A method and system for predicting oil and gas pipeline life

Abstract

The present invention relates to the technical field of oil and gas pipelines, and discloses a method and system for predicting the life of an oil and gas pipeline. The method comprises generating a detection light beam, emitting the detection light beam to an area to be detected of the oil and gas pipeline, obtaining a plurality of detection information corresponding to the detection light beam, generating a comparison light beam, emitting the comparison light beam to a standard comparison scene, dividing the comparison light beam into a first comparison light beam and a second comparison light beam, and determining first light beam data and second light beam data; constructing a comparison light beam data set according to the first light beam data and the second light beam data, and judging whether the area to be detected of the oil and gas pipeline has defects based on the detection information and the comparison light beam data set; when defects exist in the area to be detected of the oil and gas pipeline, calculating a defect level factor of the area to be detected, and performing life prediction based on the defect level factor, so that defects of the oil and gas pipeline can be accurately detected, and life prediction can be performed based on the defect level factor, thereby ensuring the safety and reliability of the use of the oil and gas pipeline.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas pipelines, and in particular to a method and system for predicting the life of an oil and gas pipeline. Background Art

[0002] After long-term use, pipelines are corroded by humid air, internal electrolytes and other substances, resulting in frequent accidents such as energy leakage and oil and gas pipeline explosions caused by defects such as corrosion, cracks or deformation, posing a huge threat to people's lives and property. Oil and gas pipeline leakage and explosion accidents not only seriously pollute the environment, but also cause casualties, causing immeasurable double harm. At present, many oil and gas pipelines in service in my country have entered a stage of fatigue and frequent accidents. In order to ensure the long-term safe operation of oil and gas pipelines, pipelines must be regularly inspected and maintained to ensure safe and effective operation of oil and gas pipelines during transportation. The determination of the degree of hazard of pipeline structural abnormalities and defects and the prediction of the remaining life of the pipeline are of great significance to the country's economic development and industrialization construction.

[0003] Traditional detection technology is mainly three-axis high-definition magnetic flux leakage detection technology. Three-axis high-definition magnetic flux leakage internal detection adds two sets of orthogonally placed Hall sensors on the basis of the original single sensor to detect the size of the leakage magnetic field at the defect of the pipe wall, and measures the axial, circumferential and radial leakage flux data respectively, which are used to determine the three-dimensional leakage magnetic field vector and describe the defects more clearly. However, traditional detection technology can only detect some volume defects in the girth weld, such as incomplete welding, excessive grinding, large openings of incomplete fusion and incomplete penetration, and large-sized bite edges, etc., and cannot detect defects such as small openings of incomplete fusion and incomplete penetration, cracks, and small-sized bite edges. Moreover, it cannot distinguish the depth of defects, making it difficult to use for applicability evaluation. Summary of the invention

[0004] In view of this, the present invention proposes a method and system for predicting the life of an oil and gas pipeline, aiming to solve the problem in the current technology that it is impossible to accurately detect defects in oil and gas pipelines and to predict the remaining life of oil and gas pipelines.

[0005] The present invention proposes a method for predicting the life of an oil and gas pipeline, comprising:

[0006] Generate a detection beam, emit the detection beam to the area to be detected of the oil and gas pipeline, and obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the area to be detected;

[0007] Generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam;

[0008] constructing a comparison beam data set according to the first beam data and the second beam data, and judging whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set;

[0009] When there are defects in the area to be inspected of the oil and gas pipeline, the defect level factor of the area to be inspected is calculated, and the life prediction is performed based on the defect level factor.

