CN113371033A - Rail transit operation safety real-time online monitoring and early warning management cloud platform based on cloud computing - Google Patents
Rail transit operation safety real-time online monitoring and early warning management cloud platform based on cloud computing Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/041—Obstacle detection
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
- B61L23/047—Track or rail movements
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
- B61L23/048—Road bed changes, e.g. road bed erosion
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Abstract
The invention discloses a cloud computing-based real-time online monitoring and early warning management cloud platform for rail transit operation safety. The track traffic safety real-time online monitoring and early warning management cloud platform comprises a region division module, a basic information acquisition module, a track parameter detection module, a track bed compactness detection module, a track change region detection module, a data processing and analyzing module, a database and an early warning terminal.
Description
Technical Field
The invention belongs to the technical field of rail transit safety monitoring, and relates to a cloud computing-based real-time online rail transit safety monitoring and early warning management cloud platform.
Background
With the continuous development of economy, the operation forms of rail transit are more and more abundant, rail transit also becomes the preferred choice of people's trip gradually, and because rail transit has the characteristics of bearing a large amount of weight, the monitoring of rail transit operation safety is also more and more important.
The current track traffic operation safety monitoring mainly focuses on the aspect of the rail train driving state, track deformation carries out safety monitoring, it is very obvious, current track traffic operation safety monitoring still has certain drawback, on the one hand, the content of current track traffic operation safety monitoring has the limitation, can't carry out comprehensive monitoring and analysis to track operation safety, on the one hand, current track traffic operation safety monitoring lacks the safety monitoring to the track change region, can't ensure the rationality of track whole operation safety monitoring result, on the other hand, the unable effectual security and the stability of ensureing train traveling of current track traffic operation safety monitoring.
Disclosure of Invention
In view of the above, in order to solve the problems in the background art, a cloud platform for real-time online monitoring and early warning of track traffic operation safety based on cloud computing for ballast tracks is provided, so that real-time monitoring and efficient early warning of track traffic safety are realized;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a cloud computing-based real-time online monitoring and early warning management cloud platform for rail transit operation safety, wherein a data processing and analyzing module is respectively connected with a basic information acquisition module, a track bed compactness detection module, a rail parameter detection module, an orbital transfer region detection module, a database and an early warning terminal, and a region dividing module is connected with the basic information acquisition module;
the region dividing module is used for dividing the track path into track sections according to a preset sequence, numbering the divided track sections according to the preset sequence, and sequentially marking the track sections as 1,2,. i,. n;
the basic information acquisition module is used for acquiring position information corresponding to each track segment, further acquiring geographic positions corresponding to each track segment by using a GPS (global positioning system) positioner carried by the unmanned aerial vehicle, further acquiring geographic positions corresponding to each track segment, and constructing a geographic position set D (D1, D2, Di, Dn) of each track segment, wherein Di represents the geographic position corresponding to the ith track segment;
the track parameter detection module comprises a track basic parameter detection unit, a track damage information detection unit, a track obstacle detection unit and a track firmness detection unit, and is used for detecting parameters corresponding to each track section;
the roadbed compactness detection module comprises a plurality of compactorsThe density tester is used for detecting the density corresponding to each track section ballast bed, laying detection points on each track section ballast bed according to a preset sequence, numbering the detection points laid by each track section, marking the detection points as 1,2, once, j, once, M, further acquiring the density corresponding to each detection point ballast bed of each track section, and constructing a density set M of each detection point ballast bed of each track sectiond(Md1,Md2,...Mdj,...Mdm),Mdj represents the compactness corresponding to the jth detection point track bed of the jth track segment, d represents the track segment number, and d is 1,2,... i,. n;
the orbital transfer area detection module comprises a plurality of planeness testers, wherein the planeness testers are respectively used for detecting the planeness of the track in the orbital transfer area, the combination area of the turnout and the track in the orbital transfer area is marked as an orbital transfer detection area, the planeness corresponding to the upper side, the inner side and the outer side of the track in the orbital transfer detection area is respectively detected, and the planeness corresponding to each side of the orbital transfer section in the orbital transfer detection area is further obtained and marked as P;
and the data processing and analyzing module is used for analyzing and processing the data detected by the track parameter detecting module, the track bed compactness detecting module and the track transfer area detecting module.
Preferably, the track basic parameter detection unit includes a plurality of basic parameter detection devices, which are respectively used for detecting basic parameters corresponding to each track segment, where the basic parameters corresponding to each track segment include a height corresponding to a left-side steel rail of each track segment, a height corresponding to a right-side steel rail of each track segment, and a distance between two side steel rails, and the distance between the left-side steel rail and the right-side steel rail of each track segment is recorded as a steel rail inner-side distance, so as to obtain the height corresponding to the left-side steel rail of each track segment, the height corresponding to the right-side steel rail of each track segment, and the inner-side distance between the right-side steel rails of each track segment, and construct a basic parameter set Jw(Jw1,Jw2,...Jwi,...Jwn)，Jwi represents the w-th basic parameter corresponding to the ith track segment, and w is a1, a2, a3, a1, a2 and a3 respectively represent the height corresponding to the left rail of each track segmentThe height of the right steel rail of each track section and the distance between the inner sides of the steel rails of each track section.
