CN113158399A - Dynamic splicing processing method and device for steel rail profile - Google Patents
Dynamic splicing processing method and device for steel rail profile Download PDFInfo
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 174
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Abstract
The invention discloses a dynamic splicing processing method and a device for a steel rail profile, wherein the method comprises the following steps: acquiring initial values of the steel rail profile splicing parameters; based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations: according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the target function is used for reducing the weight of the far-end profile point set; when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period; and when the preset iteration end condition is met, obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met. The invention can determine the accurate full-section profile of the steel rail.
Description
Technical Field
The invention relates to the technical field of steel rail detection, in particular to a steel rail profile dynamic splicing processing method and a steel rail profile dynamic splicing processing device.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
The wheel-rail relationship is a key influence factor of the safe operation and comfort of railway vehicles, and the rail profile is an important component in the wheel-rail relationship. The detection of the steel rail and the acquisition of the full-section profile for data analysis are very important for guiding safety early warning, work maintenance strategies and the like.
At present, the mode with the highest detection efficiency of the line steel rail profile is vehicle-mounted non-contact detection based on the structured light principle, the laser camera shooting assembly is used for respectively and dynamically detecting the inner side and the outer side of a steel rail, and finally, the steel rail profile is spliced into a complete profile to be output as a detection result. Some researches have been carried out on the data fusion matching splicing of the inner and outer profile shapes, and the laboratory results show that the precision is higher.
However, in these methods, a set of spliced rotation and translation matrix calculation parameters are calculated according to ideal conditions of a laboratory, however, in the actual detection vehicle operation process, the environment is severe, and the line conditions are complex, and after the calibration is completed in the laboratory, due to various nonlinear errors, the full-section profile can be branched, crossed, separated and the like (as shown in fig. 1a to 1 c) when the detection system passes through special sections such as a severe vehicle shaking section, a small radius curve and the like, and the real profile cannot be correctly output.
Disclosure of Invention
The embodiment of the invention provides a dynamic splicing processing method for a steel rail profile, which is used for determining the accurate steel rail full-section profile and comprises the following steps:
acquiring initial values of the steel rail profile splicing parameters;
based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations:
according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
and when the preset iteration end condition is met, obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met.
The embodiment of the invention also provides a dynamic splicing processing device for the steel rail profile, which is used for determining the accurate steel rail full-section profile and comprises the following components:
the acquisition unit is used for acquiring the initial value of the steel rail profile splicing parameter;
and the iteration unit is used for determining the steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP iteration based on the initial value, and each iteration period executes the following operations:
according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
and the determining unit is used for obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration ending condition is met.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the method for processing the dynamic splicing of the steel rail profile is implemented.
The embodiment of the invention also provides a computer-readable storage medium, which stores a computer program for executing the rail profile dynamic splicing processing method.
In the embodiment of the invention, in the dynamic splicing processing scheme of the steel rail profile, compared with the technical scheme that in the prior art, a set of spliced rotation and translation matrix calculation parameters are calculated according to the ideal situation of a laboratory to perform profile splicing processing, however, in the actual running process of a detected vehicle, the environment is severe, the line condition is complex, after the laboratory finishes calibration, due to various nonlinear errors, the full-section profile can be split, crossed and separated by internal and external tracks when the detection system passes through special sections such as a severe section of vehicle shaking, a small radius curve and the like, and the real profile cannot be correctly output, the method comprises the following steps: acquiring initial values of the steel rail profile splicing parameters; based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations: according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set; when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period; when the preset iteration end condition is met, the final steel rail profile is obtained according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met, and the method is realized:
firstly, when matching the inner and outer profiles, the weight of a far-end point set can be reduced by an objective function so as to ensure that a high-precision point set after coordinate conversion is taken as a main calculation value for matching, and therefore, certain nonlinear errors of larger nonlinear distortion of the detected far-end profile are eliminated;
secondly, when iterative computation is carried out by utilizing an ICP (inductively coupled plasma) algorithm, intervention is carried out on a result after each time of rotational translation matrix correction, and a transverse translation parameter is multiplied by a preset transverse translation correction parameter to be used as a steel rail profile splicing parameter corresponding to the next iteration period, so that a transverse translation error caused by the fact that the shape feature of a rail head area is close to a straight line is eliminated.