[0010] Furthermore, when the detection light beam is emitted to the area to be detected of the oil and gas pipeline, it includes:

[0011] Splitting the detection light beam to obtain a plurality of second detection light beams, wherein each second detection light beam corresponds to a light beam detection point position one by one;

[0012] Acquire beam detection information corresponding to each second detection beam, wherein the beam detection information includes smoothness information and inclination information;

[0013] Analyze all the smoothness information and the inclination information to determine the maximum smoothness information, the minimum smoothness information, the maximum inclination information and the minimum inclination information;

[0014] Calculating a smoothness difference between the maximum smoothness information and the minimum smoothness information;

[0015] Calculating a difference in inclination between the maximum inclination information and the minimum inclination information;

[0016] configuring a first weight for the smoothness difference, configuring a second weight for the inclination difference, calculating a first product value of the first weight and the smoothness difference, and calculating a second product value of the second weight and the inclination difference;

[0017] Calculating a product value and a value of the first product value and the second product value;

[0018] When the product value and value are less than the preset product value and value, the current light beam intensity is not adjusted;

[0019] When the product value is greater than or equal to the preset product value and value, the current light beam intensity is adjusted.

[0020] Furthermore, when the current light beam intensity is adjusted, it includes:

[0021] Extract all smoothness information and aggregate them to generate smoothness clusters;

[0022] Determine the cluster center of the smoothness cluster, determine the distance from each piece of smoothness information to the cluster center, select the distance greater than or equal to the preset distance, and generate a first processing set;

[0023] Determine a standard deviation of the smoothness cluster, select smoothness information greater than or equal to the standard deviation, and generate a second processing set;

[0024] Determine whether the first processing set and the second processing set have an intersection, if so, extract the intersection to obtain a first set to be processed, if not, use the first processing set as the first set to be processed;

[0025] Extract all the inclination information and aggregate them to generate inclination clusters;

[0026] Analyzing the inclination clusters, and determining a second set to be processed based on the analysis result;

[0027] Calculating an adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set;

[0028] Calculating a product value of the adjustment coefficient and the current light beam intensity and using the product value as the adjusted light beam intensity;

[0029] When analyzing the inclination clusters and determining the second to-be-processed set based on the analysis result, the method includes:

[0030] Determine the cluster center of the inclination cluster, determine the distance from each inclination information to the cluster center, select the distance greater than or equal to the preset distance, and generate a third processing set;

[0031] Determine the standard deviation of the inclination cluster, filter the inclination information greater than or equal to the standard deviation, and generate a fourth processing set, determine whether the third processing set and the fourth processing set have an intersection, if so, extract the intersection to obtain a second set to be processed, if not, use the third processing set as the second set to be processed;

[0032] When calculating the adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set, it includes:

[0033] Calculating a mean value of the smoothness information of the first set to be processed, and calculating a mean value of the inclination information of the second set to be processed;

[0034] ;

[0035] Among them, h is the adjustment coefficient, n1 is the number of smoothness information in the first set to be processed, a i is the i-th smoothness information in the first set to be processed, a 均 is the mean of smoothness information, S i is the weight corresponding to the i-th smoothness information, n2 is the number of inclination information in the second set to be processed, ej is the jth inclination information in the second set to be processed, e 均 is the mean value of the slope information, B j is the weight corresponding to the j-th inclination information.

[0036] Further, when a comparison beam data set is constructed according to the first beam data and the second beam data, and whether there is a defect in the area to be inspected of the oil and gas pipeline is determined based on the detection information and the comparison beam data set, it includes:

[0037] Calculating a first average value of all first light beam data, and constructing a first value set according to an absolute value of a difference between each first light beam data and the first average value;

[0038] Calculating a second average value of all the second light beam data, and constructing a second value set according to an absolute value of a difference between each second light beam data and the second average value;

[0039] Performing a corresponding sum operation on the first value set and the second value set to obtain the comparison beam data set, wherein the comparison beam data set includes a plurality of difference absolute value sum values;

[0040] Calculate a third average value of all detection information, and calculate a numerical ratio of the absolute value sum of the difference values ​​to the third average value;

[0041] It is determined whether there are defects in the area to be inspected of the oil and gas pipeline based on the obtained numerical ratio.

