Pressure pipeline inspection and detection digital system based on Internet of Things

Abstract

The invention provides a pressure pipeline inspection and detection digital system based on the Internet of Things. Comprises: an axonometric mapping module for drawing a three-dimensional model by using an axonometric mapping instrument to obtain an initial axonometric map; comprising an automatic drawing mode and a manual drawing mode. And the positioning module is used for collecting real-time geographic position information of the pipeline and marking and recording the real-time geographic position information in the initial axonometric map to obtain a complete axonometric map. And the data processing module is used for acquiring, storing and analyzing actual detection data of the pipeline. And the information association module is used for associating the macroscopic inspection information with the safety accessory information of the pipeline on the complete axonometric map. The detection report module is used for generating a detection record and a detection report; an interaction terminal, a tablet computer and a two-dimensional code printer. According to the invention, data can be automatically collected, processed and analyzed, personal errors are reduced, and the working efficiency of inspection work is improved; and digital management of a pressure pipeline inspection and detection process is realized.

Description

Technical Field

[0001] The present invention relates to the field of industrial detection technology, and in particular to a pressure pipeline inspection and detection digital system based on the Internet of Things. Background Art

[0002] Pressure pipelines are one of the eight types of special equipment. They generally transmit high-temperature, high-pressure, flammable and explosive media. Once an accident occurs, it will pose a serious threat to people's lives and property. Pressure pipeline safety management is a systematic project, including the company's own daily maintenance management, as well as the Chinese government's regular inspection system for pressure pipelines. Facts have proved that regular inspections of pressure pipelines can effectively discover hidden dangers that affect the safe operation of pipelines.

[0003] At present, the whole process of pressure pipeline inspection and testing is generally divided into two stages. The first stage is the on-site inspection stage, where inspectors conduct pipeline inspections, manually draw pipeline axonometric diagrams, and record relevant inspection and testing data on paper and pen. The second stage is to issue an inspection report based on the on-site inspection records, using computers to draw axonometric diagrams through drawing software (such as Auto CAD), and manually enter inspection data into the report system. This traditional approach not only has low work efficiency, but also has human errors such as misrecording and omission of measurement data, which affects the quality and process of the entire inspection. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a digital pressure pipeline inspection and testing system based on the Internet of Things, which effectively solves the repetitive tasks of multiple drawing of axonometric drawings, repeated searching of inspection positions, and manual entry of inspection and testing data in pipeline inspection and testing, and can automatically collect, process and analyze data, reduce human errors, and improve the efficiency of inspection work; it realizes the digital management of the pressure pipeline inspection and testing process.

[0005] To achieve the above-mentioned purpose, the present invention provides the following solution: a digital pressure pipeline inspection and detection system based on the Internet of Things, comprising:

[0006] An axonometric mapping module is used to obtain 3D position information of the pipeline and the surrounding environment using an axonometric mapping surveyor and draw a three-dimensional model to obtain an initial axonometric map; the axonometric mapping module includes two modes: automatic drawing and manual drawing;

[0007] A positioning module, used to collect real-time geographical location information of the pipeline using a GPS locator and a camera and mark and record it in the initial axonometric drawing to obtain a complete axonometric drawing;

[0008] A data processing module is used to obtain the actual detection data of the pipeline using the detection instrument and store and analyze it;

[0009] an information association module for associating macroscopic inspection information with safety attachment information of the pipeline on the complete axonometric drawing;

[0010] A test report module, for generating a test record in combination with the actual test data, the macro-inspection information and the safety attachment information, and transmitting the test record to an electronic reporting system to generate a test report;

[0011] An interactive terminal is used to run the axonometric mapping module, the positioning module, the data processing module, the information association module and the detection report module, and the interactive terminal includes a tablet computer and a QR code printer.

[0012] Optionally, in the axonometric mapping module:

[0013] The automatic drawing mode is used to control the axonometric mapping surveying instrument to automatically draw the axonometric drawing through the tablet computer;

[0014] The manual drawing mode is used to display the scanned data of the axonometric mapping instrument on the tablet computer and perform manual adjustments, input data or check point marking operations, and automatically save and generate the axonometric map after manual operations.

