CN111845845A - Urban rail transit safety intelligent detection system based on big data - Google Patents
Urban rail transit safety intelligent detection system based on big data Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61K—AUXILIARY EQUIPMENT SPECIALLY ADAPTED FOR RAILWAYS, NOT OTHERWISE PROVIDED FOR
- B61K9/00—Railway vehicle profile gauges; Detecting or indicating overheating of components; Apparatus on locomotives or cars to indicate bad track sections; General design of track recording vehicles
- B61K9/08—Measuring installations for surveying permanent way
- B61K9/10—Measuring installations for surveying permanent way for detecting cracks in rails or welds thereof
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B17/00—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations
- G01B17/04—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations for measuring the deformation in a solid, e.g. by vibrating string
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/06—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and measuring the absorption
- G01N23/18—Investigating the presence of flaws defects or foreign matter
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The invention discloses an urban rail transit safety intelligent detection system based on big data, which comprises a rail region division module, a radiographic module, a crack analysis processing module, an ultrasonic detection module, a deformation analysis processing module, a parameter database, a modeling analysis module, an analysis server, a mobile trolley, a remote control center and a display terminal, wherein the radiographic module and the ultrasonic detection module are used for detecting cracks and deformation conditions on a rail, analyzing the detected cracks and deformation conditions, and counting comprehensive crack coefficients and comprehensive deformation coefficients of rail transit by combining the modeling analysis module to further obtain a comprehensive rail transit danger evaluation coefficient, thereby realizing the intelligent detection of the rail transit, and the system has the characteristics of high detection accuracy and high reliability, and the obtained comprehensive rail transit danger evaluation coefficient visually displays the danger conditions of the rail transit, the method is convenient for providing reliable reference basis for the management personnel to repair the rail transit.
Description
Technical Field
The invention relates to the technical field of rail transit detection, in particular to an urban rail transit safety intelligent detection system based on big data.
Background
With the rapid development of rail transit in China, the speed of rail transit tools such as trains, motor cars and subways is continuously improved, the quality requirement on rails is higher and higher, the state of the rails is an important factor influencing the traffic safety of the rail transit tools, and the rails are inevitably subjected to potential safety hazards in the day-to-day use process, such as cracks caused by rail cracking and twisting deformation of rail lines, if the rails are not timely repaired, serious traffic accidents can be caused, and great loss is caused to lives and properties of people.
At present, the safety inspection to the track circuit generally adopts the range estimation and the instrument detection mode, it adopts the range estimation to look over whether the track has fracture and the track circuit has the deformation, the detection accuracy is not high, and can only detect the track fracture that the naked eye can see and the track circuit deformation condition, the small fracture that can not see to the naked eye can not be detected with small deformation, but these small hidden dangers if detect out in time, long this accumulation, can also cause the incident, use instrument detection track circuit safety at present simultaneously, can damage the track sometimes in the testing process, influence orbital normal use.
Disclosure of Invention
The technical task of the invention is to provide an urban rail transit safety intelligent detection system which has high detection accuracy, can detect the conditions of rail micro-cracking and rail line micro-deformation and belongs to nondestructive detection based on big data.
In order to achieve the purpose, the invention provides the following technical scheme:
an urban rail transit safety intelligent detection system based on big data comprises a rail area division module, a radiographic module, a crack analysis processing module, an ultrasonic detection module, a deformation analysis processing module, a parameter database, a modeling analysis module, an analysis server, a movable trolley, a remote control center and a display terminal;
the track area dividing module is used for dividing a track to be detected into detection sections, dividing the length section of the track from a starting point to an end point of the track into a plurality of detection sections which are identical in length and are connected with each other according to a preset dividing interval distance, numbering the detection sections according to a sequence from the starting point to the end point, and sequentially marking the detection sections as 1,2, …, i, …, n;
the radiographic module comprises radiographic inspection equipment, wherein in the running process of the moving trolley, a camera inspection instrument on the moving trolley respectively emits rays to the electric rails on the two sides of the track, the emitted rays penetrate through the electric rails on the two sides, the radiographic inspection instrument performs imaging recording through radiographic films to obtain radiographic films of all inspection sections, the obtained radiographic films are placed in a darkroom for processing to obtain radiographic films of all inspection sections of the track, and the radiographic films are sent to the crack analysis processing module;
the parameter database stores crack indexes corresponding to the areas of the cracks, stores preset distance difference thresholds, stores distance difference absolute values corresponding to deformation levels, stores deformation coefficients corresponding to the deformation levels of the rails, and stores rail traffic cracking influence coefficients and rail traffic deformation influence coefficients.
