Pipeline detection part positioning method and system based on satellite navigation positioning technology

Abstract

The invention provides a pipeline detection method and system based on a satellite navigation positioning technology. The method comprises the step of arranging a positioning module, a pressure and temperature sensor and a high-definition camera on a to-be-detected pipeline. And acquiring coordinate data of the detection position, and adding the coordinate data to the electronic axonometric map of the pipeline to generate a digital pipeline map. Under the online working condition of the pipeline, whether the pipeline has defects or not is judged according to data of the pressure sensor and the temperature sensor, and if the pipeline has the defects, the high-definition camera is used for photographing to obtain defect photos. And determining pipeline defect data according to the digital pipeline diagram, the defect picture and the detection position. Under the off-line condition, abnormal position information of the pipeline is obtained through a detection instrument. And sending the pipeline defect data and / or the abnormal position information to a detection terminal to generate a customized detection form. Through multi-sensor data combination and high-precision positioning, digital, precise and intelligent pipeline defect detection and positioning are realized, and the system has important technical and application values.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation and positioning technology, and in particular to a pipeline detection part positioning method and system based on satellite navigation and positioning technology. Background Art

[0002] Pressure pipelines are one of the eight types of special equipment. They usually 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. The safe operation of pressure pipelines is related to the safety and stability of national industrial production.

[0003] Pressure pipeline safety management is a systematic project, including the daily maintenance management of the enterprise itself, as well as the regular inspection system implemented by the Chinese government for pressure pipelines. Facts have proved that regular inspection of pressure pipelines can effectively discover hidden dangers that affect the safe operation of pipelines.

[0004] 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.

[0005] The invention patent with application number 201611037357.2 discloses a pipeline leakage detection and positioning device, which can solve the problems of poor flexibility and inaccurate positioning of existing detection devices. The pressure wave sensor in each remote detection card is used to detect the pressure wave changes transmitted from the pipeline leakage point to the two ends of the pipeline. The control module is used to receive the pressure wave changes, obtain the time of pipeline leakage according to the detected pressure wave moment and the speed v of the pressure wave propagation to the two ends of the pipeline, and then determine the distance from the two ends of the pipeline to the leakage point respectively, and transmit the specific location of the pipeline leakage to the second GSM module through the first GSM module in the form of text messages. The processor is used to receive the specific location of the pipeline leakage transmitted by the second GSM module, and start the GPS module or Beidou navigation module through the serial port switching module to guide the maintenance personnel to the pipeline leakage location. It is used to detect and locate pipeline leakage points. However, this technology is affected by the limitations of the pressure wave sensor, that is, the detection result of the pressure wave sensor may be affected by external environmental factors (such as temperature, humidity, etc.), resulting in misjudgment or missed detection. Summary of the invention

[0006] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a pipeline detection site positioning method and system based on satellite navigation positioning technology, which can realize pipeline digital marking and detection by combining satellite navigation technologies such as GPS or BDS, thereby improving the efficiency and accuracy of pipeline inspection and maintenance.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A pipeline detection location positioning method based on satellite navigation positioning technology, comprising:

[0009] A movable GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera are arranged at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and temperature sensors;

[0010] The coordinate data of the preset detection position is obtained by using the GPS / BDS positioning module, and the coordinate data is added to the electronic axonometric drawing of the pipeline to be tested to generate a digital pipeline map with a geographical location;

[0011] When the pipeline to be tested is working online, judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor, and if so, taking photos with a high-definition camera at the preset detection position corresponding to the defect to obtain defect photos;

[0012] Based on the digitized pipeline map, determine the pipeline defect data with the geographic location according to the defect photo and the preset detection location corresponding to the defect;

[0013] In an offline state of the pipeline to be tested, based on the digitized pipeline diagram, the pipeline to be tested is tested using a testing instrument to obtain abnormal position information of the pipeline to be tested;

[0014] The pipeline defect data and / or the abnormal location information are sent to a detection terminal by wireless transmission, and a corresponding customized detection form is generated by using the detection terminal.

