Feature point calibration method and device applied to railway turnout, medium and equipment

Abstract

The invention discloses a feature point calibration method and device applied to a railway turnout, a medium and equipment, and relates to the technical field of data processing. A first feature point recognition area can be determined from three-dimensional point cloud data composed of a plurality of point cloud sections, and then the first rail head width of the stock rail is determined. And determining a first rail head coordinate range according to the first rail head width and the first target rail extension direction. When a first point cloud section with a target point not located in the first rail head coordinate range is determined from a plurality of point cloud sections according to the extension direction of the first target rail, the target point not located in the first rail head coordinate range exists in all the point cloud sections in the subsequent sequence, and the distance between the target point and the first rail head coordinate range is gradually increased, the target point is determined to be the target point in the first rail head coordinate range; and the first target point which is not in the first rail head coordinate range is calibrated as the point of the switch rail. Therefore, the electronic equipment can identify and calibrate the point of the switch rail based on the three-dimensional point cloud data, so that the cost is saved, the efficiency is improved, and the accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, medium and equipment for calibrating characteristic points of railway turnouts. Background Art

[0002] A turnout is a specific structure in a railway track system, including a center rail, a guard rail, a point rail, a wing rail, etc. Usually, a turnout is provided at the intersection of a Y-shaped railway track, and by operating the turnout, a railway train can travel to any turnout track.

[0003] The structure of the turnout is relatively complex, and when a railway train is changing tracks, the wheels of the train often rub against the turnout violently, which in turn causes wear of the various components that make up the turnout.

[0004] In the prior art, the wear of turnouts is usually detected by combining manual and mechanical methods. For example, three-dimensional data of the turnout area is collected through a mechanical structure, and the positions of components such as the heart rail, guard rail, and point rail are calibrated manually to measure the wear.

[0005] However, this calibration method is costly and manual operation may lead to large errors. Summary of the invention

[0006] The present specification provides a method and device for calibrating characteristic points applied to railway turnouts, so as to at least partially solve the above-mentioned problems existing in the prior art.

[0007] This manual adopts the following technical solutions: This specification provides a method for calibrating characteristic points applied to railway turnouts, including: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Based on a preset first target range, determining a first feature point recognition area corresponding to the first target range from the three-dimensional point cloud data; determining a first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area; Determining a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the first target rail, and there are target points that are not within the first rail head coordinate range in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not within the first rail head coordinate range is calibrated as the tip of the pointed rail.

[0008] Preferably, the determining the first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area comprises: According to a preset first target track extension direction, respectively determine a first rail head width of a base rail of a plurality of point cloud sections within the first feature point recognition area; Determine the distribution parameters of the first n first rail head widths; the distribution parameters are standard deviation, variance, mean absolute deviation or coefficient of variation; According to the order of n values ​​from small to large, the value of n of the distribution parameter that is greater than or equal to the preset first parameter for the first time is determined as the over-limit parameter; Determine the value of m as the difference between the over-limit parameter and a preset second parameter; The first rail head width of the basic rail is determined according to the first m first rail head widths.

[0009] Preferably, determining the value of m as the difference between the over-limit parameter and a preset second parameter comprises: Determine whether the difference between the over-limit parameter and the preset second parameter is greater than or equal to a preset third parameter; If so, no other actions are performed; If not, the value of m is determined to be the third parameter.

[0010] Preferably, after the calibration as the pointed rail tip, the method further comprises: Determine a position along the extension direction of the first target track and at a first mileage distance from the tip of the pointed rail as an initial position for guardrail detection; Arrange the plurality of point cloud sections according to the extension direction of the first target track; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections, and there are target points in subsequent point cloud sections whose distance from the first rail head coordinate range is greater than a preset second distance, the first target point that is not within the first rail head coordinate range is marked as the toe of the guardrail.

[0011] Preferably, after the marking as the guardrail toe, the method further comprises: Starting from the point cloud section corresponding to the target point marked as the toe end of the guard rail, along the extension direction of the first target rail, the point cloud section of the target point whose first target point is within the coordinate range of the first rail head is determined as the initial position of the center rail detection; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections, and target points that are not within the first rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not within the first rail head coordinate range is calibrated as the tip of the center rail.