The crack analysis processing module is connected with the radiography module and used for receiving the track radiographic films of all detection sections sent by the radiography module, the crack analysis processing module comprises a blackness meter, the crack analysis processing module divides each received track radiographic film image of each detection section into a plurality of local film images, the blackness meter is used for obtaining the blackness of each local film image and comparing the blackness with each other, if the blackness difference exists, the track of the detection section is shown to have cracks, wherein the position where the blackness difference exists is the position where the cracks appear, the number of the positions where the track radiographic films of the detection sections have the blackness difference is counted, the number of the cracks is the number of the cracks, meanwhile, the local film images to which the cracks belong are focused and amplified, the range of the cracks in the local film images is checked, the area of each crack is counted, and simultaneously, the obtained area of each crack is compared with the crack index corresponding to the preset area of each crack, screening crack indexes corresponding to the crack areas of the detection sections with cracks to form a single crack detection section crack parameter set F (F)λ1,fλ2,...,fλj,...,fλk)，fλj represents a crack index corresponding to the jth crack of the detection section with cracks, so that the detection section number with cracks in the track to be detected and the crack detection section crack parameter set of each crack detection section are counted and sent to the modeling analysis module;
the ultrasonic detection module comprises ultrasonic distance measuring equipment, ultrasonic sensors on the moving trolley respectively and simultaneously transmit ultrasonic waves to electric rails on two sides of a track in the running process of the moving trolley, the ultrasonic sensors start timing at the same time, ultrasonic signals immediately return when contacting the electric rails of the track in the propagation process, the ultrasonic sensors immediately stop timing after receiving the reflected ultrasonic signals, the ultrasonic transmission positions of the moving trolley in each detection section are respectively determined by recording and judging the return time of the ultrasonic signals, and the ultrasonic signals are transmitted to the deformation analysis processing module;
the deformation analysis processing module is connected with the ultrasonic detection module, receives the distance between the ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides sent by the ultrasonic detection module, compares the difference value between the received ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides to obtain the absolute value of the distance difference of each detection section, compares the absolute value of the distance difference of each detection section with a preset distance difference threshold, if the absolute value is within the preset distance difference threshold, the detection section does not have the track deformation, if the absolute value is greater than the preset distance difference threshold, the detection section has the track deformation, counts the number of the track deformation detection section, sends the number to the modeling analysis module, compares the absolute value of the distance difference of each track deformation detection section with the preset distance difference absolute value corresponding to each deformation level, and screens the track deformation level corresponding to the absolute value of the distance difference of each track deformation detection section, and sending to a modeling analysis module;
the modeling analysis module is respectively connected with the crack analysis processing module and the deformation analysis processing module, receives the detection section number with cracks in the to-be-detected track and the crack detection section crack parameter set of each crack detection section, which are sent by the crack analysis processing module, counts the crack coefficient of a single crack detection section according to the received crack detection section crack parameter set of each crack detection section, calculates the track traffic comprehensive crack coefficient according to the received detection section number with cracks and the crack coefficient of each crack detection section, and sends the track traffic comprehensive crack coefficient to the analysis server;
the modeling analysis module receives the track deformation detection section number sent by the deformation analysis processing module and the track deformation detection of each track deformation detection sectionExtracting the deformation coefficient corresponding to each orbit deformation level in the parameter database, screening the deformation coefficient corresponding to each orbit deformation detection segment, and forming the deformation coefficient set xi (xi) of the orbit deformation detection segmentE1,ξE2,...,ξEl,...,ξEm)，ξEl is a deformation coefficient corresponding to the E-th track deformation level of the l-th track deformation detection section, wherein E is 1,2 and 3, and the comprehensive deformation coefficient of the track traffic is calculated and sent to an analysis server;
meanwhile, the modeling analysis module sends the received detection section number with cracks and the received track deformation detection section number to a remote control center;
the remote control center is connected with the modeling analysis module, receives the detection section number with the crack and the track deformation detection section number sent by the modeling analysis module, and dispatches related personnel for processing;
the analysis server is connected with the modeling analysis module, receives the rail transit comprehensive cracking coefficient and the rail transit comprehensive deformation coefficient sent by the modeling analysis module, counts the rail transit comprehensive danger evaluation coefficient, and sends the rail transit comprehensive danger evaluation coefficient to the display terminal;
and the display terminal is connected with the analysis server, receives the rail transit comprehensive danger evaluation coefficient sent by the analysis server and displays the rail transit comprehensive danger evaluation coefficient.
