

[0080] Among them, the data processing module is used to process the collected real-time pipeline data;

[0081] Acquire high-precision real-time pipeline data, and retrieve, group, sort and calculate the real-time pipeline data to determine high-precision pipeline characterization data.

[0082] It should be noted that the data processing module includes:

[0083] Data retrieval unit, used to retrieve pipeline real-time data collected with high precision;

[0084] Acquire the pipeline real-time data collected with high precision, retrieve the pipeline real-time data collected with high precision based on the sequential retrieval method, filter out the pipeline real-time data that is useless for high-precision fully automated AI pipeline detection, and determine the pipeline real-time data that is useful for high-precision fully automated AI pipeline detection;

[0085] A data grouping unit, used for grouping the retrieved pipeline real-time data;

[0086] Obtain pipeline real-time data that is useful for high-precision fully automated AI pipeline detection, group the pipeline real-time data based on the principle of mutual exclusivity, determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group;

[0087] A data sorting unit, used for sorting the grouped pipeline real-time data;

[0088] Acquire pipeline real-time data groups with different attributes, and sort the pipeline real-time data placed in each group to determine pipeline real-time data with a certain order;

[0089] A data calculation unit, used for calculating the sorted pipeline real-time data;

[0090] Acquire real-time pipeline data with a certain order, perform edge computing on the real-time pipeline data, and determine high-precision pipeline characterization data.

[0091] Among them, the pipeline detection module is used to perform fully automated AI detection of pipelines;

[0092] Acquire high-precision pipeline characterization data, index and retrieve the pipeline standard data corresponding to the pipeline characterization data, perform comparative detection on the pipeline characterization data based on the pipeline standard data, and determine the fully automated AI pipeline detection results.

[0093] It should be noted that the pipeline detection module includes:

[0094] A data indexing unit, used to index pipeline standard data;

[0095] Acquire high-precision pipeline characterization data, and based on the pipeline characterization data, index pipeline standard data corresponding to the pipeline characterization data from various stored pipeline standard data;

[0096] A data retrieval unit, used to retrieve pipeline standard data;

[0097] Obtain the indexed pipeline standard data corresponding to the pipeline characterization data, and retrieve the pipeline standard data;

[0098] Comparative detection unit, used for fully automated AI detection of pipelines;

[0099] Obtain pipeline standard data and pipeline characterization data, perform comparative detection on pipeline characterization data based on pipeline standard data, and determine fully automated AI pipeline detection results.

[0100] Among them, the analysis and control module is used to analyze the fully automated AI pipeline detection results and intelligently control the pipeline;

[0101] Obtain the fully automated AI pipeline detection results, conduct in-depth mining and analysis on the fully automated AI pipeline detection results based on data mining technology, determine the pipeline intelligent management and control method, and perform intelligent management and control of the pipeline based on the pipeline intelligent management and control method.

[0102] It should be noted that the analysis and control module includes:

[0103] Mining and analysis unit, used to analyze the detection results of the fully automated AI pipeline;

[0104] Obtain the fully automated AI pipeline inspection results, conduct in-depth mining and analysis on the fully automated AI pipeline inspection results based on data mining technology, and determine the intelligent pipeline management and control method;

[0105] Intelligent management and control unit, used for intelligent management and control of pipelines;

[0106] Obtain the pipeline intelligent control method, and perform intelligent control on the pipeline based on the pipeline intelligent control method.

[0107] Among them, the data storage module is used to store high-precision collected real-time pipeline data and various pipeline standard data, providing a reference and guidance basis for high-precision fully automated AI pipeline detection.

[0108] It should be noted that the data storage module includes:

[0109] Real-time storage unit, used to store high-precision collected pipeline real-time data, providing support for real-time viewing of pipeline real-time data;

[0110] The standard storage unit is used to store various pipeline standard data, providing a reference and guidance basis for high-precision fully automated AI pipeline detection.