[0012] Preferably, before determining the first feature point recognition area corresponding to the preset first target range, the method further includes: Obtaining straight and curved track information and track direction information corresponding to the three-dimensional point cloud data; the straight and curved track information includes straight track or curved track, and the track direction information includes left track or right track; A first target range is determined according to the coordinates of a plurality of target points constituting different basic tracks in the three-dimensional point cloud data, the straight and curved track information, and the track direction information.

[0013] On the other hand, this specification provides a method for calibrating characteristic points applied to railway turnouts, comprising: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Determining a second feature point recognition area corresponding to a preset second target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points; determining a second rail head width of the base rail according to a plurality of point cloud sections within the second feature point recognition area; Determining a second rail head coordinate range according to the second rail head width and a preset second target rail extension direction; When the first point cloud section in which a target point that is not within the coordinate range of the second rail head is determined from the multiple point cloud sections according to the extension direction of the second target rail, and there are target points that are not within the coordinate range of the second rail head in subsequent point cloud sections, and the distance between the target point and the coordinate range of the second rail head gradually increases, the first target point that is not within the coordinate range of the second rail head is marked as the second target point.

[0014] On the other hand, this specification provides a method for calibrating characteristic points applied to railway turnouts, comprising: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Determining a third feature point recognition area corresponding to a preset third target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points; Determining a third rail head width of the base rail according to a plurality of point cloud sections within the third feature point recognition area; Determining a coordinate range of the third rail head according to the third rail head width and a preset extension direction of the third target rail; When the first point cloud section in which a target point that is not within the coordinate range of the third rail head is determined from the multiple point cloud sections according to the extension direction of the third target rail, and there are target points in subsequent point cloud sections whose distance from the coordinate range of the third rail head is greater than a preset third distance, the first target point that is not within the coordinate range of the third rail head is marked as the third target point.

[0015] On the other hand, the present specification provides a characteristic point calibration device applied to a railway turnout, comprising: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a first feature point recognition area corresponding to a preset first target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area; A dividing unit, configured to determine a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction; A calibration unit is used for, when a first point cloud section having a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the first target rail, and target points that are not within the first rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, calibrating the first target point that is not within the first rail head coordinate range as the tip of the pointed rail.

[0016] On the other hand, the present specification provides a characteristic point calibration device applied to a railway turnout, comprising: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a second feature point recognition area corresponding to a preset second target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a second rail head width of the base rail according to a plurality of point cloud sections within the second feature point recognition area; a dividing unit, configured to determine a coordinate range of the second rail head according to the width of the second rail head and a preset extension direction of the second target rail; A calibration unit is used to calibrate the first target point that is not in the second rail head coordinate range as the second target point when, according to the extension direction of the second target rail, a first point cloud section in which a target point that is not in the second rail head coordinate range is determined from the multiple point cloud sections, and target points that are not in the second rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the second rail head coordinate range gradually increases.

[0017] On the other hand, the present specification provides a characteristic point calibration device applied to a railway turnout, comprising: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a third feature point recognition area corresponding to a preset third target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a third rail head width of the base rail according to a plurality of point cloud sections within the third feature point recognition area; A dividing unit, used for determining a coordinate range of the third rail head according to the third rail head width and a preset extension direction of the third target rail; The calibration unit is used for, when a first point cloud section in which a target point that is not within the third rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the third target rail, and when there are target points in subsequent point cloud sections whose distances from the third rail head coordinate range are greater than a preset third distance, calibrating the first target point that is not within the third rail head coordinate range as a third target point.

[0018] On the other hand, the present specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for calibrating characteristic points applied to railway turnouts provided in the above aspect is implemented.

[0019] On the other hand, the present specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the feature point calibration method for railway turnouts provided in the above aspect is implemented.

[0020] On the other hand, the present specification provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device implements the feature point calibration method for railway turnouts provided in the above aspect.

[0021] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects: based on Figure 1 The characteristic point calibration method applied to railway turnouts shown in the figure, the electronic device can obtain three-dimensional point cloud data composed of multiple point cloud sections, and determine the first characteristic point identification area corresponding to it from the three-dimensional point cloud data based on the preset first target range. Then, according to the multiple point cloud sections in the first characteristic point identification area, the first rail head width of the basic rail is determined. Then, according to the first rail head width and the preset first target track extension direction, the first rail head coordinate range is determined. Finally, when the first point cloud section with a target point that is not in the first rail head coordinate range is determined from the multiple point cloud sections according to the first target track extension direction, and there are target points that are not in the first rail head coordinate range in the subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not in the first rail head coordinate range is calibrated as the tip of the pointed rail.

