CN108562639B - A method for external detection of defects in the whole life cycle of buried steel pipelines - Google Patents
A method for external detection of defects in the whole life cycle of buried steel pipelines Download PDFInfo
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Abstract
本发明提供了一种埋地钢质管道全生命周期缺陷外检测方法，属于管道无损检测技术领域。该方法将管道自漏磁场信号历史数据作为基准，对当前的管道缺陷状况进行评价，操作简单，成本低，适用范围广，主要包括以下八个个步骤：步骤一，收集管道的基础资料；步骤二，划分管段区间及其子区间；步骤三，收集管道竣工时的自漏磁场数据；步骤四，收集管道试压时的自漏磁场数据；步骤五，收集管道初始运行时的自漏磁场数据；步骤六，收集管道运行期间的自漏磁场数据；步骤七，计算管道自漏磁场信号相关度；步骤八，确定管段缺陷严重程度排序及开挖详细检查子区间。
The invention provides a full life cycle defect detection method for buried steel pipelines, which belongs to the technical field of pipeline non-destructive testing. The method uses the historical data of the pipeline self-leakage magnetic field signal as the benchmark to evaluate the current pipeline defect status, with simple operation, low cost and wide application range, and mainly includes the following eight steps: Step 1, collect the basic data of the pipeline; step 2. Divide the interval of the pipe section and its sub-intervals; Step 3, collect the self-leakage magnetic field data when the pipeline is completed; Step 4, collect the self-leakage magnetic field data during the pressure test of the pipeline; Step 5, collect the self-leakage magnetic field data during the initial operation of the pipeline Step 6, collect the data of the self-leakage magnetic field during the operation of the pipeline; Step 7, calculate the correlation degree of the signal of the pipeline self-leakage magnetic field; Step 8, determine the sequence of the severity of the defects of the pipe section and the detailed inspection sub-section of the excavation.
Description
Technical Field
The invention relates to the field of nondestructive testing of pipelines, in particular to a nondestructive testing method for identifying, positioning and sequencing the defects of a buried steel pipeline in a full life cycle.
Background
Steel pipelines have become the main transportation mode of energy sources such as petroleum, natural gas and the like, and play an increasingly important role in national economy. In order to ensure the operation safety of the pipeline, the pipeline is required to be periodically detected so as to find problems in time, and corrective measures are taken so as to prevent serious safety accidents and avoid causing huge economic loss and casualties.
At present, conventional pipeline testing method has magnetic leakage detection, ultrasonic guided wave detection, eddy current testing, magnetic powder testing etc. and wherein the application that the magnetic leakage detected is the most extensive and ripe, but the magnetic leakage detects and is a detection technique in the pipeline, has the requirement to the specification of pipeline, causes the card stifled easily, and can cause the magnetic pollution, increases the cost of magnetization and demagnetization.
The steel pipeline is spontaneously magnetized under the action of other external loads such as internal pressure, temperature stress, soil pressure and the like in a geomagnetic field, and a self-leakage magnetic field is formed nearby the pipeline. The self-leakage magnetic field is distorted at the position of the pipeline defect due to the stress state, the quantity of the ferromagnetic materials and the change of the distribution of the ferromagnetic materials. Thus, defects can be identified and located by acquiring such distortions with a magnetic gradiometer. However, there are various problems in the application process of the method, mainly including:
(1) at present, the analysis of the magnetic induction intensity gradient signals of the self-leakage magnetic field obtained by a magnetic gradiometer is mainly based on human judgment, and the accuracy cannot be ensured;
(2) the self-leakage magnetic field theoretical calculation method needs to obtain basic parameters such as the magnetic characteristics of the pipeline and the like, and has the advantages of complex operation, higher cost, low precision and low practicability;
(3) the current method can not effectively judge the severity of the defects, and can not accurately judge the serious defects needing excavation detailed detection and repair from a large number of sections with abnormal self-leakage magnetic field gradient signals.
Based on the analysis, a simple and applicable detection method with low cost for the defects of the buried steel pipelines is urgently needed at present, so that the identification, the positioning and the severity sequencing of the pipeline defects are realized, the personal errors are reduced, the accuracy of the serious defect screening is improved, and the safety of the pipelines is effectively guaranteed.
