Pipeline deformation detection method and system

Abstract

The invention relates to a pipeline deformation detection method and system, and relates to the field of pipeline detection technologies, and the method comprises the steps: obtaining a pipeline detection inner contour; creating a detection point which can move randomly on the pipeline detection inner contour, and determining an adjacent point which is separated from the detection point by a fixed distance; establishing a detection ray penetrating through the adjacent points by taking the detection point as a starting point, and determining a detection angular bisector; convex points are defined according to the detection angular bisector, and a convex area is determined according to the convex points; the cleaning device is controlled to move to the protruding area for operation, and foreign matter cleaning resistance is obtained; judging whether the foreign matter cleaning resistance is greater than upper limit resistance; if not, the cleaning device is controlled to continue working, and the pipeline detection inner contour is obtained again after the pipeline detection inner contour completely passes through the protruding area so that the pipeline detection inner contour can be uploaded to the information collection center. The method has the effect of conveniently and accurately determining the deformation condition of the pipeline.

Description

Technical Field

[0001] The present application relates to the field of pipeline detection technology, and in particular to a pipeline deformation detection method and system. Background Art

[0002] Pipeline transportation is a relatively stable and reliable mode of transportation. Pipeline deformation is a common problem encountered during the use of pipelines. Pipeline deformation has a great impact on the pipeline. Long-term pipeline deformation will affect the normal transportation of liquid in the pipeline and even cause the pipeline to rupture. Therefore, it is necessary to detect pipeline deformation during pipeline maintenance. This detection mainly refers to the detection of pipeline geometric deformation by measuring the inner diameter of the pipeline.

[0003] In the related art, the method for detecting the inner diameter of a pipeline is usually to insert a pipeline inner diameter detection trolley with a sensor into the pipeline mouth. The detection trolley advances by performing circular motion along the inner wall of the pipeline. During the advancement, the pipeline inner diameter detection trolley uses a laser sensor to measure the inner diameter of the pipe wall, and uses a linear displacement sensor to measure its own position. The position of the trolley is captured and its trajectory is recorded in real time by a computer or other processing equipment, so as to obtain the inner diameter, roundness and internal contour of the entire pipeline.

[0004] With respect to the above-mentioned related technologies, the inventors believe that when a bulge is detected on the internal contour of the pipeline, it is impossible to effectively determine whether the bulge is caused by pipeline deformation or accumulation of transported impurities in the pipeline, and thus it is impossible to effectively and accurately determine the specific deformation of the pipeline, and there is still room for improvement. Summary of the invention

[0005] In order to facilitate a more accurate determination of pipeline deformation, the present application provides a pipeline deformation detection method and system.

[0006] In a first aspect, the present application provides a pipeline deformation detection method, which adopts the following technical solution: A pipeline deformation detection method, comprising: Obtain the pipeline detection inner contour of the pipeline; Creating a randomly movable detection point on the inner contour of the pipeline detection, and determining an adjacent point on the inner contour of the pipeline detection that is separated from the detection point by a preset fixed distance; A detection ray is established with the detection point as the starting point and passes through the adjacent points, and the detection angle bisector is determined based on the two detection rays; The detection point where the detection angle bisector intersects the pipeline detection inner contour only at the detection point is defined as a convex point, and the convex area is determined according to each convex point; Control the preset cleaning device to move to the raised area for operation and obtain the foreign matter cleaning resistance in real time; Determine whether the resistance to foreign body cleaning is greater than the preset upper limit resistance; If the foreign matter cleaning resistance is greater than the upper limit resistance, the cleaning device is controlled to stop working and the pipeline detection inner contour is obtained again to upload the pipeline detection inner contour to a preset information collection center; If the foreign body cleaning resistance is not greater than the upper limit resistance, the cleaning device is controlled to continue operating, and after completely passing through the raised area, the pipeline detection inner contour is obtained again to upload the pipeline detection inner contour to the information collection center.

[0007] Optionally, the step of determining the raised area according to each raised point includes: Get the convex distance between adjacent convex points; The convex points whose convex distance is less than the preset adjacent required distance are summarized into the same preset initially empty convex summary set; Determine the collective contour according to the convex points in the same convex induction set, and define the part of the pipeline detection inner contour that is not the collective contour as a normal inner contour; A randomly movable coordinate origin is created in the area enclosed by the inner contour of the pipeline detection, and a simulated pipeline contour is established based on the coordinate origin and randomly variable ellipse parameters; Determine the contour overlap ratio based on the simulated pipeline contour and the normal internal contour; Determine the contour overlap ratio with the largest value according to a preset sorting rule, and determine the simulated pipeline contour corresponding to the contour overlap ratio as the unstacked demand contour; The raised area is determined based on the unstacked required contour and the inner contour of the pipeline inspection.

[0008] Optionally, the step of creating a randomly movable coordinate origin in the area enclosed by the inner contour of the pipeline detection includes: Connect any two contour points on the normal internal contour to determine the contour connected line segment, and define the point where the contour connected line segments intersect as the intersection point; Counting is performed at each intersection point according to the definition of the intersection point to determine the number of intersections; Determine the maximum number of intersections according to the sorting rule, define the number of intersections as the upper limit number, and define the intersection point corresponding to the upper limit number as the theoretical center point; A unit area is defined with the theoretical center point as the center of the circle and the preset unit distance as the radius, and the difference number is determined by performing a difference calculation based on the number of intersections of each intersection point and the upper limit number in the unit area; The intersection points whose difference times are less than a preset reasonable times are defined as valid points, and a valid area is determined according to each valid point, and a random coordinate origin is created within the valid area.