[0022] It can be seen from the above method that the electronic device can identify and calibrate the tip of the pointed rail based on the three-dimensional point cloud data, saving costs, improving efficiency and increasing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings: Figure 1 A schematic flow chart of a characteristic point calibration method applied to a railway turnout provided in one embodiment of the present specification; Figure 2 A schematic cross-sectional view of a point cloud cross section provided for one embodiment of this specification; Figure 3 A schematic diagram of the structure of a point rail and a base rail provided for one embodiment of the present specification; Figure 4 A schematic diagram of the structure of a point rail and a base rail provided for one embodiment of the present specification; Figure 5 A schematic diagram of the structure of a point rail and a base rail provided for one embodiment of the present specification; Figure 6 A schematic diagram of the structure of a guard rail and a base rail provided for one embodiment of this specification; Figure 7 A schematic diagram of the structure of a guard rail and a base rail provided for one embodiment of this specification; Figure 8 A schematic diagram of the structure of a center rail and a base rail provided for one embodiment of this specification; Fig. 9 A schematic diagram of the structure of a center rail and a base rail provided for one embodiment of this specification; Fig.10 A schematic diagram of the structure of a center rail and a base rail provided for one embodiment of this specification; Fig.11 A flow chart of a characteristic point calibration method for railway turnouts provided in this specification; Fig.12 A flow chart of a characteristic point calibration method for railway turnouts provided in this specification; Fig.13 A schematic diagram of the structure of a characteristic point calibration device applied to a railway turnout provided in one embodiment of the present specification; Fig.14 A schematic diagram of the structure of an electronic device provided for one embodiment of the present specification. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] In the description of the present invention, it should be noted that the term "or" is generally used in a meaning including "and / or", unless the content clearly indicates otherwise.

[0026] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. In addition, in the description of the present application, the terms "first", "second" and the like are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0029] Figure 1 A flow chart of a characteristic point calibration method for a railway turnout provided in one embodiment of the present specification is as follows: Figure 1 As shown, the characteristic point calibration method applied to railway turnout specifically includes the following steps: S100: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections.

[0030] In this specification, the feature point calibration method applied to railway turnouts can be executed by an electronic device, which can be a terminal device such as a computer, a laptop, a single-chip microcomputer, a server, etc., and this specification does not impose any restrictions on this.

[0031] In one or more embodiments of the present specification, the three-dimensional point cloud data is collected by a line laser collector. When the line laser collector collects the three-dimensional point cloud data, the line laser output is a pulsed laser, and the direction of the line laser is perpendicular to the direction of the basic rail. Therefore, the three-dimensional point cloud data is composed of multiple point cloud sections, and each point cloud section is perpendicular to the extension direction of the basic rail. It should be noted that the extension direction of the basic rail is the direction of a section of the basic rail corresponding to the point cloud section. Those skilled in the art can understand that the basic rail often bends during the laying process, but no matter how the basic rail bends, the point cloud section is perpendicular to the corresponding basic rail.

[0032] Preferably, the point cloud section consists of a plurality of target points.

[0033] S102: Determine a first feature point recognition area corresponding to a preset first target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points.

[0034] Normally, the turnout area has a certain range. For example, the distance between the point rail and the guard rail is generally 20m. However, in the process of calibrating feature points, generally only the tip of the point rail, the toe of the guard rail, the tip of the center rail and other feature points need to be calibrated. Therefore, in order to determine the smaller range where the feature points such as the tip of the point rail, the toe of the guard rail, the tip of the center rail and the like are located in the point cloud data of the turnout area with a larger range, the electronic device can determine the first feature point recognition area corresponding to the first target range from the three-dimensional point cloud data based on the preset first target range.

[0035] Preferably, the first feature point identification area corresponds to the tip of the pointed rail.

[0036] S104: Determine a first rail head width of the basic rail according to a plurality of point cloud sections within the first feature point recognition area.

[0037] Those skilled in the art will understand that after a period of use, the stock rail will often wear out, and the stock rail in the turnout area will often wear out faster. Therefore, the rail head width of the stock rail is likely to be different from that of a new rail. Therefore, the electronic device can determine the first rail head width of the stock rail in the following manner.