According to one mode of realization of the invention, the mobile trolley is respectively connected with the radiography module and the ultrasonic detection module and runs on the track electric rail in the length section from the starting point to the terminal point of the track at a constant speed, the radiographic inspection equipment comprises a small radiographic inspection instrument and a radiographic film, the small radiographic inspection instrument is arranged at the bottom of the mobile trolley and is used for emitting rays to the electric rails on the two sides of the track, the radiographic film is arranged on the track electric rails and is used for imaging images of the rays penetrating the electric rails, and the ultrasonic distance measurement equipment comprises an ultrasonic sensor which is arranged at the bottom of the mobile trolley and is used for emitting ultrasonic signals to the track electric rails and receiving the reflected ultrasonic signals.
According to the inventionIn another implementation manner, the crack coefficient of the single crack detection section is calculated by the following formula
In the formula fλj represents the crack index corresponding to the jth crack of the detection section with cracks.
According to an implementation mode of the invention, the calculation formula of the rail transit comprehensive cracking coefficient is
In the formula sigmagThe crack coefficient of the g-th crack detection section is expressed, h is the number of the crack detection sections, and n is the total number of the rail transit detection sections.
According to an implementation mode of the invention, the calculation formula of the rail transit comprehensive deformation coefficient is
Xi in the formulaEl is a deformation coefficient corresponding to the E-th track deformation level of the l-th track deformation detection section, E is 1,2,3, h is the number of the deformation detection sections, and n is the total number of the track traffic detection sections.
According to an implementation mode of the invention, the calculation formula of the rail transit comprehensive risk assessment coefficient is
Eta is expressed as a comprehensive rail transit cracking coefficient, chi is expressed as a comprehensive rail transit deformation coefficient, alpha is expressed as a rail transit cracking influence coefficient, and beta is expressed as a rail transit deformation influence coefficient.
According to an implementation mode of the invention, the system further comprises a positioning and marking module which is respectively connected with the crack analysis processing module and the deformation analysis processing module, wherein the positioning and marking module comprises a GPS positioning instrument for positioning and marking the specific position of the track crack, counted by the crack analysis processing module, and also positioning and marking the specific position of the track deformation, counted by the deformation analysis processing module, and sending the positioned position information to the remote control center, and the remote control center receives the specific position information of the track crack and the specific position of the track deformation, sent by the positioning and marking module, and dispatches related personnel for processing.
Has the advantages that:
(1) the rail transit comprehensive danger assessment system detects the cracks and deformation conditions on the rail transit through the radiographic module and the ultrasonic detection module, analyzes the detected rail transit cracks and deformation parameters through the crack analysis processing module and the deformation analysis processing module, and counts the rail transit comprehensive cracking coefficient and the rail transit comprehensive deformation coefficient by combining the modeling analysis module so as to obtain the rail transit comprehensive danger assessment coefficient.