In conclusion, the dynamic splicing processing scheme for the steel rail profile provided by the embodiment of the invention can avoid the situations that the inner and outer profiles are frequently branched, crossed, separated and the like, and the accurate steel rail full-section profile is determined.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIGS. 1a to 1c are schematic diagrams illustrating the bifurcation, intersection, separation, etc. of the inner and outer rails of a full-section profile in the prior art;
FIG. 2 is a schematic flow chart of a dynamic splicing processing method for a steel rail profile according to an embodiment of the invention;
FIG. 3 is a schematic diagram of an image with a large interference according to an embodiment of the present invention;
FIGS. 4 a-4 b are schematic diagrams of the absence of the rail jaw according to an embodiment of the present invention;
FIGS. 5 a-5 b are schematic diagrams of overexposure or unclear visualization at the rail jaw according to an embodiment of the present invention;
fig. 6a is a first original drawing in the embodiment of the present invention, and fig. 6b is a first final stitching result in the embodiment of the present invention;
fig. 7a is a first original drawing in the embodiment of the present invention, and fig. 7b is a first final stitching result in the embodiment of the present invention;
fig. 8 is a schematic structural diagram of a dynamic splicing processing device for a steel rail profile in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The inventor considers the technical problems in the prior art, and therefore provides a steel rail profile dynamic splicing processing scheme, which combines various working conditions possibly encountered in actual operation, researches a steel rail splicing method and obtains a steel rail profile dynamic splicing strategy with higher universality and stability. The following describes the dynamic splicing processing scheme of the rail profile in detail.
Fig. 2 is a schematic flow chart of a dynamic splicing processing method for a steel rail profile in an embodiment of the present invention, as shown in fig. 2, the method includes the following steps:
step 101: acquiring initial values of the steel rail profile splicing parameters;
step 102: based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations:
step 1021: according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
step 1022: when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
step 103: and when the preset iteration end condition is met, obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met.
In the embodiment of the invention, in the dynamic splicing processing scheme of the steel rail profile, compared with the technical scheme that in the prior art, a set of spliced rotation and translation matrix calculation parameters are calculated according to the ideal situation of a laboratory to perform profile splicing processing, however, in the actual running process of a detected vehicle, the environment is severe, the line conditions are complex, after the laboratory finishes calibration, due to various nonlinear errors, the full-section profile can be split, crossed and separated by internal and external tracks when the detection system passes through special sections such as a severe section of vehicle shaking, a small radius curve and the like, and the real profile cannot be correctly output, the method realizes that:
firstly, when matching the inner and outer profiles, the weight of a far-end point set can be reduced by an objective function so as to ensure that a high-precision point set after coordinate conversion is taken as a main calculation value for matching, and therefore, certain nonlinear errors of larger nonlinear distortion of the detected far-end profile are eliminated;
secondly, when iterative computation is carried out by utilizing an ICP (inductively coupled plasma) algorithm, intervention is carried out on a result after each time of rotational translation matrix correction, and a transverse translation parameter is multiplied by a preset transverse translation correction parameter to be used as a steel rail profile splicing parameter corresponding to the next iteration period, so that a transverse translation error caused by the fact that the shape feature of a rail head area is close to a straight line is eliminated.
In conclusion, the dynamic splicing processing scheme for the steel rail profile provided by the embodiment of the invention can avoid the situations that the inner and outer profiles are frequently branched, crossed, separated and the like, and the accurate full-section steel rail profile is determined.