[0015] Optionally, the positioning module includes:

[0016] A position marking unit, used to receive the coordinate data of the pipeline and other important positions obtained by the GPS locator in real time and match them with the axonometric drawing, so that the coordinate data corresponds to the specific position in the axonometric drawing;

[0017] A defect marking unit, used to detect pipeline defects and take photos with the camera for archiving, mark the defect location in the axonometric drawing, and then associate the defect location with the defect photo;

[0018] The axonometric drawing unit is used to combine the results of the position marking unit and the defect marking unit to generate the complete axonometric drawing.

[0019] Optionally, the positioning module is also used to collect real-time geographic location information of the pipeline through laser ranging, gyroscope and triangulation, so as to mark and record it in the initial axonometric drawing.

[0020] Optionally, the data processing module includes:

[0021] A data acquisition unit, used to acquire physical data or chemical data of the pipeline using the detection instrument and transmit the acquired data to the tablet computer;

[0022] A data analysis unit, used to receive the collected data and perform preprocessing and format conversion according to different types of data to obtain processed data, perform abnormality judgment and analysis on the processed data and perform real-time monitoring;

[0023] A data storage unit, used to store the collected data and the results of the data analysis in a local database and a cloud database, and the cloud database is backed up in an encrypted transmission manner;

[0024] The visual output unit is used to display the results of the data analysis on the tablet computer in the form of visual charts and generate an initial test report based on the data analysis results.

[0025] Optionally, the data analysis unit further includes:

[0026] A basic analysis subunit is used to calculate the basic statistics of the processed data and analyze the distribution characteristics, and at the same time perform trend analysis in a time series manner to obtain the long-term trend, seasonal fluctuations and random disturbances of the data, and then use the exponential smoothing method to smooth the data to remove short-term fluctuation factors;

[0027] An anomaly detection subunit, configured to establish a normal data range and determine a detection threshold, and to calculate the processed data based on the detection threshold using an anomaly detection algorithm to automatically identify anomalies; wherein the anomaly detection algorithm is obtained by training a machine learning model using historical data;

[0028] An exception handling subunit is used to mark abnormal data and record abnormal information, send a warning to the tablet computer, analyze the abnormal data and determine the cause of the abnormality to generate an abnormal monitoring report and handling suggestions;

[0029] An optimization subunit is used to periodically update the normal data range and the detection threshold, and retrain the machine learning model according to the updated range and threshold to adjust the anomaly detection algorithm.

[0030] Optionally, the information association module includes:

[0031] A macro inspection information unit, used to summarize the pipeline appearance inspection information, environmental condition information and safety protection measures information into an information input form and store it in the data storage unit;

[0032] A safety attachment information unit, used to aggregate all safety attachments and information of the pipeline into an attachment form and store it in the data storage unit;

[0033] The associated display unit is used to perform data binding between the information input form and the attachment form at corresponding positions of the complete axonometric drawing.

[0034] Optionally, the detection report module includes:

[0035] A data aggregation unit, used to collect and aggregate the actual detection data, the macro inspection information and the safety attachment information, and perform formatting and preprocessing to obtain comprehensive data;

[0036] A data modeling unit, configured to construct a multivariate analysis model based on the comprehensive data by using statistical analysis and time series analysis methods to comprehensively evaluate the overall status of the pipeline and generate a health score for each detection indicator;

[0037] A detection record unit combines the comprehensive data, comprehensive evaluation results and health scores into a visual chart or document to obtain the detection record;

[0038] The test report unit is used to review and confirm the test record on the tablet computer, and after the review is passed, the test record is sent to the electronic report system by calling the data interface to generate the test report.

[0039] Optionally, in the interactive terminal:

[0040] The tablet computer is used for data entry and viewing, and also carries the operating environment of the axonometric mapping module, the positioning module, the data processing module, the information association module, and the detection report module;

[0041] The two-dimensional code printer is used to print out pipeline information and detection data in the form of two-dimensional codes and fix them to corresponding positions for information sharing and viewing.

