CN115056821A - Big data-based rail transit early warning system - Google Patents
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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 vehicle trains
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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 vehicle trains
- B61L23/04—Control, warning, or like safety means along the route or between vehicles or vehicle 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
- B61L25/00—Recording or indicating positions or identities of vehicles or vehicle trains or setting of track apparatus
- B61L25/02—Indicating or recording positions or identities of vehicles or vehicle trains
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/04—Automatic systems, e.g. controlled by train; Change-over to manual control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/20—Trackside control of safe travel of vehicle or vehicle train, e.g. braking curve calculation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention discloses a big data-based rail transit early warning system, which belongs to the technical field of rail transit and comprises a server, a derailment early warning module, a safety early warning module, a fault early warning module, a passenger flow early warning module, an alarm module and a data storage module; the derailment early warning module is used for preventing derailment of the rail vehicle, and specifically, the derailment of the rail vehicle is prevented by establishing a rail model, acquiring position information of the rail vehicle in real time, inputting the acquired position information of the rail vehicle into the rail model, irradiating the position of a passenger in a safety line by controlling light, and sending dissuading voice, so that the passenger is ensured to exit the safety line, the situation that the dissuading effect of the voice is not obvious, and the passenger does not hear or is not the passenger is avoided, and the safety of the rail vehicle entering the station is ensured; the fault early warning module is used for early warning the fault of the rail vehicle, so that the rail vehicle is prevented from being out of order in the running process and the running of the rail vehicle is not influenced.
Description
Technical Field
The invention belongs to the technical field of rail transit; in particular to a track traffic early warning system based on big data.
Background
Rail transit refers to a type of vehicle or transportation system in which operating vehicles need to travel on a particular rail. The most typical rail transit is a railway system consisting of conventional trains and standard railways. With the diversified development of train and railway technologies, rail transit is more and more types, and is not only distributed in long-distance land transportation, but also widely applied to medium-short distance urban public transportation. The common rail transit comprises a traditional railway, a subway, a light rail and a tramcar, and the novel rail transit comprises a magnetic suspension rail system, a monorail system, a passenger automatic rapid transit system and the like. However, accidents occur frequently in rail transit nowadays, and a great number of potential safety hazards exist, so that early warning is urgently needed to be carried out on rail transit problems.
The patent with publication number CN101695926B discloses an intelligent rail transit safety early warning system with good directivity and adjustable identification distance. The method comprises the following steps: the signal processing module is used for processing signals sent or received by the intelligent rail transit safety early warning system and comprises a processor, software is embedded into the processor, the effectiveness of the read identification card can be intelligently identified, and the influence of invalid cards and unstable card induction distance on the system is eliminated; the antenna module is used for receiving or transmitting wireless signals; the signal adjusting module is respectively connected with the signal processing module and the antenna module and is used for adjusting the power of the exchange signals between the signal processing module and the antenna module; and the shielding shell is made of a material for shielding an electromagnetic field and is provided with a directional signal opening, and the antenna module is packaged in the shielding shell and is arranged opposite to the signal opening.
However, the above patent only solves some of the rail traffic problems one-sidedly, and there are many aspects of rail traffic problems that are not solved, such as: derailment, passenger flow, platform personnel safety, and vehicle failure.
Disclosure of Invention
The invention aims to provide a track traffic early warning system based on big data, and the track traffic early warning system based on big data solves the problems in track traffic.
The purpose of the invention can be realized by the following technical scheme:
a rail transit early warning system based on big data comprises a server, a derailment early warning module, a safety early warning module, a fault early warning module, a passenger flow early warning module, an alarm module and a data storage module; the derailment early warning module is used for preventing derailment of a railway vehicle, and specifically the method for preventing derailment of the railway vehicle comprises the steps of establishing a railway model, obtaining position information of the railway vehicle in real time, inputting the obtained real-time position information of the railway vehicle into the railway model, arranging a scanning unit and a camera unit at the front end of the railway vehicle, scanning the front of the railway vehicle by the scanning unit in real time in the running process of the railway vehicle, obtaining the position of an obstacle according to the speed of scanning light, the speed of the railway vehicle and the angle of the scanning light when the obstacle is scanned, inputting the position of the obstacle into a mathematical model, not operating when the position of the obstacle is not in the range of the railway, generating an obstacle early warning signal when the position of the obstacle is in the range of the railway, sending the obstacle early warning signal to a server, and sending a shooting instruction and the position of the obstacle to the camera unit by the server, the camera shooting unit shoots pictures at the received positions of the obstacles, the shot pictures are sent to the server, the server generates an alarm signal, the pictures, the alarm signal and the positions of the obstacles are sent to the alarm module, and the alarm module gives out alarm sound and displays the pictures and the positions of the obstacles.
