CN116427221A - Rapid nondestructive testing method for degradation state of ballast bed - Google Patents
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- 238000000572 ellipsometry Methods 0.000 claims description 6
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- E—FIXED CONSTRUCTIONS
- E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
- E01B—PERMANENT WAY; PERMANENT-WAY TOOLS; MACHINES FOR MAKING RAILWAYS OF ALL KINDS
- E01B35/00—Applications of measuring apparatus or devices for track-building purposes
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- E—FIXED CONSTRUCTIONS
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- E01B—PERMANENT WAY; PERMANENT-WAY TOOLS; MACHINES FOR MAKING RAILWAYS OF ALL KINDS
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Abstract
The invention discloses a rapid nondestructive testing method for a degradation state of a ballast bed, which comprises the steps of selecting ballast particles at each detection point for scanning; calculating the volume and true sphericity of an inscribed ellipsoid with the largest volume in an area surrounded by the point cloud of the ballast particles according to the point cloud data of the ballast particles; and calculating a ballast deterioration index at each detection point by using the true ellipsoid, and evaluating the ballast deterioration state. According to the invention, through carrying out nondestructive testing on the degradation state of a limited number of ballast particles, the interference of equipment quality and environmental factors is avoided in the detection process, the degradation index of the ballast with high correlation with the degradation state of the ballast is calculated, the degradation condition of the ballast is evaluated, and more comprehensive and accurate evaluation and maintenance activities of the ballast condition in actual engineering are promoted, so that maintenance resources are saved.
Description
Technical Field
The invention belongs to the field of track detection, and particularly relates to a rapid nondestructive detection method for a degradation state of a ballast bed.
Background
Although ballastless tracks have been rapidly developed in recent decades, ballastless tracks are still the main track types for various transportation (high-speed railways, heavy-load railways, subways, etc.). Particularly in the common high-speed railways in China, ballasted tracks are the main track types. The ballast bed is a key component of a ballast track of a heavy haul railway, mainly comprises ballasts, uniformly supports sleepers, uniformly transmits load to substructures (roadbed, bridge and tunnel), and resists the movement of the sleepers and the drainage. The ballast track running for a long time is subjected to the periodic load of the train, so that the degradation (crushing and abrasion) of the ballast particles and the pollution (the gap between the ballasts is replaced by dirt materials with finer size) are rapidly increased, and the deformation, unsmooth drainage and bearing capacity reduction of the track are caused. At this time, the ballasts must be cleaned or replaced in accordance with maintenance guidelines, which is time-consuming and expensive, resulting in significant labor and capital costs. It is therefore of vital importance to determine at which stage of the track bed life cycle, contamination level or degradation level cleaning or replacement should be started and to find the most favourable cost. To obtain this key judgment, it is necessary to conduct a long-term and frequent detection of the state of the ballast bed.
However, the pollution detection of the ballast bed is not the most conventional detection item, the degradation detection of the ballast bed is not even carried out in the actual ballasted track engineering, and no specific detection regulation about the pollution or degradation of the ballast bed exists in the current ballasted track maintenance related specifications. Therefore, the ballast bed degradation detection method provided by the invention fills the blank of the current ballast bed degradation detection technology on one hand and promotes the establishment of corresponding specifications; on the other hand, the method is used as a more scientific detection means to promote reasonable formulation of a ballast maintenance plan, so that the ballast consumption is reduced, the maintenance cost is controlled, and the method is matched with the main development direction of the ballast maintenance detection in the future.
Previously, due to lack of advancement of detection technology and equipment, ballast pollution maintenance indexes are only based on total passing load, which is a rough method for predicting ballast bed conditions and estimating ballast pollution levels. Another method is to determine the pollution index of the ballast bed or the degree of fragmentation of the ballast by screening a ballast sample drilled from the site, which requires a lot of manpower and resources and crushes the original ballast bed structure, so it is a relatively limited method and is rarely used in a typical railway inspection.