[0015] Preferably, the coordinate data of the preset detection position is obtained by using the GPS / BDS positioning module, and the coordinate data is added to the electronic axonometric diagram of the pipeline to be tested to generate a digital pipeline map with a geographical location, including:

[0016] The GPS / BDS positioning module is used to obtain the coordinate data of the preset detection position; the coordinate data includes longitude, latitude and altitude information;

[0017] Performing data filtering and precision correction on the coordinate data in sequence to obtain preprocessed data;

[0018] Performing coordinate conversion on the preprocessed data to obtain conversion data matching the coordinates of the electronic axonometric drawing;

[0019] The converted data is imported into the electronic axonometric drawing to obtain a digitized pipeline map with geographical location.

[0020] Preferably, judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor includes:

[0021] Acquire a pressure signal data set collected by a pressure sensor and a temperature signal data set collected by a temperature sensor at each preset detection position;

[0022] De-noising the pressure signal data set and the temperature signal data set at each preset detection position to obtain de-noised pressure information and temperature information;

[0023] For adjacent preset detection positions, the denoised pressure information and temperature information are respectively fused to obtain fused pressure information and temperature information corresponding to each adjacent preset detection position;

[0024] The fused pressure information and temperature information are input into the constructed pipeline defect detection model to determine whether the pipeline to be tested has defects.

[0025] Preferably, denoising is performed on the pressure signal data set and the temperature signal data set of each preset detection position to obtain denoised pressure information and temperature information, including:

[0026] A connection degree model is constructed according to the spatial distances between each pressure sensor and temperature sensor;

[0027] Constructing a denoising function using the connection degree model;

[0028] The denoising function is used to remove abnormal values ​​of the pressure signal data set and the temperature signal data set in each preset detection position to generate denoised pressure information and temperature information.

[0029] Preferably, the calculation formula of the connection degree model is: Wherein, σ represents the average value of the data difference between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n in the historical time period, dis(m,n) represents the spatial distance between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n, and R represents a preset parameter.

[0030] Preferably, constructing a denoising function using the connectivity model includes:

[0031] The denoising threshold is constructed using the weighted value of the sensor data at each preset detection position; wherein the denoising threshold is:

[0032]

[0033] Among them, Y i represents the i-th data value collected by the pressure sensor or temperature sensor, W i Represents Y i The weighted value of

[0034] A temperature denoising function is constructed based on the denoising threshold and the connection degree model; the temperature denoising function is:

[0035]

[0036] in, represents the denoised pressure or temperature information at the corresponding preset detection position at time t, x(m,t) represents the measured value of the pressure sensor or temperature sensor at point m at time t, x(n,t) represents the measured value of the pressure sensor or temperature sensor at point n at time t, ρ represents the adjustable threshold, |N m | indicates the number of pressure sensors or temperature sensors in the same preset detection position,

[0037] Preferably, for adjacent preset detection positions, the denoised pressure information and temperature information are fused respectively to obtain the fused pressure information and temperature information corresponding to each adjacent preset detection position, including:

[0038] A fusion function is constructed using the denoised pressure information and temperature information corresponding to each preset detection position; the fusion function is: Among them, q ij represents the fusion function, X i represents the denoised pressure or temperature information of the i-th preset detection position, X j represents the pressure information or temperature information after denoising of the j-th preset detection position; the i-th preset detection position and the j-th preset detection position are adjacent preset detection positions;

[0039] A fusion matrix is ​​constructed according to the fusion function, and the eigenvalues ​​corresponding to the fusion matrix are calculated; the formula of the fusion matrix is:

[0040] The denoised pressure information and temperature information corresponding to each preset detection position are fused using the characteristic values ​​to obtain fused pressure information and temperature information corresponding to each preset detection position.

[0041] Preferably, the denoised pressure information and temperature information corresponding to each preset detection position are fused using the characteristic values ​​to obtain the fused pressure information and temperature information corresponding to each preset detection position, including:

[0042] Using formula Get the fusion weighted coefficient; where L represents the denoised wavelet coefficient, r i represents the i-th eigenvalue of the fusion matrix;

[0043] The fused pressure information and temperature information corresponding to adjacent preset detection positions are weighted averaged using the fusion weight coefficient to obtain the fused pressure information and temperature information corresponding to each preset detection position.