Therefore, the invention provides a pipeline full life cycle defect detection method based on self-leakage magnetic field historical data. According to the method, historical data is used as a criterion for judging the defect condition of the current pipeline by dynamically monitoring the self-leakage magnetic field of the pipeline. The defect detection method based on historical data does not need to carry out theoretical calculation on the self-leakage magnetic field, and has the advantages of simple operation, low cost and wide application range.
Disclosure of Invention
The invention provides a buried steel pipeline defect external detection method based on self-leakage magnetic field historical data. The method can realize the functions of identification, positioning, grading and the like of the defects of the buried steel pipeline, reduce the artificial influence, effectively screen the defects which seriously affect the safety of the pipeline and provide guarantee for the safe operation of the pipeline. The method for detecting the defects of the buried steel pipeline outside based on the historical data of the self-leakage magnetic field is characterized in that firstly, basic data of the pipeline is collected and partitioned, and secondly, environmental factors influencing the data acquisition precision of the magnetic gradiometer along the pipeline are checked and cleaned; thirdly, collecting magnetic induction intensity gradient signals of the self-leakage magnetic field; then, based on historical signal data, determining the correlation degree of the current self-leakage magnetic field signal and the historical signal data of each pipe section according to the currently collected self-leakage magnetic field gradient signal; and finally, based on the calculated correlation data, sequencing the pipelines from low to high according to the correlation, and screening out the pipelines with serious defect conditions for excavation and detailed inspection.
The method for detecting the defects of the buried steel pipeline outside mainly comprises the following steps:
(1) collecting basic data of the pipeline. The basic data comprises design data, completion data, routes, materials, outer diameters, wall thicknesses, burial depths, cathodic protection devices, station positions, station cathodic protection positions, design pressure and operating pressure of the pipelines, hydraulic slope lines of the pipelines, accident records of the pipelines, detection and maintenance records of the pipelines, stop records of the pipelines and working condition change records of the pipelines. These data constitute the underlying database of the pipeline.
(2) And dividing pipe section intervals and subintervals. The whole pipeline is divided into a plurality of pipeline sections, and the reasonable evaluation pipeline section interval is determined according to the input and output port position of the detection pipeline, the positions of a heating station, a compressor station and the like, the position of a reducer pipe, the position of a variable wall thickness, the position of a valve, the position of the direction change of the pipeline, the position of a crossing structure of the pipeline, the position of a test pile of the pipeline protection device, and the like. After the pipeline sections are determined, a sub-section should be determined in each section, which is the smallest unit of pipeline defect detection. And (3) naming the pipe section intervals as S, wherein S is a set formed by all the pipe section intervals, and is shown in a formula (1).
S＝{S1，S2，S3,…Si,…,Sm} (1)
Wherein S is a set formed by intervals of each pipe section, SiIn the interval of pipe sections, S1，S2，S3And (5) waiting for m pipe section intervals, and sequencing from the starting point of the pipeline to the end point of the pipeline according to the mileage of the pipeline.
Each pipe section is composed of a plurality of sub-pipe sections, and the collection of the sub-pipe sections forms an interval, namely an interval S shown in formula (2)iThe collection expression of (2). The sub-pipe segment represents a signal data acquisition point in the test.
Si＝{Si1，Si2，Si3,…Sij,…,Smn} (2)
In the formula SiFor the section of the pipe formed by the sub-sections, Si1，Si2，Si3The equal n intervals are sorted according to the pipeline mileage from the starting point of the interval of the pipeline segment to the end point of the interval of the pipeline segment, and SijFor a section S of a pipeiThe jth sub-interval of (a).
(3) And (4) collecting self-leakage magnetic field data when the pipeline is completed. After the pipeline is finished and before the pressure test of the pipeline, the magnetic induction intensity gradient signal values of the self-leakage magnetic field above the pipeline are collected from the starting point of the pipeline to the end point of the pipeline, and the gradient signals comprise components in 3 directions, namely components in the x-axis direction (components perpendicular to the axis direction of the pipeline), components in the y-axis direction (components in the axis direction of the pipeline) and components in the z-axis direction (components perpendicular to the plane of the pipeline). Arranging the data according to the finished pipeline partition, wherein each subinterval respectively comprises three groups of data, namely the data in the x-axis direction, the y-axis direction and the z-axis direction are respectively processed by BCijx，BCijy，BCijzAnd (4) showing.