[0111] In order to better demonstrate the high-precision fully automated AI pipeline detection process, this embodiment now proposes a high-precision fully automated AI pipeline detection method, which is implemented based on the high-precision fully automated AI pipeline detection system as described above, and includes the following steps:

[0112] S1: various pipeline data of the pipeline in use are acquired in real time through the data acquisition module, and high-precision real-time pipeline data acquired based on the acquired various pipeline data are determined, and the high-precision real-time pipeline data acquired are retrieved, grouped, sorted and calculated through the data processing module to determine high-precision pipeline characterization data;

[0113] It should be noted that in S1, the real-time pipeline data collected with high precision is retrieved, grouped, sorted and calculated by the data processing module to determine the high-precision pipeline characterization data, and the following operations are performed:

[0114] Obtain high-precision real-time pipeline data;

[0115] Based on the sequential retrieval method, the real-time pipeline data collected with high precision is retrieved;

[0116] Filter out the real-time pipeline data that is useless for high-precision fully automated AI pipeline detection, and determine the real-time pipeline data that is useful for high-precision fully automated AI pipeline detection;

[0117] Based on the principle of mutual exclusivity, the pipeline real-time data that is determined to be useful for high-precision fully automated AI pipeline detection is grouped;

[0118] Determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group;

[0119] Obtain pipeline real-time data groups with different attributes;

[0120] Sort the pipeline real-time data placed in each group to determine the pipeline real-time data with a certain order;

[0121] Acquire real-time pipeline data with a certain order, perform edge computing on the real-time pipeline data, and determine high-precision pipeline characterization data.

[0122] S2: Perform fully automated AI inspection on the pipeline through the pipeline inspection module to obtain high-precision pipeline characterization data, index and retrieve the pipeline standard data corresponding to the pipeline characterization data, and perform comparative inspection on the pipeline characterization data based on the pipeline standard data to determine the fully automated AI pipeline inspection results;

[0123] It should be noted that in S2, the pipeline detection module performs fully automated AI detection of the pipeline and performs the following operations:

[0124] Obtain high-precision pipeline characterization data;

[0125] Based on the pipeline characterization data, pipeline standard data corresponding to the pipeline characterization data is indexed from various stored pipeline standard data;

[0126] Retrieve the indexed pipeline standard data;

[0127] Based on pipeline standard data, the pipeline characterization data is compared and tested to determine the fully automated AI pipeline inspection results;

[0128] If the pipeline characterization data is within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be qualified for the pipeline inspection;

[0129] In the case where the pipeline characterization data is not within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be a pipeline inspection failure.

[0130] S3: Analyze the fully automated AI pipeline detection results through the analysis and control module and intelligently control the pipeline, obtain the fully automated AI pipeline detection results, conduct in-depth mining and analysis on the fully automated AI pipeline detection results based on data mining technology, determine the pipeline intelligent control method, and intelligently control the pipeline based on the pipeline intelligent control method.

[0131] It should be noted that in S3, the analysis and control module analyzes the fully automated AI pipeline detection results and intelligently controls the pipeline, performing the following operations:

[0132] Get fully automated AI pipeline detection results;

[0133] Based on data mining technology, the fully automated AI pipeline inspection results are deeply mined and analyzed to determine the intelligent pipeline management and control method;

[0134] If the pipeline inspection is qualified, the determined pipeline intelligent management and control method is to continue to carry out high-precision fully automated AI inspection of the pipeline;

[0135] In the case of pipeline inspection failure, the determined pipeline intelligent management and control method is to respond to the pipeline alarm in time, and upload the pipeline fault situation to the pipeline maintenance personnel, guide the pipeline maintenance personnel to go and repair the pipeline fault.

[0136] A high-precision fully automated AI pipeline detection method is now used to perform high-precision fully automated AI detection on pipelines. The high-precision fully automated AI pipeline detection results are shown in Table 1:

[0137] Table 1: High-precision fully automated AI pipeline detection results

[0138]

[0139] Therefore, based on the pipeline standard data, the pipeline characterization data is compared and tested to determine the fully automated AI pipeline detection results. Based on data mining technology, the fully automated AI pipeline detection results are deeply mined and analyzed to determine the pipeline intelligent management and control method. Based on the pipeline intelligent management and control method, the pipeline is intelligently managed and controlled. The pipeline detection is fully automated, which can achieve the purpose of high-precision fully automated AI detection of the pipeline, save time and effort, and improve the efficiency of pipeline detection.

[0140] In summary, the high-precision fully-automated AI pipeline detection system and method of the present invention obtains various pipeline data of the pipeline in use in real time based on multiple sensors and AI smart cameras, determines the high-precision collected pipeline real-time data based on the various pipeline data obtained, and retrieves, groups, sorts and calculates the high-precision collected pipeline real-time data to determine the high-precision pipeline characterization data, compares and detects the pipeline characterization data based on the pipeline standard data, determines the fully-automated AI pipeline detection results, and conducts in-depth mining and analysis of the fully-automated AI pipeline detection results based on data mining technology to determine the pipeline intelligent management and control method, and intelligently manages the pipeline based on the pipeline intelligent management and control method. The pipeline detection is fully automated, which can achieve the purpose of high-precision fully-automated AI detection of the pipeline, save time and effort, and improve the efficiency of pipeline detection.