[0038] Specifically, the electronic device can determine the first rail head width of the basic rail based on a plurality of point cloud sections within the first feature point recognition area.

[0039] Figure 2 A schematic cross-sectional view of a point cloud cross section provided for one embodiment of this specification, such as Figure 2 As shown, the rail head width 41 corresponding to the point cloud section.

[0040] S106: Determine a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction.

[0041] Those skilled in the art will appreciate that the tip portion of the point rail is in close contact with the base rail and gradually becomes thicker.

[0042] Figure 3 Figure 4 as well as Figure 5 These are schematic diagrams of the structure of the pointed rail and the basic rail provided in one embodiment of this specification. Figure 3 , Figure 4 as well as Figure 5 As shown, the point rail 42 is in close contact with the base rail 43, and the thickness of the tip 421 of the point rail is relatively small.

[0043] Therefore, in one or more preferred embodiments of the present specification, the electronic device can determine the first rail head coordinate range according to the first rail head width and a preset first target rail extension direction.

[0044] The first target track extension direction is the direction in which the thickness of the point rail gradually increases. The first rail head coordinate range is the coordinate range of the rail head of the base rail. Since the base rail may be curved, the first rail head coordinate range needs to be determined in combination with the first target track extension direction.

[0045] Further preferably, the extension direction of the first target track may be preset or may be determined based on the direction of each point cloud section, and this specification does not impose any limitation on this.

[0046] S108: According to the extension direction of the first target track, determine from the multiple point cloud sections whether there is a point cloud section of the first target point that is not in the first rail head coordinate range, and determine whether there are target points that are not in the first rail head coordinate range in the subsequent point cloud sections, and then determine whether the distance between the target point and the first rail head coordinate range gradually increases. If the judgment results are all yes, execute step S110, if any judgment structure is no, repeat step S108.

[0047] Preferably, the electronic device can determine whether there is a point cloud section of a target point that is not within the coordinate range of the first rail head from the multiple point cloud sections according to the extension direction of the first target rail, and determine whether there are target points that are not within the coordinate range of the first rail head in subsequent point cloud sections, and then determine whether the distance between the target point and the coordinate range of the first rail head gradually increases.

[0048] It can be understood by those skilled in the art that foreign matter may exist on the surface of the base rail, which may cause coordinate points in certain point cloud sections to be not within the coordinate range of the first rail head. However, the characteristics of the point rail are more obvious. The tip of the point rail is in close contact with the base rail, and as the base rail extends, the point rail gradually changes from thin to thick. Therefore, the electronic device can identify the point rail in the above manner.

[0049] It should be noted that when judging whether there are target points that are not within the coordinate range of the first rail head in the subsequent point cloud sections, the number of point cloud sections that need to be judged can be set by yourself, and the density of the point cloud sections can be referred to during the setting process. Preferably, the extension length of the basic rail corresponding to the point cloud section that needs to be judged is 5 cm.

[0050] S100: Marking the first target point that is not within the first rail head coordinate range as the tip of the pointed rail.

[0051] based on Figure 1 The characteristic point calibration method applied to railway turnouts shown in the figure, the electronic device can obtain three-dimensional point cloud data composed of multiple point cloud sections, and determine the first characteristic point identification area corresponding to it from the three-dimensional point cloud data based on the preset first target range. Then, according to the multiple point cloud sections in the first characteristic point identification area, the first rail head width of the basic rail is determined. Then, according to the first rail head width and the preset first target track extension direction, the first rail head coordinate range is determined. Finally, when the first point cloud section with a target point that is not in the first rail head coordinate range is determined from the multiple point cloud sections according to the first target track extension direction, and there are target points that are not in the first rail head coordinate range in the subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not in the first rail head coordinate range is calibrated as the tip of the pointed rail.

[0052] It can be seen from the above method that the electronic device can identify and calibrate the tip of the pointed rail based on the three-dimensional point cloud data, saving costs, improving efficiency and increasing accuracy.

[0053] Preferably, the electronic device may adopt the following method when executing step S104.

[0054] Specifically, firstly, the electronic device can determine the first rail head width of the basic rail of multiple point cloud sections in the first feature point recognition area according to the preset first target rail extension direction.

[0055] Secondly, the electronic device can determine the distribution parameters of the first n first rail head widths, wherein the distribution parameters are standard deviation, variance, mean absolute deviation or coefficient of variation, etc., which are not limited in this specification.