Preferably, the track damage information detection unit includes a plurality of three-dimensional laser scanners, and the three-dimensional laser scanners are respectively used for scanning and shooting each track section, so as to obtain a three-dimensional stereo image corresponding to each track section, further perform noise reduction and filtering processing on the acquired three-dimensional stereo image corresponding to each track section, extract the number of comprehensive cracks corresponding to the steel rail in the three-dimensional stereo image of each track section, number the comprehensive cracks corresponding to the steel rails on both sides of each track section according to a preset sequence, sequentially mark the comprehensive cracks as 1,2, ad(Xd1，Xd2，...Xdg,...Xdf)，XdAnd g represents the cracking area corresponding to the g-th crack of the steel rail of the d-th track section.
Preferably, the track obstacle detection unit includes a plurality of cameras, which are respectively installed in each track segment, and respectively acquire images of each track segment according to preset time periods, thereby acquiring images corresponding to each track segment in each acquisition time period, and constructing an image set T of each track segment in each acquisition time periodd(Td1,Td2,...Tde,...Tdp)，TdAnd e represents the image corresponding to the d track segment track of the e acquisition time period.
Preferably, the track firmness detection unit comprises a plurality of high-speed spike detection visual sensors, which are respectively used for detecting firmness corresponding to each track spike of each track section, counting the number of the spikes corresponding to each track section, numbering the spikes corresponding to each track section according to a preset sequence, sequentially marking the spikes as 1,2, u, v, detecting each spike of each track section through the high-speed spike detection visual sensors, further acquiring the position corresponding to each spike of each track section and the offset corresponding to each spike of each track section, and further constructing an offset set Y of each spike of each track sectiond(Yd1,Yd2,...Ydu,...Ydv)，Ydu represents the offset corresponding to the u-th spike of the d-th track segment.
Preferably, the specific processing procedure of the data processing and analyzing module for processing the detection data of the track parameter detection module includes the following steps:
a1, acquiring data detected by the track basic parameter detection unit, further acquiring a basic parameter set of each track section, acquiring the corresponding height of the left steel rail of each track section, the corresponding height of the right steel rail of each track section and the inner side distance of the steel rail of each track section according to the basic parameter set of each track section, and further analyzing the operation safety influence coefficient corresponding to the basic parameter of the steel rail of each track section;
a2, acquiring data detected by a rail damage information detection unit, further acquiring a crack area set of each crack of each rail section steel rail, further acquiring an area corresponding to each crack of each rail section steel rail according to the crack area set of each crack of each rail section steel rail, further acquiring a comprehensive crack area corresponding to each rail section steel rail according to the crack area corresponding to each crack of each rail section left side steel rail, comparing the comprehensive crack area corresponding to each rail section steel rail with a threshold value of a standard crack area corresponding to the steel rail, and further counting the damage operation safety influence coefficient of each rail section steel rail;
a3, acquiring data detected by a rail obstacle detection unit, further acquiring an image set of each rail segment in each acquisition time period, comparing and screening images corresponding to each rail segment in each acquisition time period with images corresponding to each obstacle type rail, if the image corresponding to a certain rail segment in a certain acquisition time period accords with the rail image corresponding to each obstacle type, further marking the area of the rail segment as an obstacle rail segment, marking the acquisition time period as an obstacle existence time period, extracting a number corresponding to the obstacle rail segment and a geographical position corresponding to the obstacle rail segment, and sending the geographical position corresponding to the obstacle rail segment and the time period in which the obstacle exists to an early warning terminal;
a4, acquiring data detected by a track firmness detection unit, further acquiring an offset set of each spike of each track section, acquiring an offset corresponding to each spike of each track section, comparing the offset corresponding to each spike of each track section with a standard offset corresponding to each track spike, and further counting a track section spike firmness operation safety influence coefficient;
a5, according to the operation safety influence coefficient corresponding to the basic parameters of the steel rail of each track section, the damage operation safety influence coefficient of the steel rail of each track section and the firmness operation safety influence coefficient of the spike of each track section, further counting the comprehensive operation safety influence coefficient of the steel rail of each track section.
Preferably, the data processing and analyzing module is configured to analyze the data detected by the track bed compactness detecting module, obtain a compactness set of each detection point track bed of each track segment, further obtain a compactness corresponding to each detection point track bed of each track segment, further obtain an average compactness corresponding to each track segment track bed according to the compactness corresponding to each detection point track bed of each track segment, compare the average compactness corresponding to each track segment track bed with a standard compactness corresponding to the track bed, and further calculate an operation safety influence coefficient of the compactness of each track segment track bed.
Preferably, the data processing and analyzing module is configured to analyze data detected by the orbital transfer area detecting module, obtain flatness corresponding to an upper side, an inner side, and an outer side of the orbital transfer area, compare the flatness corresponding to each side of the orbital transfer area with a standard flatness corresponding to the orbital transfer area, and count the safety influence coefficients of the operation of the flatness of each side of the orbital transfer area, so as to count the comprehensive safety influence coefficients of the operation of the orbital transfer area.
Preferably, the data processing and analyzing module is further configured to perform comprehensive analysis and processing on data detected by the track parameter detecting module, the track bed compactness detecting module and the track transfer area detecting module, and further perform statistics on the track path comprehensive operation safety influence coefficient according to the statistical comprehensive operation safety influence coefficient of each track segment steel rail, the statistical compactness operation safety influence coefficient of each track segment track bed and the statistical comprehensive operation safety influence coefficient of the track transfer area.
