A shield muck flow plasticity automatic evaluation method based on a specimen slump body cross section shape

Abstract

The application discloses a kind of automatic evaluation method of shield muck plastic flow based on slump body image segmentation and feature extraction, comprising: S1: a series of muck improvement and slump test are carried out in the room, according to the reasonable slump value range and whether sample surface is analyzed water bubble to determine its improvement state;S2: laser scanner is used to obtain the cross-sectional profile of muck slump body center position sample under each improvement state, and the related parameters such as slump body height H, top platform diameter d and extension D are calculated by obtaining the cross-sectional profile point cloud data of slump body center position;S3: determine the parameter d, D, H value range of muck slump body center position cross-sectional profile under various improvement states;S4: the slump image is rotated, translated, skew cut and the like, and the height, top platform diameter and extension of sample slump body are calculated by segmenting and extracting the features of slump body, and the improvement state of sample is determined by combining the parameter d, D, H value range of muck slump body center position cross-sectional profile under various improvement states.The application can determine the improvement state of muck by slump body image, so as to standardize, automate, accurately and quickly evaluate the plasticity of shield muck.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of shield construction, and particularly relates to a shield muck flow plasticity automatic evaluation method based on a sample slump body cross section shape. BACKGROUND

[0002] With the rapid development of urban metro, shield machines are commonly used in metro construction, and the shield construction method is the most rapid and safe construction method. Excavation is carried out through a shield cutter head, and muck excavated is put into a soil bin to provide a certain pressure to a working face to maintain the stability of the working face. The state of muck in the tunneling process has an important influence on the speed and safety of tunneling. Therefore, the improved state of muck needs to be monitored in the shield tunneling process. When shield muck is over improved, the shield muck is too dilute, which can easily cause the shield machine to spew, and has an important influence on the safety of construction. When shield muck is under improved, the flowability of muck is poor, muck is easily stuck to the cutter head, the cutter is easily worn, and the shield muck is not easily discharged. At present, the improved state of muck is still determined by a slump test. The slump value of a sample and the state of the sample after slump are determined. This method needs to measure the slump value manually and make a subjective judgment, and has strong subjectivity. SUMMARY

[0003] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, one of the purposes of the present application is to provide a shield muck flow plasticity automatic evaluation method based on a sample slump body cross section shape, which can standardize, automate, accurately and quickly evaluate the shield muck flow plasticity.

[0004] To achieve the above technical purposes, the present application adopts the following technical solutions:

[0005] A shield muck flow plasticity automatic evaluation method based on a sample slump body cross section shape, comprising:

[0006] S1: a series of muck improvement and slump tests are carried out in a laboratory, and the improved state is determined according to a recommended reasonable slump value range and whether the sample surface is analyzed water or foam;

[0007] S2: a laser scanner is used to obtain sample slump body center position cross section shape point cloud data, and related parameters of the slump body center position cross section contour line such as slump body height H, top platform diameter d and slump body extension D are calculated through the obtained slump body center position cross section contour line point cloud data;

[0008] S3: the parameter d, D and H of the sample slump body center position cross section contour line under various improved states are determined;

[0009] S4: The slump image is rotated, translated, and sheared, and then the height, top platform diameter, and spread of the sample slump body are calculated according to the slump body image. The improved state of the sample is determined according to the parameter d, D, and H of the cross-sectional profile line of the slag slump body center position in the range of values.

[0010] Further, the method for obtaining longitudinal point cloud data by using a laser scanner is as follows: after the slump test is performed on the slump test board, the driving device is started to move the bracket on which the laser scanner is fixed to the directly above of the slump body, and the laser scanner is started to scan the longitudinal point cloud data of the center point of the top surface of the slump body.