[0056] Then, the electronic device may determine the value of n when the distribution parameter is greater than or equal to the preset first parameter for the first time as the over-limit parameter in the order of n from small to large, and determine the value of m as the difference between the over-limit parameter and the preset second parameter.

[0057] Finally, the electronic device may determine the first rail head width of the basic rail according to the first m first rail head widths.

[0058] Where m and n are both positive integers, and m <n。

[0059] Further preferably, the value of n can be determined according to the density of the point cloud section, and the value of n is positively correlated with the density of the point cloud section.

[0060] Further preferably, when determining the distribution parameters of the first n first rail head widths, the electronic device may first determine the first p first rail head widths based on the density of the point cloud section, and the first p first rail head widths correspond to the basic rails with a length of the first value. p>n, and p is a positive integer. Then, the p first rail head widths are sampled to determine the n first rail head widths. Finally, the distribution parameters of the n first rail head widths are determined.

[0061] By adopting the above-mentioned method, the electronic device can reduce the influence of the center rail when determining the width of the first rail head, thereby improving the accuracy of determining the width of the first rail head.

[0062] Further preferably, when determining that the value of m is the difference between the out-of-limit parameter and a preset second parameter, the electronic device may preferentially determine whether the difference between the out-of-limit parameter and the preset second parameter is greater than or equal to a preset third parameter.

[0063] If so, no other actions are performed; If not, the value of m is determined to be the third parameter.

[0064] By adopting the above-mentioned method, the electronic device can ensure the minimum value of the number of point cloud sections used to determine the first rail head width, thereby ensuring that the first rail head width can be determined.

[0065] Preferably, after executing step 110, the electronic device can also calibrate the toe of the guardrail.

[0066] Specifically, first, the electronic device can determine the position along the extension direction of the first target rail and the first mileage distance from the tip of the point rail as the initial position of the guardrail detection. The first mileage distance is preset, such as 15m, 20m, etc., and this specification does not limit this. The first mileage distance is the distance along the extension direction of the base rail.

[0067] Secondly, the electronic device can arrange the multiple point cloud sections according to the extension direction of the first target track.

[0068] Then, the electronic device can determine whether there is a first point cloud section of the target point that is not within the first rail head coordinate range among the multiple point cloud sections, and determine whether there are target points in the subsequent point cloud sections whose distance from the first rail head coordinate range is greater than a preset second distance.

[0069] If the judgment structure is yes, the first target point that is not in the coordinate range of the first rail head is marked as the toe end of the guardrail.

[0070] If the judgment result of any item is negative, re-judge.

[0071] Preferably, after completing the calibration of the guard rail toe, the electronic device can also calibrate the tip of the center rail.

[0072] Specifically, first, the electronic device can start from the point cloud section corresponding to the target point marked as the toe end of the guardrail, and along the extension direction of the first target rail, determine the point cloud section of the target point whose first target point is within the coordinate range of the first rail head as the initial position of the heart rail detection.

[0073] Secondly, the electronic device can determine whether there is a first point cloud section of the target point that is not within the coordinate range of the first rail head among the multiple point cloud sections, and determine whether there are target points that are not within the coordinate range of the first rail head in the subsequent point cloud sections, and then determine whether the distance between the target point and the coordinate range of the first rail head gradually increases.

[0074] If the judgment results are all yes, then the first target point that is not in the coordinate range of the first rail head is marked as the tip of the center rail.

[0075] If the judgment result of any item is negative, re-judge.

[0076] By adopting the above method, the electronic device completes the positioning of the guard rail and the heart rail based on the relative position relationship between the point rail, the guard rail and the heart rail, and realizes the calibration of the guard rail toe and the heart rail tip, thereby improving the calibration efficiency, simplifying the calibration process and saving computing power.

[0077] Figure 6 as well as Figure 7 These are schematic diagrams of the structure of the guard rail and the basic rail provided in one embodiment of this specification. Figure 6 as well as Figure 7 As shown, the guard rail 44 is adjacent to the base rail 43 , and the guard rail toe 441 is the edge of the guard rail 44 .

[0078] Figure 8 , Fig. 9 as well as Fig.10 Each of them is a schematic diagram of the structure of a center rail and a basic rail provided by an embodiment of this specification.

[0079] like Figure 8 , Fig. 9 as well as Fig.10 As shown, the center rail 45 is in close contact with the base rail 43, and the thickness of the center rail tip 451 is relatively small.

