CN114580469A - Elbow identification method based on IMU detection - Google Patents

Elbow identification method based on IMU detection Download PDF

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Publication number
CN114580469A
CN114580469A CN202210168143.8A CN202210168143A CN114580469A CN 114580469 A CN114580469 A CN 114580469A CN 202210168143 A CN202210168143 A CN 202210168143A CN 114580469 A CN114580469 A CN 114580469A
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elbow
angle
pipe section
discrete point
pipeline
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CN114580469B (en
Inventor
王彬彬
方迎潮
王爱玲
余东亮
李开鸿
冯淑路
刘陇
李洪涛
张海磊
陈晶
刘宇婷
贺小康
鲁青龙
赵飞
杨川
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China Oil and Gas Pipeline Network Corp
National Pipeline Network Southwest Pipeline Co Ltd
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China Oil and Gas Pipeline Network Corp
National Pipeline Network Southwest Pipeline Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/02—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/20—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/22—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring angles or tapers; for testing the alignment of axes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/02—Preprocessing
    • G06F2218/04—Denoising
    • G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • General Engineering & Computer Science (AREA)
  • Image Analysis (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)

Abstract

The invention provides an elbow identification method based on IMU detection. The method may comprise: processing IMU detection data of a pipeline to be detected to obtain angle information, wherein the angle information comprises a pitch angle and an azimuth angle; selecting N first discrete points on a pipeline to be detected according to a set mileage interval, determining a pitch angle and an azimuth angle corresponding to each discrete point, and respectively calculating the delta p of the first N-1 discrete pointsiAnd Δ ai(ii) a Screening out delta piAnd Δ aiTaking the first discrete points which are all larger than the angle threshold value as second discrete points, segmenting the second discrete points, and enabling mileage intervals among the segmented pipe sections to be larger than set mileage intervals; discriminating each divided pipe section to discriminate the bagIncluding identifying pipe segments that satisfy elbow parameters as elbows. The invention can more accurately identify and position the elbow of the pipeline through the detection data of the IMU, thereby improving the positioning precision of the detection in the pipeline and the judgment precision of the bending deformation of the pipeline.

Description

Elbow identification method based on IMU detection
Technical Field
The invention relates to the technical field of pipeline detection, in particular to an elbow identification method based on IMU detection.
Background
The oil and gas long-distance pipeline is mostly buried in mountainous areas with complex address conditions, the traditional excavation detection method can only detect the local part of the pipeline, and the method is not suitable for the whole-line evaluation of the long-distance pipeline. The IMU-carrying in-pipeline detection technology can detect the whole pipeline on the premise of not excavating the pipeline. In addition to recording the geographic coordinates of the inner detectors, the IMU also records the inner detector attitude information at each time, including pitch and azimuth.
The position information of the pipeline can be positioned through the detection data of the IMU, the positioning error is continuously increased along with the drift of the detector along with the accumulation of time, so that the positioning error is often reduced by means of auxiliary ground calibration points or matching pipeline characteristics and the like, and the most frequent pipeline characteristic point serving as a long-distance pipeline is an elbow. The pitch angle and azimuth angle information obtained by IMU detection is widely used for evaluating the bending deformation of the pipeline, the curvature of the pipeline is calculated through the change of the angle so as to evaluate the bending deformation of the pipeline, and the calculation of the curvature is greatly influenced by the data of the elbow of the pipeline. In the prior art, the bending strain of a pipeline is usually calculated through an IMU (inertial measurement Unit), the bending strain of the pipeline cannot be reflected through a strain calculation value intuitively and quickly due to the influence of elbow data, the elbow is identified through carrying other internal detection data in internal detection, and then the data alignment is carried out to find the elbow data in the IMU, so that the method is complex and tedious.
Disclosure of Invention
The present invention aims to address at least one of the above-mentioned deficiencies of the prior art. For example, one of the objectives of the present invention is to provide an elbow identification method based on IMU (inertial Measurement Unit) detection, so as to implement all-line elbow identification for long-distance oil and gas pipelines.