[0042] Further, when judging whether there is a defect in the area to be inspected of the oil and gas pipeline according to the obtained numerical ratio, it includes:

[0043] Obtain a preset numerical ratio, extract all numerical ratios that are greater than or equal to the preset numerical ratio, and count the number of corresponding numerical ratios;

[0044] When the number of the numerical ratios is greater than or equal to the preset number of numerical ratios, it is determined that there are defects in the area to be inspected of the oil and gas pipeline;

[0045] When the number of the numerical ratios is less than the preset number of numerical ratios, it is determined that there is no defect in the area to be inspected of the oil and gas pipeline.

[0046] Furthermore, when calculating the defect level factor of the area to be inspected, it includes:

[0047] The preset numerical ratio is configured with a first calculation coefficient k1 to obtain k1×g, where k1=1.2 and g is the preset numerical ratio;

[0048] A second calculation coefficient k2 is configured for the preset numerical ratio to obtain k2×g, wherein k2=1.4;

[0049] When g<preset numerical value ratio≤k1×g, a first processing sequence is generated according to the corresponding preset numerical value ratio;

[0050] When k1×g<preset numerical value ratio≤k2×g, a second processing sequence is generated according to the corresponding preset numerical value ratio;

[0051] When k2×g<preset numerical value ratio, generate a third processing sequence according to the corresponding preset numerical value ratio;

[0052] The defect level factor of the area to be inspected is calculated based on the first processing sequence, the second processing sequence and the third processing sequence.

[0053] Further, when calculating the defect level factor of the area to be inspected based on the first processing sequence, the second processing sequence and the third processing sequence, it includes:

[0054] counting a first number of the first processing sequence, a second number of the second processing sequence, and a third number of the third processing sequence;

[0055] The defect level factor of the area to be inspected is calculated according to the following formula:

[0056] ;

[0057] Wherein, L is the defect level factor, P1 is the first quantity, P2 is the second quantity, P3 is the third quantity, and ln is the sign of the logarithmic function.

[0058] Furthermore, when performing life prediction based on the defect level factor, it includes:

[0059] The predicted life of the oil and gas pipeline is calculated according to the following formula:

[0060] Y = 18.56-5.56 × L;

[0061] Where Y is the predicted life span.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] Generate a detection beam, emit the detection beam to the area to be detected of the oil and gas pipeline, obtain multiple detection information corresponding to the detection beam, generate a comparison beam, emit the comparison beam to a standard comparison scene, divide the comparison beam into a first comparison beam and a second comparison beam, and determine the first beam data and the second beam data; construct a comparison beam data set according to the first beam data and the second beam data, and judge whether there is a defect in the area to be detected of the oil and gas pipeline based on the detection information and the comparison beam data set; when there is a defect in the area to be detected of the oil and gas pipeline, calculate the defect level factor of the area to be detected, and perform life prediction based on the defect level factor, so as to accurately detect the defects of the oil and gas pipeline, and perform life prediction based on the defect level factor, so as to ensure the safety and reliability of the oil and gas pipeline.

[0064] On the other hand, the present application also provides an oil and gas pipeline life prediction system, comprising:

[0065] A first generating module is used to generate a detection beam, emit the detection beam to a to-be-detected area of ​​the oil and gas pipeline, and obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the to-be-detected area;

[0066] A second generating module is used to generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam;

[0067] a defect judgment module, configured to construct a comparison beam data set according to the first beam data and the second beam data, and judge whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set;

[0068] The life prediction module is used to calculate the defect level factor of the area to be detected when there are defects in the area to be detected of the oil and gas pipeline, and to perform life prediction based on the defect level factor.