[0080] Preferably, before executing step S102, the electronic device may obtain the straight and curved information and the track direction information corresponding to the three-dimensional point cloud data. The straight and curved information includes straight or curved, and the track direction information includes left or right. The first target range is determined according to the coordinates of multiple target points constituting different basic tracks in the three-dimensional point cloud data, the straight and curved information, and the track direction information.

[0081] The above is a characteristic point calibration method applied to a railway turnout provided in one or more embodiments of this specification. Based on a similar idea, this specification also provides a corresponding characteristic point calibration method applied to a railway turnout, such as Fig.11 shown.

[0082] Fig.11 A schematic flow chart of a characteristic point calibration method for railway turnouts provided in this specification.

[0083] S200: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections. The point cloud section is composed of a plurality of target points. The point cloud section is perpendicular to the extension direction of the basic track.

[0084] In this specification, the feature point calibration method applied to railway turnouts can be executed by an electronic device, which can be a terminal device such as a computer, a laptop, a single-chip microcomputer, a server, etc., and this specification does not impose any restrictions on this.

[0085] S202: Determine a second feature point recognition area corresponding to a preset second target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points.

[0086] S204: Determine a second rail head width of the base rail according to a plurality of point cloud sections within the second feature point recognition area.

[0087] S206: Determine a second rail head coordinate range according to the second rail head width and a preset second target rail extension direction.

[0088] S208: According to the extension direction of the second target track, determine whether there is a point cloud section of the first target point that is not in the coordinate range of the second track head among the multiple point cloud sections, and determine whether there are target points that are not in the coordinate range of the second track head in the subsequent point cloud sections, and then determine whether the distance between the target point and the coordinate range of the second track head gradually increases. If the judgment structure is yes, execute step S210. If any of the judgment structures is no, re-execute step S208.

[0089] S210: Mark the first target point that is not in the coordinate range of the second rail head as the second target point. The second target point may be the tip of the point rail, the tip of the center rail, etc., which is not limited in this specification.

[0090] The above is a characteristic point calibration method applied to a railway turnout provided in one or more embodiments of this specification. Based on a similar idea, this specification also provides a corresponding characteristic point calibration method applied to a railway turnout, such as Fig.12 shown.

[0091] Fig.12 A schematic flow chart of a characteristic point calibration method for railway turnouts provided in this specification.

[0092] S300: Acquire three-dimensional point cloud data composed of a plurality of point cloud sections. The point cloud section is composed of a plurality of target points. The point cloud section is perpendicular to the extension direction of the basic track.

[0093] In this specification, the feature point calibration method applied to railway turnouts can be executed by an electronic device, which can be a terminal device such as a computer, a laptop, a single-chip microcomputer, a server, etc., and this specification does not impose any restrictions on this.

[0094] S302: Determine a third feature point recognition area corresponding to a preset third target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points.

[0095] S304: Determine a third rail head width of the base rail according to a plurality of point cloud sections within the third feature point recognition area.

[0096] S306: Determine a coordinate range of the third rail head according to the third rail head width and a preset extension direction of the third target rail.

[0097] S308: According to the extension direction of the third target track, determine whether there is a point cloud section of the first target point that is not in the coordinate range of the third rail head among the multiple point cloud sections, and determine whether there are target points in the subsequent point cloud sections whose distance from the coordinate range of the third rail head is greater than the preset third distance. If the judgment structure is yes, execute step S310. If any of the judgment structures is no, re-execute step S308.

[0098] S310: Marking the first target point that is not within the coordinate range of the third rail head as the third target point.

[0099] Preferably, the third target point may be the toe of a guard rail, etc., and this specification does not limit this.

[0100] It should be noted that Figure 1 The content of the characteristic point calibration method applied to railway turnouts shown in the figure is relatively detailed and Fig.11 as well as Fig.12 The content of the characteristic point calibration method applied to railway turnouts shown in the figure is similar to Figure 1 The contents of the characteristic point calibration method applied to railway turnouts are similar to those shown in FIG. Fig.11 as well as Fig.12 The content will not be described in detail, the relevant content can be found in Figure 1 The feature point calibration method applied to railway turnouts is shown.

[0101] The above is a characteristic point calibration method applied to a railway turnout provided in one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding characteristic point calibration device applied to a railway turnout, such as Fig.13 shown.