Preferably, the early warning terminal is configured to receive the geographical position corresponding to the obstacle track segment sent by the data processing and analyzing module, the time period in which the obstacle exists, and the comprehensive operation safety influence coefficient corresponding to the track path, send the geographical position corresponding to the obstacle track segment, the time period in which the obstacle exists, and the comprehensive operation safety influence coefficient corresponding to the track path to the staff of the track operation management center, and perform early warning.
The invention has the beneficial effects that:
(1) according to the cloud platform for real-time online monitoring and early warning management of the rail transit operation safety based on the cloud computing, three large aspects of the rail parameter, the track bed compactness and the track change area flatness are detected through the rail parameter detection module, the track bed compactness detection module and the track change area detection module in combination with the data processing and analyzing module, so that the problems that the content of the conventional rail transit operation safety monitoring is limited, and further the rail operation safety cannot be comprehensively monitored and analyzed are solved, the rationality of the overall rail transit operation safety monitoring result is effectively improved, and the safety and the stability of train running are effectively guaranteed.
(2) According to the invention, the track parameter detection module detects the track basic parameter detection unit, the damage information detection unit, the track obstacle information and the track firmness, so that the track parameter monitoring accuracy is greatly improved, and meanwhile, the monitoring efficiency of the track parameter operation safety and the monitoring result reference are also greatly improved.
(3) According to the invention, at the early warning terminal, the received early warning information is sent to the supervision personnel corresponding to the track of the child, so that the occurrence probability of train safety accidents is effectively reduced, and meanwhile, the safety guarantee of passengers or loaded goods and the smoothness of train running are greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram showing the connection of modules of the system of the present invention;
FIG. 2 is a schematic diagram of the connection of the track parameter detection module according to the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1 to 2, a cloud platform for real-time online monitoring and early warning management of rail transit operation safety based on cloud computing comprises a region division module, a basic information acquisition module, a rail parameter detection module, a track bed compactness detection module, an orbital transfer region detection module, a data processing and analysis module, a database and an early warning terminal, wherein the data processing and analysis module is respectively connected with the basic information acquisition module, the track bed compactness detection module, the rail parameter detection module, the orbital transfer region detection module, the database and the early warning terminal, and the region division module is connected with the basic information acquisition module;
the region dividing module is used for dividing the track path into track sections according to a preset sequence, numbering the divided track sections according to the preset sequence, and sequentially marking the track sections as 1,2,. i,. n;
the basic information acquisition module is used for acquiring position information corresponding to each track segment, further acquiring geographic positions corresponding to each track segment by using a GPS (global positioning system) positioner carried by the unmanned aerial vehicle, further acquiring geographic positions corresponding to each track segment, and constructing a geographic position set D (D1, D2, Di, Dn) of each track segment, wherein Di represents the geographic position corresponding to the ith track segment;
the track parameter detection module comprises a track basic parameter detection unit, a track damage information detection unit, a track obstacle detection unit and a track firmness detection unit, and is used for detecting parameters corresponding to each track section;
the track basic parameter detection unit comprises a plurality of basic parameter detection devices which are respectively used for detecting basic parameters corresponding to each track section, wherein the basic parameters corresponding to each track section comprise the height corresponding to the left steel rail of each track section, the height corresponding to the right steel rail of each track section and the distance between the two side steel rails, the distance between the left steel rail and the right steel rail of each track section is recorded as the inner side distance of the steel rail, the height corresponding to the left steel rail of each track section, the height corresponding to the right steel rail of each track section and the inner side distance of the steel rail of each track section are further obtained, and a basic parameter set J of each track section is constructedw(Jw1,Jw2,...Jwi,...Jwn)，Jwi represents the w-th basic parameter corresponding to the ith track segment, and w is a1, a2, a3, a1, a2 and a3 respectively represent the height corresponding to the left rail of each track segment, the height corresponding to the right rail of each track segment and the inner spacing of the rails of each track segment.
The left side and the right side of the steel rail are consistent with the left side and the right side of the train wheels in the running direction of the train.
The basic parameter detection equipment is a laser range finder which is respectively used for detecting the height corresponding to the left steel rail of each track section, the height corresponding to the right steel rail of each track section and the inner side distance of the steel rail of each track section;
in a specific embodiment, the track basic parameter detection further includes basic detection area division, the right side steel rails of the left side steel rails of each track section are divided into detection areas according to a preset sequence, the central points of the detection areas are arranged as basic detection points, wherein the basic detection points of the left side steel rails and the basic detection points of the right side steel rails are in a one-to-one correspondence relationship, the basic detection points of the left side steel rails of each track section are numbered according to the preset sequence and are sequentially marked as 1,2,. x,. y, the basic detection points of the right side steel rails of each track section are numbered according to the preset sequence and are sequentially marked as 1 ', 2,. x,. y', the basic detection points of each left side steel rail of each track section are respectively connected with the corresponding basic detection points of each right side steel rail of each track section, and then a connection line segment corresponding to the basic detection points of each left side steel rail of each track section and each right side steel rail of each track section is obtained, numbering connecting line segments corresponding to the track segments according to a preset sequence, sequentially marking the connecting line segments as 1,2, a.k.a.h., marking the length corresponding to the connecting line segments as the inner side distance of the steel rail, and simultaneously detecting the height corresponding to each left side steel rail basic detection point of each track segment and each right side steel rail basic detection point steel rail of each track segment by using a laser distance meter so as to obtain the height corresponding to each left side steel rail basic detection point of each track segment and each right side steel rail basic detection point steel rail of each track segment;
according to the embodiment of the invention, the detection points are distributed on the left steel rail of each track section and the right steel rail of each track section, so that the reliability and the accuracy of the detection data of the height of the left steel rail of each track section, the height of the right steel rail and the inner side distance of the steel rail are greatly improved, and the detection error caused by integral detection or local detection is effectively reduced.