[0141] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0142] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. High-precision fully automated AI pipeline inspection system, characterized by: include: The data acquisition module is used to collect real-time pipeline data. Based on a variety of sensors and AI smart cameras, various pipeline data of the pipeline in use are obtained in real time. Based on the various pipeline data obtained, the real-time pipeline data collected with high precision is determined; The data processing module is used to process the collected pipeline real-time data, obtain the pipeline real-time data collected with high precision, and retrieve, group, sort and calculate the pipeline real-time data to determine the high-precision pipeline characterization data; The pipeline detection module is used to perform fully automated AI detection on pipelines, obtain high-precision pipeline characterization data, index and retrieve pipeline standard data corresponding to the pipeline characterization data, perform comparative detection on the pipeline characterization data based on the pipeline standard data, and determine the fully automated AI pipeline detection results; The analysis and control module is used to analyze the fully automated AI pipeline detection results and intelligently control the pipeline. The fully automated AI pipeline detection results are obtained. Based on data mining technology, the fully automated AI pipeline detection results are deeply mined and analyzed to determine the pipeline intelligent control method. Based on the pipeline intelligent control method, the pipeline is intelligently controlled. The data storage module is used to store high-precision collected real-time pipeline data and various pipeline standard data.

2. The high-precision fully automated AI pipeline detection system according to claim 1 is characterized in that: The data acquisition module comprises: AI smart camera, used to obtain visual data of the pipeline when it is in use. The AI ​​smart camera is installed around the pipeline and surrounds the pipeline in all directions to obtain visual data of the pipeline; Ultrasonic flowmeter, used to obtain pipeline flow data when the pipeline is in use. The ultrasonic flowmeter is installed on the pipeline and obtains pipeline flow data based on the fact that the propagation speed of ultrasonic waves in the flowing medium is equal to the vector sum of the average flow velocity of the measured medium and the speed of the sound wave in the stationary medium; The pressure sensor is used to obtain the pipeline pressure data when the pipeline is in use. The pressure sensor is installed on the pipeline and converts the pressure signal into a usable output electrical signal based on the pressure signal it senses to obtain the pipeline pressure data; The temperature sensor is used to obtain the temperature data of the pipeline when the pipeline is in use. The temperature sensor is installed on the pipeline and obtains the pipeline temperature data based on the sensed temperature signal and converts the temperature signal into a usable output signal.

3. The high-precision fully automated AI pipeline detection system according to claim 2 is characterized in that: The data processing module comprises: Data retrieval unit, used to retrieve pipeline real-time data collected with high precision; Acquire the pipeline real-time data collected with high precision, retrieve the pipeline real-time data collected with high precision based on the sequential retrieval method, filter out the pipeline real-time data that is useless for high-precision fully automated AI pipeline detection, and determine the pipeline real-time data that is useful for high-precision fully automated AI pipeline detection; A data grouping unit, used for grouping the retrieved pipeline real-time data; Obtain pipeline real-time data that is useful for high-precision fully automated AI pipeline detection, group the pipeline real-time data based on the principle of mutual exclusivity, determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group; A data sorting unit, used for sorting the grouped pipeline real-time data; Acquire pipeline real-time data groups with different attributes, and sort the pipeline real-time data placed in each group to determine the pipeline real-time data; A data calculation unit, used for calculating the sorted pipeline real-time data; Acquire real-time pipeline data and perform edge computing on the real-time pipeline data to determine high-precision pipeline characterization data.

4. The high-precision fully automated AI pipeline detection system according to claim 3 is characterized in that: The pipeline detection module comprises: A data indexing unit, used to index pipeline standard data; Acquire high-precision pipeline characterization data, and based on the pipeline characterization data, index pipeline standard data corresponding to the pipeline characterization data from various stored pipeline standard data; A data retrieval unit, used to retrieve pipeline standard data; Obtain the indexed pipeline standard data corresponding to the pipeline characterization data, and retrieve the pipeline standard data; Comparative detection unit, used for fully automated AI detection of pipelines; Obtain pipeline standard data and pipeline characterization data, perform comparative detection on pipeline characterization data based on pipeline standard data, and determine fully automated AI pipeline detection results.