[0069] It is understandable that the oil and gas pipeline life prediction system and method provided above have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0071] Figure 1A schematic diagram of a flow chart of a method for predicting the life of an oil and gas pipeline provided by an embodiment of the present invention;

[0072] Figure 2 A schematic diagram of the structure of an oil and gas pipeline life prediction system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0074] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides a method for predicting the life of an oil and gas pipeline, including:

[0075] S110: Generate a detection beam, and emit the detection beam to a to-be-detected area of ​​the oil and gas pipeline to obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the to-be-detected area;

[0076] In this embodiment, the beam detection points are a series of preset positions on the oil and gas pipeline for receiving the detection beam to obtain the measurement data of these specific positions. The setting of these points is based on the structure and detection requirements. In the detection of oil and gas pipelines, it is first necessary to identify the key detection areas, such as welds, elbows, valve connections and other parts where leakage or corrosion may occur. In order to ensure the comprehensiveness and accuracy of the detection, it is necessary to set points at key parts of the pipeline and evenly distributed intervals. This helps to avoid missing any potential problem areas.

[0077] In this embodiment, the detection information includes vibration velocity, vibration displacement, vibration frequency, acceleration, etc.

[0078] In some embodiments of the present application, when the detection light beam is emitted to the area to be detected of the oil and gas pipeline, it includes:

[0079] Splitting the detection light beam to obtain a plurality of second detection light beams, wherein each second detection light beam corresponds to a light beam detection point position one by one;

[0080] Acquire beam detection information corresponding to each second detection beam, wherein the beam detection information includes smoothness information and inclination information;

[0081] Analyze all the smoothness information and the inclination information to determine the maximum smoothness information, the minimum smoothness information, the maximum inclination information and the minimum inclination information;

[0082] Calculating a smoothness difference between the maximum smoothness information and the minimum smoothness information;

[0083] Calculating a difference in inclination between the maximum inclination information and the minimum inclination information;

[0084] configuring a first weight for the smoothness difference, configuring a second weight for the inclination difference, calculating a first product value of the first weight and the smoothness difference, and calculating a second product value of the second weight and the inclination difference;

[0085] Calculating a product value and a value of the first product value and the second product value;

[0086] When the product value and value are less than the preset product value and value, the current light beam intensity is not adjusted;

[0087] When the product value is greater than or equal to the preset product value and value, the current light beam intensity is adjusted.

[0088] In this embodiment, a laser beam can be divided into multiple independent second detection beams by using optical elements such as gratings, beam splitters or acousto-optic modules, etc. These second detection beams retain certain characteristics of the original beam, such as wavelength and polarization state, but can be independently controlled and directed to different detection points.

[0089] In this embodiment, the smoothness information refers to the flatness of the detected surface at a microscopic scale. This can be evaluated by detecting the quality of the reflected light beam. If the surface is very smooth, the reflected light will be relatively uniform; otherwise, scattering and uneven light intensity will occur. Here, the smoothness information is a specific value, and the inclination information reflects the inclination angle of the detected surface relative to the reference plane. Here, the inclination information is a specific value.

[0090] In this embodiment, the first weight is 0.6 and the second weight is 0.4.

[0091] In this embodiment, the preset product value and value is 1000.

[0092] The beneficial effect of the above technical solution is that the present invention determines whether the light beam intensity needs to be adjusted through the product value and the preset product value and the value, thereby ensuring the accuracy of the collected detection information and avoiding the collection error of the detection information, which in turn causes the defect judgment error.

[0093] In some embodiments of the present application, when adjusting the current light beam intensity, it includes:

[0094] Extract all smoothness information and aggregate them to generate smoothness clusters;

[0095] Determine the cluster center of the smoothness cluster, determine the distance from each piece of smoothness information to the cluster center, select the distance greater than or equal to the preset distance, and generate a first processing set;

[0096] Determine a standard deviation of the smoothness cluster, select smoothness information greater than or equal to the standard deviation, and generate a second processing set;

[0097] Determine whether the first processing set and the second processing set have an intersection, if so, extract the intersection to obtain a first set to be processed, if not, use the first processing set as the first set to be processed;

[0098] Extract all the inclination information and aggregate them to generate inclination clusters;

[0099] Analyzing the inclination clusters, and determining a second set to be processed based on the analysis result;

[0100] Calculating an adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set;

[0101] Calculating a product value of the adjustment coefficient and the current light beam intensity and using the product value as the adjusted light beam intensity;