In order to achieve the purpose, the invention provides an elbow identification method based on IMU detection. The method can comprise the following steps: processing IMU detection data of a pipeline to be detected to obtain angle information, wherein the angle information comprises a pitch angle and an azimuth angle; and identifying the elbow of the pipeline to be detected through the angle information.
Further, the pipe to be detected is subjected to elbow identification through the angle information and can be wrappedComprises the following steps: selecting N first discrete points on a pipeline to be detected according to a set mileage interval, determining a pitch angle and an azimuth angle corresponding to each discrete point, and respectively calculating the delta p of the first N-1 discrete pointsiAnd Δ aiWherein Δ pi＝pi+1-pi，△ai＝ai+1-ai，pi+1And piThe pitch angles, a, corresponding to the i +1 th discrete point and the i th discrete point respectivelyi+1And aiAzimuth angles corresponding to the i +1 th discrete point and the i th discrete point are respectively, i is 1,2, …, N; screening out delta piAnd Δ aiTaking the first discrete points which are all larger than the angle threshold value as second discrete points, segmenting the second discrete points, and enabling mileage intervals among the segmented pipe sections to be larger than set mileage intervals; and judging each divided pipe section, wherein the judgment comprises identifying the pipe section meeting the elbow parameters as the elbow.
Further, the step of identifying each pipe section may include: a1, solving the sum sigma delta p of the difference values of the pitch angles and the sum sigma delta a of the difference values of the azimuth angles corresponding to all the second discrete points on each pipe section, and taking the angle with the large absolute value in the sigma delta p and the sigma delta a as the judgment angle theta of the pipe section; a2, screening a third discrete point on each pipe section according to the type of the angle corresponding to the judgment angle theta and the positive and negative conditions of the angle theta, segmenting the third discrete point to obtain a secondary pipe section of each pipe section, wherein the mileage interval between the secondary pipe sections of each pipe section after segmentation is larger than the set mileage interval; a3, judging the bend condition of the pipeline according to the number of the discrete points except the two ends in the secondary pipe section and the number of the section of the longest pipe section in the secondary pipe section.
Further, the judging the elbow condition of the pipeline may include: judging whether an elbow identification section exists or not, and identifying the elbow identification section under the condition of existence.
Further, the determining whether the elbow identification section exists may include: if the data length of each secondary pipe section is 1, judging that each secondary pipe section does not comprise an elbow; if the secondary pipe section with the data length larger than 1 exists and the longest secondary pipe section is only one section, judging that the longest secondary pipe section is an elbow identification section; if the secondary pipe section with the data length larger than 1 is provided and the longest secondary pipe section has at least two sections, all the longest secondary pipe sections are elbow identification sections.
And further, identifying the elbow identification section by using elbow identification parameters.
Further, the elbow identification parameters may include: the shortest length of the bend, the smallest angle of the bend, and the curvatures corresponding to the cold bend and the hot bend.
Further, the step of screening out the third discrete point may include: under the condition that the theta is a pitch angle and a positive value, screening out a second discrete point with delta p being more than 0 on the pipe section as the third discrete point; under the condition that the theta is a pitch angle and a negative value, screening out a second discrete point with delta p < 0 on the pipe section and taking the second discrete point as the third discrete point; screening out a second discrete point with delta a being greater than 0 on the pipe section as the third discrete point under the condition that the theta is an azimuth angle and is a positive value; and in the case that the theta is an azimuth angle and has a negative value, screening out a second discrete point with Delta a < 0 on the pipe section as the third discrete point.
Further, the method comprises the steps of: after the third discrete point on each pipe segment is screened out, a part of the second discrete points are remained on each pipe segment, and when the data length of the data segment consisting of the remained second discrete points is greater than 1, the steps A1 to A3 are continuously repeated until the data length of the data segment consisting of the remained second discrete points on each pipe segment is less than or equal to 1.
Further, the set mileage interval may be a pipe diameter D.
Further, the method for processing the IMU detection data of the pipe to be detected may include: and performing noise reduction processing and integration processing on IMU detection data of the pipeline to be detected through db 46-order wavelet transformation.