[0042] The present invention discloses the following technical effects by providing a digital pressure pipeline inspection and detection system based on the Internet of Things:

[0043] 1. The present invention uses a digital pressure pipeline inspection and testing system based on the Internet of Things to quickly draw a three-dimensional model on site using an axonometric mapping instrument, and can select automatic drawing or manual drawing mode according to actual usage requirements. The automatic drawing mode is suitable for large-scale and efficient three-dimensional modeling, while the manual drawing mode allows users to perform detail corrections and inputs to ensure the accuracy and completeness of the model.

[0044] 2. The present invention uses the positioning module to accurately mark the real-time geographical location information of the pressure pipeline, each important location of the pipeline, the defect location, etc. in the generated axonometric diagram, and automatically takes pictures of the defect location and archives it with the location information, which is convenient for subsequent viewing and analysis. In addition, the present invention also considers the use of laser ranging, gyroscope, triangulation and other combined technologies to achieve the measurement of the geographic coordinate information of the pipeline when there is no satellite signal and it is impossible to directly measure or difficult to reach the pipeline measurement location.

[0045] 3. The present invention uses detection instruments (thickness gauge, hardness tester, ultrasonic flaw detector, spectrometer, metallographic analyzer, etc.) to automatically obtain, store and analyze the actual detection data of the pipeline, which not only improves the detection efficiency and accuracy, but also enhances the traceability and security of the data, helps to timely discover and deal with pipeline defects, and ensures the safe operation of the pipeline.

[0046] 4. The present invention associates various detection information with the axonometric drawing, making information input and position marking intuitive and easy to operate, which is convenient for users to browse and analyze; and by generating a detection report, it is convenient for users to make decisions and manage.

[0047] 5. The present invention can conveniently perform data input processing through a tablet computer, and can print out important information of pipelines and inspections in real time in the form of QR codes through a wireless and portable QR code printer and fix it in a corresponding position to facilitate information sharing and real-time viewing.

[0048] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments 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 based on these drawings without paying creative labor.

[0050] Figure 1 A schematic diagram of a system architecture provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] 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.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] like Figure 1 As shown, the present invention provides a digital pressure pipeline inspection and detection system based on the Internet of Things, including:

[0054] 1. An axonometric mapping module is used to obtain the 3D position information of the pipeline and the surrounding environment using an axonometric mapping instrument and draw a three-dimensional model to obtain an initial axonometric map; the axonometric mapping module includes two modes: automatic drawing and manual drawing.

[0055] The automatic drawing mode is used to control the axonometric plotter to automatically draw the axonometric map through the tablet computer, which is suitable for large-scale and efficient three-dimensional modeling. If the target points within a certain range on the pipeline are visible at the measurement position, the pitch angle, deflection angle and distance of the target points can be continuously obtained in the automatic mode, and the pipeline axonometric map can be continuously and real-time generated.

[0056] The manual drawing mode is used to display the scanned data of the axonometric plotter on the tablet computer and perform manual adjustments, input data or check point marking operations, and automatically save and generate the axonometric map after manual operations. The manual drawing mode allows the user to make detailed corrections and inputs to ensure the accuracy and completeness of the model. If the target point within a certain range on the pipeline can estimate the length and determine the direction, or the length and direction of the target point have been obtained, it can also be switched to manual mode, directly select the direction and input the length, and then the drawing system will continuously and real-time generate the pipeline axonometric map.

[0057] 2. Positioning module, used to collect the real-time geographic location information of the pipeline using GPS locator and camera and mark and record it in the initial axonometric diagram to obtain a complete axonometric diagram. It can realize the accurate geographic positioning of the pressure pipeline and the marking of important locations and defect locations. The positioning module includes:

[0058] The position marking unit is used to receive the coordinate data of the pipeline and other important positions obtained by the GPS locator in real time and match them with the axonometric drawing, so that the coordinate data corresponds to the specific position in the axonometric drawing.

[0059] The defect marking unit is used to detect pipeline defects and take photos with the camera for archiving, mark the defect position in the axonometric drawing, and then associate the defect position with the defect photo.

[0060] The axonometric drawing unit is used to combine the results of the position marking unit and the defect marking unit to generate the complete axonometric drawing.

[0061] The positioning module also takes into account the use of a combination of technologies such as laser ranging, gyroscopes, and triangulation to measure the geographic coordinate information of the pipeline in the absence of satellite signals or when the pipeline measurement site cannot be directly measured or is difficult to reach, so as to mark and record the information in the initial axonometric drawing.