[0102] When analyzing the inclination clusters and determining the second to-be-processed set based on the analysis result, the method includes:

[0103] Determine the cluster center of the inclination cluster, determine the distance from each inclination information to the cluster center, select the distance greater than or equal to the preset distance, and generate a third processing set;

[0104] Determine the standard deviation of the inclination cluster, filter the inclination information greater than or equal to the standard deviation, and generate a fourth processing set, determine whether the third processing set and the fourth processing set have an intersection, if so, extract the intersection to obtain a second set to be processed, if not, use the third processing set as the second set to be processed;

[0105] In this embodiment, the method for determining the cluster center includes random initialization, selection of the farthest point, K-Means, iterative optimization, etc., which is selected according to actual needs.

[0106] In this embodiment, the cluster center of the inclination cluster is determined, and the distance from each inclination information to the cluster center is determined, the distance greater than or equal to the preset distance is screened, and a third processing set is generated; the standard deviation of the inclination cluster is determined, the inclination information greater than or equal to the standard deviation is screened, and a fourth processing set is generated, and it is determined whether the third processing set and the fourth processing set have an intersection. If so, the intersection is extracted to obtain a second set to be processed. If not, the third processing set is used as the second set to be processed.

[0107] The beneficial effect of the above technical solution is that the present invention calculates the adjustment coefficient of the current light beam intensity according to the first set to be processed and the second set to be processed, so as to realize the targeted adjustment of the light beam intensity and ensure the accuracy of the collection of detection information.

[0108] In some embodiments of the present application, when calculating the adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set, the method includes:

[0109] Calculating a mean value of the smoothness information of the first set to be processed, and calculating a mean value of the inclination information of the second set to be processed;

[0110] ;

[0111] Among them, h is the adjustment coefficient, n1 is the number of smoothness information in the first set to be processed, a i is the i-th smoothness information in the first set to be processed, a 均 is the mean of smoothness information, S i is the weight corresponding to the i-th smoothness information, n2 is the number of inclination information in the second set to be processed, e j is the jth inclination information in the second set to be processed, e 均 is the mean value of the slope information, B j is the weight corresponding to the j-th inclination information.

[0112] S120: Generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam;

[0113] In this embodiment, the standard comparison scene refers to an area to be inspected where no defects exist, and corresponding light beam detection points are also set in the standard comparison scene.

[0114] S130: constructing a comparison beam data set according to the first beam data and the second beam data, and judging whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set;

[0115] In some embodiments of the present application, when a comparison beam data set is constructed according to the first beam data and the second beam data, and whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline is determined based on the detection information and the comparison beam data set, the method includes:

[0116] Calculating a first average value of all first light beam data, and constructing a first value set according to an absolute value of a difference between each first light beam data and the first average value;

[0117] Calculating a second average value of all the second light beam data, and constructing a second value set according to an absolute value of a difference between each second light beam data and the second average value;

[0118] Performing a corresponding sum operation on the first value set and the second value set to obtain the comparison beam data set, wherein the comparison beam data set includes a plurality of difference absolute value sum values;

[0119] Calculate a third average value of all detection information, and calculate a numerical ratio of the absolute value sum of the difference values ​​to the third average value;

[0120] It is determined whether there are defects in the area to be inspected of the oil and gas pipeline based on the obtained numerical ratio.

[0121] In this embodiment, the light beam data is consistent with the above-mentioned detection information.

[0122] In this embodiment, the average value of all vibration frequencies is calculated, and then the difference between each vibration frequency and the average value is calculated. Finally, the absolute value is taken to obtain the absolute value of the difference, and the absolute value of the difference of the remaining light beam data is calculated to finally construct the first value set and the second value set.

[0123] In this embodiment, the corresponding summing operation is as follows: for example, the absolute value of the vibration frequency difference in the first value set and the absolute value of the vibration frequency difference in the second value set are summed.

[0124] In this embodiment, a plurality of third average values ​​can also be obtained, and correspond one to one with the absolute value and the value of the difference.