(2) The rail traffic crack and deformation detection method has the advantages that the nondestructive detection is carried out on the crack and deformation conditions of the rail traffic by using the ray inspection equipment and the ultrasonic ranging equipment, the detection method is nondestructive, the nondestructive detection is nondestructive, the rail is not damaged in the detection process, the normal use of the rail is ensured, the micro crack and micro deformation conditions of the rail traffic can be detected, and the detection precision is high.
(3) According to the track repairing method, the detection section of the track to be detected is divided, the detection section number with cracks and the track deformation detection section number counted by the modeling analysis module are combined to provide rough positioning of the position of the track to be repaired for relevant personnel, meanwhile, the specific position of the track detection section with cracks and the specific position of the track detection section with deformation are marked by the positioning marking module, fine positioning of the position of the track to be repaired is provided for the relevant personnel, double positioning is achieved, the relevant personnel can find the track conveniently, the searching time is saved, and the track repairing progress is 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 block diagram of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the urban rail transit safety intelligent detection system based on big data comprises a rail area division module, a radiographic module, a crack analysis processing module, an ultrasonic detection module, a deformation analysis processing module, a parameter database, a modeling analysis module, a mobile trolley, an analysis server, a remote control center, a display terminal and a positioning mark module.
The track area dividing module is used for dividing the detection section of the track to be detected, recording the length section of the track from the starting point to the end point of the track as s, dividing the track according to a preset division interval distance, recording the interval distance as d, dividing the track to be detected into a plurality of detection sections which have the same length and are mutually connected, recording the number of the divided detection sections as n,
the detection segments are numbered in order from the start point to the end point, and are labeled 1,2, …, i, …, n.
In the preferred embodiment, the smaller the preset division spacing distance is, the better the division distance is, the finer the division is, the more the detection sections are divided, and more accurate detection section numbers are provided for the subsequent track repair.
The moving trolley is respectively connected with the radiography module and the ultrasonic detection module and runs on the track electric track in the length section from the starting point to the end point of the track at a constant speed.
Radiographic module, including radiographic inspection equipment, radiographic inspection equipment includes small-size type radiographic inspection appearance and ray film, small-size radiographic inspection appearance is installed in the travelling car bottom, and it is used for launching ray to track both sides electric rail, ray film installs on track electric rail, and it is used for passing through the image of electric rail to the ray and visualizes, and the travelling car is at the driving process, and the flaw detector of making a video recording on the travelling car is respectively to track both sides electric rail transmission ray, and the ray of its transmission pierces through both sides electric rail, gives the development record through ray film, obtains each detection section radiographic film to put the radiographic film that obtains into the darkroom and handle and obtain each detection section track radiographic film, and send to crack analysis processing module.
The preferred embodiment is based on the principle of radiographic inspection, the radiation can penetrate the substances which can not be penetrated by naked eyes to make the film photosensitive, i.e. when the ray beam with uniform intensity is penetrated and irradiated on the track electric rail, the silver halide in the film emulsion layer can generate latent image, if the local area of the track electric rail has defects or structure difference, it will change the attenuation of the object to the radiation, so that the transmitted radiation intensity of different parts is different, the radiation intensity irradiated on each part of the film will also generate difference, the defects can be distinguished according to the blackness difference of each part of the film after darkroom processing, the crack condition on the track electric rail can be detected in such a way, the qualitative is more accurate, and the displayed film can be stored for a long time.
Meanwhile, the radiographic inspection equipment of the embodiment further comprises intensifying screens attached to the front side and the rear side of the radiographic film and used for radiography together with the radiographic film, most rays penetrate through the radiographic film due to the strong penetrating power of the rays, the radiographic film only absorbs little energy of incident rays, and the intensifying screens can absorb partial ray energy to achieve the purpose of shortening exposure time.
And the parameter database stores crack indexes corresponding to the areas of the cracks, stores a preset distance difference threshold value, stores distance difference absolute values corresponding to deformation levels, stores deformation coefficients corresponding to the deformation levels of the rails, and stores rail traffic cracking influence coefficients and rail traffic deformation influence coefficients.