The track damage information detection unit comprises a plurality of three-dimensional laser scanners which are respectively used for scanning and shooting each track section, further acquiring a three-dimensional image corresponding to each track section, further performing noise reduction and filtering processing on the acquired three-dimensional image corresponding to each track section, extracting the number of comprehensive cracks corresponding to steel rails in the three-dimensional image of each track section, numbering the comprehensive cracks corresponding to the steel rails on two sides of each track section according to a preset sequence, sequentially marking the comprehensive cracks as 1,2, g, f, further extracting the outline corresponding to each crack of the steel rails in the three-dimensional image of each track section, further acquiring the crack area corresponding to each crack of the steel rails of each track section, and constructing a crack area set X of each crack of the steel rails of each track sectiond(Xd1，Xd2，...Xdg,...Xdf)，XdAnd g represents the cracking area corresponding to the g-th crack of the steel rail of the d-th track section.
In the embodiment of the invention, in the track damage information detection unit, the three-dimensional laser scanner is used for scanning and shooting each track, so that the crack detection accuracy of the steel rails on two sides is greatly improved, the problem of inaccurate crack detection caused by visual angle blind areas when a camera shoots pictures is avoided, and the specific condition of current track cracking is more intuitively displayed in a three-dimensional image mode.
The track obstacle detection unit comprises a plurality of cameras which are respectively installed in each track section and respectively acquire images of each track section according to preset time periods, so that images corresponding to each track section in each acquisition time period are acquired, and an image set T of each track section in each acquisition time period is constructedd(Td1,Td2,...Tde,...Tdp)，TdAnd e represents the image corresponding to the d track segment track of the e acquisition time period.
According to the embodiment of the invention, the potential safety hazard caused when the obstacles exist for train running is effectively avoided by detecting the obstacles of each track section in real time, and meanwhile, the running smoothness is greatly ensured.
The track firmness detection unit comprises a plurality of high-speed spike detection visual sensors, the track firmness detection visual sensors are respectively used for detecting firmness corresponding to each track spike of each track section, the quantity of the spikes corresponding to each track section is counted, the spikes corresponding to each track section are numbered according to a preset sequence, the numbers are marked as 1,2, u, v, the high-speed spike detection visual sensors are used for detecting each spike of each track section, the corresponding positions of each spike of each track section and the corresponding offset of each spike of each track section are obtained, and then an offset set Y of each spike offset set of each track section is establishedd(Yd1,Yd2,...Ydu,...Ydv)，Ydu represents the offset corresponding to the u-th spike of the d-th track segment.
In the track firmness detection unit, the high-speed spike detection visual sensor is used for detecting the offset corresponding to the spikes of each track section, so that the current loosening condition of the spikes is effectively reflected, and a data basis is provided for the follow-up statistics of the track section spike firmness operation safety influence coefficient.
According to the embodiment of the invention, the track parameter detection module detects the track basic parameter detection unit, the damage information detection unit, the track obstacle information and the track firmness, so that the track parameter monitoring accuracy is greatly improved, and meanwhile, the monitoring efficiency of the track parameter operation safety and the monitoring result reference are also greatly improved.
The specific processing process of the data processing and analyzing module for processing the detection data of the track parameter detection module comprises the following steps:
a1, acquiring data detected by the track basic parameter detection unit, further acquiring a basic parameter set of each track section, acquiring the corresponding height of the left steel rail of each track section, the corresponding height of the right steel rail of each track section and the inner side distance of the steel rail of each track section according to the basic parameter set of each track section, and further analyzing the operation safety influence coefficient corresponding to the basic parameter of the steel rail of each track section;
the analysis of the operation safety influence coefficient corresponding to the basic parameters of each track section comprises the analysis of the operation safety influence coefficient of the height difference of the steel rails at the two sides of each track section, the operation safety influence coefficient of the height of the steel rails at the two sides of each track section and the operation safety influence coefficient of the inner side distance of the steel rails of each track section.
The analysis process of the operation safety influence coefficient of the height difference of the steel rails on the two sides of each track section is as follows: comparing the corresponding heights of the left steel rail basic detection points of each track section and the right steel rail basic detection points of each track section, and further counting the corresponding height difference of the left steel rail and the right steel rail of each track section, wherein the calculation formula is
ΔHdThe height difference between the left rail and the right rail of the d-th track section is shown as a1dr represents the height of the r basic detection point of the rail at the left side of the d track segment corresponding to the rail, a2dr 'represents the height of the r' basic detection point of the rail on the right side of the d track section corresponding to the rail, r represents the basic detection point number of the rail on the left side of each track section, and r is 1,2The basic detection points of the steel rails are numbered, r 'is 1', 2 ', x', y ', r and r' take values synchronously, the height difference corresponding to the left steel rail and the right steel rail of each track section is compared with the standard height difference corresponding to the steel rails on two sides of each track section, and then the operation safety influence coefficient of the height difference of the steel rails on two sides of each track section is calculated, wherein the calculation formula is that
αdRepresents the operation safety influence coefficient, delta H, corresponding to the height difference of the steel rails at two sides of the d-th track sectiond standardAnd (4) representing the standard height difference corresponding to the steel rails on two sides of the d-th track section.