5. The high-precision fully automated AI pipeline detection system according to claim 4 is characterized in that: The analysis and control module includes: Mining and analysis unit, used to analyze the detection results of the fully automated AI pipeline; Obtain the fully automated AI pipeline inspection results, conduct in-depth mining and analysis on the fully automated AI pipeline inspection results based on data mining technology, and determine the intelligent pipeline management and control method; Intelligent management and control unit, used for intelligent management and control of pipelines; Obtain the pipeline intelligent control method, and perform intelligent control on the pipeline based on the pipeline intelligent control method.

6. The high-precision fully automated AI pipeline detection system according to claim 5 is characterized in that: The data storage module comprises: Real-time storage unit, used to store high-precision collected pipeline real-time data, providing support for real-time viewing of pipeline real-time data; The standard storage unit is used to store various pipeline standard data, providing a reference and guidance basis for high-precision fully automated AI pipeline detection.

7. A high-precision fully automated AI pipeline detection method, implemented based on the high-precision fully automated AI pipeline detection system according to claim 6, characterized in that: The steps include: S1: various pipeline data of the pipeline in use are acquired in real time through the data acquisition module, and high-precision real-time pipeline data acquired based on the acquired various pipeline data are determined, and the high-precision real-time pipeline data acquired are retrieved, grouped, sorted and calculated through the data processing module to determine high-precision pipeline characterization data; S2: Perform fully automated AI inspection on the pipeline through the pipeline inspection module to obtain high-precision pipeline characterization data, index and retrieve the pipeline standard data corresponding to the pipeline characterization data, and perform comparative inspection on the pipeline characterization data based on the pipeline standard data to determine the fully automated AI pipeline inspection results; S3: Analyze the fully automated AI pipeline detection results through the analysis and control module and intelligently control the pipeline, obtain the fully automated AI pipeline detection results, conduct in-depth mining and analysis on the fully automated AI pipeline detection results based on data mining technology, determine the pipeline intelligent control method, and intelligently control the pipeline based on the pipeline intelligent control method.

8. The high-precision fully automated AI pipeline detection method according to claim 7, characterized in that: In S1, the real-time pipeline data collected with high precision is retrieved, grouped, sorted and calculated by the data processing module to determine the high-precision pipeline characterization data, and the following operations are performed: Obtain high-precision real-time pipeline data; Based on the sequential retrieval method, the real-time pipeline data collected with high precision is retrieved; Filter out the real-time pipeline data that is useless for high-precision fully automated AI pipeline detection, and determine the real-time pipeline data that is useful for high-precision fully automated AI pipeline detection; Based on the principle of mutual exclusivity, the pipeline real-time data that is determined to be useful for high-precision fully automated AI pipeline detection is grouped; Determine pipeline real-time data groups with different attributes, and place pipeline real-time data with the same attributes in each group; Obtain pipeline real-time data groups with different attributes; Sort the pipeline real-time data placed in each group to determine the pipeline real-time data with a certain order; Acquire real-time pipeline data and perform edge computing on the real-time pipeline data to determine high-precision pipeline characterization data.

9. The high-precision fully automated AI pipeline detection method according to claim 8, characterized in that: In S2, the pipeline is fully automatically inspected by AI through the pipeline inspection module, and the following operations are performed: Obtain high-precision pipeline characterization data; Based on the pipeline characterization data, pipeline standard data corresponding to the pipeline characterization data is indexed from various stored pipeline standard data; Retrieve the indexed pipeline standard data; Based on pipeline standard data, the pipeline characterization data is compared and tested to determine the fully automated AI pipeline inspection results; If the pipeline characterization data is within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be qualified pipeline inspection; In the case where the pipeline characterization data is not within the pipeline standard data range, the fully automated AI pipeline inspection result is determined to be a pipeline inspection failure.

10. The high-precision fully automated AI pipeline detection method according to claim 9, characterized in that: In S3, the fully automated AI pipeline detection results are analyzed and the pipeline is intelligently controlled through the analysis and control module, and the following operations are performed: Get fully automated AI pipeline detection results; Based on data mining technology, the fully automated AI pipeline inspection results are deeply mined and analyzed to determine the intelligent pipeline management and control method; If the pipeline inspection is qualified, the determined pipeline intelligent management and control method is to continue to carry out high-precision fully automated AI inspection of the pipeline; In the case of pipeline inspection failure, the determined pipeline intelligent management and control method is to respond to the pipeline alarm in time, and upload the pipeline fault situation to the pipeline maintenance personnel, guide the pipeline maintenance personnel to go and repair the pipeline fault.

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