Compared with the prior art, the beneficial effects of the invention can include: by selecting the angle threshold value, the length, the angle, the curvature radius and the elbow trend of the elbow can be quickly and accurately resolved in a mode of segmenting the continuous pipeline according to the angle threshold value and then independently identifying the elbow, so that the accuracy of detection in the pipeline and the accuracy of bending deformation evaluation are improved.
Drawings
FIG. 1 shows the invention at a first discrete point SiIn the second discrete point SjA schematic diagram of (a);
figure 2 shows a schematic flow diagram of an IMU detection based elbow identification method in example 1 of the present invention;
FIG. 3 shows a schematic of the IMU full range pitch and azimuth changes in example 1 of the present invention;
FIG. 4 shows a schematic representation of a pipe segment with an angle change exceeding a threshold point in example 1 of the present invention;
FIG. 5 is a schematic diagram showing position and attitude information of a bend on a pipeline centerline in example 1 of the present invention;
fig. 6 shows a schematic comparison of a pipe bend and a horn-detected bend in example 1 of the present invention.
Detailed Description
Hereinafter, the elbow identification method based on IMU detection according to the present invention will be described in detail with reference to the accompanying drawings and exemplary embodiments.
In the description of the present application, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or element must have a particular orientation, be constructed in a particular orientation, and be operated, and thus should not be construed as limiting the present application. In the present application, the "first end" of each component may be an "upper end" as shown in the drawings, the "second end" may be a "lower end" as shown in the drawings, the "upper end" and the "lower end" are in accordance with the up-and-down direction of the drawings, but do not limit the structure of the assembly of the present disclosure, for example, after the direction of the assembly shown in the drawings is changed, the "first end" may also be a "left end" as shown in the drawings, the "second end" may be a "right end" as shown in the drawings, and the like.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The invention provides an elbow identification method based on IMU detection.
Exemplary embodiment 1
The elbow identification method based on IMU detection can comprise the following steps:
and S1, acquiring the angle information of the IMU in the pipe to be tested, wherein the angle information comprises the pitch angle value and the azimuth angle value of the IMU.
The IMU is called an Inertial Measurement Unit (IMU) and an Inertial Measurement Unit (IMU), and is mainly used for detecting and measuring a sensor of acceleration and rotation motion. The IMU can be carried on a pipeline internal detector in a pipeline to be detected, the pressure difference of a medium conveyed in the pipeline is used as power, the IMU moves in the pipeline, the angular velocity is collected in real time, the collected angular velocity can be subjected to noise reduction treatment on the collected angular velocity through db 46-order wavelet transformation, the angular velocity integration after noise reduction obtains angle information, the angle information can comprise a pitch angle (an included angle between the central axis of the detector and the horizontal direction) and an azimuth angle (an included angle between the central axis of the detector and the due north direction), the IMU moves in the pipeline to be detected by using the pressure difference of the medium conveyed in the pipeline as power, and therefore, the mileage of the IMU is the full length of the pipeline to be detected.
In this step, data may be collected by placing an IMU into the pipeline under test.
And S2, identifying the elbow of the pipeline to be detected through the angle data.
All elbows of the pipeline to be detected can be identified only through IMU detection data without alignment of different data.
Exemplary embodiment 2
On the basis of the exemplary embodiment 1, step S2 of the identification method may include:
s21, selecting N first discrete points S on the pipeline to be tested according to the set mileage interval, wherein the pipeline to be tested (namely, the mileage of the IMU)i. Determining the pitch angle and the azimuth angle corresponding to each discrete point. Separately calculating the deltap of the first N-1 discrete pointsiAnd Δ aiWherein Δ pi＝pi+1-pi，△ai＝ai+1-ai，pi+1And piI +1 th discrete point S and i th discrete point S respectivelyiCorresponding pitch angle, ai+1And aiThe azimuth angles corresponding to the i +1 th discrete point and the i-th discrete point are 1,2, …, N. And reserving mileage sections in which the difference value of the front pitch angle and the back pitch angle and the difference value of the azimuth angle of the IMU in each set mileage interval are larger than the angle threshold.
The purpose of selecting the set mileage interval is to discretize continuous pipeline detection data, and the mileage interval is two adjacent discrete points with a certain interval. The set mileage interval may be the pipe diameter D, but the present invention is not limited thereto, and may be other mileage intervals.