The analysis process of the safety influence coefficient of the height operation of the steel rails on the two sides of each track section is as follows: comparing the height corresponding to each left steel rail basic detection point of each track section and each right steel rail basic detection point steel rail of each track section with the standard height corresponding to each left steel rail of each track section and the standard height corresponding to each right steel rail of each track section respectively, and further counting the height operation safety influence coefficient of the steel rails at two sides of each track section, wherein the calculation formula is that
βdRepresenting the operational safety influence coefficient corresponding to the height of the steel rails on both sides of the d-th track section, a1d standard，a2d standardRespectively showing the standard height corresponding to the left rail of the d-th track section and the standard height corresponding to the right rail of the d-th track section, and mu shows the track height change ratio.
The analysis process of the safety influence coefficient of the running of the inner side spacing of the steel rails of each track section is as follows: comparing the inside space of each track section steel rail with the standard inside space corresponding to each track section steel rail, and further counting the operation safety influence coefficient of the inside space of each track section steel rail, wherein the calculation formula is
δdRepresents the corresponding running safety influence coefficient of the inside spacing of the steel rails of the d-th track segment, a3dt represents the length of the t connecting line segment of the g track segment steel railDegree, a3d standardThe standard inner pitch corresponding to the d-th track segment is shown, t represents the number of the connecting line segment of each track segment, and t is 1, 2.
According to the calculated height difference operation safety influence coefficient of the steel rails at two sides of each track section, the height operation safety influence coefficient of the steel rails at two sides of each track section and the operation safety influence coefficient of the inner side space of each track steel rail, the operation safety influence coefficient corresponding to the basic parameter of each track section steel rail is calculated, and the calculation formula is that
γdAnd representing the operation safety influence coefficient corresponding to the basic rail parameter of the d-th track section.
A2, acquiring data detected by a rail damage information detection unit, further acquiring a crack area set of each crack of each rail section steel rail, further acquiring an area corresponding to each crack of each rail section steel rail according to the crack area set of each crack of each rail section steel rail, further acquiring a comprehensive crack area corresponding to each rail section steel rail according to the crack area corresponding to each crack of each rail section left side steel rail, comparing the comprehensive crack area corresponding to each rail section steel rail with a threshold value of a standard crack area corresponding to the steel rail, and further counting the damage operation safety influence coefficient of each rail section steel rail;
wherein, the calculation formula of the safe influence coefficient of the damaged operation of the steel rail of each track section is
φdRepresenting the safe influence coefficient of operation, X, corresponding to the damage of the steel rail of the d-th track sectiond zShowing the cracking area, X, corresponding to the z-th crack of the steel rail of the d-th track sectiond standardAnd a threshold value of standard cracking area of the d-th track segment is represented, z represents the comprehensive crack number of the steel rails on two sides of each track segment, and z is 1, 2.
A3, acquiring data detected by a rail obstacle detection unit, further acquiring an image set of each rail segment in each acquisition time period, comparing and screening images corresponding to each rail segment in each acquisition time period with images corresponding to each obstacle type rail, if the image corresponding to a certain rail segment in a certain acquisition time period accords with the rail image corresponding to each obstacle type, further marking the area of the rail segment as an obstacle rail segment, marking the acquisition time period as an obstacle existence time period, extracting a number corresponding to the obstacle rail segment and a geographical position corresponding to the obstacle rail segment, and sending the geographical position corresponding to the obstacle rail segment and the time period in which the obstacle exists to an early warning terminal;
a4, acquiring data detected by a track firmness detection unit, further acquiring an offset set of each spike of each track section, acquiring an offset corresponding to each spike of each track section, comparing the offset corresponding to each spike of each track section with a standard offset corresponding to each track spike, and further counting a track section spike firmness operation safety influence coefficient;
wherein, the calculation formula of the operating safety influence coefficient of the firmness of the spikes of each track section is
Represents the running safety influence coefficient, Y, corresponding to the firmness of the spikes of the d-th track sectiond qIndicates the offset, Y, corresponding to the qth spike of the d track segmentStandard of meritIndicating the standard offset for the rail spike.
A5, according to the operation safety influence coefficient corresponding to the basic parameters of each track section steel rail, the damage operation safety influence coefficient of each track section steel rail and the firmness operation safety influence coefficient of each track section spike, further counting the comprehensive operation safety influence coefficient of each track section steel rail, wherein the calculation formula is
λdAnd (3) representing the comprehensive operation safety influence coefficient corresponding to the steel rail of the d-th track section, wherein n represents the number of the track sections.
According to the embodiment of the invention, the track basic parameter detection unit, the damage information detection unit, the track obstacle information and the track firmness detection data are analyzed, so that the operation safety influence coefficient corresponding to the track parameter of each current track section is effectively analyzed, the problem that the content of the existing track traffic operation safety monitoring is one-sidedly solved, and the authenticity of the monitoring result is greatly improved.