[0125] The beneficial effect of the above technical solution is that the present invention judges whether there are defects in the area to be inspected of the oil and gas pipeline based on the obtained numerical ratio, thereby achieving accurate judgment of defects and avoiding errors in manual judgment. It can not only judge defects such as incomplete welding, excessive grinding, lack of fusion and lack of penetration with large openings, and large-sized undercuts, but also defects such as lack of fusion and lack of penetration with small openings, cracks, and small-sized undercuts.

[0126] In some embodiments of the present application, when judging whether there is a defect in the area to be inspected of the oil and gas pipeline according to the obtained numerical ratio, it includes:

[0127] Obtain a preset numerical ratio, extract all numerical ratios that are greater than or equal to the preset numerical ratio, and count the number of corresponding numerical ratios;

[0128] When the number of the numerical ratios is greater than or equal to the preset number of numerical ratios, it is determined that there are defects in the area to be inspected of the oil and gas pipeline;

[0129] When the number of the numerical ratios is less than the preset number of numerical ratios, it is determined that there is no defect in the area to be inspected of the oil and gas pipeline.

[0130] In this embodiment, the preset numerical ratio is 150.

[0131] In this embodiment, the number of preset numerical ratios is 6.

[0132] S140: When there are defects in the area to be inspected of the oil and gas pipeline, a defect level factor of the area to be inspected is calculated, and life prediction is performed based on the defect level factor.

[0133] In some embodiments of the present application, when calculating the defect level factor of the area to be inspected, it includes:

[0134] The preset numerical ratio is configured with a first calculation coefficient k1 to obtain k1×g, where k1=1.2 and g is the preset numerical ratio;

[0135] A second calculation coefficient k2 is configured for the preset numerical ratio to obtain k2×g, wherein k2=1.4;

[0136] When g<preset numerical value ratio≤k1×g, a first processing sequence is generated according to the corresponding preset numerical value ratio;

[0137] When k1×g<preset numerical value ratio≤k2×g, a second processing sequence is generated according to the corresponding preset numerical value ratio;

[0138] When k2×g<preset numerical value ratio, generate a third processing sequence according to the corresponding preset numerical value ratio;

[0139] The defect level factor of the area to be inspected is calculated based on the first processing sequence, the second processing sequence and the third processing sequence.

[0140] The beneficial effect of the above technical solution is that the present invention calculates the defect level factor of the area to be inspected based on the first processing sequence, the second processing sequence and the third processing sequence, which can lay the foundation for the life prediction of the oil and gas pipeline, provide data support, and ensure the prediction accuracy.

[0141] In some embodiments of the present application, when calculating the defect level factor of the area to be inspected based on the first processing sequence, the second processing sequence, and the third processing sequence, it includes:

[0142] counting a first number of the first processing sequence, a second number of the second processing sequence, and a third number of the third processing sequence;

[0143] The defect level factor of the area to be inspected is calculated according to the following formula:

[0144] ;

[0145] Wherein, L is the defect level factor, P1 is the first quantity, P2 is the second quantity, P3 is the third quantity, and ln is the sign of the logarithmic function.

[0146] In some embodiments of the present application, when performing life prediction based on the defect level factor, it includes:

[0147] The predicted life of the oil and gas pipeline is calculated according to the following formula:

[0148] Y = 18.56-5.56 × L;

[0149] Where Y is the predicted life span.

[0150] The beneficial effect of the above technical solution is that the present invention can accurately detect defects in oil and gas pipelines, and predict the life span based on defect level factors, thereby ensuring the safety and reliability of the oil and gas pipelines.

[0151] like Figure 2 As shown, in another preferred embodiment based on the above embodiment, this embodiment provides an oil and gas pipeline life prediction system, including:

[0152] A first generating module is used to generate a detection beam, emit the detection beam to a to-be-detected area of ​​the oil and gas pipeline, and obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the to-be-detected area;

[0153] A second generating module is used to generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam;

[0154] a defect judgment module, configured to construct a comparison beam data set according to the first beam data and the second beam data, and judge whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set;

[0155] The life prediction module is used to calculate the defect level factor of the area to be detected when there are defects in the area to be detected of the oil and gas pipeline, and to perform life prediction based on the defect level factor.