In contrast, nondestructive inspection techniques have been increasingly used in recent years. Ground Penetrating Radar (GPR) is used to detect the pollution level of railway ballast as a detection technique commonly used in current railway ballast maintenance inspection. However, there are still non-negligible drawbacks in the ground penetrating radar itself and in the corresponding ballast maintenance standards: (1) GPR can only detect pollution, which is generated during the use of railway ballast, and its source is affected by various factors such as total passing load, type of transportation, railway ballast materials, special structure, region and climatic conditions. The speed of the railway ballast reaching the pollution level required to be maintained is different under different conditions, so that when the ground penetrating radar detects that the pollution is not serious, the railway ballast is possibly deteriorated to the extent that emergency maintenance is required; (2) The correlation between equipment quality (antenna), environmental interference sources (cables, etc.) and pollution indexes can seriously affect the determination of the pollution level of the railway ballast, and the ground penetrating radar can need complex on-site or laboratory railway ballast screening to assist in inspection; (3) The difficulty of data analysis is high, the data obtained by the GPR needs to be processed and analyzed in a complex mode, specialized software and technical support are needed, and the requirements on detection personnel are high.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a rapid nondestructive testing method for the degradation state of a ballast bed. The non-destructive detection is carried out on the degradation state of the limited ballast particles, the condition that the ballast particles are not interfered by the quality of equipment and environmental factors is ensured in the detection process, the degradation index of the ballast is further calculated, the degradation condition of the ballast is estimated, and more comprehensive and accurate ballast condition estimation and maintenance activities in actual engineering are promoted so as to save maintenance resources.
The above object of the present invention is achieved by the following technical solutions:
a rapid nondestructive testing method for the degradation state of a ballast bed comprises the following steps:
step 1, scanning ballast particles of detection points with set track length intervals to obtain ballast particle point cloud data, wherein the number of the ballast particles scanned by each detection point is 10-30;
step 2, calculating an inscribed ellipsoid with the largest volume in a region surrounded by a point cloud of the ballast particles corresponding to each ballast particle, and outputting the volume of the inscribed ellipsoid and the volume of the ballast particles;
step 3,Calculating true ellipsometry E of each ballast particle of the detection point according to the volume of the ballast particle and the volume of the corresponding inscribed ellipsoid 3D ；
Step 4, calculating a degradation index D of the ballast bed at the detection point according to the true ellipsoids of all the ballast particles at the detection point b 。
Step 2 as described above comprises the steps of:
2.1, reconstructing the surfaces of the ballast particles by using the ballast particle point cloud data and calculating the volume of the ballast particles;
step 2.2, the parameter equation of the ellipsoid comprises three parameters, namely a three-dimensional real matrix P, a three-dimensional vector q and a real number r, wherein the external points are defined as points which are not in an ellipsoid set determined by the parameter equation of the ellipsoid, the internal points are defined as points in the ellipsoid set determined by the parameter equation of the ellipsoid, and the initial internal points are determined;
2.3, the parameter equation of the ellipsoid, the ellipsoid does not contain any external points, and the three-dimensional real matrix P is a positive definite matrix to jointly form a semi-definite rule equation;
the imported railway ballast particle point cloud data is used as an external point, the external point and the initial internal point input in the step 2.3 are substituted into a semi-definite programming equation together, the solution of the equation is searched, if three parameters are solved, the step 2.4 is started, and if the three parameters are not solved, the step 2.2 is returned to search the initial internal point again;
step 2.4, randomly generating a new internal point in the area surrounded by the ballast particle point cloud;
step 2.5, checking whether the iteration times are smaller than the total iteration times, if the iteration times are smaller than or equal to the total iteration times, entering step 2.6, and if the iteration times are larger than or equal to the total iteration times, entering step 2.10;
step 2.6, calculating a semi-definite rule equation again by using the updated internal points and the particle point cloud data in the step 2.4, if the parameters of three ellipsoids are solved, obtaining a new internal ellipsoid and entering the step 2.7; if no solution exists, the step 2.8 is carried out;
step 2.7, if the volume of the new internal ellipsoid is not more than the volume of the internal ellipsoid generated last time, entering step 2.8; otherwise, enter step 2.9;
step 2.8, increasing the accumulated invalid iteration number by 1, returning to step 2.4 if the accumulated invalid iteration number is smaller than 6, deleting the finally generated internal point if the accumulated invalid iteration number is equal to 6, assigning the accumulated invalid iteration number to be 0, and returning to step 2.4;
step 2.9, updating the volume of the internal ellipsoid and returning to step 2.4;
and 2.10, outputting the finally obtained internal ellipsoid as an inscribed ellipsoid, and outputting the volume of the finally obtained inscribed ellipsoid and the volume of the ballast particles.