(4) And collecting self-leakage magnetic field data during pressure test of the pipeline. After the pipeline pressure testing is finished, the pipeline is about to be subjected to pressure testing. When in pressure test, the pressure test pressure of the pipeline and the hydraulic gradient line of the pressure test pipe section are firstly recorded. In the pressure test process, three-component signals of the magnetic induction gradient of the self-leakage magnetic field of the pipeline are collected from the starting point to the end point of the pipeline section under pressure, and the signals also comprise three parts, namely a component in the x-axis direction (a component perpendicular to the axial direction of the pipeline), a component in the y-axis direction (a component in the axial direction of the pipeline) and a component in the z-axis direction (a component perpendicular to the plane of the pipeline). Arranging the data according to the finished pipeline partition, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BT is respectively usedijx，BTijy，BTijzAnd (4) showing.
(5) Self-leakage magnetic field data collection during initial operation of pipeline. After pressure test and rectification after pressure test, the whole pipeline can be regarded as a non-defective pipeline. And collecting a self-leakage magnetic field magnetic induction gradient three-component signal of the pipeline from the starting point to the end point of the pipeline by using a three-component magnetic gradiometer, wherein the signal also comprises three parts, namely a component in the x-axis direction (a component vertical to the axial line direction of the pipeline), a component in the y-axis direction (a component along the axial line direction of the pipeline) and a component in the z-axis direction (a component vertical to the plane of the pipeline). Arranging the data according to the finished pipeline subareas, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and the data are respectively processed by a BS (base station)ijx，BSijy，BSijzAnd (4) showing.
(6) Self-leakage magnetic field data is collected during operation of the pipeline. In the running process of the pipeline, the self-leakage magnetic field of the pipeline is periodically collected, ferromagnetic interferents along the pipeline are cleared before collection, then a three-component magnetic gradiometer is used for collecting three-component signals of the self-leakage magnetic field magnetic induction gradient of the pipeline from the starting point to the end point of the pipeline, and the signals also comprise three parts, namely a component in the x-axis direction (a component perpendicular to the axis direction of the pipeline), a component in the y-axis direction (a component in the axis direction of the pipeline) and a component in the z-axis direction (a component perpendicular to the plane of the pipeline). Arranging the data according to the finished pipeline partition, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BO is respectively usedijx，BOijy，BOijzAnd (4) showing.
(7) And (3) analyzing the correlation of the gradient three-component signal of the pipeline self-leakage magnetic field. And in the whole life cycle of the pipeline, evaluating the defect condition of the pipeline by calculating the similarity coefficient of the current self-leakage magnetic field signal and the self-leakage magnetic field signal (historical data) obtained in the last detection. Classifying the collected self-leakage magnetic field signal values according to pipeline subintervals at each stage of pipeline defect evaluation, and obtaining component values S of the self-leakage magnetic field data of each subinterval at the current stage and the similarity coefficients of the previous stage along the directions of the x axis, the y axis and the z axisix，Siy，SizAnd the average value SiThe calculation method (2) is as shown in equations (3) to (6).
In the formula fiThe average value of the similarity of the ith subinterval of the pipeline is taken as the average value; f. ofix，fiy，fizThe component of the similarity of the ith subinterval of the pipeline along the x axis, the y axis and the z axis; bpijx，BpijyAnd BpijzThe component of the magnetic induction intensity gradient of the current self-leakage magnetic field in the ith subinterval of the pipeline along the x axis, the y axis and the z axis; blijx，BlijyAnd BlijzThe magnetic induction gradient components of the self-leakage magnetic field along the x axis, the y axis and the z axis in the last detection of the ith subinterval of the pipeline are shown.
(8) Determining the severity sequencing of the pipe section defects and excavating the detailed inspection pipe section. According to fiThe magnitude of (c) is used to rank the defect status of all segments (m segments in total) of the inspection pipeline (from low to high). Pipe section fiThe smaller the value of (A), the more serious the defect level thereof. After sequencing is finished, firstly, selecting the first and second ranked pipe sections as excavation detailed detection pipe sections, performing excavation and contact detection, evaluating the applicability of the defects according to relevant standards, and stopping excavation detailed detection if the two subintervals meet the applicability evaluation; and if at least one point does not meet the suitability evaluation, continuously selecting two points which are ranked relatively back as the pipe sections for detailed excavation detection, and repeating the operation until the two continuously taken detailed excavation detection points meet the suitability evaluation, and stopping the operation.