[0102] Fig.13 A schematic diagram of a characteristic point calibration device for a railway turnout provided in accordance with an embodiment of the present specification is shown in FIG. Fig.13 As shown, the characteristic point calibration device applied to railway turnout specifically includes: The acquisition unit 900 is used to acquire three-dimensional point cloud data composed of a plurality of point cloud sections; the point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit 902 is used to determine a first feature point recognition area corresponding to a preset first target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points; A determination unit 904, configured to determine a first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area; A division unit 906 is used to determine a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction; The calibration unit 908 is used to calibrate the first target point that is not within the first rail head coordinate range as the tip of the pointed rail when, according to the extension direction of the first target rail, a first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections, and when there are target points that are not within the first rail head coordinate range in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases.

[0103] It should be noted that all actions of acquiring signals, information or data in this application are carried out in compliance with the relevant data protection laws and policies of the country where they are located, and with the authorization given by the owner of the corresponding device.

[0104] This specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 , Fig.11 as well as Fig.12 A feature point calibration method for railway turnouts is provided.

[0105] This specification also provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device implements the above Figure 1 , Fig.11 as well as Fig.12 A feature point calibration method for railway turnouts is provided.

[0106] Fig.14 The structure diagram of an electronic device provided in one embodiment of this specification. Fig.14 As shown, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 , Fig.11 as well as Fig.12 The characteristic point calibration method applied to railway turnouts. Of course, in addition to the software implementation, this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0107] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0108] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0109] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0110] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0111] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0115] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0116] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0117] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0118] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0119] It should be understood by those skilled in the art that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0120] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0121] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0122] The above description is only an embodiment of this specification and is not intended to limit this specification. For those skilled in the art, this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this specification should be included in the scope of the claims of this application.

Claims

1. A method for calibrating characteristic points of railway turnouts, characterized in that: include: Acquire three-dimensional point cloud data composed of multiple point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Based on a preset first target range, determining a first feature point recognition area corresponding to the first target range from the three-dimensional point cloud data; determining a first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area; Determining a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the first target rail, and there are target points that are not within the first rail head coordinate range in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not within the first rail head coordinate range is calibrated as the tip of the pointed rail.

2. The characteristic point calibration method applied to railway turnout according to claim 1 is characterized in that: The step of determining the first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area comprises: According to a preset first target track extension direction, respectively determine a first rail head width of a base rail of a plurality of point cloud sections within the first feature point recognition area; Determine the distribution parameters of the first n first rail head widths; the distribution parameters are standard deviation, variance, mean absolute deviation or coefficient of variation; According to the order of n values ​​from small to large, the value of n of the distribution parameter that is greater than or equal to the preset first parameter for the first time is determined as the over-limit parameter; Determine the value of m as the difference between the over-limit parameter and a preset second parameter; The first rail head width of the basic rail is determined according to the first m first rail head widths.

3. The characteristic point calibration method applied to railway turnout according to claim 2 is characterized in that: Determining the value of m as the difference between the over-limit parameter and a preset second parameter includes: Determine whether the difference between the over-limit parameter and the preset second parameter is greater than or equal to a preset third parameter; If so, no other actions are performed; If not, the value of m is determined to be the third parameter.

4. The characteristic point calibration method applied to railway turnout according to claim 1 is characterized in that: After the marking as the pointed rail tip, the method further comprises: Determine a position along the extension direction of the first target track and at a first mileage distance from the tip of the pointed rail as an initial position for guardrail detection; Arrange the plurality of point cloud sections according to the extension direction of the first target track; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections, and there are target points in subsequent point cloud sections whose distance from the first rail head coordinate range is greater than a preset second distance, the first target point that is not within the first rail head coordinate range is marked as the toe of the guardrail.

5. The characteristic point calibration method applied to railway turnout according to claim 4 is characterized in that: After the marking as the guardrail toe, the method further comprises: Starting from the point cloud section corresponding to the target point marked as the toe end of the guard rail, along the extension direction of the first target rail, the point cloud section of the target point whose first target point is within the coordinate range of the first rail head is determined as the initial position of the center rail detection; When the first point cloud section in which a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections, and target points that are not within the first rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, the first target point that is not within the first rail head coordinate range is calibrated as the tip of the center rail.