[0009] Optionally, after the number of intersections is determined, the pipeline deformation detection method further includes: Determine whether there are at least two intersection points with the same and maximum number of intersections; If there are not at least two intersection points with the same and maximum number of intersections, the theoretical center point is determined based on the intersection points; If there are at least two intersection points with the same and maximum number of intersections, the intersection points are defined as candidate points, and any candidate point is determined as the simulation center point, and the unit area is determined according to the simulation center point; Counting is performed at the candidate points in each unit area to determine the number of candidates; The candidate number with the largest value is determined according to the sorting rule, and the simulation center point corresponding to the candidate number is determined as the theoretical center point.

[0010] Optionally, after the number of alternatives is determined, the pipeline deformation detection method further includes: Determine whether there are at least two simulation center points with the same number of alternatives; If there are not at least two simulation center points with the same number of candidates, the theoretical center point is determined based on the simulation center point; If there are at least two simulation center points with the same number of candidates, the distance between the candidates is determined based on the simulation center point and the candidate points in the corresponding unit area; Perform mean calculation based on alternative separation distances to determine simulated mean distances; The simulated mean distance with the smallest value is determined according to the sorting rules, and the theoretical center point is determined according to the simulated center point corresponding to the simulated mean distance.

[0011] Optionally, the method further includes a step of determining randomly variable ellipse parameters, the step comprising: Get the distance between the contours of the connected line segments; According to the sorting rule, the two contour points with the largest distance between them are determined as the major axis endpoints, and the two contour points of the contour connected line segments perpendicular to the contour connected line segments formed by the major axis endpoints are defined as the minor axis endpoints, and the minor axis endpoints and the major axis endpoints are defined together as the limit endpoints; Determine the distance between points based on the limit endpoints and convex points; The extreme endpoints where the distance between points is less than the preset proximity distance are defined as similar endpoints; Counting similar endpoints at the minor axis endpoints and the major axis endpoints to determine the number of similarities; According to the preset correction matching relationship, the correction distance corresponding to the similar quantity is confirmed; The difference calculation is performed based on the contour distance between the minor axis endpoints and the corresponding correction distance to determine the lower limit value of the parameter, and the sum calculation is performed based on the contour distance between the major axis endpoints and the corresponding correction distance to determine the upper limit value of the parameter; The parameter variation interval is determined according to the parameter lower limit value and the parameter upper limit value, and the randomly variable ellipse parameters are determined within the parameter variation interval.

[0012] Optionally, after the raised area is determined, the pipeline deformation detection method further includes: The midpoint of the set contour is defined as the most concave point, and the distance between the concave points is determined based on the most concave point and the contour points on the unstacked required contour; Determine the distance between the concave points with the smallest value according to the sorting rule, and define the distance between the concave points as the concave deformation depth; Determine an abnormal contour line according to the unstacked demand contour and the convex area, and obtain abnormal endpoint coordinates of two endpoints of the abnormal contour line; Determine the upper limit deformation depth corresponding to the unstacked required contour and the abnormal endpoint coordinates according to the preset depth matching relationship; Determine whether the concave deformation depth is greater than the upper limit deformation depth; If the depression deformation depth is not greater than the upper limit deformation depth, the cleaning device is controlled to operate; If the concave deformation depth is greater than the upper limit deformation depth, the convex area is removed to modify the inner contour of the pipeline inspection.

[0013] In a second aspect, the present application provides a pipeline deformation detection system, which adopts the following technical solution: A pipeline deformation detection system, comprising: An acquisition module, used for acquiring the pipeline detection inner contour of the pipeline; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module creates a randomly movable detection point on the inner contour of the pipeline detection, and determines an adjacent point on the inner contour of the pipeline detection that is separated from the detection point by a preset fixed distance; The processing module establishes a detection ray that passes through adjacent points with the detection point as the starting point, and determines the detection angle bisector according to the two detection rays; The processing module defines the detection point when the detection angle bisector intersects the pipeline detection inner contour only at the detection point as a convex point, and determines the convex area according to each convex point; The processing module controls the preset cleaning device to move to the raised area for operation and enables the acquisition module to acquire the foreign matter cleaning resistance in real time; The judging module judges whether the foreign matter cleaning resistance is greater than a preset upper limit resistance; If the judging module judges that the foreign matter cleaning resistance is greater than the upper limit resistance, the processing module controls the cleaning device to stop working and obtain the pipeline detection inner contour again to upload the pipeline detection inner contour to the preset information collection center; If the judgment module determines that the foreign body cleaning resistance is not greater than the upper limit resistance, the processing module controls the cleaning device to continue operating, and obtains the pipeline detection inner contour again after completely passing through the raised area to upload the pipeline detection inner contour to the information collection center.