S22, screening out Δ piAnd Δ aiFirst discrete points S both greater than an angular thresholdiAs a second discrete point SjReferring to FIG. 1, DP in FIG. 1 refers to Si+1And SiPitch angle difference (p) of pointsi+1-pi). For the second discrete point SjSegmenting, wherein the mileage interval between the segmented pipe sections (namely the data sections) is larger than the set mileage intervalAnd (4) separating. The starting point of the segmented pipe section is a discontinuous point in the second discrete points, and the segmentation principle is Sj+1-Sj>And setting the mileage interval. Each piece of segmented data is marked as Lk(k is 1 to m), m is a second discrete point SjThe number of segmentation stages.
And S23, judging each separated pipe section, wherein the judgment comprises identifying the pipe section meeting the elbow parameters as an elbow.
In the present embodiment, the angle threshold is selected according to the criterion that the bending strain calculated from the attitude data is greater than 0.125% (R/R > -0.125) and is used to distinguish straight tubes, for example, the corresponding curvature radius may be 500D to 800D, such as 600D, 700D, etc.
Exemplary embodiment 3
On the basis of the exemplary embodiment 2, step S23 of the identification method may include:
s231, determining the pipe section LkThe angle θ of discrimination.
Specifically, each pipe section L is determinedkAll second discrete points S onjAnd corresponding to the sum sigma delta p of the pitch angle difference and the sum sigma delta a of the azimuth angle difference, and taking the angle with the large absolute value in the sigma delta p and the sigma delta a as the judgment angle theta of the pipe section. Where Δ p is the difference between the pitch angles of two adjacent second discrete points, e.g. Sj+1Pitch angle of (S)jΔ a is the difference in azimuth angle between two adjacent second discrete points, e.g. Sj+1Azimuth angle-S ofjIs measured.
S232, screening pipe sections LkAll points L with the same angle change of the corresponding angle as the positive and negative conditions of the judgment angle thetak1。
Screening out a third discrete point L on each pipe section according to the type of the angle corresponding to the judgment angle theta and the positive and negative conditions of the angle thetak1The third discrete point Lk1The angular change of the correspondence determination angle θ is the same as the positive and negative of θ.
For example, when θ is a pitch angle p and θ is a positive value, a second discrete point Δ p > 0 is screened on the pipe section as the third discrete point Lk1The third discrete point Lk1Excluding points where Dp ≦ 0 (i.e., Δ p ≦ 0). This situation can be formulated as LkThe pipe section is wholly vertically bent and the bending direction is vertically upward.
And screening out a second discrete point with deltap < 0 on the pipe section as the third discrete point when the theta is a pitch angle p and the theta is a negative value. This situation can be formulated as LkThe pipe section is wholly vertically bent and the bending direction is vertically downward.
And screening out a second discrete point with Delta a > 0 on the pipe section as the third discrete point under the condition that the theta is an azimuth angle a and the theta is a positive value. This situation can be formulated as LkThe pipe section is bent horizontally as a whole and the bending direction is horizontal to east.
And screening out a second discrete point with delta a < 0 on the pipe section as the third discrete point when the theta is an azimuth angle a and the theta is a negative value. This situation can be formulated as LkThe pipe section is bent horizontally and the bending direction is horizontally north.
S233, for the third discrete point Lk1And (4) carrying out segmentation again to obtain a secondary pipe section (which can be regarded as a data section), and judging the elbow condition. And the mileage interval between the secondary pipe sections of each pipe section after segmentation is larger than the set mileage interval. I.e. the starting point of the re-segmented pipe segment is the third discrete point Lk1At a point of discontinuity, i.e. as SLk1+1-SLk1>Set mileage interval for the third discrete point Lk1In which segmentation is performed.
Judging the bend condition may include:
①Lk1after segmentation, each segment contains 1 data, and L is judgedk1Each segment of data contains no bends.
②Lk1And after segmentation, the pipe sections containing the middle data points with the number larger than 1 are arranged, and the longest pipe section is only one section, and at the moment, the longest pipe section is judged to be an elbow judging section.