Drawings
FIG. 1 is a flow chart of an implementation of the detection method;
FIG. 2 is a schematic diagram of the relative positions of three components of the self-leakage magnetic field of the pipeline and the pipeline;
FIG. 3 illustrates the component of the magnetic induction intensity of the self-leakage magnetic field along the x-axis direction, which is obtained by two times of detection before and after the pipeline;
FIG. 4 illustrates the component of the magnetic induction intensity of the self-leakage magnetic field along the y-axis direction, which is obtained by two times of detection before and after the pipeline;
FIG. 5 illustrates the component of the magnetic induction intensity of the self-leakage magnetic field along the z-axis direction obtained by two times of detection before and after the pipeline.
Detailed Description
The following detailed description is given with reference to the accompanying drawings and examples in order to make the advantages and features of the present invention more readily understandable by those skilled in the art, and to thereby clearly define the scope of the present invention.
The method for detecting the defects of the buried steel pipeline in the whole life cycle mainly comprises eight steps, the flow is shown as the attached figure 1, and the specific steps are as follows:
step one, collecting basic data of the pipeline. The basic data comprises design data, completion data, routes, materials, outer diameters, wall thicknesses, burial depths, cathodic protection devices, station positions, station cathodic protection positions, design pressure and operating pressure of the pipelines, hydraulic slope lines of the pipelines, accident records of the pipelines, detection and maintenance records of the pipelines, stop records of the pipelines and working condition change records of the pipelines.
And step two, dividing the pipe section interval and the sub pipe sections thereof. The whole pipeline is divided into a plurality of pipeline sections, and the pipeline section division is reasonably determined according to pipeline information such as the input and output port position of a detection pipeline, the positions of a heating station, a compressor station and the like, the position of a reducer pipe, the position of a variable wall thickness, the position of a valve, the position of a pipeline direction change, the position of a pipeline with a crossing structure, the position of a pipeline female protection test pile and the like. After the pipeline partition is determined, the sub-pipeline sections in the partition are determined in each pipeline section partition, and the sub-interval is the minimum unit for detecting the pipeline defect. The pipe sections should be no more than 100m and the sub-pipe sections should be no more than 1 m. At least one inspection point is determined for each sub-pipe section in order to accurately locate the position of the defect in a later inspection. And (3) naming the pipe section intervals as S, wherein S is a set formed by all the pipe section intervals, and is shown in a formula (1).
S＝{S1，S2，S3,…Si,…,Sm} (7)
Wherein S is a set formed by intervals of each pipe section, SiIs a pipe section, S1，S2，S3And (4) waiting for m pipe sections, and sequencing from the starting point of the pipeline to the end point of the pipeline according to the mileage of the pipeline.
Each pipeline section consists of a plurality of sub-pipe sections, the sub-pipe sections are assembled to form a pipe section, and the section S is shown as a formula (2)iThe collection expression of (2).
Si＝{Si1，Si2，Si3,…Sij,…,Smn} (8)
In the formula SiFor the section of the pipe formed by the sub-sections, Si1，Si2，Si3The equal n intervals are sorted from the starting point of the pipe section to the end point of the pipe section according to the mileage of the pipe, and SijIs a pipe section SiThe jth sub-segment of (a).
And step three, collecting the self-leakage magnetic field data when the pipeline is completed. After the pipeline is finished and before the pressure test of the pipeline, a three-component magnetic gradiometer is adopted to collect the magnetic induction intensity gradient three-component signal value of the self-leakage magnetic field above the pipeline from the starting point of the pipeline to the terminal point of the pipeline. And sorting the data according to the finished pipeline partitions. Each subinterval contains three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction are respectively used as BCijx，BCijy，BCijzAnd (4) showing.
And step four, collecting the self-leakage magnetic field data during pressure test of the pipeline. When in pressure test, the pressure test pressure of the pipeline and the hydraulic gradient line of the pressure test pipe section are firstly recorded. In the pressure test process, ferromagnetic interference objects along the pipeline are firstly removed, and then a three-component magnetic gradiometer is adopted to collect the magnetic induction intensity of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pressure test pipeline sectionGradient three-component signal. And sorting the data according to the finished pipeline partitions. Each subinterval contains three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BT is used for the dataijx，BTijy，BTijzAnd (4) showing.