In particular implementations, the condition for the end of the predetermined iteration may be that the value of the ICP objective function is less than a small value, such as 0.005.
In an embodiment, in step 101, obtaining an initial value of a rail profile splicing parameter may include: and calibrating the left and right profile synthesis of the same calibration block by a laboratory to obtain a calibrated rotation-translation matrix parameter synthesized by the inner and outer profiles of the same steel rail, and taking the calibrated rotation-translation matrix parameter as an initial value of the steel rail profile splicing parameter.
In specific implementation, the method for obtaining the initial value of the steel rail profile splicing parameter is beneficial to further improving the precision of the steel rail profile.
In an embodiment, after the step 101, the method for dynamically splicing the rail profile may further include: selecting a preset area from the steel rail profile as a calculation area;
therefore, in the subsequent step 102, iteratively determining the corresponding rail profile data point for each period by using an iterative closest point method ICP based on the initial value may include: and iteratively determining the steel rail profile data point corresponding to each period in the calculation domain by utilizing an iterative closest point method ICP (inductively coupled plasma) based on the initial value.
In specific implementation, a calculation domain is determined, and based on the initial value, the rail profile data point corresponding to each period in the calculation domain is determined by iteration through an iterative closest point method ICP (inductively coupled plasma), so that the calculation amount is reduced, part of interference points are eliminated, and the efficiency and the precision of dynamic splicing processing of the rail profile are further improved.
In one embodiment, selecting the preset region from the rail profile as the calculation region may include:
determining coordinate position information of the vertex of the inner outline shape track and the side grinding point;
and determining the calculation domain as a rectangle, and determining the position information of the rectangular calculation domain according to the coordinate position information of the vertex of the inner and outer profile tracks and the side grinding points.
In specific implementation, the implementation mode of selecting the calculation domain further improves the efficiency and the precision of the dynamic splicing processing of the steel rail profile.
In one embodiment, the outer side rail vertex and side grinding point coordinates are respectively
The coordinates of the top point and the side grinding point of the inner side rail are respectively
The position information of the rectangular calculation domain comprises: the coordinates of the upper left end point of the diagonal of the calculation domain are as follows:
the coordinates of the right lower end point of the diagonal of the calculation domain are as follows:
wherein: delta1、δ2、δ3And delta4The value range of (A) is 2 to 5.
In specific implementation, the specific calculation domain information further improves the efficiency and the precision of the dynamic splicing processing of the steel rail profile.
In one embodiment, in the step 1021, the objective function may be:
wherein the middle portion point set is selected as
All points in the computation domain within the interval.
In specific implementation, the target function can eliminate the phenomenon that a certain nonlinear error still exists in the correction of the distortion by the model with the calibration method, so that the weight of a far-end point set is reduced by the target function when the internal and external profile matching is carried out, and the precision of the steel profile is further improved.
In an embodiment, in the step 1022, the method for processing dynamic splicing of a rail profile may further include determining the lateral translation correction parameter according to the following method:
determining the matched rail jaw distance according to a preset number of rail contour images with the definition larger than a preset value;
determining a probability density function according to the rail jaw distance;
constructing a likelihood function according to the probability density function;
and determining an optimal transverse translation correction parameter according to the likelihood function.
In specific implementation, the above-mentioned embodiment of determining the lateral translation correction parameter helps to further improve the more accurate and real rail profile.
In an embodiment, in step 103, when the preset iteration end condition is satisfied, obtaining a final profile according to the profile data point corresponding to the iteration cycle when the preset iteration end condition is satisfied may include:
when the preset iteration ending condition is met, obtaining a steel rail profile data point corresponding to the iteration cycle when the preset iteration ending condition is met;
screening the steel rail profile data points corresponding to the iteration cycle when the preset iteration ending condition is met to obtain steel rail profile data points after screening;
and obtaining the final steel rail profile according to the steel rail profile data points after screening treatment.