Further, the track model building method specifically comprises the steps of obtaining track route information, wherein the track route information comprises track positions, track ranges and route names, building a mathematical model, inputting the track route information into the mathematical model, obtaining historical position information of the rail vehicles, selecting historical position information of a plurality of groups of rail vehicles, inputting the historical position information into the mathematical model, and matching the driving route names of the rail vehicles with the route names in the track route information; and the position of the rail vehicle is brought into the matched rail route information, historical position information of a plurality of groups of unused rail vehicles is extracted and input into the mathematical model to verify the correctness of the mathematical model, and the mathematical model which is verified to be correct is marked as the rail model.
Further, the safety early warning module is used for early warning passengers on a platform before a railway vehicle enters a station, and the specific method comprises the steps of setting a warning safety line and a dissuading unit, detecting the condition of the passengers in the warning safety line N minutes before the railway vehicle enters the station, acquiring the positions of the passengers in the safety line when the passengers exist in the safety line, generating dissuading signals, sending the dissuading signals and the positions of the passengers in the safety line to the server, sending the dissuading signals and the positions of the passengers in the safety line to the dissuading unit by the server, controlling the positions of the passengers in the safety line by lamplight through the dissuading unit, sending dissuading voices, and dissuading the passengers in the safety line.
Further, the fault early warning module is used for early warning the faults of the rail vehicles, and the specific method comprises the steps of acquiring detection data of the rail vehicles, the running time of the rail vehicles and the running environment of the rail vehicles in real time, integrating and marking as input data; and acquiring a prediction model, inputting input data into the prediction model to acquire an output result, and marking the output result as a prediction tag, wherein the prediction tag is a state tag corresponding to the input data, when the state tag fails, the prediction tag is sent to a server, and when the state tag does not fail, the operation is not carried out.
Further, the passenger flow early warning module is used for early warning the number of passengers in the rail transit station, the specific method is that a plurality of chip areas are divided in the rail transit station, the passenger warning density is set, the passenger warning density comprises primary warning density and secondary warning density, the passenger density in each chip area and the passenger density in the station are obtained in real time, when the passenger density in each chip area does not exceed the primary warning density, the corresponding chip area is marked as an unfilled chip area, when the passenger density in each chip area exceeds the primary warning density, a shunting signal is generated and sent to the server, the server sends the shunting signal, the position of the overdue chip area and the position of the unfilled chip area nearest to the overdue chip area to managers in the station, the managers shunt the passengers in the corresponding chip areas, and the excessive passengers are shunted to the unfilled chip area nearest to the overfilled chip area, and when the passenger density in the station exceeds the secondary warning density, generating an access limiting signal, sending the access limiting signal to a server, acquiring the rail vehicle information X minutes before departure, and sending the rail vehicle information X minutes before departure to a station entrance for display.