And step five, collecting the self-leakage magnetic field data when the pipeline initially runs. Firstly, ferromagnetic interferents along the pipeline are removed, and then a three-component magnetic gradiometer is used for collecting three-component signals of the magnetic induction intensity gradient of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pipeline. And sorting the data according to the finished pipeline partitions. Each subinterval contains three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BS is used respectivelyijx，BSijy，BSijzAnd (4) showing.
And step six, collecting the self-leakage magnetic field data during the operation of the pipeline. Firstly, ferromagnetic interferents along the pipeline are removed, and then a three-component magnetic gradiometer is used for collecting three-component signals of the magnetic induction intensity gradient of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pipeline. And sorting the data according to the finished pipeline partitions. Each subinterval contains three sets of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, respectively using BOijx，BOijy，BOijzAnd (4) showing.
And step seven, calculating the similarity coefficient of the pipeline self-leakage magnetic field signals. Evaluating the defect condition of the pipeline by calculating the similarity coefficient of the self-leakage magnetic field signal of the current pipeline and the self-leakage magnetic field signal (historical data) obtained by last detection, and obtaining the component values S of the similarity coefficient corresponding to each subinterval along the directions of the x axis, the y axis and the z axisix，Siy，SizAnd the average value SiAs shown in equations (3) to (6).
In the formula fiThe average value of the similarity of the ith subinterval of the pipeline is taken as the average value; f. ofix，fiy，fizThe component of the similarity of the ith subinterval of the pipeline along the x axis, the y axis and the z axis; bpijx，BpijyAnd BpijzThe component of the magnetic induction intensity gradient of the current self-leakage magnetic field in the ith subinterval of the pipeline along the x axis, the y axis and the z axis; blijx，BlijyAnd BlijzThe magnetic induction gradient components of the self-leakage magnetic field along the x axis, the y axis and the z axis in the last detection of the ith subinterval of the pipeline are shown.
And step eight, determining the sequencing of the severity of the defects of the pipe sections and excavating detailed inspection pipe sections. According to fiThe magnitude of (c) is used to rank the defect status of all segments (m segments in total) of the inspection pipeline (from low to high). Pipe section fiThe smaller the value of (A), the more serious the defect level thereof. After sequencing is finished, firstly, selecting the first and second ranked pipe sections as excavation detailed detection pipe sections, excavating, carrying out detailed detection on the pipe defect conditions by adopting methods such as metal magnetic memory detection, ultrasonic detection and ray detection, evaluating the applicability of the defects according to relevant standards, and stopping excavation detailed detection if the two subintervals meet the applicability evaluation; and if at least one point does not meet the suitability evaluation, continuously selecting two points which are ranked relatively back as the pipe sections for detailed excavation detection, and repeating the operation until the two continuously taken detailed excavation detection points meet the suitability evaluation, and stopping the operation.
The method of the invention is applied to detect the defects of the pressure test stage of an experimental pipeline, so as to further explain the application principle of the invention:
and step one, collecting basic data of the pipeline according to the method in the step one. The diameter of the pipe is 426mm, the wall thickness is 9.5mm, and the length is 45 m.
And secondly, dividing the pipe section interval and the sub-pipe sections thereof according to the calculation method in the second step. Since the experimental pipe was short, it was divided equally into 6 sections of 7.5m each. Each pipe section is divided into 15 sub-pipe sections, and each sub-pipe section selects a measuring point. I.e. m is 6 and n is 15.
And step three, collecting the self-leakage magnetic field data when the pipeline is completed. Three-component magnetic induction intensity data of the leakage magnetic field above the pipeline are collected by a three-component magnetic gradiometer, and change curves of the three components (an x-axis component, a y-axis component and a z-axis component) of the magnetic induction intensity of the leakage magnetic field along the mileage of the pipeline when the pipeline is finished (without internal pressure) are obtained and are respectively shown as solid lines in figures 3, 4 and 5.
And step four, collecting the self-leakage magnetic field data during pressure test of the pipeline. Similarly, a three-component magnetic gradiometer is used for collecting three-component data of the magnetic induction intensity of the self-leakage magnetic field above the pipeline, and the change curves of the three-component (the x-axis component, the y-axis component and the z-axis component) of the magnetic induction intensity of the self-leakage magnetic field along the mileage of the pipeline during pressure test are respectively shown as dotted lines in fig. 3, 4 and 5.