[0156] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0157] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0158] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0159] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for predicting the life of an oil and gas pipeline, characterized in that: include: Generate a detection beam, emit the detection beam to the area to be detected of the oil and gas pipeline, and obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the area to be detected; Generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam; constructing a comparison beam data set according to the first beam data and the second beam data, and judging whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set; When there are defects in the area to be inspected of the oil and gas pipeline, a defect level factor of the area to be inspected is calculated, and life prediction is performed based on the defect level factor; When the detection light beam is emitted to the area to be detected in the oil and gas pipeline, it includes: Splitting the detection light beam to obtain a plurality of second detection light beams, wherein each second detection light beam corresponds to a light beam detection point position one by one; Acquire beam detection information corresponding to each second detection beam, wherein the beam detection information includes smoothness information and inclination information; Analyze all the smoothness information and the inclination information to determine the maximum smoothness information, the minimum smoothness information, the maximum inclination information and the minimum inclination information; Calculating a smoothness difference between the maximum smoothness information and the minimum smoothness information; Calculating a difference in inclination between the maximum inclination information and the minimum inclination information; configuring a first weight for the smoothness difference, configuring a second weight for the inclination difference, calculating a first product value of the first weight and the smoothness difference, and calculating a second product value of the second weight and the inclination difference; Calculating a product value and a value of the first product value and the second product value; When the product value and value are less than the preset product value and value, the current light beam intensity is not adjusted; When the product value is greater than or equal to the preset product value and value, the current light beam intensity is adjusted.

2. The oil and gas pipeline life prediction method according to claim 1, characterized in that: When adjusting the current beam intensity, include: Extract all smoothness information and aggregate them to generate smoothness clusters; Determine the cluster center of the smoothness cluster, determine the distance from each piece of smoothness information to the cluster center, select the distance greater than or equal to the preset distance, and generate a first processing set; Determine a standard deviation of the smoothness cluster, select smoothness information greater than or equal to the standard deviation, and generate a second processing set; Determine whether the first processing set and the second processing set have an intersection, if so, extract the intersection to obtain a first set to be processed, if not, use the first processing set as the first set to be processed; Extract all the inclination information and aggregate them to generate inclination clusters; Analyzing the inclination clusters, and determining a second set to be processed based on the analysis result; Calculating an adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set; Calculating a product value of the adjustment coefficient and the current light beam intensity and using the product value as the adjusted light beam intensity; When analyzing the inclination clusters and determining the second to-be-processed set based on the analysis result, the method includes: Determine the cluster center of the inclination cluster, determine the distance from each inclination information to the cluster center, select the distance greater than or equal to the preset distance, and generate a third processing set; Determine the standard deviation of the inclination cluster, filter the inclination information greater than or equal to the standard deviation, and generate a fourth processing set, determine whether the third processing set and the fourth processing set have an intersection, if so, extract the intersection to obtain a second set to be processed, if not, use the third processing set as the second set to be processed; When calculating the adjustment coefficient of the current light beam intensity according to the first to-be-processed set and the second to-be-processed set, it includes: Calculating a mean value of the smoothness information of the first set to be processed, and calculating a mean value of the inclination information of the second set to be processed; ； Among them, h is the adjustment coefficient, n1 is the number of smoothness information in the first set to be processed, a i is the i-th smoothness information in the first set to be processed, a 均 is the mean of smoothness information, S i is the weight corresponding to the i-th smoothness information, n2 is the number of inclination information in the second set to be processed, e j is the jth inclination information in the second set to be processed, e 均 is the mean value of the slope information, B j is the weight corresponding to the j-th inclination information.