The selection of the initial interior point in step 2.2 as described above comprises the steps of:
and selecting an initial ellipsoid in the point cloud of the ballast particles, and finding coordinates of six endpoints of three axes of the initial ellipsoid as six initial internal points.
If there is no solution in the step 2.3, the method returns to the step 2.2 to find the initial internal point with smaller initial ellipsoidal volume again.
The track length is set to 500m-1.5km as described above.
In the step 3, the true ellipsometry E of the ballast particles is calculated 3D Based on the following formula:
wherein V is E V is the volume of inscribed ellipsoids of the ballast particles P Is the volume of the ballast particles.
In step 4 as described above, the deterioration index D of the ballast bed at the detection point is calculated b Based on the following formula:
wherein E is 3Di And (3) representing the true sphericity of the ith ballast particle, wherein n is the number of scanned ballast particles at a single detection point.
Compared with the prior art, the invention has the following beneficial effects:
1. the ballast bed degradation detection has a more direct link with the service condition of the ballast bed than the ballast bed pollution detection. The method for detecting the degradation of the ballast bed can promote the effective and comprehensive assessment of the service condition of the ballast bed and more scientifically guide the maintenance activity of the ballast bed.
2. According to the track bed degradation detection technology, experiments prove that the correlation between the track bed degradation index and the track bed degradation degree is good, and the track bed degradation degree can be accurately estimated, so that the problem that the GPR technical index is easy to misjudge is solved.
3. The nondestructive testing technology (scanning and calculating) adopted by the invention is not influenced by equipment quality and other signal interference, and the application scene is wider.
4. The scanning process of the invention has simple operation, convenient parameter input and clear and understandable output result, so the detection technology of the invention has lower requirement on detection personnel and is easy to realize.
Drawings
FIG. 1 is a schematic diagram of the structure of the present invention;
FIG. 2 is an example of the final calculation result of an inscribed ellipsoid;
FIG. 3 is a schematic diagram showing the degradation degree of the ballast corresponding to the average true sphericity;
fig. 4 is a schematic view of a scanning of ballast particles.
Detailed Description
The present invention will be further described in detail below in conjunction with the following examples, for the purpose of facilitating understanding and practicing the present invention by those of ordinary skill in the art, it being understood that the examples described herein are for the purpose of illustration and explanation only and are not intended to limit the invention.
A rapid nondestructive testing method for the degradation state of a ballast bed comprises the following steps:
step 1, scanning selected ballast particles at detection points with set track length intervals to obtain ballast particle point cloud data, wherein the number of the ballast particles scanned by each detection point is 20 in the embodiment;
and 1.1, in a track section detected regularly, taking a detection point every 1km in track length, and randomly selecting 1 ballast particle near a sleeper at the detection point.