In specific implementation, after the steel rail profile data points corresponding to the iteration period when the preset iteration ending condition is met are screened, the final steel rail profile is obtained according to the screened steel rail profile data points, and the precision of the steel rail profile is further improved.
The following description is given by way of example to facilitate an understanding of how the invention may be practiced.
The dynamic splicing processing method for the steel rail profile provided by the embodiment of the invention comprises the following steps:
(1) confirming an initial value
Carrying out calibration of left and right profile synthesis on the same calibration block through a laboratory to obtain a calibration rotation translation matrix [ R, t ] of the same steel rail inner and outer profile synthesis, and taking the parameter as an initial value of dynamic profile splicing;
the splicing parameters obtained by calibration in a laboratory can realize millimeter-scale registration of steel rail profile splicing, but the high-precision requirement (within 0.2 mm) of a system is difficult to achieve, and the non-linear errors caused by factors such as different imaging positions do not have good adaptability, so that the laboratory calibration synthesis parameters are required to be used as initial values to further process subsequent profile splicing.
(2) Selecting a computing Domain
Without loss of generality, the following method description takes the left rail as an example:
the inventors consider a technical problem: to improve the calculation efficiency and eliminate the influence of non-railhead interference (such as dirt, vegetation, etc.) in the image as much as possible, a calculation domain as small as possible (the size of a preset area) needs to be selected.
Calculating the vertex and the side grinding point of the inner profile track: by definition, the vertex of the rail is the highest point of the top surface of the profile rail (the position indicated by two small circles at the top in FIG. 3), and the side grinding point (also called the gauge point) is the point 16mm below the vertex of the rail (the two side points in FIG. 3)Position indicated by small o), according to the definition, the corresponding point can be obtained by performing statistical calculation on the point set after the image light bar is extracted. The coordinates of the outside rail top and the side grinding point are recorded as
The coordinates of the inner rail top and the side grinding point are recorded as
In the embodiment of the invention, the calculation domain is selected as a rectangle (mainly calculating the rail top position of the upper half part of the rail head), the condition that the outer side of the steel rail is not in contact with the wheel and the abrasion is negligible is considered, so the coordinates of the upper left end point of the diagonal line of the calculation domain are as follows:
the coordinates of the right lower end point of the diagonal of the calculation domain are:
wherein delta1～δ4The number is a small number, and is usually selected to be 2-5 pixels, mainly to avoid the related boundary problem caused by the fact that the boundary of the calculation domain just exceeds the valid calculation point.
The selection of the calculation domain has a positive effect on the matching of partial images seriously interfered by dirt and stray light, as shown in fig. 2, a camera on one side has a plurality of spots due to the dirt, and the selection of the calculation domain not only reduces the calculation amount, but also eliminates partial interference points.
(3) Inner and outer side matching objective function
In the world coordinate system, the inner and outer profile point sets in the calculation domain are respectively marked as P (P)1,p2,p3…) and Q (Q)1,q2,q3…). These two point sets are actually the detected image data for the same location of the rail and therefore can be matched by the iterative closest point method (ICP). The inventors consider a technical problem: in the actual detection result, the inner and outer contour channelsThe conditions of bifurcation, intersection and the like often occur, one of the main reasons is that a far-end profile detected by each side camera has larger nonlinear distortion (compared with a near end), and a certain nonlinear error still exists in the correction of the distortion by the currently used calibration method model, so that the weight of a set of far-end points (the far-end points refer to points far away from a rail vertex and a rail distance point in a measured half-section profile) needs to be reduced (the weight is reflected in a second part of a following formula, namely an N-middle point set in the following formula) in an objective function during matching of the inner profile and the outer profile (the weight is reflected in a N-middle point set)CAnd calculating the point pairs, namely calculating the deviation of the point set again to ensure that the high-precision point set after coordinate conversion is used as a main calculation value for matching. The middle point of the inner and outer outlines is set as A (a)1,a2,a3…) and B (B)1,b2,b3…), the ICP algorithm matches the objective function as:
wherein, the middle part point set (referring to the point set of the coincident part near the vertex of the orbit in the two half-section profiles, namely the point set of the coincident part of the abscissa, the specific selection method is detailed in the description of (4) iterative process optimization) below) is selected as
All the points in the calculation domain in the interval, p and q are the points in the inner and outer profiles, respectively, a and b are the points in the middle point sets of the inner and outer profiles, respectively, R and T are the rotation and translation matrices, respectively, N represents the total number of point sets, and NC represents the total number of middle point sets.