[0014] In summary, the present application includes at least one of the following beneficial technical effects: When the pipeline is deformed, the convex points in the inner contour can be identified and analyzed, and the corresponding cleaning device can be controlled to process the convex points to determine whether the convex points are formed by the accumulation of debris inside the pipeline, so that the obtained inner contour of the pipeline is more accurate, so as to more accurately determine the deformation of the pipeline; For some bulges, the overall deformation of the pipeline can be used to determine whether the bulge is caused by the accumulation of debris inside the pipeline, thereby reducing the need for a cleaning device to operate on each bulge and improving the overall detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the pipeline deformation detection method.

[0016] Figure 2 It is a schematic diagram of the pipeline outline.

[0017] Figure 3 is a flow chart of the method for determining the convex region.

[0018] Figure 4 It is a flowchart of the method of creating the coordinate origin.

[0019] Figure 5 It is a flowchart of the intersection point screening method.

[0020] Figure 6 is a flow chart of the simulation center point screening method.

[0021] Figure 7 It is a flow chart of the method for determining ellipse parameters.

[0022] Figure 8 It is a flow chart of the abnormal convex point removal method.

[0023] Fig. 9 It is a module flow chart of the pipeline deformation detection method. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 9 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0026] The embodiment of the present application discloses a pipeline deformation detection method. When performing pipeline deformation detection, the internal contour of the pipeline is obtained by a pipeline detection vehicle, and the convex point situation of the obtained internal contour is analyzed. In combination with the overall deformation of the pipeline, some convex points that are unlikely to be deformed are removed, and then a cleaning device is controlled to operate on each convex point to determine whether the convex point is formed by impurity accumulation inside the pipeline, thereby facilitating a more accurate determination of the pipeline deformation situation.

[0027] Reference Figure 1 The pipeline deformation detection method comprises the following steps: Step S100: obtaining the pipeline detection inner contour of the pipeline.

[0028] The inner profile of the pipeline is the internal cross-sectional profile of the pipeline obtained after the pipeline inner diameter detection vehicle moves circumferentially inside the pipeline. Figure 2 .

[0029] Step S101: creating a randomly movable detection point on the inner contour of the pipeline detection, and determining adjacent points on the inner contour of the pipeline detection that are spaced a preset fixed distance from the detection point.

[0030] The detection point is a random point on the inner contour of the pipeline detection. The fixed distance is a fixed distance set by the staff. The adjacent point is a point on the inner contour of the pipeline detection with a fixed straight-line distance from the detection point. Therefore, there is an adjacent point on each side of the detection point.

[0031] Step S102: establishing a detection ray that passes through adjacent points with the detection point as the starting point, and determining a detection angle bisector based on two detection rays.

[0032] The detection ray is a ray with the detection point as the endpoint and passing through an adjacent point. Two detection rays will form an angle with the detection point as the vertex. The detection angle bisector is the bisector of the angle. Figure 2 .

[0033] Step S103: defining the detection point where the detection angle bisector intersects the pipeline detection inner contour only at the detection point as a convex point, and determining a convex area according to each convex point.

[0034] When the detection angle bisector intersects the inner contour of the pipeline detection only at the detection point, it means that the detection point is set to bulge inwards. Figure 2 , defining it as a convex point for identification, which is convenient for subsequent analysis; the convex area is the area where the convex point is located, and the convex area can be determined by the adjacent convex points, or by the method of steps S200 to S206.

[0035] Step S104: Control the preset cleaning device to move to the raised area to operate and obtain the foreign matter cleaning resistance in real time.

[0036] The cleaning device is a device carried by the pipeline inner diameter detection trolley that has the function of cleaning foreign objects inside the pipeline, such as a movable shovel carried on the trolley. By moving the cleaning device to the raised area to perform operations, foreign objects inside the pipeline can be cleaned. The moving method of the cleaning device is to abut against one end of the raised area and control it to move to the other end of the raised area. The foreign object cleaning resistance is the resistance that the cleaning device will encounter during the movement, which can be determined by setting a pressure sensor at a position on the cleaning device used to shovel the raised position.

[0037] Step S105: Determine whether the foreign matter cleaning resistance is greater than a preset upper limit resistance.

[0038] The upper limit resistance is the minimum foreign matter cleaning resistance set by the staff to determine that the bulge is not formed by the accumulation of debris inside the pipeline. The purpose of the judgment is to know whether the currently detected bulge position is formed by the inward depression of the outside of the pipeline, that is, to judge whether the bulge is a deformation of the pipeline.

[0039] Step S1051: If the foreign matter cleaning resistance is greater than the upper limit resistance, the cleaning device is controlled to stop the operation and obtain the pipeline detection inner contour again to upload the pipeline detection inner contour to a preset information collection center.

[0040] When the resistance to foreign body cleaning is greater than the upper limit resistance, it indicates that the raised position is formed by pipeline deformation. At this time, the obtained pipeline detection inner contour at the raised position is the true contour of the pipeline. At this time, it can be uploaded normally to the information collection center for the staff to conduct subsequent deformation analysis. The information collection center is the information center where the staff obtains the internal data of the pipeline.

[0041] Step S1052: If the foreign matter cleaning resistance is not greater than the upper limit resistance, the cleaning device is controlled to continue operating, and after completely passing through the raised area, the pipeline detection inner contour is obtained again to upload the pipeline detection inner contour to the information collection center.