Step 1.2, scanning the selected ballast particles to obtain ballast particle point cloud data:
step 1.2.1, as shown in fig. 3, selecting a relatively flat surface of scanned ballast particles as a sticker pasting surface, pasting at least 3 coordinate stickers on the sticker pasting surface, and in addition, selecting a first placing surface of the ballast particles (the placing surface is a contact surface of the particles and a black plastic hard plate, and is based on the condition that the ballast particles can stand on the black plastic hard plate), placing the first placing surface of the ballast particles on the horizontal black plastic hard plate, exposing a second placing surface and the sticker pasting surface, and pasting coordinate stickers (at intervals of 2 cm-3 cm) on one surface (the top surface of the black plastic hard plate) of the black plastic hard plate, on which the ballast particles are placed;
step 1.2.2, aligning a paste surface of the ballast particles, which is pasted with the coordinate paste, with a three-dimensional scanner, performing first scanning to establish the relative spatial position between the coordinate paste on the ballast particles and the coordinate paste on the black plastic hard board, and scanning the ballast particles for a plurality of times from a plurality of angles by using a handheld three-dimensional scanner after the first scanning to establish the coordinates of the ballast particles except the surface point cloud of the first placing surface;
step 1.2.3, as shown in fig. 3, rotating the ballast particles to enable the second placing surface to be used as a contact surface between the ballast particles and the black plastic hard board, and enabling the first placing surface and the sticker pasting surface to be exposed and keeping the sticker pasting surface to be unshielded;
step 1.2.4, scanning the coordinate decal on the ballast particles again, and identifying the relative spatial positions of the coordinate decal on the ballast particles and the coordinate points on the black plastic hard board, so as to reestablish the connection between the coordinate decal on the ballast particles and the coordinate points on the black plastic hard board;
step 1.2.5, scanning the ballast particles for multiple times to ensure that the point cloud coordinates of the first placing surface are established;
and step 1.2.6, finally, processing three-dimensional point cloud noise by using digital image processing software and automatically generating a triangular curved surface. Then, the ballast particle point cloud data (the ballast particle point cloud is composed of millions of points of the particle surface profile) is output in a file format of "stl".
Step 1.3: and placing back the scanned ballast particles in situ.
Step 1.4: and (3) selecting different ballast particles at each detection point, and repeating the steps 1.1 to 1.3 until 20 ballast particles are scanned at the detection point.
Step 1.5: moving to the next detection point, and repeating the steps 1.1 to 1.4.
Step 1.6: and (5) repeating the step 1.5 until all detection point sampling scanning works are completed.
Step 2: calculating an inscribed ellipsoid with the largest volume in an area surrounded by the point cloud of the ballast particles corresponding to each ballast particle according to the point cloud data of the ballast particles, and outputting the volume of the inscribed ellipsoid and the volume of the ballast particles:
2.1, reconstructing the surfaces of the ballast particles by using the ballast particle point cloud data and calculating the volume of the ballast particles;
step 2.2, in the present algorithm: an ellipsoid is represented using a set of all the points that make up the ellipsoid (this set is called an ellipsoid set), the points within the set satisfying a specific expression, this expression being called the parametric equation for the ellipsoid. The parametric equation for ellipsoids contains three parameters, three-dimensional real matrix P, three-dimensional vector q, and real number r, respectively. Once the three parameters are determined, the ellipsoids are determined. And defines the external points as points not within the set of ellipsoids determined by the parametric equation of the ellipsoids (which do not satisfy the parametric equation of the ellipsoids), and defines the internal points as points within the set of ellipsoids determined by the parametric equation of the ellipsoids (which satisfy the parametric equation of the ellipsoids).
Determining and inputting coordinates of an initial internal point: the point cloud and the space rectangular coordinate system of the ballast particles are displayed by using the Python visualization tool, an initial ellipsoid (approximately only but not exceeding the ballast particle point cloud) in the ballast particle point cloud is selected, and coordinates of six endpoints of three axes of the initial ellipsoid are found and are input as initial internal points.
Step 2.3, in the present algorithm: the parametric equation for an ellipsoid (i.e. the ellipsoid must contain all internal points), the first boundary condition-the ellipsoid does not contain any external points, and the second boundary condition-P is a positive definite matrix together constitute a semi-definite rule equation. By solving the semi-definite programming equation, a three-dimensional real matrix P, a three-dimensional vector q and a real number r can be obtained, so that ellipsoids with three parameters uniquely determined are obtained.