[0044] Preferably, based on the digitized pipeline map, determining the pipeline defect data with the geographical location according to the defect photo and the preset detection location corresponding to the defect comprises:

[0045] Associating the defect photo with the preset detection location corresponding to the defect, and creating a structured data record for the defect photo; the data record includes location, time, sensor data, and photo path information;

[0046] The data record is marked in the digitized pipeline map, and the data record is determined as pipeline defect data with geographic location.

[0047] A pipeline detection location positioning system based on satellite navigation positioning technology, comprising:

[0048] A sensor setting unit, used to set a movable GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and temperature sensors;

[0049] A pipeline map generating unit, used to obtain the coordinate data of the preset detection position by using the GPS / BDS positioning module, and add the coordinate data to the electronic axonometric map of the pipeline to be tested to generate a digital pipeline map with a geographical location;

[0050] A defect identification unit is used to determine whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor when the pipeline to be tested is working online, and if so, take a photo with a high-definition camera at the preset detection position corresponding to the defect to obtain a defect photo;

[0051] A defect data acquisition unit, configured to determine the pipeline defect data with the geographic location based on the digitized pipeline map, the defect photo and the preset detection location corresponding to the defect;

[0052] An offline detection unit, used to detect the pipeline to be tested based on the digitized pipeline map and using a detection instrument when the pipeline to be tested is offline, so as to obtain abnormal position information of the pipeline to be tested;

[0053] The report generating unit is used to send the pipeline defect data and / or the abnormal location information to the detection terminal by wireless transmission, and generate a corresponding customized detection form by using the detection terminal.

[0054] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0055] The present invention provides a pipeline detection part positioning method based on satellite navigation positioning technology, comprising: setting a movable GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and a temperature sensor; using the GPS / BDS positioning module to obtain the coordinate data of the preset detection position, and adding the coordinate data to the electronic axonometric diagram of the pipeline to be tested to generate a digitized pipeline map with a geographical location; in the case of online working of the pipeline to be tested, according to the collected data of the pressure sensor and the temperature sensor, It is determined whether the pipeline to be tested has defects. If so, a high-definition camera at the preset detection position corresponding to the defect is used to take a photo to obtain a defect photo; based on the digitized pipeline map, the pipeline defect data with the geographical location is determined according to the defect photo and the preset detection position corresponding to the defect; when the pipeline to be tested is offline, the pipeline to be tested is tested according to the detection instrument based on the digitized pipeline map to obtain abnormal position information of the pipeline to be tested; the pipeline defect data and / or the abnormal position information are sent to the detection terminal by wireless transmission, and the detection terminal is used to generate a corresponding customized detection form. The present invention realizes digital, precise and intelligent pipeline defect detection and positioning through the combination of multi-sensor data and high-precision positioning module, which has important technical and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] 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.

[0057] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0058] Figure 2 A structural diagram of a system unit provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] The purpose of the present invention is to provide a pipeline inspection site positioning method based on satellite navigation positioning technology, which realizes digital, precise and intelligent pipeline defect detection and positioning through the combination of multi-sensor data and high-precision positioning module, and has important technical and application value.

[0061] 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.

[0062] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides a pipeline detection location positioning method based on satellite navigation positioning technology, comprising:

[0063] Step 100: a movable GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera are arranged at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and temperature sensors;

[0064] Step 200: using the GPS / BDS positioning module to obtain the coordinate data of the preset detection position, and adding the coordinate data to the electronic axonometric drawing of the pipeline to be tested to generate a digital pipeline map with the geographic location;

[0065] Step 300: judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor, and if so, taking photos with a high-definition camera at the preset detection position corresponding to the defect to obtain defect photos;

[0066] Step 400: Based on the digital pipeline map, determine pipeline defect data with geographic location according to the defect photo and the preset detection location corresponding to the defect;

[0067] Step 500: When the pipeline to be tested is offline, based on the digital pipeline map, the pipeline to be tested is tested using a testing instrument to obtain abnormal position information of the pipeline to be tested;

[0068] Step 600: Send the pipeline defect data and / or the abnormal location information to a detection terminal by wireless transmission, and use the detection terminal to generate a corresponding customized detection form.