[0011] Further, the related parameters of the cross-sectional profile line of the slump body center position, such as the slump body height H, the top platform diameter d, and the spread D of the slump body, are calculated by obtaining the cross-sectional profile line point cloud data of the slump body center position. A coordinate system is established with the center of the sample as the origin, the sample height direction as the positive half of the y-axis, and the right side of the center of the slump body as the positive half of the x-axis. The highest point A(x t ,y t ), the lowest point C(x m ,y m ) of the sample cross section in the negative direction of the x-axis, and the highest point B(x p ,y p ), the lowest point D(x n ,y n ) of the sample cross section in the positive direction of the x-axis are calculated, and then the parameters d, D, and H of the cross-sectional profile line of the slump body center position are obtained.

[0012] The calculation method is as follows:

[0013] Input: slump body point cloud data (x j ,y j ) in the rectangular coordinate system (j = 1, 2…k). Wherein, k is the number of point cloud;

[0014] The point cloud data (x j ,y j ) is an ordered arrangement with respect to the horizontal coordinate x i , and satisfies x j < x j+1 ;

[0015] Output: point coordinates A(x t ,y t ), B(x p ,y p ), C(x m ,y m ), and D(x n ,y n ) (wherein n, t, p, and m ∈ [1, k])

[0016] Step1 define empty set one, empty set two

[0017] Step2 calculate the highest point of the cross-section profile Y = max(y j )

[0018] For i<k:

[0019] Step3 filter out the point cloud data on both sides of the sample collapse profile by calculating the absolute value of the difference between the longitudinal coordinates of adjacent coordinate points greater than or equal to 3mm, and add the coordinate points to set 1:

[0020] |y i+1 -y i |≥3mm

[0021] Step4 filter out the top point cloud data of the sample collapse profile by calculating the absolute value of the difference between the longitudinal coordinates of the point cloud data and the highest point of the cross-section profile less than or equal to 3mm, and add the coordinate points to set 2:

[0022] |y i -Y|≤3mm:

[0023] Step5 the scanning path of the laser scanner is from the negative half of the x-axis to the positive half of the x-axis, i.e. x i <x i+1 ; the highest point of the sample cross-section A(x t ,y t ) in the negative direction of the x-axis is the first coordinate point in set 2, the lowest point C(x m ,y m ) is the first coordinate point in set 1; the highest point of the sample cross-section B(x p ,y p ) in the positive direction of the x-axis is the last coordinate point in set 2, the lowest point D(x n ,y n ) is the last coordinate point in set 1. Calculate H, d and D by formulas (1), (2) and (3):

[0024] H=y h (1)

[0025] d=x n -x m (2)

[0026] D=x p -x t (3)。

[0027] Further, the corresponding data range of the under-improved state collapse body includes the collapse body top platform diameter range [0, d 欠 ] and the spread [30cm, D欠 Height range [H] 欠 [30cm]; The corresponding data range for a suitable modified state of collapse, including the diameter range of the top platform of the collapse body [d 欠 ,d 过 ], Extensibility [D 欠 D 过 Height range [H] 过 H 欠 The corresponding data range for the modified state of the collapse includes the diameter range of the top platform of the collapse, d > d. 过 Extensibility D > D 过 Height range [0, H] 过 The method for judging the improvement state of improved slag is as follows:

[0028] If the improved slag collapse is cone-shaped, i.e., d = 0 and H > H 欠 If so, the improved slag is in an under-improved state;

[0029] If the diameter d of the top platform of the improved slag slump is equal to the top diameter of the slump tube used in the slump test, and the height H of the improved slag slump is greater than H... 欠 If so, the improved slag is in an under-improved state;

[0030] If the diameter d, height H, and ductility D of the top platform of the improved slag collapse body satisfy: d 欠 ≤d≤d 过 D 欠 ≤D≤D 过 H 过 ≤H≤H 欠 Then the improved slag is in a suitable improved state;

[0031] If the diameter d, height H, and ductility D of the top platform of the improved slag collapse body satisfy: d > d 过 D > D 过 H < H 过 If so, the improved slag is in an over-improved state.