(4) Iterative process optimization
The invention also finds a technical problem: the radius of a curve section of an actual rail profile near a rail top area is large, and geometric characteristics of a rail head area tend to be linear under the influence of external forces such as long-term rail abrasion. In addition, in a section with a portion of the rail worn seriously, in order to prevent further development of surface cracks, a department of industry may perform milling and grinding treatment on the surface of the rail, and after similar maintenance treatment, the rail head portion of the rail is directly aligned. For this practical situation, since the weight of the middle point set is greater in the objective function, the convergence result of the horizontal translation parameters in the translation matrix in the practical iterative matching process may be more dependent on the horizontal distribution of the points after the extraction of the image light bars, and is less related to the actual shape of the steel rail, thereby causing the steel rail to be "narrowed" or "widened", which causes great interference to the subsequent analysis of the steel rail profile.
One of the main reasons that the inventor comprehensively considers the situations that the bifurcation occurs in the inside and outside detection profile of the steel rail and the like is the error when the actual image of the steel rail is extracted into the profile with one pixel width, and the error can cause the separation of the inside and outside profiles of the steel rail in the vertical direction and hardly causes the interference to the horizontal position. Therefore, in the embodiment of the invention, the target function in the step (3) is considered, when the ICP algorithm is used for iterative calculation, intervention is performed on the result after each rotation translation matrix correction, and a coefficient ξ (transverse translation correction parameter) smaller than 1 is multiplied by the transverse translation parameter to serve as an initial value of the next calculation, so as to eliminate the transverse translation error caused by the approach of the shape feature of the railhead area to a straight line.
(5) Determination of transverse translation correction parameter xi
The invention also finds a technical problem: the calculation errors of the transverse translation parameters are derived from the distribution of light bar extraction points, the shape characteristics of a rail head region, the uneven distribution of lines, the random change of position and posture caused by vehicle vibration and other system errors, and the calculation errors of the transverse translation parameters caused by the error sources are independently and simultaneously distributed, so that when the parameters are selected, the embodiment of the invention utilizes the maximum likelihood estimation to select a Gaussian distribution model for calculation.
The invention also discovers that: the inner and outer rail jaws of the steel rail (the rail jaw refers to the position of the small circular center of the left and right lower corners R2.5 of the rail head of the steel rail, and R2.5 means that the circular arc section with the radius of 2.5 of the left and right lower corners in a standard diagram of the profile of the steel rail (each profile of the steel rail has national standard)) are not directly contacted with the wheel rail, so that almost no abrasion is caused, and the distance between the rail jaws of the inner and outer steel rails can be used as a reference basis for judging the transverse translation of the spliced steel rail. Due to the influences of dirt, railway ballast, vehicle position and posture and the like in an actual line, a part of a rail jaw image is lost when the rail profile is detected (see fig. 4a to 4b), and meanwhile, the shape characteristics of the rail jaw part can enable the rail jaw part of the partial profile image to be overexposed or unclear (see fig. 5a to 5b), so that the rail jaw part cannot be used as a transverse reference basis during dynamic matching, but a complete profile containing a clear rail jaw can be selected to calculate transverse translation correction parameters in the step. Specifically, the determination process includes:
selecting Nd(200-500) clear rail profile images, operating the matching algorithm, and calculating the distance D of the matched rail jaw, wherein the distance of the rail jaw is a determined value D for the same rail profile.