[0069] Specifically, the technical route of this embodiment is as follows:

[0070] 1. Equipment preparation: First, install a movable GPS / BDS positioning module, pressure sensor, temperature sensor and high-definition camera at several preset detection positions of the pipeline to be tested.

[0071] Specifically, in the initial setting, the embodiment pairs and calibrates the GPS / BDS positioning module with the central control unit in the pipeline detection system. Then, the API of the GPS / BDS module is called or its data transmission interface is read. For example, the standard positioning data in NMEA format provided by it is read through the serial port.

[0072] 2. Coordinate data acquisition: In this embodiment, at each preset detection position, the precise coordinate data of the position is acquired through the GPS / BDS positioning module.

[0073] 3. Generation of digital pipeline map: This embodiment integrates the acquired coordinate data into the electronic axonometric map to generate a digital pipeline map with geographical locations. The map is used to display the specific layout of the pipeline and each detection location.

[0074] 4. Defect detection and response: This embodiment monitors the pressure and temperature changes of each detection position in real time. When abnormal data is found, the system determines that the pipeline may have defects. At this time, the high-definition camera is controlled to take photos of the defective part.

[0075] 5. Generate pipeline defect data: Based on the digital pipeline map and defect photos, this embodiment determines the geographic coordinates of the defect location and generates a pipeline defect data report with the geographic location to facilitate subsequent maintenance personnel to perform maintenance.

[0076] Preferably, the coordinate data of the preset detection position is obtained by using the GPS / BDS positioning module, and the coordinate data is added to the electronic axonometric diagram of the pipeline to be tested to generate a digital pipeline map with a geographical location, including:

[0077] The GPS / BDS positioning module is used to obtain the coordinate data of the preset detection position; the coordinate data includes longitude, latitude and altitude information;

[0078] Performing data filtering and precision correction on the coordinate data in sequence to obtain preprocessed data;

[0079] Performing coordinate conversion on the preprocessed data to obtain conversion data matching the coordinates of the electronic axonometric drawing;

[0080] The converted data is imported into the electronic axonometric drawing to obtain a digitized pipeline map with geographical location.

[0081] Coordinate data preprocessing can include data filtering, precision correction and coordinate format conversion. Preprocessing is mainly to ensure the accuracy and consistency of data.

[0082] Furthermore, the data filtering in this embodiment is to check the validity of the coordinate data and eliminate unreasonable data points or data points with too large errors.

[0083] Furthermore, if the coordinate system of the GPS / BDS positioning system used is inconsistent with the electronic isometric drawing, a coordinate system conversion is required. For example, from the WGS-84 coordinate system to the local coordinate system used. After the conversion, the present embodiment imports the coordinate data into the electronic isometric drawing. The electronic isometric drawing is a digital pipeline layout diagram used to visually display the specific layout of the pipeline and each detection position.

[0084] Specifically, this embodiment uses geographic information system (GIS) software, such as ArcGIS, QGIS, etc., to import coordinate data into the electronic axonometric drawing to draw the pipeline and detection points. And this embodiment uses programming drawing libraries, such as Matplotlib, Plotly, etc., to draw the pipeline and each detection point on a digital map.

[0085] In addition, the present embodiment also adds relevant additional information to the electronic axonometric drawing, such as the name of the detection position, the type of detection device, the detection time and other remark information. When drawing, each detection point is marked and annotated to increase readability.

[0086] Finally, this embodiment finally saves the digitized pipeline map with geographic location as a file (such as JPEG, PNG, PDF, etc. format) for subsequent viewing and use, and can also be uploaded to the pipeline management system for archiving and management.

[0087] Through the above steps, this embodiment can effectively integrate the collected coordinate data into the electronic axonometric diagram to generate a digital pipeline map with geographic location information. These implementation steps will ensure that the map can accurately display the specific layout of the pipeline and each inspection location, which is convenient for subsequent defect detection and maintenance management.