The crack analysis processing module is connected with the radiographic module and used for receiving the rail radiographic films of all detection sections sent by the radiographic module, the crack analysis processing module comprises a blackness meter, the crack analysis processing module divides each received rail radiographic film image of each detection section into a plurality of local film images, the blackness meter is used for obtaining the blackness of each local film image and comparing the blackness with each other, if the blackness difference exists, the rail of the detection section is shown to have cracks, wherein the position where the blackness difference exists is the position where the cracks appear, the number of the positions where the rail radiographic films of the detection sections have the blackness difference is counted, the number of the cracks is the number of the cracks, meanwhile, the local film images to which the cracks belong are focused and amplified, the range of the cracks in the local film images is checked, the area of each crack is counted, and simultaneously, the obtained area of each crack is compared with the crack index corresponding to the preset area of each crack, screening crack indexes corresponding to the crack areas of the detection sections with cracks to form a single crack detection section crack parameter set F (F)λ1,fλ2,...,fλj,...,fλk)，fλj is expressed as a crack index corresponding to the jth crack of the detection section with cracks, so that the detection section number with cracks in the track to be detected and the crack detection section crack parameter set of each crack detection section are counted and sent to the modeling analysis module.
The ultrasonic detection module comprises ultrasonic ranging equipment, the ultrasonic ranging equipment comprises an ultrasonic sensor, the ultrasonic sensor is installed at the bottom of the movable trolley and used for transmitting ultrasonic signals to the rail electric rail and receiving the reflected ultrasonic signals. During the running process of the movable trolley, ultrasonic waves are respectively and simultaneously emitted to the electric rails on the two sides of the track by the ultrasonic sensors on the movable trolley, the ultrasonic sensors start timing at the same time of emitting time, ultrasonic signals immediately return when encountering the electric rails on the track in the propagation process, the ultrasonic sensors immediately stop timing after receiving the reflected ultrasonic signals, the time for returning the ultrasonic signals is recorded and judged, the distances between the ultrasonic emitting positions of the movable trolley on each detection section and the electric rails on the two sides are determined, and the ultrasonic emitting positions are sent to the deformation analysis processing module.
In the preferred embodiment, the nondestructive detection is performed on the cracks and deformation conditions of the rail transit by using the ray inspection equipment and the ultrasonic ranging equipment, the adopted detection method is nondestructive detection, the nondestructive detection is nondestructive, the rail is not damaged in the detection process, the normal use of the rail is ensured, the micro-cracking and micro-deformation conditions of the rail transit can be detected, and the detection precision is high.
The deformation analysis processing module is connected with the ultrasonic detection module, receives the distance between the ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides sent by the ultrasonic detection module, compares the difference value between the ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides to obtain the absolute value of the distance difference of each detection section, compares the absolute value of the distance difference of each detection section with a preset distance difference threshold, if the absolute value is within the preset distance difference threshold, the detection section does not have the track deformation, if the absolute value is greater than the preset distance difference threshold, the detection section has the track deformation, counts the number of the track deformation detection section, sends the number to the modeling analysis module, compares the absolute value of the distance difference of each track deformation detection section with the distance difference absolute value corresponding to each preset deformation level, and screens the track deformation level corresponding to the absolute value of the distance difference of each track deformation detection section, and sent to the modeling analysis module.
The modeling analysis module is respectively connected with the crack analysis processing module and the deformation analysis processing module, receives the detection section number of the crack in the track to be detected sent by the crack analysis processing module and the crack detection section crack parameter set of each crack detection section, and counts the crack coefficient of the single crack detection section according to the received crack detection section crack parameter set of each crack detection section
In the formula fλj represents the memoryCalculating the comprehensive crack coefficient of the rail transit according to the crack index corresponding to the jth crack in the crack detection section and the received crack detection section number with cracks and the crack coefficient of each crack detection section
In the formula sigmagThe comprehensive crack coefficient is expressed as the crack coefficient of the g-th crack detection section, h is expressed as the number of the crack detection sections, d is expressed as the preset division interval distance, s is expressed as the length of the track to be detected, the larger the comprehensive crack coefficient is, the more the positions of the track with cracks are shown, the higher the crack degree is, and the modeling analysis module sends the calculated comprehensive crack coefficient of the track traffic to the analysis server.