The ballast bed compactness detection module comprises a plurality of compactness testers which are respectively used for detecting compactness corresponding to each track section ballast bed, arranging detection points of each track section ballast bed according to a preset sequence, numbering the detection points arranged by each track section, sequentially marking the detection points as 1,2, a.j.m, further acquiring the compactness corresponding to each detection point ballast bed of each track section, and constructing a compactness set M of each detection point ballast bed of each track sectiond(Md1,Md2,...Mdj,...Mdm),Mdj represents the compactness corresponding to the jth detection point track bed of the jth track segment, d represents the track segment number, and d is 1,2,... i,. n;
according to the embodiment of the invention, the compactness of the track bed of each track section is detected by using the compactness tester, so that the reliability of the detection result is greatly improved, and a data basis is provided for the subsequent safety analysis of the compactness corresponding to the track bed of each track section.
The data processing and analyzing module is used for analyzing the data detected by the track bed compactness detecting module to obtain a compactness set of each detection point track bed of each track section and further obtain compactness corresponding to each detection point track bed of each track section, and further obtain average compactness corresponding to each track section track bed according to the compactness corresponding to each detection point track bed of each track section, comparing the average compactness corresponding to each track section track bed with the standard compactness corresponding to the track bed, and further counting the running safety influence coefficient of the compactness of each track section track bed, wherein the running safety influence coefficient calculation formula of the compactness of each track section track bed is
ηdRepresenting the operational safety influence coefficient, M, corresponding to the density of the ballast bed of the d-th track sectionStandard of meritShowing track bed pairsThe required degree of compactness of the product is standard,
the average compactness corresponding to the d track segment ballast bed is shown.
According to the embodiment of the invention, the compactness of each track section is analyzed, so that the compactness corresponding to each track section ballast bed at present is effectively analyzed, the stability and the pressure resistance of the ballast bed are directly influenced by the compactness of the ballast bed, and further, the running safety of a train is effectively guaranteed.
The orbital transfer area detection module comprises a plurality of planeness testers, wherein the planeness testers are respectively used for detecting the planeness of the track in the orbital transfer area, the combination area of the turnout and the track in the orbital transfer area is marked as an orbital transfer detection area, the planeness corresponding to the upper side, the inner side and the outer side of the track in the orbital transfer detection area is respectively detected, and the planeness corresponding to each side of the orbital transfer section in the orbital transfer detection area is further obtained and marked as P;
the upper side surface of the track refers to a surface which is contacted with the train bottom, the inner side surface of the track refers to a surface opposite to the steel rails on two sides of the track, namely two end side surfaces connected with the sleeper rail, and the outer side surface of the track is opposite to the inner side surface of the track.
The data processing and analyzing module is used for analyzing the data detected by the orbital transfer area detecting module, acquiring the flatness corresponding to the upper side, the inner side and the outer side of the orbital transfer detecting area, comparing the flatness corresponding to the side of each orbital transfer detecting area with the standard flatness corresponding to the orbital transfer area, counting the operation safety influence coefficient of the flatness of the side of each orbital transfer detecting area, and further counting the comprehensive operation safety influence coefficient of the orbital transfer area.
Wherein, the calculation formula of the operation safety influence coefficient of the flatness of each track side surface of the track-changing detection area is
The operation safety influence coefficient corresponding to the flatness of the c-th track side surface of the track change detection area is shown, c represents the track side surface orientation of the track change area, c is s1, s2, s3, s1, s2 and s3 respectively represent the upper side surface, the inner side surface and the outer side surface corresponding to the track change detection area, and P is the total value of the upper side surface, the inner side surface and the outer side surface of the track change detection area, and the total value of the upper side surface, the inner side surface and the outer side surface of the track change detection area is the total value of the track change detection areacIndicating the flatness, P, corresponding to the c-th track side of the track-changing detection areaStandard of meritAnd indicating the standard flatness corresponding to the track of the track changing area.
Wherein, the calculation formula of the comprehensive operation safety influence coefficient of the orbital transfer area is
And representing the comprehensive operation safety influence coefficient corresponding to the track transfer area.
According to the embodiment of the invention, the flatness corresponding to the side surface of each track in the track transfer detection area is analyzed, so that the running safety of the track in the current track transfer area is effectively analyzed, the occurrence of safety accidents such as rollover and the like during the track transfer of a train is greatly reduced, and the safety and the stability during the track transfer are effectively ensured.
The data processing and analyzing module is also used for comprehensively analyzing and processing the data detected by the track parameter detecting module, the track bed compactness detecting module and the track transfer area detecting module, and further carrying out statistics on the track path comprehensive operation safety influence coefficient according to the statistical comprehensive operation safety influence coefficient of each track section steel rail and the statistical compactness operation safety influence coefficient of each track section track bed.
Wherein the track path comprehensive operation safety influence coefficient calculation formula is
And Q represents the comprehensive operation safety influence coefficient corresponding to the track path.
The data processing and analyzing module is further used for comparing the counted comprehensive operation safety influence coefficient of the track path with a numerical value corresponding to a preset track path operation safety influence coefficient corresponding to the early warning, if the comprehensive operation safety influence coefficient of the track path is larger than the preset track path operation safety influence coefficient corresponding to the early warning, the track path is recorded as an early warning path, and then the comprehensive operation safety influence coefficient corresponding to the track path is sent to the early warning terminal.