[0042] When the resistance to cleaning foreign matter is not greater than the upper limit resistance, it means that the part detected at this position is composed of accumulated debris. At this time, normal control of the cleaning device can achieve the cleaning of the debris. At the same time, when the cleaning device completely passes through the raised area, it means that the raised position is completely composed of accumulated debris. At this time, the debris has been cleaned by the cleaning device. The detection trolley can be moved again to re-acquire the inner contour of the pipeline detection, so as to obtain the actual deformation of the pipeline. In order to improve the overall operation efficiency, the trolley can only be controlled to move in the raised area.

[0043] Reference Figure 3 The step of determining the raised area according to each raised point includes: Step S200: obtaining the protrusion spacing distance between adjacent protrusion points.

[0044] Adjacent convex points are the two convex points that are closest to each other on the inner contour of the pipeline detection, and the convex separation distance is the distance value between the two convex points on the inner contour of the pipeline detection.

[0045] Step S201: summarizing convex points whose convex interval distance is less than a preset adjacent required distance into the same preset convex summary set which is initially empty.

[0046] The adjacent required distance is the maximum bulge distance set by the staff when two bulge points are in the same pipe deformation position. The bulge points with relatively close distances are grouped into the same bulge summary set, which can facilitate the analysis of the specific bulge conditions inside the pipe. There are multiple bulge summary sets, which are initially empty sets for the placement of bulge points.

[0047] Step S202: determining a set contour according to the convex points in the same convex summary set, and defining the portion of the pipeline detection inner contour that is not the set contour as a normal inner contour.

[0048] The set contour is the contour formed by the convex points in the same convex induction set. The contour is determined by the convex points on both sides of the convex induction set. Figure 2 The normal internal contour is the contour on which no convex points exist on the pipeline detection internal contour. The collective contour and the normal internal contour are determined to distinguish different positions of the pipeline detection internal contour, which is convenient for subsequent analysis.

[0049] Step S203: creating a randomly movable coordinate origin in the area enclosed by the inner contour of the pipeline detection, and establishing a simulated pipeline contour according to the coordinate origin and the randomly variable ellipse parameters.

[0050] The coordinate origin is a random point in the area enclosed by the inner contour of the pipeline detection. The ellipse parameters include the major axis value and the minor axis value of the ellipse. A coordinate system with different directions as the X-axis is established at the coordinate origin. Different ellipses can be constructed according to the corresponding ellipse parameters. The ellipse simulates the pipeline contour, that is, the internal contour that may appear when the pipeline is compressed and deformed. The setting of the ellipse parameters can be randomly determined, so there are countless simulated pipeline contours.

[0051] Step S204: determining the contour overlap ratio according to the simulated pipeline contour and the normal internal contour.

[0052] The contour overlap ratio is the ratio of the overlapped portion of the established simulated pipeline contour and the current normal internal contour to the overall normal internal contour, which can be determined by the ratio of the number of overlapping contour points to the number of entire contour points.

[0053] Step S205: determining the contour overlap ratio with the largest value according to a preset sorting rule, and determining the simulated pipeline contour corresponding to the contour overlap ratio as the unstacked demand contour.

[0054] The sorting rule is a method set by the staff to sort the numerical values, such as the bubble method. The sorting rule can be used to determine the contour overlap ratio with the largest value, that is, the simulated pipeline contour corresponding to the contour overlap ratio is the theoretical contour closest to the pipeline contour. At this time, it is defined as the unstacked demand contour for subsequent analysis; the unstacked demand contour is the internal contour that should be maintained when the pipeline has the current degree of deformation and does not bulge inward.

[0055] Step S206: determining the raised area according to the undeposited required contour and the pipeline detection inner contour.

[0056] The raised area is the area enclosed by the contour line of the raised point and the contour line of the unstacked required contour. Figure 2 .

[0057] Reference Figure 4 The steps of creating a randomly movable coordinate origin in the area enclosed by the inner contour of the pipeline detection include: Step S300: connect any two contour points on the normal internal contour to determine contour connected line segments, and define the point where the contour connected line segments intersect as the intersection point.

[0058] The contour connected line segment is a line segment formed by two contour points on the normal internal contour as endpoints, and the intersection point is the point where two contour intersection line segments that will intersect intersect.

[0059] Step S301: Counting is performed at each intersection point according to the definition of the intersection point to determine the number of intersections.

[0060] The number of intersections refers to the number of times the same intersection point is repeatedly defined, that is, the number of times two different contour connected line segments intersect at the same intersection point.

[0061] Step S302: Determine the maximum number of intersections according to the sorting rule, define the number of intersections as the upper limit number, and define the intersection point corresponding to the upper limit number as the theoretical center point.

[0062] The sorting rules can be used to determine the number of intersections with the largest value, and define it as the upper limit to distinguish different numbers of intersections. At the same time, since the center point of the ellipse has the largest number of intersections, the intersection point can be defined as the theoretical center point for identification, which is convenient for subsequent analysis.

[0063] Step S303: defining a unit area with the theoretical center point as the circle center and the preset unit distance as the radius, and performing a difference calculation based on the number of intersections of each intersection point and the upper limit number in the unit area to determine the difference number.