③Lk1After the segmentation, the pipe sections containing data with the length larger than 1 are arranged, and the longest pipe section has 2 sections or more than 2 sections, at the moment, all the longest pipes are judgedThe sections are elbow distinguishing sections. The data length refers to the number of data in a segment of data.
S234, screening out a third discrete point L on each pipe sectionk1Thereafter, the pipe section LkHas remained a second discrete point Lk2I.e. Lk2＝Lk-Lk1. At Lk2When the data length of (1) is greater than 1, the steps S231 to S233 are continuously repeated until the data length of the remaining second discrete points on each pipe section is less than or equal to 1, thereby completing the step of aligning the section LkProcessing of the data of (1).
In particular, L is the number of steps repeatedk2Replace LkThat is, step S231 is to determine Lk2The step of judging the angle theta, S231 is to screen the pipe section Lk2All points L with the same angle change as the positive and negative conditions of the judgment angle thetak21，Lk21Replace Lk1And step S233 is to Lk21Carrying out segmentation again to obtain a secondary pipe section (which can be regarded as a data section), judging the elbow condition, and then judging Lk2-Lk21And if the data length is greater than 1, continuing to repeat steps S231 to S233.
Because the bent pipes are usually laid continuously when the terrain has large relief, each bent pipe is connected only through a short straight pipe, and the steps S233 and S234 can distinguish the bent pipes; and, the detector will be accompanied by data fluctuation when entering and exiting the elbow, and steps S233 and S234 can distinguish the threshold value caused by the data fluctuation from the real pipe elbow data.
In this embodiment, the determining the bend condition of the pipeline includes: judging whether the elbow identification section exists, and drawing up the identification parameters of the elbow to identify the elbow identification section under the condition of existence.
The identification parameters for the proposed bend may include: the shortest length of the bend, the smallest angle of the bend, and the curvatures corresponding to the cold bend and the hot bend.
The identification parameters of the elbow are construction parameters of the IMU measuring pipeline, and can be modified according to different measuring pipelines. For example, the parameters of the pipeline used in the present invention may be: the minimum length is 3m, the cold bend radius is 40D, and the hot bend radius > is 8D, and the angle is calculated by a curvature calculation formula (angle/tube length is curvature). During identification, the parameters of the judging section need to meet the parameters of the elbow, and the curvature is in the inherent curvature range of cold bending and hot bending under the condition that the length is met.
Exemplary embodiment 4
The elbow identification method based on IMU detection can comprise the following steps:
step 1, carrying out noise reduction processing on the collected angular velocity through db 46-order wavelet transform; and integrating the angular velocity after noise reduction to obtain angle information. The angle information includes a pitch angle (an angle between the central axis of the detector and the horizontal direction) and an azimuth angle (an angle between the central axis of the detector and the north direction). The pipe diameter D is used as a mileage interval S, a continuous pipeline is divided into N discrete points with the interval S, and two points S on the interval mileage S are calculatedi、Si+1( i 1,2, 3.. N) and a difference in the pitch angle and the azimuth angle.
And 2, taking the angle difference between the two points calculated in the step 1 as a precondition for elbow screening, and selecting an angle threshold value, wherein the angle threshold value is selected according to the curvature radius of 500D. Screening out SiN and all points S greater than an angle thresholdj. For S identified in the previous stepjAccording to Sj+1-Sj>D to SjThe segmentation process is performed again (i.e. as per S)jWhether segmented for consecutive discrete points). Each piece of segmented data is marked as Lk( k 1,2, 3.. m), m is SjThe number of segmentation stages.
Step 3, each segment L segmented in the step 2kData is processed individually, first for a segment LkThe pitch angle difference value and the azimuth angle difference value are summed to obtain a sum, the absolute values of the two values are compared, and the angle with the larger absolute value is selected as LkThe angle of discrimination of (1).