The imported railway ballast particle point cloud data is used as an external point, and is substituted into a semi-definite programming equation together with the initial internal point input in the step 2.3, and the solution of the equation is found. If the three parameters are solved, the step 2.4 is entered, and if the three parameters are not solved, the step 2.2 is returned to find the initial internal point with smaller initial ellipsoidal volume again.
Step 2.4, randomly generating a new internal point in an area surrounded by the ballast particle point cloud on the basis of the original internal point;
step 2.5, checking whether the iteration times are smaller than the total iteration times, if the iteration times are smaller than or equal to the total iteration times, entering step 2.6, and if the iteration times are larger than or equal to the total iteration times, entering step 2.10.
And 2.6, calculating a semi-definite rule equation again by using the updated internal points and the particle point cloud data in the step 2.4, and if the parameters of the three ellipsoids are solved, obtaining a new internal ellipsoid and entering the step 2.7. If no solution exists, the process proceeds to step 2.8.
Step 2.7, checking whether the volume of the new internal ellipsoid is larger than the volume of the internal ellipsoid generated last time, and if the volume of the new internal ellipsoid is not larger than the volume of the internal ellipsoid generated last time, entering step 2.8. Otherwise, step 2.9 is entered.
Step 2.8, increasing the accumulated invalid iteration number by 1, returning to step 2.4 if the accumulated invalid iteration number is smaller than 6, deleting the finally generated internal point if the accumulated invalid iteration number is equal to 6, assigning the accumulated invalid iteration number to be 0, and returning to step 2.4;
step 2.9, updating the volume of the internal ellipsoid and returning to step 2.4.
Step 2.10, outputting the finally obtained internal ellipsoid as an inscribed ellipsoid, and outputting the volume of the finally obtained inscribed ellipsoid and the volume of the ballast particles;
step 3: calculating true ellipsometry E of each ballast particle of the detection point by using the volume of the ballast particle output in the step 2 and the volume of the corresponding inscribed ellipsoid 3D ：
Wherein E is 3D True ellipticity, V, of the ballast particles E V is the volume of inscribed ellipsoids of the ballast particles P Is the volume of the ballast particles.
Step 4, calculating a degradation index D of the ballast bed at the detection point according to the true ellipsoids of all the ballast particles at the detection point b ：
Wherein E is 3Di Representing true ellipsometry of the ith ballast particle, n being the number of scanned ballast particles at a single detection point, in this embodiment n=20;
when the degradation index of the ballast bed is smaller than 0.47, the service condition of the detection point ballast bed is good, and the detection point ballast bed is not required to be maintained.
When the degradation index of the ballast bed is greater than or equal to 0.47 and less than 0.50, the service condition of the ballast bed at the detection point is generally indicated, and the degradation begins to be increased, so that periodic detection is needed.
When the deterioration index of the ballast bed is 0.50 or more and less than 0.53, it means that the detected point ballast bed is seriously deteriorated and maintenance is required.
When the degradation index of the ballast bed is more than or equal to 0.53, the degradation of the ballast bed at the detection point is seriously influenced by the drainage and bearing capacity of the ballasted track, and the ballast track must be immediately maintained.
It should be noted that the specific embodiments described in this application are merely illustrative of the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or its scope as defined in the accompanying claims.