The fifth and sixth steps are not required for detecting the defects in the pressure test stage of the pipeline.
And step seven, calculating the similarity coefficient of the pipeline self-leakage magnetic field signals. And sorting the three-component data of the magnetic induction intensity of the self-leakage magnetic field obtained before and after the pressure test according to the pipe section subareas, and calculating the component values and the average values of the similarity coefficients of the self-leakage magnetic field of each section of the pipeline along the x axis, the y axis and the z axis.
And step eight, sequencing the severity of the pipe section defects and determining the excavation detailed inspection pipe section. According to the mean value f of the similarity coefficientiThe defect conditions of all the pipe sections (total 6 sections) of the detection pipeline are sequenced (from low to high). Pipe section fiThe smaller the value of (A), the more serious the defect level thereof. The results are shown in Table 1. Selecting a pipe section S according to the sequencing result3And S1And carrying out detailed detection. The detailed detection result shows that the defect condition of the pipe section meets the applicability evaluation standard. Thus, this detection is ended.
TABLE 1 sequencing of severity of pipe segment defects
| Sorting | Pipe section | Coefficient of similarity |
| 1 | S3 | 0.893167 |
| 2 | S1 | 0.926192 |
| 3 | S2 | 0.952753 |
| 4 | S5 | 0.972155 |
| 5 | S4 | 0.977544 |
| 6 | S6 | 0.983419 |
Claims (7)
1. Buried steelThe method for detecting the defects of the buried steel pipeline in the whole life cycle is characterized by mainly comprising the following eight steps: collecting basic data of a pipeline; dividing pipe section intervals and sub-pipe sections thereof; collecting self-leakage magnetic field data when the pipeline is completed; collecting self-leakage magnetic field data during pressure test of the pipeline; collecting self-leakage magnetic field data of the pipeline during initial operation; collecting self-leakage magnetic field data during the operation of the pipeline; step seven, calculating the signal correlation degree of the self-leakage magnetic field of the pipeline, wherein the signal correlation degree of the self-leakage magnetic field of the pipeline is to classify the collected self-leakage magnetic field data according to the interval of the pipeline, and calculate the component values f of the similarity coefficients of the current detection self-leakage magnetic field data and the last detection self-leakage magnetic field data of each pipeline interval along the directions of the x axis, the y axis and the z axisix，fiy，fizAnd the average value fiCalculating according to formulas (3) to (6):
where n is the number of sub-segments in the interval of the ith segment, fiThe average value of the self-leakage magnetic field similarity coefficient of the ith pipe section interval is obtained; f. ofix，fiy，fizThe component of the self-leakage magnetic field similarity coefficient of the ith pipe section interval along the x axis, the y axis and the z axis; bpijx，BpijyAnd BpijzThe magnetic induction gradient of the self-leakage magnetic field detected this time in the ith pipe section interval of the pipeline is along the components of the x axis, the y axis and the z axis; blijx，BlijyAnd BlijzThe component of the magnetic induction intensity gradient of the self-leakage magnetic field along the x axis, the y axis and the z axis in the last detection of the ith subinterval of the pipeline; and step eight, determining defect severity sequencing and excavating detailed inspection pipe sections.
2. The method of claim 1, wherein in step two, the pipe segment interval and its sub-intervals are divided, wherein the division is to determine a reasonable evaluation pipe segment interval according to the input and output port positions of the detection pipe, the positions of the heating station and the compressor station, the position of the reducer pipe, the position of the wall thickness, the position of the valve, the position of the pipe direction change, the position of the pipe with the crossing structure and the position of the pipe cathode protection test pile; after the pipeline partition is determined, sub-pipeline sections in the partition are determined in each pipeline section interval, wherein the sub-pipeline sections are the minimum units for detecting pipeline defects; the interval of the pipe sections is not more than 100m, and the sub-pipe sections are not more than 1 m; each sub-pipe section at least determines one detection point so as to accurately position the position of the defect in later detection; the pipeline interval is named as S, and the S is a set formed by all the pipe section intervals and is shown in a formula (1); each pipe section interval is composed of a plurality of sub pipe sections, and an interval is formed by a set of the sub pipe sections, as shown in formula (2):
S＝{S1，S2，S3,…Si,…,Sm} (1)
Si＝{Si1，Si2，Si3,…Sij,…,Sin} (2)
wherein S is a set formed by intervals of each pipe section, SiIn the interval of pipe sections, S1，S2，S3，…Si…SmSequencing the m pipe section intervals from the starting point of the pipeline to the end point of the pipeline according to the mileage of the pipeline; si1，Si2，Si3，…Sij…SinN sub-pipe sections are sorted from the starting point of the pipe section interval to the end point of the pipe section interval according to the mileage of the pipeline, and SijFor a section S of a pipeiThe jth sub-segment of (a).