Step 4, for L identified in step 3kThe pipe section distinguishing angle calculates positive and negative conditions of sigma delta theta of the distinguishing angle theta, and at the moment, four conditions occur, which respectively correspond to the following conditions:
(1) the angle is determined to be the pitch angle p and is positive (set L)kThe whole pipe section is vertically bent and the bending direction is vertically upward);
(2) the judgment angle is the pitch angle p and is a negative value (drawing L)kThe whole pipe section is vertically bent and the bending direction is vertically downward);
(3) the discrimination angle is the azimuth angle a and is positive (set L)kThe pipe section is bent horizontally and the bending direction is horizontal to the east);
(4) the discrimination angle is the azimuth angle a and is a negative value (to set L)kThe pipe section as a whole is bent horizontally and the bending direction is horizontally north). Screening LkAll points where the change of the medium angle is the same as the positive or negative of the discrimination angle, for example: if the angle is positive and the pitch angle is judged, then L is selectedkMiddle delta p>All points L of 0k1。
Step 5, for L in step 4kL thus screenedk1The distance S between two adjacent points is calculated againLk1+1-SLk1. According to SLk1+1-SLk1>D, to Lk1Segmenting again, and discriminating Lk1Number of data points (L) contained in each segmentk1The length of each segment after segmentation). Screening out Lk1The longest segment after segmentation will now include three cases, so as to set three different results:
1、Lk1after segmentation, each segment contains 1 data, and L is judgedk1Each segment of data contains no bends.
2、Lk1And after segmentation, the pipe section containing the data length larger than 1 is arranged, and the longest pipe section is only one section, and at the moment, the longest pipe section is judged to be an elbow judging section.
3、Lk1And after segmentation, the pipe sections containing data with the length larger than 1 exist, the longest pipe section has 2 sections or more than 2 sections, and at the moment, all the longest pipe sections are judged to be elbow judging sections.
Step 6, identifying L with the same change as the discrimination angle in step 4k1L ofk2＝L-Lk1If L isk2If the data length of (1) is greater than 1, let Lk＝Lk2Repeating steps 3 to 5Content up to Lk2Is less than or equal to 1, thereby completing the processing of a segment LkData processing of ( k 1,2, 3.. m) is completed for LkPost-processing execution pair Lk+1And (3) repeatedly executing the steps from 3 to 6, and judging and obtaining the elbow judging sections in all the detection data by circulating.
Step 7, drawing up identification parameters of the elbow, comprising the following contents: and (5) identifying the elbow judging section identified in the step (5) according to the shortest length of the elbow, the minimum angle of the elbow and the curvatures corresponding to cold bending and hot bending. If the identification parameters of the elbow are met, the elbow is identified.
The invention carries out three-time segmentation on continuous IMU pipeline detection data, and the purpose of the three-time segmentation is as follows:
screening discrete points with curvature radius larger than a set value for the first time, and screening discrete point separation sections L according to the distance between the discrete points larger than a set mileage distance (such as 1-time pipe diameter)kThe purpose is to distinguish between straight pipes and pipes where bends have occurred.
And the second time, screening out the pipe sections with the same direction as the judging angle of the pipeline from each threshold pipe section so as to distinguish the angle change caused by the elbow of the pipeline and the data fluctuation of the detector passing through the vicinity of the elbow.
And thirdly, the data of the second segmentation is further divided according to a distance (such as dividing according to a pipe diameter larger than 1 time) larger than a preset mileage distance, so that a plurality of adjacent elbows can be identified as one elbow when the elbows are continuously laid, and the continuously laid elbows can be distinguished through another interval, thereby ensuring the identification accuracy.
The above-described exemplary embodiments of the present invention are further explained below by way of detailed examples.
Example 1
The length of the pipeline to be measured is 5km, the inner diameter D of the pipeline is 1016mm, the minimum length of the elbow is 3m, and the minimum angle of the elbow is 2.5 degrees.
As shown in fig. 2, the entire method for identifying an elbow based on IMU detection in this example may first solve the attitude information difference, screen the threshold points, perform the threshold point judgment, and then perform the elbow condition judgment, and specifically, the method may include the following steps:
step 1, carrying out noise reduction processing on the collected angular velocity through db46 order wavelet transformation, integrating the angular velocity after noise reduction to obtain angle information, dividing a continuous 5km pipeline into 5000 discrete points with the interval of 1m by adopting the pipe diameter D (taking 1m) as a mileage interval S, and calculating two points S on the interval mileage S, wherein pitch angle and azimuth angle information are shown in figure 3i、Si+1( i 1,2, 3.. 5000) pitch angle difference Δ P and azimuth angle Δ a.