The modeling analysis module receives the track deformation detection segment number sent by the deformation analysis processing module and the track deformation grade corresponding to the absolute value of the distance difference of each track deformation detection segment, extracts the deformation coefficient corresponding to each track deformation grade in the parameter database, screens the deformation coefficient corresponding to each track deformation detection segment, and forms a track deformation detection segment deformation coefficient set xi (xi)E1,ξE2,...,ξEl,...,ξEm)，ξEl is the deformation coefficient corresponding to the E-th track deformation level of the l-th track deformation detection section, E is 1,2 and 3, and the comprehensive deformation coefficient of the track traffic is calculated
Xi in the formulaEl represents the deformation coefficient corresponding to the E-th track deformation level of the l-th track deformation detection section, E is 1,2 and 3, h represents the number of the deformation detection sections, d represents the preset division spacing distance, s represents the track length to be detected, the larger the comprehensive deformation coefficient is, the higher the track deformation degree is, and the modeling analysis module sends the statistical comprehensive deformation coefficient of the track traffic to the analysis server.
Meanwhile, the modeling analysis module sends the received detection section number with the crack and the track deformation detection section number to a remote control center.
And the positioning and marking module is respectively connected with the crack analysis processing module and the deformation analysis processing module, comprises a GPS positioning instrument, positions and marks the specific position of the crack, which is counted by the crack analysis processing module and has the rail deformation, positions and marks the specific position, which is counted by the deformation analysis processing module and has the rail deformation, and sends the positioned position information to the remote control center.
The remote control center is respectively connected with the modeling analysis module and the positioning marking module, receives the detection section number with cracks and the track deformation detection section number sent by the modeling analysis module, and simultaneously receives the specific position information of the track cracks and the specific position of the track deformation sent by the positioning marking module, and dispatches related personnel for processing.
In this preferred embodiment, the detection section serial number and the track deformation detection section serial number that have crackle through the statistics of modeling analysis module provide the coarse positioning that needs to repair the track position for relevant personnel, simultaneously through the track detection section specific position that the location mark module mark has crackle and the track detection section specific position that has deformation, provide the meticulous location that needs to repair the track position for relevant personnel, the setting of dual location, make things convenient for relevant personnel to find fast, the seek time is saved, orbital repair progress has been improved.
The analysis server is connected with the modeling analysis module, receives the rail transit comprehensive cracking coefficient and the rail transit comprehensive deformation coefficient sent by the modeling analysis module, and counts the rail transit comprehensive danger evaluation coefficient
Eta is expressed as a rail transit comprehensive cracking coefficient, chi is expressed as a rail transit comprehensive deformation coefficient, alpha is expressed as a rail transit cracking influence coefficient, beta is expressed as a rail transit deformation influence coefficient, the larger the rail transit comprehensive danger evaluation coefficient is, the larger the rail transit danger is, and the analysis server sends the statistical rail transit comprehensive danger evaluation coefficient to the display terminal.