The probability density function is:
constructing a likelihood function:
let L be the maximum value, then let the following be the minimum:
wherein d represents the actual calculated jaw distance; d represents the rail jaw distance of the theoretical profile; sigma is standard deviation, and xi is transverse matching correction parameter.
And then, the most appropriate correction value can be obtained by using a Levenberg-Marquardt algorithm for solving the optimization problem of the multi-parameter nonlinear system.
Considering the operational mode of detecting trains: the method is characterized in that each road bureau allocates a detection vehicle according to a set plan to detect the corresponding route, and the detection mode has repeatability, so that the calculation of correction parameters is carried out on the same route of the same vehicle, and a simple correction parameter library can be further automatically established for different vehicles and routes, so that the correction method is of great significance.
(6) Final rail profile
After the steps (1) to (6) are performed, the contour splicing is completed, and in this case, the invention also considers that: and proper screening of the inner and outer data points is also needed to be carried out to be used as the final output profile. And (4) directly selecting the detection result of the camera on the corresponding side from the non-middle parts of the inner side and the outer side of the final profile for the reason in the step (3). Under the similar engineering condition, most of point sets in the middle part adopt mathematical models such as fitting and the like to perform fusion calculation, but considering that the system is taken as a detection system, if the middle real points are fitted, the caused artificial error is uncontrollable, so that the point sets in the middle part are completely reserved when the final profile is determined, and the points have important significance for ensuring the precision of the detection system. And finally, outputting the data point set as a final profile, and performing corresponding further processing according to the detected point set when performing profile analysis and corresponding calculation.
The final stitching result is shown in fig. 6a to 7b, where fig. 6a and 7a are the original figures, and fig. 6b and 7b are the post-stitching result (final profile).
In order to realize dynamic synthesis of the inner contour and the outer contour in a driving situation, a method with high adaptability needs to be provided, so that a plurality of reasons which can cause synthesis failure, such as the transverse position of the synthesized contour is controlled by using the width of the rail jaw, must be avoided. The embodiment of the invention realizes the high-precision synthesis of the profile after various interferences.
In summary, the dynamic splicing processing scheme for the steel rail profile provided by the embodiment of the invention realizes that:
(1) in order to realize dynamic synthesis of the steel rail profile, a synthesis method with universality is adopted by combining engineering practice, synthesis calculation can be completed under various interference and complex environments, and higher precision can be realized;
(2) a smaller calculation domain is determined by using the rail top gauge point, so that the algorithm searching and calculating time is greatly prolonged;
(3) considering engineering practice, different weights are given to different parts of the steel rail profile (secondary calculation is carried out on the middle point set in an objective function and the subsequent calculation of transverse offset parameters), and the more accurate middle point set is used as an important basis for matching;
(4) the geometric characteristics of the inside and outside splicing of the steel rail and a mode method in the actual operation of a business department are fully considered, a transverse translation matrix in a synthetic matrix is corrected, and a method is provided for determining correction parameters;
(5) based on the purpose of detection and the sufficient understanding of the profile detection system, a concise scheme is provided for accepting or rejecting the synthesized profile point set, the artificial errors caused by traditional mathematical fitting and the like are abandoned, and the real measurement value is reserved as the detection result.
The embodiment of the invention also provides a device for dynamically splicing and processing the steel rail profile, which is described in the following embodiment. Because the principle of solving the problems of the device is similar to the dynamic splicing processing method of the steel rail profile, the implementation of the device can refer to the implementation of the dynamic splicing processing method of the steel rail profile, and repeated parts are not described again.
Fig. 8 is a schematic structural diagram of a dynamic rail profile splicing processing device in an embodiment of the present invention, and as shown in fig. 8, the device includes:
the acquisition unit 02 is used for acquiring the initial values of the steel rail profile splicing parameters;
an iteration unit 04, configured to iteratively determine, based on the initial value, a steel rail profile data point corresponding to each period by using an iterative closest point method ICP, where each iteration period performs the following operations:
according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
and the determining unit 06 is configured to, when a preset iteration end condition is met, obtain a final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met.