[0062] 3. Data processing module is used to obtain the actual inspection data of the pipeline using the inspection instrument and store and analyze it. It realizes a fully automated process, improves inspection efficiency and accuracy, enhances data traceability and security, helps to timely discover and deal with pipeline defects, and ensures the safe operation of the pipeline.

[0063] 3.1 The data processing module includes:

[0064] The data acquisition unit is used to collect the physical data or chemical data of the pipeline using the detection instrument and transmit the collected data to the tablet computer; physical data: for example, the ultrasonic detector will emit ultrasonic waves and receive echoes, and measure the wall thickness of the pipeline by calculating the time difference of the echoes; the temperature sensor directly measures the temperature of the pipeline surface. Chemical data: for example, the gas analyzer will analyze the composition of the gas sample in the pipeline by sucking it in and output the concentration data of each gas.

[0065] The data analysis unit is used to receive the collected data and perform preprocessing (including data filtering, outlier detection, data completion and other operations) and format conversion (such as unifying into a time series data format) according to different types of data to obtain processed data, perform abnormality judgment and analysis on the processed data and perform real-time monitoring.

[0066] The data storage unit is used to store the collected data and the results of data analysis in a local database and a cloud database. The cloud database is backed up by encrypted transmission to ensure high availability and security of the data.

[0067] The visual output unit is used to display the results of the data analysis on the tablet computer in the form of visual charts, and to generate an initial test report based on the data analysis results, including a data overview, detailed analysis, defects found and suggestions, etc.

[0068] 3.2 The data analysis unit further includes:

[0069] The basic analysis subunit is used to calculate the basic statistics of the processed data (such as mean, variance, standard deviation, maximum value, minimum value, median, etc.) and analyze the distribution characteristics (such as drawing a histogram or density function of the data). At the same time, it performs trend analysis in a time series manner and obtains the long-term trend, seasonal fluctuations and random disturbances of the data, and then uses the exponential smoothing method to smooth the data to remove the impact of short-term fluctuation factors.

[0070] An anomaly detection subunit is used to establish a normal data range and determine a detection threshold, and based on the detection threshold, use an anomaly detection algorithm to calculate the processed data to automatically identify anomalies; wherein the anomaly detection algorithm is obtained by training a machine learning model using historical data; such as a one-class support vector machine (One-Class SVM), isolation forest (Isolation Forest), DBSCAN and other algorithms, which can automatically identify abnormal patterns.

[0071] The exception handling subunit is used to mark the abnormal data and record the abnormal information (such as time, location, degree of abnormality, etc.), send a warning to the tablet computer, analyze the abnormal data and determine the cause of the abnormality to generate an abnormal monitoring report (including time series diagram, abnormal point mark, statistical analysis results, etc.) and processing suggestions;

[0072] The optimization subunit is used to regularly update the normal data range and the detection threshold, and retrain the machine learning model according to the updated range and threshold to adjust the anomaly detection algorithm. It can also continuously monitor the anomaly detection performance of the system and continuously optimize the system through a feedback mechanism. For example, an expert manual review link is introduced to correct system false positives and false negatives.

[0073] 4. An information association module is used to associate the macroscopic inspection information and the safety attachment information of the pipeline on the complete axonometric drawing to facilitate user browsing and analysis. The information association module includes:

[0074] The macro inspection information unit is used to summarize the pipeline appearance inspection information (such as corrosion, leakage, deformation, etc.), environmental status information and safety protection measures information into an information input form and save it in the data storage unit; the user can enter the inspection information through touch screen input or select preset options.

[0075] The safety accessory information unit is used to summarize all the safety accessories and information of the pipeline (including the status and model, production date, calibration date, etc. of the safety valve, pressure gauge, alarm device, etc.) into an attachment form and save it in the data storage unit; the user can manually input or scan the QR code / barcode to automatically read the attachment information.

[0076] The associated display unit is used to data bind the information input form and the attachment form at the corresponding position of the complete axonometric drawing. On the axonometric drawing, the corresponding position marks can be distinguished by different icons, such as yellow dots for macro inspection points and red squares for safety attachment positions. When the user clicks on these marks, the system will pop up a detailed information window to display the associated inspection information or attachment information.