[0032] Furthermore, the slump image is rotated, translated, and sheared. The slump body is then segmented using an image segmentation algorithm. The size of the slump body is restored according to the corresponding proportions. The diameter d, height H, and extensibility D of the top platform of the slump body are calculated based on the coordinates of the pixels of the slump body. The improved state of the sample is then determined in conjunction with the aforementioned improved state evaluation method.

[0033] Wherein: when the sample slump body is conical, d=0, and the improved state of the sample is under-improved state; when the sample slump body is circular platform, the diameter of the top platform in the image is calculated according to the size of the pixel points, the height is H1, the extension is D1, the volume of the sample slump cylinder is V, the ratio of the image size to the actual size is x, x is calculated according to the volume calculation formula of the circular platform, and the actual size is determined, and the specific formula is as follows:

[0034]

[0035] Further, the improved slag soil to be evaluated is a foam improved slag soil.

[0036] Further, the process of preparing the foam improved slag soil is further included before the slump test.

[0037] Compared with the prior art, the present application has the beneficial effects that:

[0038] 1. The present application develops a set of automatic scanning devices, automatically obtains the cross-sectional shape of the center position of the slump body, and displays it in the form of an image, and various improved state sample slump body center position cross-sectional contour lines are classified and saved, which can provide corresponding training data for slag soil improvement state determination by using image recognition technology later.

[0039] 2. The present application proposes the value range of the slump body center cross-sectional sample contour line parameters, i.e. the top platform diameter, height and extension of the slump body under various improved states, and proposes the under-improved / suitable improved judgment critical surface and under-improved / suitable improved judgment critical according to the parameter value range. Field personnel only need to perform a slump test, take a picture of the slump body, and calculate the top platform diameter, height and extension of the slump body by a computer to automatically identify the improvement state of the slag soil; the whole process does not need manual measurement of part of the measurement parameters and judgment of the improvement state of the slag soil according to the surface characteristics of the slag soil and subjective experience;

[0040] 3. The present application more standardized, automated, accurate and fast evaluation of the plasticity of the shield slag soil, greatly simplifies the determination process of the sample improvement state, and more quickly and efficiently determines the improvement state of the slag soil. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 It is a slag soil cross-sectional shape schematic diagram of various improved state critical surfaces;

[0042] Figure 2 It is a slag soil cross-sectional shape schematic diagram of under-improved slag soil;

[0043] Figure 3 It is a slag soil cross-sectional shape schematic diagram of suitable improved slag soil;

[0044] Figure 4Fig. 2 is a schematic diagram of the improved slag soil cross-sectional shape;

[0045] Figure 5 Fig. 4 is a modified state diagram for each working condition. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0047] A shield slag soil flow plasticity automatic evaluation method based on sample slump body cross-sectional shape, referring to Fig. 1, includes the following steps: Figures 1-4

[0048] (1) The slag soil in this embodiment is round gravel soil, and the foam modified slag soil is configured, and the slump test of the modified slag soil is performed, and the specific test conditions are shown in Table 1:

[0049] Table 1 Test conditions

[0050]

[0051] (2) Determine the slag soil cross-sectional shape of the critical interface between the under-modified and the suitable modified state after the sample slump, and determine the slag soil cross-sectional shape of the critical interface between the suitable modified and the over-modified state, and extract the parameters of the modified slag soil cross-sectional shape (the longitudinal cross-sectional shape of the top center point of the over-modified slag soil slump body) belonging to the suitable modified state.

[0052] According to experience, the slump body is generally in the shape of a circular truncated cone, so the longitudinal cross-sectional shape of the top center point is approximately isosceles trapezoidal, and the cross-sectional shape parameters include the top platform diameter d, the height H, and the bottom diameter D of the modified slag soil slump body, and also indirectly include the slump degree h which can reflect the modified state. The data range of the suitable modified state slump body for reference and comparison in this embodiment includes the top platform diameter range [d 欠 ,d 过 ], the bottom diameter range [D 欠 ,D 过 ], and the height range [H 过 ,H 欠 ]. In this embodiment, d 欠 =10cm, d 过 =25cm, D 欠 =40cm, D 过 =48.6cm, H 过 =5cm, and H 欠 =25cm. ​