In an embodiment, the determining unit is specifically configured to:
when the preset iteration ending condition is met, obtaining a steel rail profile data point corresponding to the iteration cycle when the preset iteration ending condition is met;
screening the steel rail profile data points corresponding to the iteration cycle when the preset iteration ending condition is met to obtain steel rail profile data points after screening;
and obtaining the final steel rail profile according to the steel rail profile data points after screening treatment.
In one embodiment, the objective function is:
wherein the middle portion point set is selected as
All points in the computation domain within the interval.
In one embodiment, the obtaining unit is specifically configured to: and calibrating the left and right profile synthesis of the same calibration block by a laboratory to obtain a calibrated rotation-translation matrix parameter synthesized by the inner and outer profiles of the same steel rail, and taking the calibrated rotation-translation matrix parameter as an initial value of the steel rail profile splicing parameter.
In one embodiment, the above dynamic splicing processing device for rail profile may further include: the calculation domain determining unit is used for selecting a preset region from the steel rail profile as a calculation domain;
the iteration unit is specifically configured to: and iteratively determining the steel rail profile data point corresponding to each period in the calculation domain by utilizing an iterative closest point method ICP (inductively coupled plasma) based on the initial value.
In an embodiment, the calculation domain determining unit is specifically configured to:
determining coordinate position information of the vertex of the inner outline shape track and the side grinding point;
and determining the calculation domain as a rectangle, and determining the position information of the rectangular calculation domain according to the coordinate position information of the vertex of the inner and outer profile tracks and the side grinding points.
In one embodiment, the above dynamic splicing processing device for rail profile may further include: a transverse translation correction parameter determination unit for determining the transverse translation correction parameter according to the following method:
determining the matched rail jaw distance according to a preset number of rail contour images with the definition larger than a preset value;
determining a probability density function according to the rail jaw distance;
constructing a likelihood function according to the probability density function;
and determining an optimal transverse translation correction parameter according to the likelihood function.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the method for processing the dynamic splicing of the steel rail profile is implemented.
The embodiment of the invention also provides a computer-readable storage medium, which stores a computer program for executing the rail profile dynamic splicing processing method.
In the embodiment of the invention, in the dynamic splicing processing scheme of the steel rail profile, compared with the technical scheme that in the prior art, a set of spliced rotation and translation matrix calculation parameters are calculated according to the ideal situation of a laboratory to perform profile splicing processing, however, in the actual running process of a detected vehicle, the environment is severe, the line condition is complex, after the laboratory finishes calibration, due to various nonlinear errors, the full-section profile can be split, crossed and separated by internal and external tracks when the detection system passes through special sections such as a severe section of vehicle shaking, a small radius curve and the like, and the real profile cannot be correctly output, the method comprises the following steps: acquiring initial values of the steel rail profile splicing parameters; based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations: according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set; when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period; when the preset iteration end condition is met, the final steel rail profile is obtained according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met, and the method is realized:
firstly, when matching the inner and outer profiles, the weight of a far-end point set can be reduced by an objective function so as to ensure that a high-precision point set after coordinate conversion is taken as a main calculation value for matching, and therefore, certain nonlinear errors of larger nonlinear distortion of the detected far-end profile are eliminated;
secondly, when iterative computation is carried out by utilizing an ICP (inductively coupled plasma) algorithm, intervention is carried out on a result after each time of rotational translation matrix correction, and a transverse translation parameter is multiplied by a preset transverse translation correction parameter to be used as a steel rail profile splicing parameter corresponding to the next iteration period, so that a transverse translation error caused by the fact that the shape feature of a rail head area is close to a straight line is eliminated.