[0077] 5. A test report module is used to generate a test record by combining the actual test data, the macro inspection information and the safety attachment information, and transmit the test record to an electronic reporting system to generate a test report. This makes the test information clear and easy to understand, which helps users make decisions and maintain management. The test report module includes:

[0078] The data aggregation unit is used to collect and aggregate the actual detection data, the macro-inspection information and the safety attachment information and perform formatting (organization in a unified format, such as time sequence, detection location sorting, etc.) and preprocessing (outlier detection, data completion, etc.) to obtain comprehensive data.

[0079] The data modeling unit is used to construct a multivariate analysis model based on the comprehensive data using statistical analysis (such as mean and variance analysis to understand the trend and fluctuation range of the data) and time series analysis (such as moving average, exponential smoothing and other methods to analyze time series data and detect trend changes and abnormal fluctuations) to comprehensively evaluate the overall status of the pipeline and generate health scores for various detection indicators, such as pipeline wall thickness score, pressure score, chemical property stability score, etc.

[0080] A detection record unit combines the comprehensive data, comprehensive evaluation results and health scores into a visual chart or document to obtain the detection record;

[0081] The test report unit is used to review and confirm the test record on the tablet computer. After the review is passed, the test record is sent to the electronic reporting system by calling the data interface (using HTTP request, such as POST, to send the packaged data to the receiving endpoint of the electronic reporting system) to generate the test report.

[0082] 6. An interactive terminal, used to run the axonometric mapping module, the positioning module, the data processing module, the information association module and the detection report module, and the interactive terminal includes a tablet computer and a QR code printer.

[0083] The tablet computer is used for data entry and viewing, and at the same time carries the operating environment of the axonometric mapping module, the positioning module, the data processing module, the information association module and the detection report module.

[0084] The QR code printer can generate links for important information about pipelines and inspections. The content in the links can be updated in real time according to user operations (such as adding data, deleting data), and then the links are printed out in real time in the form of QR codes and fixed in corresponding locations to facilitate information sharing and real-time viewing.

[0085] Therefore, the present invention provides a digital pressure pipeline inspection and testing system based on the Internet of Things, which effectively solves the repetitive tasks such as multiple drawing of axonometric drawings, repeated searching of inspection positions, and manual entry of inspection and testing data in pipeline inspection and testing. It can automatically collect, process and analyze data, reduce human errors, and improve the efficiency of inspection work; it realizes the digital management of the pressure pipeline inspection and testing process.

[0086] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0087] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A digital pressure pipeline inspection and detection system based on the Internet of Things, characterized in that: include: An axonometric mapping module is used to obtain 3D position information of the pipeline and the surrounding environment using an axonometric mapping surveyor and draw a three-dimensional model to obtain an initial axonometric map; the axonometric mapping module includes two modes: automatic drawing and manual drawing; A positioning module, used to collect real-time geographical location information of the pipeline using a GPS locator and a camera and mark and record it in the initial axonometric drawing to obtain a complete axonometric drawing; A data processing module is used to obtain the actual detection data of the pipeline using the detection instrument and store and analyze it; an information association module for associating macroscopic inspection information with safety attachment information of the pipeline on the complete axonometric drawing; A test report module, for generating a test record in combination with the actual test data, the macro-inspection information and the safety attachment information, and transmitting the test record to an electronic reporting system to generate a test report; An interactive terminal is used to run the axonometric mapping module, the positioning module, the data processing module, the information association module and the detection report module, and the interactive terminal includes a tablet computer and a QR code printer.

2. According to the Internet of Things-based pressure pipeline inspection and detection digital system according to claim 1, it is characterized in that: In the axonometric mapping module: The automatic drawing mode is used to control the axonometric mapping surveying instrument to automatically draw the axonometric drawing through the tablet computer; The manual drawing mode is used to display the scanned data of the axonometric mapping instrument on the tablet computer and perform manual adjustments, input data or check point marking operations, and automatically save and generate the axonometric map after manual operations.