6. The characteristic point calibration method applied to railway turnout according to claim 1 is characterized in that: Before determining the first feature point recognition area corresponding to the preset first target range, the method further includes: Obtaining straight and curved track information and track direction information corresponding to the three-dimensional point cloud data; the straight and curved track information includes straight track or curved track, and the track direction information includes left track or right track; A first target range is determined according to the coordinates of a plurality of target points constituting different basic tracks in the three-dimensional point cloud data, the straight and curved track information, and the track direction information.

7. A characteristic point calibration method applied to railway turnouts, characterized in that: include: Acquire three-dimensional point cloud data composed of multiple point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Determining a second feature point recognition area corresponding to a preset second target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points; determining a second rail head width of the base rail according to a plurality of point cloud sections within the second feature point recognition area; Determining a second rail head coordinate range according to the second rail head width and a preset second target rail extension direction; When the first point cloud section in which a target point that is not within the coordinate range of the second rail head is determined from the multiple point cloud sections according to the extension direction of the second target rail, and there are target points that are not within the coordinate range of the second rail head in subsequent point cloud sections, and the distance between the target point and the coordinate range of the second rail head gradually increases, the first target point that is not within the coordinate range of the second rail head is marked as the second target point.

8. A method for calibrating characteristic points applied to railway turnouts, characterized in that: include: Acquire three-dimensional point cloud data composed of multiple point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; Determining a third feature point recognition area corresponding to a preset third target range from the three-dimensional point cloud data according to the coordinates of the plurality of target points; Determining a third rail head width of the base rail according to a plurality of point cloud sections within the third feature point recognition area; Determining a coordinate range of the third rail head according to the third rail head width and a preset extension direction of the third target rail; When the first point cloud section in which a target point that is not within the coordinate range of the third rail head is determined from the multiple point cloud sections according to the extension direction of the third target rail, and there are target points in subsequent point cloud sections whose distance from the coordinate range of the third rail head is greater than a preset third distance, the first target point that is not within the coordinate range of the third rail head is marked as the third target point.

9. A characteristic point calibration device applied to railway turnouts, characterized in that: include: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a first feature point recognition area corresponding to a preset first target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a first rail head width of the base rail according to a plurality of point cloud sections within the first feature point recognition area; A dividing unit, configured to determine a first rail head coordinate range according to the first rail head width and a preset first target rail extension direction; A calibration unit is used for, when a first point cloud section having a target point that is not within the first rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the first target rail, and target points that are not within the first rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the first rail head coordinate range gradually increases, calibrating the first target point that is not within the first rail head coordinate range as the tip of the pointed rail.

10. A characteristic point calibration device applied to railway turnouts, characterized in that: include: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a second feature point recognition area corresponding to a preset second target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a second rail head width of the base rail according to a plurality of point cloud sections within the second feature point recognition area; a dividing unit, configured to determine a coordinate range of the second rail head according to the width of the second rail head and a preset extension direction of the second target rail; A calibration unit is used to calibrate the first target point that is not in the second rail head coordinate range as the second target point when, according to the extension direction of the second target rail, a first point cloud section in which a target point that is not in the second rail head coordinate range is determined from the multiple point cloud sections, and target points that are not in the second rail head coordinate range are present in subsequent point cloud sections, and the distance between the target point and the second rail head coordinate range gradually increases.

11. A characteristic point calibration device applied to railway turnouts, characterized in that: include: An acquisition unit, used for acquiring three-dimensional point cloud data composed of a plurality of point cloud sections; The point cloud section is composed of a plurality of target points; the point cloud section is perpendicular to the extension direction of the basic track; A matching unit, configured to determine, from the three-dimensional point cloud data, a third feature point recognition area corresponding to a preset third target range according to the coordinates of the plurality of target points; a determination unit, configured to determine a third rail head width of the base rail according to a plurality of point cloud sections within the third feature point recognition area; A dividing unit, used for determining a coordinate range of the third rail head according to the third rail head width and a preset extension direction of the third target rail; The calibration unit is used for, when a first point cloud section in which a target point that is not within the third rail head coordinate range is determined from the multiple point cloud sections according to the extension direction of the third target rail, and when there are target points in subsequent point cloud sections whose distances from the third rail head coordinate range are greater than a preset third distance, calibrating the first target point that is not within the third rail head coordinate range as a third target point.

12. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method described in any one of claims 1 to 8 is implemented.

14. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method according to any one of claims 1 to 8.

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