In conclusion, the dynamic splicing processing scheme for the steel rail profile provided by the embodiment of the invention can avoid the situations that the inner and outer profiles are frequently branched, crossed, separated and the like, and the accurate steel rail profile is determined.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A dynamic splicing processing method for a steel rail profile is characterized by comprising the following steps:
acquiring initial values of the steel rail profile splicing parameters;
based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP (inductively coupled plasma) iteration, wherein each iteration period executes the following operations:
according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
and when the preset iteration end condition is met, obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration end condition is met.
2. The dynamic splicing processing method for the steel rail profile according to claim 1, wherein when a preset iteration end condition is satisfied, obtaining a final steel rail profile according to a steel rail profile data point corresponding to an iteration cycle when the preset iteration end condition is satisfied, comprises:
when the preset iteration ending condition is met, obtaining a steel rail profile data point corresponding to the iteration cycle when the preset iteration ending condition is met;
screening the steel rail profile data points corresponding to the iteration cycle when the preset iteration ending condition is met to obtain steel rail profile data points after screening;
and obtaining the final steel rail profile according to the steel rail profile data points after screening treatment.
3. The dynamic splicing processing method for the steel rail profile according to claim 1, wherein the objective function is as follows:
where p and q are points in the medial and lateral profiles, respectively, a and b are points in the point set in the medial portion of the medial and lateral profiles, respectively, R and T are a rotation matrix and a translation matrix, respectively, N represents the total number of point sets, andCrepresenting the total number of mid-section point sets.
4. The dynamic rail profile splicing processing method according to claim 1, wherein the obtaining of the initial values of the rail profile splicing parameters comprises: and calibrating the left and right profile synthesis of the same calibration block by a laboratory to obtain a calibrated rotation-translation matrix parameter synthesized by the inner and outer profiles of the same steel rail, and taking the calibrated rotation-translation matrix parameter as an initial value of the steel rail profile splicing parameter.
5. The dynamic splicing processing method for the steel rail profile shape according to claim 1, further comprising: selecting a preset area from the steel rail profile as a calculation area;
based on the initial value, determining a steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP iteration, wherein the method comprises the following steps: and iteratively determining the steel rail profile data point corresponding to each period in the calculation domain by utilizing an iterative closest point method ICP (inductively coupled plasma) based on the initial value.
6. The dynamic rail profile splicing processing method according to claim 5, wherein the step of selecting a preset region from the rail profile as a calculation region comprises the steps of:
determining coordinate position information of the vertex of the inner outline shape track and the side grinding point;
and determining the calculation domain as a rectangle, and determining the position information of the rectangular calculation domain according to the coordinate position information of the vertex of the inner and outer profile tracks and the side grinding points.
7. The dynamic splicing processing method for the steel rail profile according to claim 1, wherein the transverse translation correction parameter is determined according to the following method:
determining the matched rail jaw distance according to a preset number of rail contour images with the definition larger than a preset value;
determining a probability density function according to the rail jaw distance;
constructing a likelihood function according to the probability density function;
and determining an optimal transverse translation correction parameter according to the likelihood function.
8. A rail profile dynamic splicing processing device is characterized by comprising:
the acquisition unit is used for acquiring the initial value of the steel rail profile splicing parameter;
and the iteration unit is used for determining the steel rail profile data point corresponding to each period by utilizing an iterative closest point method ICP iteration based on the initial value, and each iteration period executes the following operations:
according to the steel rail profile splicing parameters of the current period and a pre-established ICP (inductively coupled plasma) matched target function, obtaining steel rail profile data points corresponding to the current period; the objective function is used for reducing the weight of the far-end profile point set;
when the preset iteration ending condition is not met, multiplying the transverse translation parameter corresponding to the steel rail profile of the current period by the preset transverse translation correction parameter to serve as the steel rail profile splicing parameter corresponding to the next iteration period;
and the determining unit is used for obtaining the final steel rail profile according to the steel rail profile data point corresponding to the iteration cycle when the preset iteration ending condition is met.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.
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