3. The method as claimed in claim 1, wherein step three, the self-leakage magnetic field data when the pipeline is completed is collected, characterized in that, before the self-leakage magnetic field is collected, ferromagnetic interferents along the pipeline are removed; then after the pipeline is completed and before pressure testing, collecting magnetic induction intensity gradient three-component signal values of a self-leakage magnetic field above the pipeline from the starting point of the pipeline to the end point of the pipeline by using a three-component magnetic gradiometer; finally, sorting the data according to the finished pipe segment partitions, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BC is used for the data respectivelyijx，BCijy，BCijzAnd (4) showing.
4. The method of claim 1, wherein step four, collect the magnetic field data of the self-leakage while testing the pressure of the pipeline, wherein, before testing the pressure, should clear away the ferromagnetic interfering substance along the pipeline first; then collecting a magnetic induction intensity gradient three-component signal of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pressure testing pipeline section by adopting a three-component magnetic gradiometer; arranging data according to the finished pipe section partitions; each subinterval contains three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BT is used for the dataijx，BTijy，BTijzAnd (4) showing.
5. The method of claim 1, wherein step five, the self-leakage magnetic field data of the initial operation of the pipeline is collected, characterized in that ferromagnetic interferents along the pipeline should be removed first; then collecting a magnetic induction intensity gradient three-component signal of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pipeline by using a three-component magnetic gradiometer; finally, sorting the data according to the finished pipe segment partitions, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and the data are respectively sorted by using a BS (base station)ijx，BSijy，BSijzAnd (4) showing.
6. The method of claim 1, wherein step six, self-leakage magnetic field data is collected during operation of the pipeline, wherein ferromagnetic interferents along the pipeline are first cleared; then collecting a magnetic induction intensity gradient three-component signal of the self-leakage magnetic field of the pipeline from the starting point to the end point of the pipeline by using a three-component magnetic gradiometer; and finally, sorting the data according to the finished pipe segment partitions, wherein each subinterval respectively comprises three groups of data, namely data in the x-axis direction, the y-axis direction and the z-axis direction, and BO is respectively usedijx，BOijy，BOijzAnd (4) showing.
7. The method of claim 1 wherein eight of the steps of determining the severity of the defects in the pipe sections, sequencing and excavating the detailing pipe sections, wherein f is the orderiThe value of (3) is used for sequencing the defect conditions of the m pipe section intervals of the detection pipeline from low to high; pipe section fiThe smaller the value of (A), the more serious the defect level thereof; after sequencing is finished, firstly, selecting the first and second ranked pipe sections as excavation detailed detection pipe sections, performing excavation and contact detection, evaluating the applicability of the defects according to relevant standards, and stopping excavation detailed detection if the two subintervals meet the applicability evaluation; and if at least one point does not meet the suitability evaluation, continuously selecting two points which are ranked relatively back as the pipe sections for detailed excavation detection, and repeating the operation until the two continuously taken detailed excavation detection points meet the suitability evaluation, and stopping the operation.
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| CN112329590B (en) * | 2020-10-30 | 2024-05-10 | 中海石油(中国)有限公司 | Pipeline assembly detection system and detection method |
| CN113063844A (en) * | 2021-03-25 | 2021-07-02 | 西南石油大学 | Method for judging pipeline safety based on non-contact detection and comparison of pipeline magnetic field strength at different times |
| CN113758528A (en) * | 2021-09-22 | 2021-12-07 | 深圳前海运通水务有限公司 | Comprehensive processing method for data formed after detection of full water pipeline by using multiple devices |
| CA3235329A1 (en) * | 2021-10-19 | 2023-04-27 | Igor Sergeevich KOLESNIKOV | In-line device for determining mechanical stresses in pipelines |
| WO2024016162A1 (en) * | 2022-07-19 | 2024-01-25 | 烟台杰瑞石油装备技术有限公司 | Coiled tubing string full-life-cycle management method and system, and storage medium |
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