The display terminal is connected with the analysis server, receives the rail transit comprehensive danger evaluation coefficient sent by the analysis server, and displays the rail transit comprehensive danger evaluation coefficient, so that related personnel can conveniently and visually know the comprehensive danger condition of the rail.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (7)
1. The utility model provides an urban rail transit safety intellectual detection system based on big data which characterized in that: the system comprises a track area division module, a radiographic module, a crack analysis processing module, an ultrasonic detection module, a deformation analysis processing module, a parameter database, a modeling analysis module, an analysis server, a mobile trolley, a remote control center and a display terminal;
the track area dividing module is used for dividing a track to be detected into detection sections, dividing the length section of the track from a starting point to an end point of the track into a plurality of detection sections which are identical in length and are connected with each other according to a preset dividing interval distance, numbering the detection sections according to a sequence from the starting point to the end point, and sequentially marking the detection sections as 1,2, …, i, …, n;
the radiographic module comprises radiographic inspection equipment, wherein in the running process of the moving trolley, a camera inspection instrument on the moving trolley respectively emits rays to the electric rails on the two sides of the track, the emitted rays penetrate through the electric rails on the two sides, the radiographic inspection instrument performs imaging recording through radiographic films to obtain radiographic films of all inspection sections, the obtained radiographic films are placed in a darkroom for processing to obtain radiographic films of all inspection sections of the track, and the radiographic films are sent to the crack analysis processing module;
the parameter database stores crack indexes corresponding to the areas of the cracks, stores preset distance difference thresholds, stores distance difference absolute values corresponding to deformation levels, stores deformation coefficients corresponding to the deformation levels of the rails, and stores rail traffic cracking influence coefficients and rail traffic deformation influence coefficients;
the crack analysis treatmentThe module is connected with the radiographic module and used for receiving the radiographic film of each detection section track sent by the radiographic module, the crack analysis processing module comprises a blackness meter, the crack analysis processing module divides each received detection section track radiographic film image into a plurality of local film images, the blackness meter is used for obtaining the blackness of each local film image and comparing the blackness with each other, if the blackness difference exists, the detection section track is shown to have cracks, the position where the blackness difference exists is the position where the cracks appear, the number of the positions where the blackness difference exists of the detection section track radiographic film is counted, namely the number of the cracks, the local film images to which the cracks belong are focused and amplified, the range of the cracks in the local film images is checked, the area of each crack is counted, and the area of each obtained crack is compared with the crack index corresponding to the preset area of each crack, screening crack indexes corresponding to the crack areas of the detection sections with cracks to form a single crack detection section crack parameter set F (F)λ1,fλ2,...,fλj,...,fλk)，fλj represents a crack index corresponding to the jth crack of the detection section with cracks, so that the detection section number with cracks in the track to be detected and the crack detection section crack parameter set of each crack detection section are counted and sent to the modeling analysis module;
the ultrasonic detection module comprises ultrasonic distance measuring equipment, ultrasonic sensors on the moving trolley respectively and simultaneously transmit ultrasonic waves to electric rails on two sides of a track in the running process of the moving trolley, the ultrasonic sensors start timing at the same time, ultrasonic signals immediately return when contacting the electric rails of the track in the propagation process, the ultrasonic sensors immediately stop timing after receiving the reflected ultrasonic signals, the ultrasonic transmission positions of the moving trolley in each detection section are respectively determined by recording and judging the return time of the ultrasonic signals, and the ultrasonic signals are transmitted to the deformation analysis processing module;
the deformation analysis processing module is connected with the ultrasonic detection module, receives the distance between the ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides sent by the ultrasonic detection module, compares the difference value between the received ultrasonic emission position of the mobile trolley of each detection section and the electric rails on two sides to obtain the absolute value of the distance difference of each detection section, compares the absolute value of the distance difference of each detection section with a preset distance difference threshold, if the absolute value is within the preset distance difference threshold, the detection section does not have the track deformation, if the absolute value is greater than the preset distance difference threshold, the detection section has the track deformation, counts the number of the track deformation detection section, sends the number to the modeling analysis module, compares the absolute value of the distance difference of each track deformation detection section with the preset distance difference absolute value corresponding to each deformation level, and screens the track deformation level corresponding to the absolute value of the distance difference of each track deformation detection section, and sending to a modeling analysis module;