3. According to the Internet of Things-based pressure pipeline inspection and detection digital system according to claim 2, it is characterized in that: The positioning module comprises: A position marking unit, used to receive the coordinate data of the pipeline and other important positions obtained by the GPS locator in real time and match them with the axonometric drawing, so that the coordinate data corresponds to the specific position in the axonometric drawing; A defect marking unit, used to detect pipeline defects and take photos with the camera for archiving, mark the defect location in the axonometric drawing, and then associate the defect location with the defect photo; The axonometric drawing unit is used to combine the results of the position marking unit and the defect marking unit to generate the complete axonometric drawing.

4. According to the Internet of Things-based pressure pipeline inspection and detection digital system according to claim 3, it is characterized in that: The positioning module is also used to collect real-time geographic location information of the pipeline through laser ranging, gyroscope and triangulation, so as to mark and record it in the initial axonometric drawing.

5. According to the Internet of Things-based pressure pipeline inspection and detection digital system according to claim 4, it is characterized in that: The data processing module comprises: A data acquisition unit, used to acquire physical data or chemical data of the pipeline using the detection instrument and transmit the acquired data to the tablet computer; A data analysis unit, used to receive the collected data and perform preprocessing and format conversion according to different types of data to obtain processed data, perform abnormality judgment and analysis on the processed data and perform real-time monitoring; A data storage unit, used to store the collected data and the results of the data analysis in a local database and a cloud database, and the cloud database is backed up in an encrypted transmission manner; The visual output unit is used to display the results of the data analysis on the tablet computer in the form of visual charts and generate an initial test report based on the data analysis results.

6. According to the Internet of Things-based pressure pipeline inspection and detection digital system according to claim 5, it is characterized in that: The data analysis unit also includes: A basic analysis subunit is used to calculate the basic statistics of the processed data and analyze the distribution characteristics, and at the same time perform trend analysis in a time series manner to obtain the long-term trend, seasonal fluctuations and random disturbances of the data, and then use the exponential smoothing method to smooth the data to remove short-term fluctuation factors; An anomaly detection subunit, configured to establish a normal data range and determine a detection threshold, and to calculate the processed data based on the detection threshold using an anomaly detection algorithm to automatically identify anomalies; wherein the anomaly detection algorithm is obtained by training a machine learning model using historical data; An exception handling subunit is used to mark abnormal data and record abnormal information, send a warning to the tablet computer, analyze the abnormal data and determine the cause of the abnormality to generate an abnormal monitoring report and handling suggestions; An optimization subunit is used to periodically update the normal data range and the detection threshold, and retrain the machine learning model according to the updated range and threshold to adjust the anomaly detection algorithm.

7. The pressure pipeline inspection and detection digital system based on the Internet of Things according to claim 6 is characterized in that: The information association module includes: A macro inspection information unit, used to summarize the pipeline appearance inspection information, environmental condition information and safety protection measures information into an information input form and store it in the data storage unit; A safety attachment information unit, used to aggregate all safety attachments and information of the pipeline into an attachment form and store it in the data storage unit; The associated display unit is used to perform data binding between the information input form and the attachment form at corresponding positions of the complete axonometric drawing.

8. The pressure pipeline inspection and detection digital system based on the Internet of Things according to claim 7 is characterized in that: The detection report module includes: A data aggregation unit, used to collect and aggregate the actual detection data, the macro inspection information and the safety attachment information, and perform formatting and preprocessing to obtain comprehensive data; A data modeling unit, configured to construct a multivariate analysis model based on the comprehensive data by using statistical analysis and time series analysis methods to comprehensively evaluate the overall status of the pipeline and generate a health score for each detection indicator; A detection record unit, which combines the comprehensive data, comprehensive evaluation results and health scores into a visual chart or document to obtain the detection record; The test report unit is used to review and confirm the test record on the tablet computer, and after the review is passed, the test record is sent to the electronic report system by calling the data interface to generate the test report.

9. The pressure pipeline inspection and detection digital system based on the Internet of Things according to claim 8 is characterized in that: In the interactive terminal: The tablet computer is used for data entry and viewing, and also carries the operating environment of the axonometric mapping module, the positioning module, the data processing module, the information association module, and the detection report module; The two-dimensional code printer is used to print out pipeline information and detection data in the form of two-dimensional codes and fix them to corresponding positions for information sharing and viewing.

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