Step 2, selecting the angle threshold value of 0.23 degrees and screening out Si( i 1,2, 3.. 5000) all points S at which Δ P and Δ a are greater than 0.23 °jDots as denoted by "+" in fig. 4. For S identified in the previous stepjAccording to Sj+1-Sj>D to SjThe segmentation processing is carried out again, the 5km pipeline is divided into 156 segments, and each segment of segmented data is marked as Lk(k＝1、2、3......156)。
Step 3, each segment L segmented in the step 2kData is processed individually, first for a segment LkThe pitch angle difference value and the azimuth angle difference value are summed to obtain the sum of delta P and the sum of delta a, the absolute values of the two values are compared, and the angle with larger absolute value is selected as LkThe discrimination angle theta.
Step 4, for L identified in step 3kJudging angle theta of pipe section, calculating angle theta, and screening LkAll points where the angle change is the same as the positive or negative of the discrimination angle theta.
Step 5, press SLk+1-SLk1>D, to Lk1Segmenting again, and judging Lk1The number of data points each segment contains. Screening out Lk1The longest segment after segmentation will now include three cases, so as to set three different results:
(1)Lk1after segmentation, each segment contains 1 data, and L is judgedk1Each section of data of the device does not contain an elbow;
(2)Lk1after segmentation, the pipe section containing data with length larger than 1 is arranged, and the longest pipe section is only one section, at the momentJudging the longest pipe section as an elbow judging section;
(3)Lk1and after segmentation, the pipe sections containing data with the length larger than 1 are arranged, and the longest pipe section has 2 sections or more than 2 sections, and at the moment, all the longest pipe sections are judged to be elbow judging sections.
Step 6, identifying L with the same change as the discrimination angle in step 4k1L is recordedk2＝L-Lk1If L isk2If the data length of (1) is greater than 1, let Lk＝Lk2Repeating the steps 3 to 5 until Lk2Is less than or equal to 1, thereby completing the processing of a segment LkData processing of (k ═ 1,2, 3,... m) is completed, and L is completedkPost-processing execution pair Lk+1The steps 3 to 6 are repeatedly executed, and the elbow judging sections in all the detection data are judged and obtained in a circulating way.
Step 7, drawing up identification parameters of the elbow, comprising the following contents: and (5) identifying the elbow judging section identified in the step (5) according to the shortest length of the elbow, the minimum angle of the elbow and the curvatures corresponding to cold bending and hot bending. If the identification parameters of the elbow are met, the elbow is identified, and the pipeline elbow obtained by screening the 5km pipeline is shown in figure 5.
As shown in fig. 6, the elbow information identified by the method is completely matched with the third-party circumferential weld detection result, so that alignment of different data can be omitted when positioning analysis and bending strain calculation of the IMU detection data are performed.
In summary, the elbow identification method based on IMU detection according to the present invention has the following advantages:
the elbow of the pipeline is identified through IMU data, and the obtained elbow content comprises the following steps: the length of the elbow, the direction of the elbow, the angle and the curvature radius of the elbow can greatly reduce the workload of pipeline positioning and matching with the pipeline characteristics, and improve the precision of pipeline positioning. The invention can not align different data when performing positioning analysis and bending strain calculation of IMU detection data, can directly identify the elbow data in the IMU, and can truly reflect the bending of the pipeline by the bending strain calculation result after eliminating the elbow data.
Although the present invention has been described above in connection with exemplary embodiments, it will be apparent to those skilled in the art that various modifications and changes may be made to the exemplary embodiments of the present invention without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (10)

1. An elbow identification method based on IMU detection is characterized by comprising the following steps:
processing IMU detection data of a pipeline to be detected to obtain angle information, wherein the angle information comprises a pitch angle and an azimuth angle;
and identifying the elbow of the pipeline to be detected through the angle information.