[0064] The unit distance is a fixed distance set by the staff. The unit area can be delineated to define the area where the actual center point of the pipeline may appear. The difference number is the difference between the number of intersections of the intersection points in the unit area and the upper limit number, and the difference is an absolute value.

[0065] Step S304: defining the intersection points whose difference times are less than a preset reasonable times as valid points, determining a valid area according to each valid point, and creating a random coordinate origin in the valid area.

[0066] The reasonable number is the maximum difference number when the difference between the recognized intersection number and the upper limit number set by the staff is not large. When the difference number is less than the reasonable number, it means that the corresponding intersection point may also be used as the center point of the current pipeline. At this time, it is defined as a valid point to distinguish different intersection points; the effective area is the outermost area formed by the connection of each valid point. At this time, the effective area is the area where the actual center point of the pipeline may exist. At this time, the coordinate origin is only created in the effective area, which can reduce the amount of simulated pipeline contours required for production, reduce the overall calculation amount, and improve the overall operation efficiency.

[0067] Reference Figure 5 After the number of intersections is determined, the pipeline deformation detection method further includes: Step S400: Determine whether there are at least two intersection points with the same and maximum number of intersections.

[0068] The purpose of the judgment is to find out whether only one intersection point can be determined as the theoretical center point.

[0069] Step S4001: If there are not at least two intersection points with the same and maximum number of intersections, a theoretical center point is determined based on the intersection points.

[0070] When there are not at least two intersection points with the same and maximum number of intersections, it means that only one intersection point can be determined as the theoretical center point. In this case, the theoretical center point can be determined normally.

[0071] Step S4002: If there are at least two intersection points with the same and maximum number of intersections, the intersection points are defined as candidate points, and any candidate point is determined as a simulation center point, and a unit area is determined according to the simulation center point.

[0072] When there are at least two intersection points with the same and largest number of intersections, it means that there are multiple intersection points that can serve as theoretical center points. At this time, they need to be further screened. Alternative points are defined to distinguish different intersection points. The simulation center point is a selected alternative point. The corresponding unit area can be delineated based on the simulation center point as the center of the circle and the unit distance as the radius.

[0073] Step S401: Counting candidate points in each unit area to determine the number of candidates.

[0074] The number of alternatives is the total number of alternative points in the determined unit area, which can be obtained by counting the alternative points one by one.

[0075] Step S402: determining the candidate quantity with the largest value according to the sorting rule, and determining the simulation center point corresponding to the candidate quantity as the theoretical center point.

[0076] The sorting rules can be used to determine the number of alternatives with the largest value, that is, the unit area demarcated at this time contains the largest number of alternatives, that is, the unit area is the most likely to solve the actual center position of the pipeline. At this time, the corresponding simulation center point is determined as the theoretical center point to facilitate the subsequent creation of the coordinate origin.

[0077] Reference Figure 6 After the number of alternatives is determined, the pipeline deformation detection method also includes: Step S500: Determine whether there are at least two candidate simulation center points with the same number.

[0078] The purpose of judgment is to find out whether there are multiple simulation center points that meet the requirements.

[0079] Step S5001: If there are not at least two simulation center points with the same number of candidates, determine the theoretical center point based on the simulation center point.

[0080] When there are not at least two simulation center points with the same number of candidates, it means that there is only one simulation center point that meets the requirements, and it can be determined as the theoretical center point.

[0081] Step S5002: If there are at least two simulation center points with the same number of candidates, the candidate spacing distance is determined according to the simulation center point and the candidate points in the corresponding unit area.

[0082] When there are at least two simulation center points with the same number of alternatives, it means that there are multiple simulation center points that meet the requirements and need to be further screened; the alternative separation distance is the straight-line distance between the simulation center point and the alternative points in the corresponding unit area.

[0083] Step S501: performing mean calculation based on the candidate spacing distances to determine a simulated mean distance.

[0084] The simulated mean distance is the average of the alternative separation distances determined under a single simulated center point.

[0085] Step S502: Determine the simulated mean distance with the smallest value according to the sorting rule, and determine the theoretical center point according to the simulated center point corresponding to the simulated mean distance.

[0086] The sorting rules can be used to determine the simulation mean distance with the smallest value, that is, the distance between the surrounding candidate points and the simulation center point is relatively close. At this time, the actual center position of the pipeline is likely to be within the unit area formed by the simulation center point. Therefore, the simulation center point is determined as the theoretical center point; when there are still multiple simulation center points that meet the requirements, a simulation center point can be randomly selected as the theoretical center point for subsequent analysis.

[0087] Reference Figure 7 , further comprising the step of determining randomly variable ellipse parameters, the step comprising: Step S600: Obtain the distance between contours of connected line segments.

[0088] The distance between contours is the length of the line segments connecting the determined contours.

[0089] Step S601: According to the sorting rules, the two contour points with the largest distance between them are determined as the major axis endpoints, and the two contour points of the contour connected line segments perpendicular to the contour connected line segments formed by the major axis endpoints are defined as the minor axis endpoints, and the minor axis endpoints and the major axis endpoints are jointly defined as the extreme endpoints.