[0053] (3) the d, D, H of the improved slag soil to be evaluated are compared with the corresponding data range of the appropriate improved state of the slump body, and the improved state of the improved slag soil to be evaluated is judged:

[0054] If the improved slag soil slump body is conical, that is, d=0, and H>H 欠 , the improved slag soil is under improved state;

[0055] If the top platform diameter d of the improved slag soil slump body is equal to the top diameter of the slump cylinder used in the slump test, and the height H of the improved slag soil slump body is H 欠 , the improved slag soil is under improved state;

[0056] If the top platform diameter d, the height H, and the bottom diameter D of the improved slag soil slump body satisfy: d 欠 ≤d≤d 过 , D 欠 ≤D≤D 过 , and H 过 ≤H≤H 欠 , the improved slag soil is in appropriate improved state;

[0057] If the top platform diameter d, the height H, and the bottom diameter D of the improved slag soil slump body satisfy: d>d 过 , D>D 过 , and H<H 过 , the improved slag soil is over improved state.

[0058] According to the above judgment standard, the improved state of the sample is determined according to the cross-sectional shape of the center position of the sample after slump, and the determination result is shown in Table 1. Figure 5 Therefore, the sample improved state evaluation method according to the cross-sectional shape of the top surface center position of the sample slump body is reasonable, accurate, and more feasible.

[0059] (4) The slump image is rotated, translated, and sheared, and the slump body is segmented by an image segmentation algorithm, the top platform diameter d, the height H, and the extension D of the slump body are calculated according to the coordinates and proportions of the segmented slump body pixels, and the improved state of the sample is determined by combining the above improved state evaluation method.

[0060] The above embodiments are preferred embodiments of the present application, and those skilled in the art can make various transformations or improvements on the basis of the above embodiments, and these transformations or improvements should be within the scope of the present application without departing from the general concept of the present application.

Claims

1. A method for automatically evaluating the plasticity of a shield muck flow based on the cross-sectional shape of a slump body of a test sample, characterized by, The method comprises the following steps: S1: a series of slag soil improvement and slump test are carried out in the room, and the improvement state is determined according to the reasonable slump value range and whether the sample surface is separated from water and foam; S2: the laser scanner is used to obtain the cross-sectional shape point cloud data of the sample slump body center position, and the related parameters of the cross-sectional profile line of the slump body center position are calculated, such as the slump body height H, the top platform diameter d and the extension degree D of the slump body; S3: the parameter d, D and H of the cross-sectional profile line of the sample slump body center position under various improvement states are determined; S4: the slump body image is rotated, translated, and sheared, the slump body is segmented, and the The method for obtaining longitudinal point cloud data by using a laser scanner is as follows: after the slump test is carried out on the slump test board, the bracket on which the laser scanner is fixed is moved to the top of the slump body by starting the driving device, and the longitudinal point cloud data of the slump body over the top center point are scanned by starting the laser scanner.