the modeling analysis module is respectively connected with the crack analysis processing module and the deformation analysis processing module, receives the detection section number with cracks in the to-be-detected track and the crack detection section crack parameter set of each crack detection section, which are sent by the crack analysis processing module, counts the crack coefficient of a single crack detection section according to the received crack detection section crack parameter set of each crack detection section, calculates the track traffic comprehensive crack coefficient according to the received detection section number with cracks and the crack coefficient of each crack detection section, and sends the track traffic comprehensive crack coefficient to the analysis server;
the modeling analysis module receives the track deformation detection segment number sent by the deformation analysis processing module and the track deformation grade corresponding to the absolute value of the distance difference of each track deformation detection segment, extracts the deformation coefficient corresponding to each track deformation grade in the parameter database, screens the deformation coefficient corresponding to each track deformation detection segment, and forms a track deformation detection segment deformation coefficient set xi (xi)E1,ξE2,...,ξEl,...,ξEm)，ξEl is a deformation coefficient corresponding to the E-th track deformation grade of the l-th track deformation detection section, E is 1,2 and 3, a track traffic comprehensive deformation coefficient is calculated, and the modeling analysis module sends the calculated track traffic comprehensive deformation coefficient to an analysis server;
meanwhile, the modeling analysis module sends the received detection section number with cracks and the received track deformation detection section number to a remote control center;
the remote control center is connected with the modeling analysis module, receives the detection section number with the crack and the track deformation detection section number sent by the modeling analysis module, and dispatches related personnel for processing;
the analysis server is connected with the modeling analysis module, receives the rail transit comprehensive cracking coefficient and the rail transit comprehensive deformation coefficient sent by the modeling analysis module, counts the rail transit comprehensive danger evaluation coefficient, and sends the rail transit comprehensive danger evaluation coefficient to the display terminal;
and the display terminal is connected with the analysis server, receives the rail transit comprehensive danger evaluation coefficient sent by the analysis server and displays the rail transit comprehensive danger evaluation coefficient.
2. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the utility model discloses a rail track, including the rail track, the travelling car is installed in the travelling car bottom, the travelling car is connected with radiography module and ultrasonic detection module respectively, at the uniform velocity on the track electric rail from the track starting point to this length section of terminal point, radiographic inspection equipment includes small-size radiographic inspection appearance and ray film, small-size radiographic inspection appearance is installed in the travelling car bottom, and it is used for the track both sides electric rail transmission ray, the ray film is installed on the track electric rail, and it is used for penetrating through the image of electric rail to the ray and visualizes, ultrasonic ranging equipment includes ultrasonic sensor, ultrasonic sensor installs in the travelling car bottom, and it is used for transmitting ultrasonic signal and the ultrasonic signal of receiving the reflection back to the track electric rail.
3. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the calculation formula of the single crack detection section cracking coefficient is
In the formula fλj represents the crack index corresponding to the jth crack of the detection section with cracks.
4. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the calculation formula of the comprehensive cracking coefficient of the rail transit is
In the formula sigmagThe crack coefficient of the g-th crack detection section is expressed, h is the number of the crack detection sections, and n is the total number of the rail transit detection sections.
5. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the calculation formula of the comprehensive deformation coefficient of the rail transit is
Xi in the formulaEl is a deformation coefficient corresponding to the E-th track deformation level of the l-th track deformation detection section, E is 1,2,3, h is the number of the deformation detection sections, and n is the total number of the track traffic detection sections.
6. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the calculation formula of the rail transit comprehensive risk assessment coefficient is
Eta is expressed as a comprehensive rail transit cracking coefficient, chi is expressed as a comprehensive rail transit deformation coefficient, alpha is expressed as a rail transit cracking influence coefficient, and beta is expressed as a rail transit deformation influence coefficient.
7. The urban rail transit safety intelligent detection system based on big data according to claim 1, characterized in that: the positioning and marking module comprises a GPS positioning instrument, the specific position of the rail crack, counted by the crack analysis processing module, is positioned and marked, the specific position of the rail crack, counted by the deformation analysis processing module, is also positioned and marked, the position information of the position is sent to the remote control center, the remote control center receives the specific position information of the rail crack and the specific position of the rail deformation, sent by the positioning and marking module, and relevant personnel are dispatched to process the information.
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