According to the embodiment of the invention, the data detected by the three modules, namely the track parameter, the track bed compactness and the rail transfer area flatness, are analyzed, so that the problems that the content of the conventional track traffic operation safety monitoring is limited and the track operation safety cannot be comprehensively monitored and analyzed are solved, and the rationality and the scientificity of the track overall operation safety monitoring result are effectively improved.
The early warning terminal is used for receiving the geographical position corresponding to the obstacle track section, the time period of the obstacle and the comprehensive operation safety influence coefficient corresponding to the track path, sent by the data processing and analyzing module, sending the geographical position corresponding to the obstacle track section, the time period of the obstacle and the comprehensive operation safety influence coefficient corresponding to the track path to the personnel in the track operation management center, and giving early warning.
The embodiment of the invention effectively reduces the occurrence probability of train safety accidents by sending the received early warning information to the supervision personnel corresponding to the track of the child, and greatly improves the safety guarantee of passengers or loaded goods and the smoothness of train running.
The database is used for storing standard height difference corresponding to steel rails on two sides of each track section, standard height corresponding to steel rails on the left side of each track section, standard height corresponding to steel rails on the right side of each track section, standard inner side distance corresponding to the steel rails of each track section, standard offset corresponding to track spikes, a threshold value of standard cracking area corresponding to the steel rails, standard compactness corresponding to a track bed, standard flatness corresponding to a track of a track change area and a track height change ratio.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. The utility model provides a track traffic operation safety real-time on-line monitoring early warning management cloud platform based on cloud, its characterized in that: the data processing and analyzing module is respectively connected with the basic information acquisition module, the track bed compactness detection module, the track parameter detection module, the track change area detection module, the database and the early warning terminal, and the area division module is connected with the basic information acquisition module;
the region dividing module is used for dividing the track path into track sections according to a preset sequence, numbering the divided track sections according to the preset sequence, and sequentially marking the track sections as 1,2,. i,. n;
the basic information acquisition module is used for acquiring position information corresponding to each track segment, further acquiring geographic positions corresponding to each track segment by using a GPS (global positioning system) positioner carried by the unmanned aerial vehicle, further acquiring geographic positions corresponding to each track segment, and constructing a geographic position set D (D1, D2, Di, Dn) of each track segment, wherein Di represents the geographic position corresponding to the ith track segment;
the track parameter detection module comprises a track basic parameter detection unit, a track damage information detection unit, a track obstacle detection unit and a track firmness detection unit, and is used for detecting parameters corresponding to each track section;
the ballast bed compactness detection module comprises a plurality of compactness testers which are respectively used for detecting compactness corresponding to each track section ballast bed, arranging detection points of each track section ballast bed according to a preset sequence, numbering the detection points arranged by each track section, sequentially marking the detection points as 1,2, a.j.m, further acquiring the compactness corresponding to each detection point ballast bed of each track section, and constructing a compactness set M of each detection point ballast bed of each track sectiond(Md1,Md2,...Mdj,...Mdm),Mdj represents the d-thDetecting the compactness corresponding to the track bed at the jth track section, wherein d represents the track section number, and d is 1,2,. i,. n;
the orbital transfer area detection module comprises a plurality of planeness testers, wherein the planeness testers are respectively used for detecting the planeness of the track in the orbital transfer area, the combination area of the turnout and the track in the orbital transfer area is marked as an orbital transfer detection area, the planeness corresponding to the upper side, the inner side and the outer side of the track in the orbital transfer detection area is respectively detected, and the planeness corresponding to each side of the orbital transfer section in the orbital transfer detection area is further obtained and marked as P;
and the data processing and analyzing module is used for analyzing and processing the data detected by the track parameter detecting module, the track bed compactness detecting module and the track transfer area detecting module.
2. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the track basic parameter detection unit comprises a plurality of basic parameter detection devices which are respectively used for detecting basic parameters corresponding to each track section, wherein the basic parameters corresponding to each track section comprise the height corresponding to the left steel rail of each track section, the height corresponding to the right steel rail of each track section and the distance between the two side steel rails, the distance between the left steel rail and the right steel rail of each track section is recorded as the inner side distance of the steel rail, the height corresponding to the left steel rail of each track section, the height corresponding to the right steel rail of each track section and the inner side distance of the steel rail of each track section are further obtained, and a basic parameter set J of each track section is constructedw(Jw1,Jw2,...Jwi,...Jwn)，Jwi represents the w-th basic parameter corresponding to the ith track segment, and w is a1, a2, a3, a1, a2 and a3 respectively represent the height corresponding to the left rail of each track segment, the height corresponding to the right rail of each track segment and the inner spacing of the rails of each track segment.
3. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1The method is characterized in that: the track damage information detection unit comprises a plurality of three-dimensional laser scanners which are respectively used for scanning and shooting each track section, further acquiring a three-dimensional image corresponding to each track section, further performing noise reduction and filtering processing on the acquired three-dimensional image corresponding to each track section, extracting the number of comprehensive cracks corresponding to steel rails in the three-dimensional image of each track section, numbering the comprehensive cracks corresponding to the steel rails on two sides of each track section according to a preset sequence, sequentially marking the comprehensive cracks as 1,2, g, f, further extracting the outline corresponding to each crack of the steel rails in the three-dimensional image of each track section, further acquiring the cracking area corresponding to each crack of the steel rails of each track section, and constructing a set X of cracking area sets of each crack of the steel rails of each track sectiond(Xd1，Xd2，...Xdg,...Xdf)，XdAnd g represents the cracking area corresponding to the g-th crack of the steel rail of the d-th track section.
4. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the track obstacle detection unit comprises a plurality of cameras which are respectively arranged in each track section and respectively acquire images of each track section according to preset time periods, so that images corresponding to each track section in each acquisition time period are acquired, and an image set T of each track section in each acquisition time period is constructedd(Td1,Td2,...Tde,...Tdp)，TdAnd e represents the image corresponding to the d track segment track of the e acquisition time period.
5. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the track firmness detection unit comprises a plurality of high-speed spike detection visual sensors which are respectively used for detecting firmness corresponding to each track spike of each track section, counting the quantity of the spikes corresponding to each track section, numbering the spikes corresponding to each track section according to a preset sequence, and sequentially marking the spikes as 1,2, u, v and further passing through the high-speed spikesThe detection vision sensor detects each spike of each track section, and then obtains the corresponding position of each spike of each track section and the corresponding offset of each spike of each track section, and further constructs the offset set Y of each spike of each track sectiond(Yd1,Yd2,...Ydu,...Ydv)，Ydu represents the offset corresponding to the u-th spike of the d-th track segment.
6. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the specific processing process of the data processing and analyzing module for processing the detection data of the track parameter detection module comprises the following steps:
a1, acquiring data detected by the track basic parameter detection unit, further acquiring a basic parameter set of each track section, acquiring the corresponding height of the left steel rail of each track section, the corresponding height of the right steel rail of each track section and the inner side distance of the steel rail of each track section according to the basic parameter set of each track section, and further analyzing the operation safety influence coefficient corresponding to the basic parameter of the steel rail of each track section;
a2, acquiring data detected by a rail damage information detection unit, further acquiring a crack area set of each crack of each rail section steel rail, further acquiring an area corresponding to each crack of each rail section steel rail according to the crack area set of each crack of each rail section steel rail, further acquiring a comprehensive crack area corresponding to each rail section steel rail according to the crack area corresponding to each crack of each rail section left side steel rail, comparing the comprehensive crack area corresponding to each rail section steel rail with a threshold value of a standard crack area corresponding to the steel rail, and further counting the damage operation safety influence coefficient of each rail section steel rail;
a3, acquiring data detected by a rail obstacle detection unit, further acquiring an image set of each rail segment in each acquisition time period, comparing and screening images corresponding to each rail segment in each acquisition time period with images corresponding to each obstacle type rail, if the image corresponding to a certain rail segment in a certain acquisition time period accords with the rail image corresponding to each obstacle type, further marking the area of the rail segment as an obstacle rail segment, marking the acquisition time period as an obstacle existence time period, extracting a number corresponding to the obstacle rail segment and a geographical position corresponding to the obstacle rail segment, and sending the geographical position corresponding to the obstacle rail segment and the time period in which the obstacle exists to an early warning terminal;
a4, acquiring data detected by a track firmness detection unit, further acquiring an offset set of each spike of each track section, acquiring an offset corresponding to each spike of each track section, comparing the offset corresponding to each spike of each track section with a standard offset corresponding to each track spike, and further counting a track section spike firmness operation safety influence coefficient;
a5, according to the operation safety influence coefficient corresponding to the basic parameters of the steel rail of each track section, the damage operation safety influence coefficient of the steel rail of each track section and the firmness operation safety influence coefficient of the spike of each track section, further counting the comprehensive operation safety influence coefficient of the steel rail of each track section.
7. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the data processing and analyzing module is used for analyzing the data detected by the track bed compactness detecting module, acquiring a compactness set of each detection point track bed of each track section, further acquiring compactness corresponding to each detection point track bed of each track section, further acquiring average compactness corresponding to each track section track bed according to the compactness corresponding to each detection point track bed of each track section, comparing the average compactness corresponding to each track section track bed with the standard compactness corresponding to the track section track bed, and further counting the running safety influence coefficient of the compactness of each track section track bed.
8. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the data processing and analyzing module is used for analyzing the data detected by the orbital transfer area detecting module, acquiring the flatness corresponding to the upper side, the inner side and the outer side of the orbital transfer detecting area, comparing the flatness corresponding to the side of each orbital transfer detecting area with the standard flatness corresponding to the orbital transfer area, counting the operation safety influence coefficient of the flatness of the side of each orbital transfer detecting area, and further counting the comprehensive operation safety influence coefficient of the orbital transfer area.
9. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the data processing and analyzing module is also used for comprehensively analyzing and processing the data detected by the track parameter detecting module, the track bed compactness detecting module and the track transfer area detecting module, and further counting the track path comprehensive operation safety influence coefficient according to the counted track section steel rail comprehensive operation safety influence coefficient, the track bed compactness operation safety influence coefficient and the track transfer area comprehensive operation safety influence coefficient.
10. The cloud platform for real-time online monitoring, early warning and management of rail transit operation safety based on cloud computing according to claim 1, wherein: the early warning terminal is used for receiving the geographical position corresponding to the obstacle track section, the time period of the obstacle and the comprehensive operation safety influence coefficient corresponding to the track path, sent by the data processing and analyzing module, sending the geographical position corresponding to the obstacle track section, the time period of the obstacle and the comprehensive operation safety influence coefficient corresponding to the track path to the personnel in the track operation management center, and giving early warning.
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