Claims (7)
1. The rapid nondestructive testing method for the degradation state of the ballast bed is characterized by comprising the following steps of:
step 1, scanning ballast particles of detection points with set track length intervals to obtain ballast particle point cloud data, wherein the number of the ballast particles scanned by each detection point is 10-30;
step 2, calculating an inscribed ellipsoid with the largest volume in a region surrounded by a point cloud of the ballast particles corresponding to each ballast particle, and outputting the volume of the inscribed ellipsoid and the volume of the ballast particles;
step 3, calculating true ellipsometry E of each ballast particle of the detection point according to the volume of the ballast particle and the volume of the corresponding inscribed ellipsoid 3D ；
Step 4, calculating a degradation index D of the ballast bed at the detection point according to the true ellipsoids of all the ballast particles at the detection point b 。
2. The rapid nondestructive testing method of the deterioration state of ballast bed according to claim 1, wherein the step 2 comprises the steps of:
2.1, reconstructing the surfaces of the ballast particles by using the ballast particle point cloud data and calculating the volume of the ballast particles;
step 2.2, the parameter equation of the ellipsoid comprises three parameters, namely a three-dimensional real matrix P, a three-dimensional vector q and a real number r, wherein the external points are defined as points which are not in an ellipsoid set determined by the parameter equation of the ellipsoid, the internal points are defined as points in the ellipsoid set determined by the parameter equation of the ellipsoid, and the initial internal points are determined;
2.3, the parameter equation of the ellipsoid, the ellipsoid does not contain any external points, and the three-dimensional real matrix P is a positive definite matrix to jointly form a semi-definite rule equation;
the imported railway ballast particle point cloud data is used as an external point, the external point and the initial internal point input in the step 2.3 are substituted into a semi-definite programming equation together, the solution of the equation is searched, if three parameters are solved, the step 2.4 is started, and if the three parameters are not solved, the step 2.2 is returned to search the initial internal point again;
step 2.4, randomly generating a new internal point in the area surrounded by the ballast particle point cloud;
step 2.5, checking whether the iteration times are smaller than the total iteration times, if the iteration times are smaller than or equal to the total iteration times, entering step 2.6, and if the iteration times are larger than or equal to the total iteration times, entering step 2.10;
step 2.6, calculating a semi-definite rule equation again by using the updated internal points and the particle point cloud data in the step 2.4, if the parameters of three ellipsoids are solved, obtaining a new internal ellipsoid and entering the step 2.7; if no solution exists, the step 2.8 is carried out;
step 2.7, if the volume of the new internal ellipsoid is not more than the volume of the internal ellipsoid generated last time, entering step 2.8; otherwise, enter step 2.9;
step 2.8, increasing the accumulated invalid iteration number by 1, returning to step 2.4 if the accumulated invalid iteration number is smaller than 6, deleting the finally generated internal point if the accumulated invalid iteration number is equal to 6, assigning the accumulated invalid iteration number to be 0, and returning to step 2.4;
step 2.9, updating the volume of the internal ellipsoid and returning to step 2.4;
and 2.10, outputting the finally obtained internal ellipsoid as an inscribed ellipsoid, and outputting the volume of the finally obtained inscribed ellipsoid and the volume of the ballast particles.
3. The method for rapid nondestructive inspection of a degradation state of a ballast bed according to claim 2, wherein the selecting of the initial internal point in step 2.2 comprises the steps of:
and selecting an initial ellipsoid in the point cloud of the ballast particles, and finding coordinates of six endpoints of three axes of the initial ellipsoid as six initial internal points.
4. A method for rapid nondestructive testing of ballast bed degradation according to claim 3, wherein if there is no solution in step 2.3, the process returns to step 2.2 to find the initial internal point with smaller initial ellipsoidal volume again.
5. The rapid nondestructive inspection method of a deterioration state of ballast bed according to claim 1, wherein the set track length is 500m-1.5km.
6. The rapid nondestructive inspection method of the deterioration state of ballast bed according to claim 1, wherein in the step 3, true ellipsometry E of the ballast particles is calculated 3D Based on the following formula:
wherein V is E V is the volume of inscribed ellipsoids of the ballast particles P Is the volume of the ballast particles.
7. The method for rapid nondestructive inspection of a deterioration state of a ballast bed according to claim 6, wherein in step 4, the deterioration index D of the ballast bed at the inspection point is calculated b Based on the following formula:
wherein E is 3Di And (3) representing the true sphericity of the ith ballast particle, wherein n is the number of scanned ballast particles at a single detection point.
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