CN115221748A - Method for predicting stress of steel wire in hoisting steel wire rope based on three-dimensional image recognition - Google Patents

Abstract

The invention provides a method for predicting the stress of a steel wire in a hoisting steel wire rope based on three-dimensional image recognition. Firstly, carrying out stress analysis on a steel wire rope in a lifting system based on simulation analysis software; then, processing the surface of the steel wire rope, mounting the steel wire rope to a tensile testing machine, debugging a three-dimensional stress-strain meter, shooting a surface picture of the steel wire rope when the steel wire rope is gradually loaded, setting reference spots on the shot picture, dividing grids, comparing the change conditions of pixel points in different grids, and calculating to obtain the surface stress and the strain of the steel wire rope; and finally, comparing and analyzing the simulation result and the detection result, verifying the consistency of the simulation result and the detection result, and predicting the stress of the steel wire inside the actual hoisting steel wire rope according to the simulation result and the detection result.

Description

Method for predicting stress of steel wire in hoisting steel wire rope based on three-dimensional image recognition

Technical Field

The invention relates to a method for predicting the stress of a steel wire in a hoisting steel wire rope based on three-dimensional image recognition.

Background

When the mine degree of depth is great, owing to receive the restriction of alternating stress, friction formula hoisting device can not be applicable to the deep well and promote the operating mode, and single rope wound form hoisting device is owing to receive the restriction of rope than the ratio, and the equipment volume will be very big, and this has greatly increased the production maintenance cost, and consequently, the student generally thinks at present uses many ropes wound form hoisting device to carry out the deep well and promotes the transportation comparatively reasonable.

The steel wire rope in the winding type lifting system is a key part in the lifting system and is also a part with the most complex bearing working condition, and once the steel wire rope is damaged, the steel wire rope is easy to fail and break, and serious mine safety accidents can be caused, so that the steel wire rope needs to be subjected to nondestructive detection on the premise of not influencing the work of the system.

At present, there are many nondestructive testing methods for steel wire ropes, including ultrasonic testing, radiation testing, eddy current testing, electromagnetic testing, mechanical testing, etc. which are commonly used for nondestructive testing, and electromagnetic testing is widely used in industry. However, the above methods detect a damaged part, and cannot predict a part that may be damaged, and there is a certain information hysteresis. Therefore, a new steel wire rope detection method is needed to detect steel wire ropes at different positions in a hoisting system and judge areas which may be damaged, and the steel wire rope damage mechanism needs to be deeply researched.

According to research, the steel wire rope is mostly damaged due to surface abrasion, the abrasion is caused because the steel wire rope has a region with large stress and the steel wire rope in the region generates relative displacement, the steel wire rope stress can be divided into tensile stress, bending stress and contact stress, and a certain corresponding relation exists among different stresses and between the stress and the load at the rope end.

At present, no patent or literature is disclosed for predicting the stress of the steel wire inside the hoisting rope.

Disclosure of Invention

Aiming at the technical problems, the invention provides a method for predicting the stress of the steel wire inside the hoisting steel wire rope based on three-dimensional image recognition, which can recognize the surface stress of the steel wire rope in a hoisting system at lower cost and predict the stress value of the steel wire inside the steel wire rope under the condition of not influencing the normal operation of mine hoisting system equipment.

In order to achieve the technical purpose, the invention adopts the following technical scheme:

a method for predicting the stress of a steel wire in a hoisting steel wire rope based on three-dimensional image recognition comprises the following steps:

s1, carrying out stress analysis on a steel wire rope in a lifting system based on simulation analysis software to obtain a region with larger stress of the steel wire rope;

s2, detecting the steel wire rope in the running process based on a three-dimensional stress strain gauge;

s21, processing the surface of the steel wire rope to be detected, firstly cleaning the surface of the steel wire rope, then uniformly spraying white matte paint on the surface of the steel wire rope, finally spraying black matte paint to form uniform fine black spots on the surface of the steel wire rope,

s22, placing a three-dimensional stress strain gauge, adjusting a light angle, a lens position and an angle, and adjusting a lens focal length and an aperture so that the surface of the steel wire rope to be observed can be clearly seen by a software interface of the three-dimensional stress strain gauge;

s23, calibrating by using a calibration plate, determining a conversion relation between a pixel point in the picture and the physical size of the steel wire rope, and shooting a surface image of the steel wire rope;

s24, processing and analyzing the image shot by the three-dimensional strain gauge;

s241, selecting a reference spot;

s242, dividing the picture into m multiplied by n grids,

s243, numbering grids in each picture from the reference spot, comparing each picture with grids with the same number in the first picture, calculating the change condition of pixel points in the grids, wherein the change of the pixel points corresponds to the strain of the surface of the steel wire rope, converting according to the conversion relation determined by the calibration plate, calculating the surface strain of the steel wire rope, and calculating the surface stress of the steel wire rope through the surface strain of the steel wire rope and the elastic modulus of the surface material of the steel wire rope;

and S3, deducing the internal steel wire stress of the actual steel wire rope according to the simulation of the step S1 and the detection result of the step S2.