2. The method of claim 1, wherein, The calculation method is as follows:

3. The method of claim 1, wherein, The related parameters of the cross-sectional profile line of the slump body center position, such as the slump body height H, the top platform diameter d, and the extension D of the slump body, are calculated by obtaining the cross-sectional profile line point cloud data of the slump body center position. A coordinate system is established with the sample center as the origin, the sample height direction as the positive half of the y-axis, and the right side of the slump body center as the positive half of the x-axis. The highest point A(x t ,y t ), the lowest point C(x m ,y m ) of the sample cross section in the negative direction of the x-axis of the sample cross-sectional profile line, and the highest point B(x p ,y p ), the lowest point D(x n ,y n ) of the sample cross section in the positive direction of the x-axis are calculated, and then the parameters d, D, and H of the cross-sectional profile line of the slump body center position are obtained. Step 1: define empty set one and empty set two Input: Point cloud data of the collapsing body after conversion to the rectangular coordinate system (x j ,x j+1 ), j = 1, 2…k, wherein k is the number of point clouds; Point cloud data (x j ,y j ) is an ordered arrangement with respect to the horizontal coordinate x j , satisfying x j <x j+1 ; Output: Calculate the point coordinates A(x t ,y t ), B(x p ,y p ), C(x m ,y m ), D(x n ,y n ), where n, t, p, m ∈ [1, k]; For i < k: Step 2 Calculate the maximum longitudinal coordinate value Y = max(y) of the cross-sectional profile j ) Step 3: the point cloud data on both sides of the sample slump body profile are screened out by calculating the absolute value of the difference between the longitudinal coordinates of adjacent coordinate points, and the coordinate points are added to set one: Step 4: the top point cloud data of the sample slump body profile are screened out by calculating the absolute value of the difference between the longitudinal coordinates of the point cloud data and the highest point of the cross-sectional profile, and the coordinate points are added to set two: | y i+1 - y i | ≥ 3 mm The slump body image is rotated, translated and sheared, the slump body is segmented by the threshold segmentation method, the size of the segmented slump body is restored according to the corresponding proportion, the top platform diameter d, the height H and the extension degree D of the slump body are calculated according to step 3, and the improvement state of the sample is determined according to the above improvement state evaluation method; |y i - Y | < 3 mm: Step 5 the scanning path of the laser scanner is from the negative half axis of x axis to the positive half axis of x axis, namely x i <x i+1 ; the highest point A(x t ,y t ) of the sample cross section in the negative direction of x axis is the first coordinate point in set two, the lowest point C(x m ,y m ) is the first coordinate point in set one; the highest point B(x p ,y p ) of the sample cross section in the positive direction of x axis is the last coordinate point in set two, the lowest point D(x n ,y n ) is the last coordinate point in set one, and the thickness of the sample is calculated by formulas (1), (2) and (3) H = y h (1) d = x n - x m (2) D = x p - x t (3).

4. The method of claim 1, wherein, The corresponding data range of the under-modified state slump body includes the slump body top platform diameter range [0, d 欠 ], the spread [30, D 欠 ], and the height range [H 欠 , 30]; the corresponding data range of the suitable modified state slump body includes the slump body top platform diameter range [d 欠 , d 过 ], the spread [D 欠 , D 过 ], and the height range [H 过 , H 欠 ]; and the corresponding data range of the over-modified state slump body includes the slump body top platform diameter range d>D 过 , the spread D>D 过 , and the height range [0, H 过 ]. The method for judging the modified state of the modified slag soil is: If the improved slag soil is in a conical shape, i.e. d = 0, and H > H 欠 , the improved slag soil is in an under-improved state. If the top platform diameter d of the improved slag soil slump body is equal to the top diameter of the slump cone used in the slump test, and the height H of the improved slag soil slump body is greater than H 欠 , then the improved slag soil is under-improved. If the top platform diameter d, height H, and spread D of the improved slag soil meet: d 欠 ≤ d ≤ d 过 , D 欠 ≤ D ≤ D 过 , H 过 ≤ H ≤ H 欠 , then the improved slag soil is in a suitable improved state; If the top platform diameter d, height H, and spread D of the improved slag soil meet: d>d 过 , D>D 过 , and H<H 过 , the improved slag soil is over-improved.

5. The method of claim 1, wherein, Wherein: when the sample slump body is conical, d = 0, and the improvement state of the sample is under-improved; when the sample slump body is a circular truncated cone, the top platform diameter d1, the height H1 and the extension degree D1 in the image are calculated according to the size of the image pixel points, the volume of the sample slump cylinder is V, the size ratio of the image size and the actual size is x, x is calculated according to the volume calculation formula of the circular truncated cone, and the actual size of the top platform diameter d1x, the height H1x and the extension degree D1x are determined, and the specific formula (4) is as follows: The improved slag soil to be evaluated is foam improved slag soil.

6. The method of claim 1, wherein, The process of preparing the foam improved slag soil is further included before the slump test.

7. The method of claim 1, wherein, ​

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