[0088] Preferably, judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor includes:

[0089] Acquire a pressure signal data set collected by a pressure sensor and a temperature signal data set collected by a temperature sensor at each preset detection position;

[0090] De-noising the pressure signal data set and the temperature signal data set at each preset detection position to obtain de-noised pressure information and temperature information;

[0091] For adjacent preset detection positions, the denoised pressure information and temperature information are respectively fused to obtain fused pressure information and temperature information corresponding to each adjacent preset detection position;

[0092] The fused pressure information and temperature information are input into the constructed pipeline defect detection model to determine whether the pipeline to be tested has defects.

[0093] Preferably, denoising is performed on the pressure signal data set and the temperature signal data set of each preset detection position to obtain denoised pressure information and temperature information, including:

[0094] A connection degree model is constructed according to the spatial distances between each pressure sensor and temperature sensor;

[0095] Constructing a denoising function using the connection degree model;

[0096] The denoising function is used to remove abnormal values ​​of the pressure signal data set and the temperature signal data set in each preset detection position to generate denoised pressure information and temperature information.

[0097] Preferably, the calculation formula of the connection degree model is: Wherein, σ represents the average value of the data difference between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n in the historical time period, dis(m,n) represents the spatial distance between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n, and R represents a preset parameter.

[0098] Exemplarily, in this embodiment, the pressure or temperature sensors at point m and point n are neighboring sensors. The closer the positions of the two sensors are, the greater the correlation between the two sensors. Therefore, the present invention measures the degree of connection between the two sensors based on the spatial distance between them. In practical applications, since the sensor may be affected by its own parameters or environmental factors, the measured value collected by the sensor at a certain moment may deviate greatly from the actual value. Therefore, the present invention introduces R to correct the problem of sensor correlation deviation caused by the influence of its own parameters or environmental factors. In general, the value of R is 1.

[0099] Preferably, constructing a denoising function using the connectivity model includes:

[0100] The denoising threshold is constructed using the weighted value of the sensor data at each preset detection position; wherein the denoising threshold is:

[0101]

[0102] Among them, Y i represents the i-th data value collected by the pressure sensor or temperature sensor, W i Represents Y i The weighted value of

[0103] A temperature denoising function is constructed based on the denoising threshold and the connection degree model; the temperature denoising function is:

[0104]

[0105] in, represents the denoised pressure or temperature information at the corresponding preset detection position at time t, x(m,t) represents the measured value of the pressure sensor or temperature sensor at point m at time t, x(n,t) represents the measured value of the pressure sensor or temperature sensor at point n at time t, ρ represents the adjustable threshold, |N m | indicates the number of pressure sensors or temperature sensors in the same preset detection position,

[0106] It should be noted that, in this embodiment, the W can be set with reference to the model or position of each pressure sensor or temperature sensor. i If the temperature sensors are of the same model, W i Set to 1.

[0107] Furthermore, this embodiment can avoid a situation where a large deviation occurs between the measurement value collected by the sensor at a certain moment and the actual value by using a denoising function to fuse the measurement values ​​of the sensors at the same monitoring point, thereby making the measurement values ​​of the sensors more realistic.

[0108] Preferably, for adjacent preset detection positions, the denoised pressure information and temperature information are fused respectively to obtain the fused pressure information and temperature information corresponding to each adjacent preset detection position, including:

[0109] A fusion function is constructed using the denoised pressure information and temperature information corresponding to each preset detection position; the fusion function is: Among them, q ij represents the fusion function, X i represents the denoised pressure or temperature information of the i-th preset detection position, X j represents the pressure information or temperature information after denoising of the j-th preset detection position; the i-th preset detection position and the j-th preset detection position are adjacent preset detection positions;

[0110] A fusion matrix is ​​constructed according to the fusion function, and the eigenvalues ​​corresponding to the fusion matrix are calculated; the formula of the fusion matrix is:

[0111] The denoised pressure information and temperature information corresponding to each preset detection position are fused using the characteristic values ​​to obtain fused pressure information and temperature information corresponding to each preset detection position.