Further, step 1 specifically includes the following substeps:

s11, deducing an equation of the center line of each steel wire of the hoisting steel wire rope by using a Frenet frame;

s12, establishing a hoisting steel wire rope model based on three-dimensional drawing software capable of carrying out parametric modeling according to actual hoisting steel wire rope parameters and the steel wire center line equation;

and S13, establishing a hoisting steel wire rope finite element model based on statics finite element simulation analysis software, dividing grids, setting material properties, setting contact parameters, applying load and constraint, carrying out finite element solution, and outputting steel wire rope stress and strain.

Further, when the reference blob is selected in step S241, a blob that is not deformed or has the smallest amount of deformation is selected as the reference blob.

Further, in step S242, the size of the grid is set according to the analysis accuracy and the size of the spots in the picture, so that each spot occupies at least 2 × 2 grids.

Further, step S3 specifically includes:

and detecting the surface stress of the steel wire rope by using a three-dimensional stress strain gauge, comparing the surface stress with a simulation result, determining the proportional relation between simulation data and detection data, and predicting the stress of the steel wire inside the hoisting steel wire rope.

Has the advantages that:

compared with the existing method for detecting the internal stress of the steel wire rope, the method for predicting the internal steel wire stress of the hoisting steel wire rope based on three-dimensional image recognition has the advantages that:

firstly, the method combines the simulation technology and the image processing technology, can detect the steel wire rope on the basis of not influencing the normal operation of the mine hoisting system equipment, and can be used as a daily monitoring means of the steel wire rope.

Secondly, the method has lower cost and convenient assembly and disassembly, and can be applied to mine hoisting systems with different parameters.

Thirdly, the method overcomes the limitation of the traditional method and can detect the stress values of the steel wire rope at different positions of the lifting system.

Drawings

FIG. 1 is a flow chart of a method for predicting the stress of a steel wire inside a hoisting steel wire rope according to the present invention;

FIG. 2 is a simulation calculation result of the equivalent stress at the whole rope and the 1/2 rope length section of the hoisting steel wire rope according to the present invention;

FIG. 3 is the surface of the steel cord after the treatment of the present invention;

FIG. 4 (a) is the data measured by the three-dimensional strain gauge of the present invention;

fig. 4 (b) is a simulation result of the wire rope in a suspended state.

Detailed Description

The present invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.

In this embodiment, stress analysis is performed on a steel wire rope in a hoisting system based on simulation analysis software, and the method includes the following steps:

(1) Deducing an equation of the center line of each steel wire of the hoisting steel wire rope based on a Frenet standard frame;

(2) Establishing a hoisting steel wire rope model based on three-dimensional drawing software capable of carrying out parametric modeling according to actual hoisting steel wire rope parameters and equations;

(3) Establishing a finite element model of the hoisting steel wire rope based on statics simulation analysis software, dividing grids, setting material properties, setting contact parameters, applying load and constraint, and carrying out finite element solution, wherein the solution result is shown in figure 2.

(4) And analyzing the solved steel wire rope model, and searching a region with larger stress. As can be seen from fig. 2, the stress values of the steel wires inside the steel wire rope at the contact positions between strands are large.

Then, based on a three-dimensional stress strain gauge, the steel wire rope is detected during loading, and the method comprises the following steps:

(1) Processing the surface of the steel wire rope to be detected, firstly cleaning the surface of the steel wire rope, then uniformly spraying white matte paint on the surface of the steel wire rope, and finally spraying black matte paint to form uniform fine black spots on the surface of the steel wire rope;

(2) Placing a three-dimensional stress strain gauge, and adjusting the light angle, the lens position and the angle;

(3) Adjusting the focal length and the aperture of the lens to enable the software interface of the three-dimensional stress-strain gauge to clearly see the surface of the steel wire rope to be observed;

(4) Calibrating by using a calibration plate, and determining the conversion relation between the pixel point in the picture and the physical size of the steel wire rope;

(5) And shooting a steel wire rope surface image in the loading process, and carrying out image processing and analysis on the steel wire rope surface image to solve the steel wire rope surface stress.

The image processing and analyzing process comprises the following steps:

(1) Selecting a spot with no deformation or minimum deformation as a reference spot;

(2) Dividing the picture into m multiplied by n grids, wherein the size of the grids is set according to the analysis precision and the size of the spots in the picture, and each spot is ensured to occupy at least 2 multiplied by 2 grids;

(3) Numbering the grids within each picture starting from the reference blob;

(4) And comparing each picture with the grids with the same number in the first picture, calculating the change condition of the pixel points in the grids, converting the change of the pixel points, namely the strain of the surface of the steel wire rope, according to the conversion relation determined by the calibration plate, calculating the surface strain of the steel wire rope, and calculating the surface stress of the steel wire rope according to the elastic modulus of the surface material of the steel wire rope.