[0090] In theory, the two endpoints of the major axis are the farthest apart in the ellipse. At this time, the two major axis endpoints can be determined by the sorting rules. Similarly, the two minor axis endpoints can be determined according to the characteristic that the major axis and the minor axis are perpendicular to each other in the ellipse. The two are jointly defined as the limit endpoints for subsequent analysis and processing.

[0091] Step S602: determining the distance between points according to the limit endpoints and the convex points.

[0092] The point spacing distance is the straight-line distance between the extreme endpoint and the convex point.

[0093] Step S603: defining the extreme endpoints whose points are separated by a distance less than a preset proximity distance as similar endpoints.

[0094] The proximity distance is the maximum point spacing distance set by the staff when there are relatively close convex points around the extreme endpoint. When there is a point spacing distance in the extreme endpoint that is less than the proximity distance, it means that the extreme endpoint is close to the convex position. At this time, the convex position may be the position of the short axis or the long axis. Therefore, the distance between the long axis endpoint or the short axis endpoint obtained at this time is inaccurate and needs further analysis. At this time, similar endpoints are defined to facilitate subsequent analysis.

[0095] Step S604: Count similar endpoints in the minor axis endpoints and the major axis endpoints respectively to determine the similarity number.

[0096] The similarity number refers to the number of similar endpoints determined as similar endpoints among the two short-axis endpoints or the two long-axis endpoints, wherein the similarity numbers of the short-axis endpoints and the long-axis endpoints are determined separately.

[0097] Step S605: confirming the correction distance corresponding to the similarity quantity according to the preset correction matching relationship.

[0098] The correction distance is the distance value that needs to be corrected for the distance between points when the major axis or minor axis may be in a raised position. Different similarity numbers indicate different position conditions at both ends, so the corresponding correction distances are also different. The correction matching relationship between the two is set by the staff according to actual conditions.

[0099] Step S606: performing difference calculation based on the contour distance between the minor axis endpoints and the corresponding correction distance to determine the parameter lower limit value, and performing sum calculation based on the contour distance between the major axis endpoints and the corresponding correction distance to determine the parameter upper limit value.

[0100] The lower limit of the parameter is the value obtained by subtracting the determined correction distance from the contour separation distance of the contour connected line segments formed by the two short axis endpoints, and the upper limit of the parameter is the value obtained by adding the determined correction distance to the contour separation distance of the contour connected line segments formed by the two long axis endpoints.

[0101] Step S607: determining a parameter variation interval according to the parameter lower limit value and the parameter upper limit value, and determining randomly variable ellipse parameters within the parameter variation interval.

[0102] The parameter variation interval is an interval with a parameter lower limit value and a parameter upper limit value as two interval endpoints. By randomly selecting ellipse parameters in the parameter variation interval to reduce the number of ellipses to be generated, the overall calculation amount is reduced to improve the overall operation efficiency.

[0103] Reference Figure 8 After the raised area is determined, the pipeline deformation detection method further includes: Step S700: define the midpoint of the set contour as the most concave point, and determine the distance between the concave points according to the most concave point and the contour points on the unstacked required contour.

[0104] The most concave point is the midpoint of the contour of a single set contour, that is, the most convex position point among the identified convex points, and the distance between concave points is the straight-line distance between the most concave point and the contour point on the unstacked demand contour.

[0105] Step S701: Determine the concave point spacing with the smallest value according to the sorting rule, and define the concave point spacing as the concave deformation depth.

[0106] The smallest distance between concave points can be determined by the sorting rule, that is, the distance between the concave points is the depth of the inward depression of the outer part of the convex point. In this case, it is defined as the concave deformation depth for subsequent analysis.

[0107] Step S702: determining an abnormal contour line according to the unstacked demand contour and the convex area, and obtaining abnormal endpoint coordinates of two endpoints of the abnormal contour line.

[0108] The abnormal contour line is a contour line on the unstacked demand contour in the convex area, and the abnormal endpoint coordinates are the coordinates of the endpoints at both ends of the abnormal contour line compared to the coordinate origin.

[0109] Step S703: determining the upper limit deformation depth corresponding to the unstacked required contour and the abnormal endpoint coordinates according to a preset depth matching relationship.

[0110] The upper limit deformation depth is the maximum deformation depth that can occur at the abnormal endpoint coordinate when the pipeline can be deformed into the shape of the stacking requirement contour. Different unstacked requirement contours and abnormal endpoint coordinates correspond to different deformation depths. The depth matching relationship between the three can be determined in advance by the staff through impact deformation simulation using MATLAB simulation software.

[0111] Step S704: determine whether the concave deformation depth is greater than the upper limit deformation depth.

[0112] The purpose of the judgment is to find out whether the convex position is likely to be formed by an inward depression from the outside under the current pipeline profile.

[0113] Step S7041: If the depression deformation depth is not greater than the upper limit deformation depth, the cleaning device is controlled to operate.

[0114] When the concave deformation depth is not greater than the upper limit deformation depth, it means that the bulge at this time may be formed by the inward concave deformation of the outside of the pipeline. At this time, the cleaning device can be controlled normally to operate to analyze the bulge.