[0112] Preferably, the denoised pressure information and temperature information corresponding to each preset detection position are fused using the characteristic values ​​to obtain the fused pressure information and temperature information corresponding to each preset detection position, including:

[0113] Using formula Get the fusion weighted coefficient; where L represents the denoised wavelet coefficient, r i represents the i-th eigenvalue of the fusion matrix;

[0114] The fused pressure information and temperature information corresponding to adjacent preset detection positions are weighted averaged using the fusion weight coefficient to obtain the fused pressure information and temperature information corresponding to each preset detection position.

[0115] Specifically, this embodiment is based on the fusion matrix and dynamically allocates the corresponding fusion weighting coefficient L to each sensor according to the information measured by each sensor in real time, so as to obtain the final fused information of each preset detection position, which can be closer to the actual pressure value and temperature value.

[0116] Specifically, in order to determine whether the pipeline to be tested has defects, this embodiment inputs the collected pressure information and temperature information into the constructed pipeline defect detection model for analysis. This embodiment has a pre-trained machine learning model that can determine whether the pipeline has defects based on sensor data (pressure and temperature). The following are the specific steps:

[0117] Step 1: Load the pre-trained model. Generally, the pre-trained model can be various machine learning or deep learning models (such as random forest, support vector machine, neural network, etc.). This embodiment is built and trained by Scikit-Learn or TensorFlow / Keras in Python.

[0118] Step 2: Preprocessing data. In this embodiment, the pressure and temperature data collected in real time are converted into a feature vector format acceptable to the model.

[0119] Step 3: Model prediction. This embodiment uses the loaded model to predict the preprocessed input data to determine whether the pipeline has defects.

[0120] Step 4: Determine the results and process them. Determine whether the pipeline has defects based on the prediction results and perform corresponding processing (such as alarm, marking, dispatching maintenance personnel, etc.).

[0121] Through the above steps, this embodiment can realize defect detection of real-time collected pressure and temperature information. The specific steps include loading the pre-trained model, pre-processing the input data, inputting the data into the model for prediction, and judging whether the pipeline has defects based on the prediction results. This can not only effectively monitor the pipeline status, but also take timely measures when defects are detected to ensure the safe operation of the pipeline.

[0122] Preferably, based on the digitized pipeline map, determining the pipeline defect data with the geographical location according to the defect photo and the preset detection location corresponding to the defect comprises:

[0123] Associating the defect photo with the preset detection location corresponding to the defect, and creating a structured data record for the defect photo; the data record includes location, time, sensor data, and photo path information;

[0124] The data record is marked in the digitized pipeline map, and the data record is determined as pipeline defect data with geographic location.

[0125] Optionally, this embodiment first collects defect photos, and when an abnormality is detected, a high-definition camera can be triggered to take defect photos, and the photos are associated with location data. When the temperature sensor or pressure sensor detects an abnormal value, the high-definition camera is triggered to take photos and save them.

[0126] Secondly, this embodiment associates the defect photo with the detection location, that is, associates the captured defect photo with the corresponding detection location coordinate data, and creates a structured data record for the defect data. The data record structure is achieved by creating a dictionary or database table to store the defect data, including location, time, sensor data, photo path and other information.

[0127] Thirdly, this embodiment marks the defect location on the digital pipeline map, marks the defect location on the existing digital pipeline map, and adds annotations for easy intuitive viewing and management. Finally, this embodiment generates a defect data report, organizes the detailed information of all defect points into a report, which is convenient for maintenance personnel to view and troubleshoot problems, and stores the defect data and reports in the pipeline management system for subsequent query and management.

[0128] Through the above steps, this embodiment generates pipeline defect data with geographic location from defect photos and preset detection locations. This not only includes specific coordinates, sensor readings and time information, but also can visually display defect points in the map, providing detailed and accurate data support for maintenance and management.