2. The IMU detection-based elbow recognition method as claimed in claim 1, wherein the elbow recognition of the pipe to be tested through the angle information comprises:
selecting N first discrete points on a pipeline to be detected according to a set mileage interval, determining a pitch angle and an azimuth angle corresponding to each discrete point, and respectively calculating the delta p of the first N-1 discrete pointsiAnd Δ aiWherein Δ pi＝pi+1-pi，△ai＝ai+1-ai，pi+1And piThe pitch angles, a, corresponding to the i +1 th discrete point and the i th discrete point respectivelyi+1And aiAzimuth angles corresponding to the i +1 th discrete point and the i th discrete point are respectively, i is 1,2, …, N;
screening out delta piAnd Δ aiTaking the first discrete points which are all larger than the angle threshold value as second discrete points, segmenting the second discrete points, and enabling mileage intervals among the segmented pipe sections to be larger than set mileage intervals;
and judging each divided pipe section, wherein the judgment comprises identifying the pipe section meeting the elbow parameters as the elbow.
3. The IMU detection-based elbow recognition method of claim 2, wherein the step of discriminating each pipe segment comprises:
a1, solving the sum sigma delta p of the difference values of the pitching angles corresponding to all the second discrete points on each pipe section and the sum sigma delta a of the difference values of the azimuth angles, and taking the angle with the large absolute value in the sigma delta p and the sigma delta a as the judgment angle theta of the pipe section;
a2, screening a third discrete point on each pipe section according to the type of the angle corresponding to the judgment angle theta and the positive and negative conditions of the angle theta, segmenting the third discrete point to obtain a secondary pipe section of each pipe section, wherein the mileage interval between the secondary pipe sections of each pipe section after segmentation is larger than the set mileage interval;
a3, judging the bend condition of the pipeline according to the number of the discrete points except the two ends in the secondary pipe section and the number of the section of the longest pipe section in the secondary pipe section.
4. The IMU detection-based elbow identification method of claim 3, wherein said determining the elbow condition of the pipe comprises:
judging whether an elbow identification section exists or not, and identifying the elbow identification section under the condition of existence.
5. The IMU detection based elbow identification method of claim 4, wherein the determining whether an elbow identification segment exists comprises:
if the data length of each secondary pipe section is 1, judging that each secondary pipe section does not comprise an elbow;
if the secondary pipe section with the data length larger than 1 exists and the longest secondary pipe section is only one section, judging that the longest secondary pipe section is an elbow identification section;
if the secondary pipe section with the data length larger than 1 is provided and the longest secondary pipe section has at least two sections, all the longest secondary pipe sections are elbow identification sections.
6. The IMU detection-based elbow identification method of claim 4, wherein the elbow identification section is identified using elbow identification parameters.
7. The IMU detection-based elbow identification method of claim 6, wherein the elbow identification parameters comprise: the shortest length of the bend, the smallest angle of the bend, and the curvatures corresponding to the cold bend and the hot bend.
8. The IMU detection-based elbow identification method of claim 3, wherein the step of screening out the third discrete point comprises:
under the condition that the theta is a pitch angle and a positive value, screening out a second discrete point with delta p being more than 0 on the pipe section as the third discrete point;
under the condition that the theta is a pitch angle and a negative value, screening out a second discrete point with delta p < 0 on the pipe section and taking the second discrete point as the third discrete point;
screening out a second discrete point with Delta a > 0 on the pipe section as the third discrete point under the condition that the theta is an azimuth angle and a positive value;
and in the case that the theta is an azimuth angle and has a negative value, screening out a second discrete point with Delta a < 0 on the pipe section as the third discrete point.
9. The IMU detection-based elbow identification method of claim 3, further comprising the steps of:
after the third discrete point on each pipe segment is screened out, a part of the second discrete points are remained on each pipe segment, and when the data length of the data segment consisting of the remained second discrete points is greater than 1, the steps A1 to A3 are continuously repeated until the data length of the data segment consisting of the remained second discrete points on each pipe segment is less than or equal to 1.
10. The IMU detection-based elbow identification method of claim 3, wherein the set mileage interval is a pipe diameter D.
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