And finally, comparing and analyzing the simulation result and the detection result, determining the proportional relation between the simulation data and the detection data, and predicting the stress of the steel wire in the hoisting steel wire rope.

The simulation and detection results are shown in fig. 4. As can be seen from the figure, the steel wire rope strain result has bulges and depressions, the whole steel wire rope is wavy, and the stage points 2 and 3 are positioned on the raised parts in the figure and are the outer surfaces of the strands; the stage points 0 and 1 are located in the depressions and are the inter-strand contact areas of the strands. Except for the initial loading stage, the strain values of the stage points 0 and 1 are both greater than the strain values of the stage points 2 and 3; as the load increases, the rate of rise of the strain at phase points 0, 1 is greater than at phase points 2, 3.

In fig. 4 (b), the boundary load of the simulation model gradually increases with the increase of time, and the change rules of the phase points 0 'and 1' are the same as those of the phase points 0 and 1 in fig. 4 (a); the change rule of the stage points 2 'and 3' is the same as that of the stage points 2 and 3 in fig. 4 (a), and the phenomenon proves that the simulation is consistent with the detection result.

After the loading is finished, the results of the detection and the suspension rope simulation calculation are shown in table 1. The deviation is 16.83% at the maximum and less than 20%, which further proves that the simulation is consistent with the detection.

TABLE 1 comparison of simulation data and test data

Claims (5)

1. A method for predicting the stress of a steel wire in a hoisting steel wire rope based on three-dimensional image recognition is characterized by comprising the following steps:

s1, carrying out stress analysis on a steel wire rope in a lifting system based on simulation analysis software to obtain a region with larger stress of the steel wire rope;

s2, detecting the steel wire rope in the running process based on a three-dimensional stress strain gauge;

s21, processing the surface of the steel wire rope to be detected, firstly cleaning the surface of the steel wire rope, then uniformly spraying white matte paint on the surface of the steel wire rope, finally spraying black matte paint to form uniform fine black spots on the surface of the steel wire rope,

s22, placing a three-dimensional stress strain gauge, adjusting a light angle, a lens position and an angle, and adjusting a lens focal length and an aperture so that the surface of the steel wire rope to be observed can be clearly seen by a software interface of the three-dimensional stress strain gauge;

s23, calibrating by using a calibration plate, determining a conversion relation between a pixel point in the picture and the physical size of the steel wire rope, and shooting a steel wire rope surface image;

s24, processing and analyzing the image shot by the three-dimensional strain gauge;

s241, selecting a reference spot;

s242, dividing the picture into m multiplied by n grids,

s243, numbering grids in each picture from the reference spot, comparing each picture with grids with the same number in the first picture, calculating the change condition of pixel points in the grids, wherein the change of the pixel points corresponds to the strain of the surface of the steel wire rope, converting according to the conversion relation determined by the calibration plate, calculating the surface strain of the steel wire rope, and calculating the surface stress of the steel wire rope through the surface strain of the steel wire rope and the elastic modulus of the surface material of the steel wire rope;

and S3, deducing the stress of the steel wire inside the actual steel wire rope according to the simulation of the step S1 and the detection result of the step S2.

2. The method for predicting the stress of the steel wire in the hoisting steel wire rope based on the three-dimensional image recognition according to claim 1, wherein the step 1 specifically comprises the following substeps:

s11, deducing a central line equation of each steel wire of the hoisting steel wire rope by utilizing a Frenet frame;

s12, establishing a hoisting steel wire rope model based on three-dimensional drawing software capable of carrying out parametric modeling according to actual hoisting steel wire rope parameters and the steel wire center line equation;

and S13, establishing a finite element model of the hoisting steel wire rope based on statics finite element simulation analysis software, dividing grids, setting material properties, setting contact parameters, applying load and constraint, carrying out finite element solution, and outputting steel wire rope stress and strain.

3. The method for predicting the internal wire stress of the hoist rope based on the three-dimensional image recognition according to claim 1, wherein in the step S241, when the reference spot is selected, a spot which is not deformed or has the smallest deformation amount is selected as the reference spot.

4. The method for predicting the stress of the steel wire inside the hoisting steel wire rope based on the three-dimensional image recognition according to claim 1, wherein in the step S242, the size of the grid is set according to the analysis precision and the size of the spots in the picture, so that each spot at least occupies 2 x 2 grids.

5. The method for predicting the stress of the steel wire in the hoisting steel wire rope based on the three-dimensional image recognition according to claim 1, wherein the step S3 is specifically as follows:

and detecting the surface stress of the steel wire rope by using a three-dimensional stress strain gauge, comparing the surface stress with a simulation result, determining the proportional relation between simulation data and detection data, and predicting the stress of the steel wire inside the hoisting steel wire rope.

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