3. The oil and gas pipeline life prediction method according to claim 1 is characterized in that: When a comparison beam data set is constructed according to the first beam data and the second beam data, and whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline is determined based on the detection information and the comparison beam data set, the method includes: Calculating a first average value of all first light beam data, and constructing a first value set according to an absolute value of a difference between each first light beam data and the first average value; Calculating a second average value of all the second light beam data, and constructing a second value set according to an absolute value of a difference between each second light beam data and the second average value; Performing a corresponding sum operation on the first value set and the second value set to obtain the comparison beam data set, wherein the comparison beam data set includes a plurality of difference absolute value sum values; Calculate a third average value of all detection information, and calculate a numerical ratio of the absolute value sum of the difference values ​​to the third average value; It is determined whether there are defects in the area to be inspected of the oil and gas pipeline based on the obtained numerical ratio.

4. The oil and gas pipeline life prediction method according to claim 3 is characterized in that: When judging whether there is a defect in the area to be inspected of the oil and gas pipeline according to the obtained numerical ratio, it includes: Obtain a preset numerical ratio, extract all numerical ratios that are greater than or equal to the preset numerical ratio, and count the number of corresponding numerical ratios; When the number of the numerical ratios is greater than or equal to the preset number of numerical ratios, it is determined that there are defects in the area to be inspected of the oil and gas pipeline; When the number of the numerical ratios is less than the preset number of numerical ratios, it is determined that there are no defects in the area to be inspected of the oil and gas pipeline.

5. The oil and gas pipeline life prediction method according to claim 4 is characterized in that: When calculating the defect level factor of the area to be inspected, it includes: The preset numerical ratio is configured with a first calculation coefficient k1 to obtain k1×g, where k1=1.2 and g is the preset numerical ratio; A second calculation coefficient k2 is configured for the preset numerical ratio to obtain k2×g, wherein k2=1.4; When g<preset numerical value ratio≤k1×g, a first processing sequence is generated according to the corresponding preset numerical value ratio; When k1×g<preset numerical value ratio≤k2×g, a second processing sequence is generated according to the corresponding preset numerical value ratio; When k2×g<preset numerical value ratio, generate a third processing sequence according to the corresponding preset numerical value ratio; The defect level factor of the area to be inspected is calculated based on the first processing sequence, the second processing sequence and the third processing sequence.

6. The oil and gas pipeline life prediction method according to claim 5 is characterized in that: When calculating the defect level factor of the area to be inspected based on the first processing sequence, the second processing sequence and the third processing sequence, it includes: counting a first number of the first processing sequence, a second number of the second processing sequence, and a third number of the third processing sequence; The defect level factor of the area to be inspected is calculated according to the following formula: ; Wherein, L is the defect level factor, P1 is the first quantity, P2 is the second quantity, P3 is the third quantity, and ln is the sign of the logarithmic function.

7. The oil and gas pipeline life prediction method according to claim 6 is characterized in that: When life prediction is performed based on the defect level factors, it includes: The predicted life of the oil and gas pipeline is calculated according to the following formula: Y = 18.56-5.56 × L; Where Y is the predicted life span.

8. An oil and gas pipeline life prediction system, applied to the oil and gas pipeline life prediction method according to any one of claims 1 to 7, characterized in that: include: A first generating module is used to generate a detection beam, emit the detection beam to a to-be-detected area of ​​the oil and gas pipeline, and obtain a plurality of detection information corresponding to the detection beam, wherein a plurality of beam detection points are preset in the to-be-detected area; A second generating module is used to generate a contrast beam, emit the contrast beam to a standard contrast scene, divide the contrast beam into a first contrast beam and a second contrast beam, and determine first beam data and second beam data of the first contrast beam and the second contrast beam; a defect judgment module, configured to construct a comparison beam data set according to the first beam data and the second beam data, and judge whether there is a defect in the to-be-detected area of ​​the oil and gas pipeline based on the detection information and the comparison beam data set; The life prediction module is used to calculate the defect level factor of the area to be detected when there are defects in the area to be detected of the oil and gas pipeline, and to perform life prediction based on the defect level factor.

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