[0115] Step S7042: If the concave deformation depth is greater than the upper limit deformation depth, the convex area is removed to modify the inner contour of the pipeline detection.

[0116] When the concave deformation depth is greater than the upper limit deformation depth, it means that the bulge at this position under the current pipeline contour cannot be caused by the inward depression of the outside. Therefore, the bulge is formed by the accumulation of debris inside the pipeline. At this time, the bulge area is removed and filled with the unaccumulated required contour to realize the modification of the inner contour of the pipeline detection, so that there is no need for a cleaning device to operate at each bulge position, thereby improving the overall detection efficiency.

[0117] Reference Fig. 9 Based on the same inventive concept, an embodiment of the present invention provides a pipeline deformation detection system, including: An acquisition module, used for acquiring the pipeline detection inner contour of the pipeline; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module creates a randomly movable detection point on the inner contour of the pipeline detection, and determines an adjacent point on the inner contour of the pipeline detection that is separated from the detection point by a preset fixed distance; The processing module establishes a detection ray that passes through adjacent points with the detection point as the starting point, and determines the detection angle bisector according to the two detection rays; The processing module defines the detection point when the detection angle bisector intersects the pipeline detection inner contour only at the detection point as a convex point, and determines the convex area according to each convex point; The processing module controls the preset cleaning device to move to the raised area for operation and enables the acquisition module to acquire the foreign matter cleaning resistance in real time; The judging module judges whether the foreign matter cleaning resistance is greater than a preset upper limit resistance; If the judging module judges that the foreign matter cleaning resistance is greater than the upper limit resistance, the processing module controls the cleaning device to stop working and obtain the pipeline detection inner contour again to upload the pipeline detection inner contour to the preset information collection center; If the judging module judges that the foreign matter cleaning resistance is not greater than the upper limit resistance, the processing module controls the cleaning device to continue the operation, and obtains the pipeline detection inner contour again after completely passing through the raised area to upload the pipeline detection inner contour to the information collection center; The convex area determination module determines the convex area according to the overall situation of the pipeline; The coordinate origin creation module defines the area where the coordinate origin may exist according to the overall situation of the pipeline, so as to facilitate the creation of the coordinate origin and improve the overall operation efficiency; An intersection point screening module is used to determine a unique intersection point as a theoretical center point among multiple intersection points that meet the requirements; A simulation center point screening module is used to determine a unique simulation center point as a theoretical center point among multiple simulation center points that meet the requirements; The ellipse parameter determination module limits the production range of the ellipse parameters according to the overall situation of the current pipeline, thereby improving the overall operation efficiency; The module for removing abnormal convex points is used to remove convex points that cannot be caused by pipeline deformation.

[0118] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

Claims

1. A pipeline deformation detection method, characterized in that: include: Obtain the pipeline detection inner contour of the pipeline; Creating a randomly movable detection point on the inner contour of the pipeline detection, and determining an adjacent point on the inner contour of the pipeline detection that is separated from the detection point by a preset fixed distance; A detection ray is established with the detection point as the starting point and passes through the adjacent points, and the detection angle bisector is determined based on the two detection rays; The detection point where the detection angle bisector intersects the pipeline detection inner contour only at the detection point is defined as a convex point, and the convex area is determined according to each convex point; Control the preset cleaning device to move to the raised area for operation and obtain the foreign matter cleaning resistance in real time; Determine whether the resistance to foreign body cleaning is greater than the preset upper limit resistance; If the foreign matter cleaning resistance is greater than the upper limit resistance, the cleaning device is controlled to stop working and the pipeline detection inner contour is obtained again to upload the pipeline detection inner contour to a preset information collection center; If the foreign matter cleaning resistance is not greater than the upper limit resistance, the cleaning device is controlled to continue operating, and after completely passing through the raised area, the pipeline detection inner contour is obtained again to upload the pipeline detection inner contour to the information collection center.

2. The pipeline deformation detection method according to claim 1, characterized in that: The step of determining the raised area according to each raised point comprises: Get the convex distance between adjacent convex points; The convex points whose convex distance is less than the preset adjacent required distance are summarized into the same preset initially empty convex summary set; Determine the collective contour according to the convex points in the same convex induction set, and define the part of the pipeline detection inner contour that is not the collective contour as a normal inner contour; A randomly movable coordinate origin is created in the area enclosed by the inner contour of the pipeline detection, and a simulated pipeline contour is established based on the coordinate origin and randomly variable ellipse parameters; Determine the contour overlap ratio based on the simulated pipeline contour and the normal internal contour; Determine the contour overlap ratio with the largest value according to a preset sorting rule, and determine the simulated pipeline contour corresponding to the contour overlap ratio as the unstacked demand contour; The raised area is determined based on the unstacked required contour and the inner contour of the pipeline inspection.

3. The pipeline deformation detection method according to claim 2, characterized in that: The steps of creating a randomly movable coordinate origin in the area enclosed by the inner contour of the pipeline inspection include: Connect any two contour points on the normal internal contour to determine the contour connected line segment, and define the point where the contour connected line segments intersect as the intersection point; Counting is performed at each intersection point according to the definition of the intersection point to determine the number of intersections; Determine the maximum number of intersections according to the sorting rule, define the number of intersections as the upper limit number, and define the intersection point corresponding to the upper limit number as the theoretical center point; A unit area is defined with the theoretical center point as the center of the circle and the preset unit distance as the radius, and the difference number is determined by performing a difference calculation based on the number of intersections of each intersection point and the upper limit number in the unit area; The intersection points whose difference times are less than a preset reasonable times are defined as valid points, and a valid area is determined according to each valid point, and a random coordinate origin is created within the valid area.