[0129] Corresponding to the above method, such as Figure 2 As shown, the present invention also provides a pipeline detection location positioning system based on satellite navigation positioning technology, comprising:

[0130] A sensor setting unit, used to set a GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and temperature sensors;

[0131] A pipeline map generating unit, used to obtain the coordinate data of the preset detection position by using the GPS / BDS positioning module, and add the coordinate data to the electronic axonometric map of the pipeline to be tested to generate a digital pipeline map with a geographical location;

[0132] A defect identification unit is used to determine whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor. If so, a high-definition camera at the preset detection position corresponding to the defect is used to take a photo to obtain a defect photo;

[0133] The defect data acquisition unit is used to determine the pipeline defect data with the geographical location based on the digitized pipeline map, the defect photo and the preset detection location corresponding to the defect.

[0134] The beneficial effects of the present invention are as follows:

[0135] (1) The present invention uses a combination of multiple sensors to detect pipeline status in real time and accurately, thereby improving the flexibility and reliability of the system.

[0136] (2) The present invention can generate powerful digital pipeline maps, visually display pipeline defects, and facilitate data management and analysis.

[0137] (3) The present invention uses a high-definition camera and a GPS / BDS positioning module to quickly take defect photos and accurately locate the fault point, thereby improving the efficiency and timeliness of pipeline maintenance.

[0138] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0139] 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 pipeline detection location positioning method based on satellite navigation positioning technology, characterized in that: include: A movable GPS / BDS positioning module, pressure sensor, temperature sensor and high-definition camera are set at the preset detection position of the pipeline to be tested; Each of the preset detection positions is respectively provided with at least two pressure sensors and a temperature sensor; The coordinate data of the preset detection position is obtained by using the GPS / BDS positioning module, and the coordinate data is added to the electronic axonometric drawing of the pipeline to be tested to generate a digital pipeline map with a geographical location; When the pipeline to be tested is working online, judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor, and if so, taking photos with a high-definition camera at the preset detection position corresponding to the defect to obtain defect photos; Based on the digitized pipeline map, determine the pipeline defect data with the geographic location according to the defect photo and the preset detection location corresponding to the defect; In an offline state of the pipeline to be tested, based on the digitized pipeline diagram, the pipeline to be tested is tested using a testing instrument to obtain abnormal position information of the pipeline to be tested; The pipeline defect data and / or the abnormal location information are sent to a detection terminal by wireless transmission, and a corresponding customized detection form is generated by using the detection terminal.

2. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 1 is characterized in that: The coordinate data of the preset detection position is obtained by using the GPS / BDS positioning module, and the coordinate data is added to the electronic axonometric drawing of the pipeline to be tested to generate a digital pipeline map with a geographical location, including: The GPS / BDS positioning module is used to obtain the coordinate data of the preset detection position; the coordinate data includes longitude, latitude and altitude information; Performing data filtering and precision correction on the coordinate data in sequence to obtain preprocessed data; Performing coordinate conversion on the preprocessed data to obtain conversion data matching the coordinates of the electronic axonometric drawing; The converted data is imported into the electronic axonometric drawing to obtain a digitized pipeline map with geographical location.

3. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 1 is characterized in that: Judging whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor includes: Acquire a pressure signal data set collected by a pressure sensor and a temperature signal data set collected by a temperature sensor at each preset detection position; De-noising the pressure signal data set and the temperature signal data set at each preset detection position to obtain de-noised pressure information and temperature information; For adjacent preset detection positions, the denoised pressure information and temperature information are respectively fused to obtain fused pressure information and temperature information corresponding to each adjacent preset detection position; The fused pressure information and temperature information are input into the constructed pipeline defect detection model to determine whether the pipeline to be tested has defects.

4. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 3 is characterized in that: De-noising the pressure signal data set and the temperature signal data set of each preset detection position to obtain the de-noised pressure information and temperature information, including: A connection degree model is constructed according to the spatial distances between each pressure sensor and temperature sensor; Constructing a denoising function using the connection degree model; The denoising function is used to remove abnormal values ​​of the pressure signal data set and the temperature signal data set in each preset detection position to generate denoised pressure information and temperature information.

5. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 4 is characterized in that: The calculation formula of the connection degree model is: Wherein, σ represents the average value of the data difference between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n in the historical time period, dis(m,n) represents the spatial distance between the pressure sensor or temperature sensor at point m and the pressure sensor or temperature sensor at point n, and R represents a preset parameter.

6. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 5 is characterized in that: The denoising function is constructed using the connection degree model, including: The denoising threshold is constructed using the weighted value of the sensor data at each preset detection position; wherein the denoising threshold is: Among them, Y i represents the i-th data value collected by the pressure sensor or temperature sensor, W i Represents Y i The weighted value of A temperature denoising function is constructed based on the denoising threshold and the connection degree model; the temperature denoising function is: in, represents the denoised pressure or temperature information at the corresponding preset detection position at time t, x(m,t) represents the measured value of the pressure sensor or temperature sensor at point m at time t, x(n,t) represents the measured value of the pressure sensor or temperature sensor at point n at time t, ρ represents the adjustable threshold, |N m | indicates the number of pressure sensors or temperature sensors in the same preset detection position, 7. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 6 is characterized in that: For adjacent preset detection positions, the denoised pressure information and temperature information are fused respectively to obtain the fused pressure information and temperature information corresponding to each adjacent preset detection position, including: A fusion function is constructed using the denoised pressure information and temperature information corresponding to each preset detection position; the fusion function is: Among them, q ij represents the fusion function, X i represents the denoised pressure or temperature information of the i-th preset detection position, X j represents the pressure information or temperature information after denoising of the j-th preset detection position; the i-th preset detection position and the j-th preset detection position are adjacent preset detection positions; A fusion matrix is ​​constructed according to the fusion function, and the eigenvalues ​​corresponding to the fusion matrix are calculated; the formula of the fusion matrix is: The denoised pressure information and temperature information corresponding to each preset detection position are fused using the characteristic values ​​to obtain fused pressure information and temperature information corresponding to each preset detection position.

8. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 7 is characterized in that: The denoised pressure information and temperature information corresponding to each preset detection position are respectively fused using the characteristic values ​​to obtain fused pressure information and temperature information corresponding to each preset detection position, including: Using formula Get the fusion weighted coefficient; where L represents the denoised wavelet coefficient, r i represents the i-th eigenvalue of the fusion matrix; The fused pressure information and temperature information corresponding to adjacent preset detection positions are weighted averaged using the fusion weight coefficient to obtain the fused pressure information and temperature information corresponding to each preset detection position.

9. The pipeline detection location positioning method based on satellite navigation positioning technology according to claim 1 is characterized in that: Based on the digitized pipeline map, pipeline defect data with geographic location is determined according to the defect photo and the preset detection location corresponding to the defect, including: Associating the defect photo with the preset detection location corresponding to the defect, and creating a structured data record for the defect photo; the data record includes location, time, sensor data, and photo path information; The data record is marked in the digitized pipeline map, and the data record is determined as pipeline defect data with geographic location.

10. A pipeline detection location positioning system based on satellite navigation positioning technology, characterized in that: include: A sensor setting unit, used to set a movable GPS / BDS positioning module, a pressure sensor, a temperature sensor and a high-definition camera at a preset detection position of the pipeline to be tested; each of the preset detection positions is respectively provided with at least two pressure sensors and temperature sensors; A pipeline map generating unit, used to obtain the coordinate data of the preset detection position by using the GPS / BDS positioning module, and add the coordinate data to the electronic axonometric map of the pipeline to be tested to generate a digital pipeline map with a geographical location; A defect identification unit is used to determine whether the pipeline to be tested has defects according to the collected data of the pressure sensor and the temperature sensor when the pipeline to be tested is working online, and if so, take a photo with a high-definition camera at the preset detection position corresponding to the defect to obtain a defect photo; A defect data acquisition unit, configured to determine the pipeline defect data with geographic location based on the digitized pipeline map, the defect photo and the preset detection location corresponding to the defect; An offline detection unit, used to detect the pipeline to be tested based on the digitized pipeline map and using a detection instrument when the pipeline to be tested is offline, so as to obtain abnormal position information of the pipeline to be tested; The report generating unit is used to send the pipeline defect data and / or the abnormal location information to the detection terminal by wireless transmission, and generate a corresponding customized detection form by using the detection terminal.

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