4. The pipeline deformation detection method according to claim 3, characterized in that: After the number of intersections is determined, the pipeline deformation detection method further includes: Determine whether there are at least two intersection points with the same and maximum number of intersections; If there are not at least two intersection points with the same and maximum number of intersections, the theoretical center point is determined based on the intersection points; If there are at least two intersection points with the same and maximum number of intersections, the intersection points are defined as candidate points, and any candidate point is determined as the simulation center point, and the unit area is determined according to the simulation center point; Counting is performed at the candidate points in each unit area to determine the number of candidates; The candidate number with the largest value is determined according to the sorting rule, and the simulation center point corresponding to the candidate number is determined as the theoretical center point.

5. The pipeline deformation detection method according to claim 4, characterized in that: After the number of alternatives is determined, the pipeline deformation detection method also includes: Determine whether there are at least two simulation center points with the same number of alternatives; If there are not at least two simulation center points with the same number of candidates, the theoretical center point is determined based on the simulation center point; If there are at least two simulation center points with the same number of candidates, the distance between the candidates is determined based on the simulation center point and the candidate points in the corresponding unit area; Perform mean calculation based on alternative separation distances to determine simulated mean distances; The simulated mean distance with the smallest value is determined according to the sorting rules, and the theoretical center point is determined according to the simulated center point corresponding to the simulated mean distance.

6. The pipeline deformation detection method according to claim 3, characterized in that: Also included is the step of determining randomly variable ellipse parameters, the step comprising: Get the distance between the contours of the connected line segments; According to the sorting rule, the two contour points with the largest distance between them are determined as the major axis endpoints, and the two contour points of the contour connected line segments perpendicular to the contour connected line segments formed by the major axis endpoints are defined as the minor axis endpoints, and the minor axis endpoints and the major axis endpoints are defined together as the limit endpoints; Determine the distance between points based on the limit endpoints and convex points; The extreme endpoints where the distance between points is less than the preset proximity distance are defined as similar endpoints; Counting similar endpoints at the minor axis endpoints and the major axis endpoints to determine the number of similarities; According to the preset correction matching relationship, the correction distance corresponding to the similar quantity is confirmed; The difference calculation is performed based on the contour distance between the minor axis endpoints and the corresponding correction distance to determine the lower limit value of the parameter, and the sum calculation is performed based on the contour distance between the major axis endpoints and the corresponding correction distance to determine the upper limit value of the parameter; The parameter variation interval is determined according to the parameter lower limit value and the parameter upper limit value, and the randomly variable ellipse parameters are determined within the parameter variation interval.

7. The pipeline deformation detection method according to claim 2, characterized in that: After the raised area is determined, the pipeline deformation detection method further includes: The midpoint of the set contour is defined as the most concave point, and the distance between the concave points is determined based on the most concave point and the contour points on the unstacked required contour; Determine the distance between the concave points with the smallest value according to the sorting rule, and define the distance between the concave points as the concave deformation depth; Determine an abnormal contour line according to the unstacked demand contour and the convex area, and obtain abnormal endpoint coordinates of two endpoints of the abnormal contour line; Determine the upper limit deformation depth corresponding to the unstacked required contour and the abnormal endpoint coordinates according to the preset depth matching relationship; Determine whether the concave deformation depth is greater than the upper limit deformation depth; If the depression deformation depth is not greater than the upper limit deformation depth, the cleaning device is controlled to operate; If the concave deformation depth is greater than the upper limit deformation depth, the convex area is removed to modify the inner contour of the pipeline inspection.

8. A pipeline deformation detection system, characterized in that: include: An acquisition module, used for acquiring the pipeline detection inner contour of the pipeline; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module creates a randomly movable detection point on the inner contour of the pipeline detection, and determines an adjacent point on the inner contour of the pipeline detection that is separated from the detection point by a preset fixed distance; The processing module establishes a detection ray that passes through adjacent points with the detection point as the starting point, and determines the detection angle bisector according to the two detection rays; The processing module defines the detection point when the detection angle bisector intersects the pipeline detection inner contour only at the detection point as a convex point, and determines the convex area according to each convex point; The processing module controls the preset cleaning device to move to the raised area for operation and enables the acquisition module to acquire the foreign matter cleaning resistance in real time; The judging module judges whether the foreign matter cleaning resistance is greater than a preset upper limit resistance; If the judging module judges that the foreign matter cleaning resistance is greater than the upper limit resistance, the processing module controls the cleaning device to stop working and obtain the pipeline detection inner contour again to upload the pipeline detection inner contour to the preset information collection center; If the judgment module determines that the foreign body cleaning resistance is not greater than the upper limit resistance, the processing module controls the cleaning device to continue operating, and obtains the pipeline detection inner contour again after completely passing through the raised area to upload the pipeline detection inner contour to the information collection center.

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