The invention has the beneficial effects that: by arranging the derailment early warning module, scanning is carried out in real time in the front of the rail vehicle in the running process of the rail vehicle, when an obstacle is scanned, the position of the obstacle is input into the mathematical model, when the position of the obstacle is in the range of the rail, an obstacle early warning signal is generated, a rail vehicle driver is helped to find the obstacle in time, precious reaction time is obtained, safety accidents are avoided, the obstacle early warning signal is sent to the server, the server sends a shooting instruction and the position of the obstacle to the camera unit, the camera unit shoots a picture of the received obstacle position, the rail vehicle driver is further helped to know what obstacle is, meanwhile, the driver is also given the opportunity of judging whether the obstacle affects the running of the rail vehicle, the early warning accuracy is ensured, and unnecessary trouble is avoided for the driver due to inaccurate early warning, the risk is reduced;
the method comprises the steps that passengers on a platform are warned before a railway vehicle enters the station through a safety warning module, when passengers exist in a safety line, the positions of the passengers in the safety line are obtained, an dissuading signal is generated, the dissuading signal and the positions of the passengers in the safety line are sent to a server, the server sends the dissuading signal and the positions of the passengers in the safety line to a dissuading unit, the dissuading unit controls light to irradiate the positions of the passengers in the safety line, dissuading voice is sent out, the passengers in the safety line are dissuaded, the dissuading voice is emitted to the positions of the passengers in the safety line through the control light, the passengers are guaranteed to exit the safety line, the situation that the voice dissuading effect is not obvious is avoided, and the passengers can not hear or say that the passengers are not the passengers, and the safety of the railway vehicle entering the station is guaranteed; the fault early warning module is used for early warning the fault of the rail vehicle, so that the rail vehicle is prevented from being in fault in the running process, and the running of the rail vehicle is not influenced;
the passenger quantity in the rail transit station is pre-warned through the passenger flow pre-warning module, the passenger density in each parcel and the passenger density in the station are obtained in real time, when the passenger density in each parcel exceeds a primary warning density, a shunting signal is generated, each parcel is conveniently managed through dividing the parcel, and meanwhile, the parcels with high passenger density are shunted, so that the safety problem and the probability of disease transmission and infection are reduced; when the passenger density in the station exceeds the second-level warning density, a limit signal is generated and sent to the server, the server acquires the rail vehicle information in X minutes before departure, and the rail vehicle information in X minutes before departure is sent to a station entrance for display, so that the rail vehicle can enter the station only when riding the rail vehicle information displayed on the server, the flow of personnel entering the station is limited, and the safety accident caused by too much personnel is avoided.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.
As shown in fig. 1, a big data-based rail transit early warning system includes a server, a derailment early warning module, a safety early warning module, a fault early warning module, a passenger flow early warning module, an alarm module, and a data storage module;
the derailment early warning module is used for preventing the derailment of the rail vehicle, and specifically the method for preventing the derailment of the rail vehicle comprises the steps of establishing a rail model, obtaining position information of the rail vehicle in real time, wherein the position information of the rail vehicle comprises a running route name of the rail vehicle, position location of the rail vehicle and speed of the rail vehicle, inputting the obtained real-time position information of the rail vehicle into the rail model, arranging a scanning unit and a camera shooting unit at the front end of the rail vehicle, wherein the scanning unit is used for scanning the front of the rail vehicle in real time and measuring positions of possible obstacles on the rail vehicle, the scanning unit can use laser scanning, the camera shooting unit is used for shooting when receiving an instruction, the scanning unit scans the front of the rail vehicle in real time in the running process of the rail vehicle, and when the obstacles are scanned, the position information of the rail vehicle is obtained according to the speed of scanning light, the speed of the rail vehicle, Scanning the angle of light to obtain the position of an obstacle, inputting the position of the obstacle into a mathematical model, when the position of the obstacle is not in the range of a track, not operating, when the position of the obstacle is in the range of the track, generating an obstacle early warning signal, sending the obstacle early warning signal to a server, sending a shooting instruction and the position of the obstacle to a camera unit by the server, shooting a picture of the received position of the obstacle by the camera unit, sending the shot picture to the server, generating an alarm signal by the server, sending the picture, the alarm signal and the position of the obstacle to an alarm module, and sending an alarm sound by the alarm module and displaying the picture and the position of the obstacle;
further, another method for preventing the derailment of the rail vehicle by the derailment early warning module is to obtain rail line information, wherein the rail line information comprises what part in a line is a safe section and what part is a dangerous section, the judgment standards of the safe section and the dangerous section are the radian of the rail line, the angle of a turning and the number of accidents, and the maximum running speeds of the rail vehicle in different dangerous sections are set according to the discussion and setting of an expert group according to rail traffic safety standards;
further, the method for establishing the track model specifically comprises the steps of obtaining track route information, wherein the track route information comprises track positions, track ranges and route names, the track ranges are ranges used when the track vehicles run on the track, the track vehicles cannot collide with sundries in the ranges, establishing a mathematical model, inputting the track route information into the mathematical model, obtaining historical position information of the track vehicles, the historical position information of the track vehicles comprises the running route names of the track vehicles, the track vehicle position positioning and the track vehicle speed, selecting a plurality of groups of historical position information of the track vehicles to input into the mathematical model, and matching the running route names of the track vehicles with the route names in the track route information; the method comprises the steps of bringing the position of the rail vehicle into matched rail route information, obtaining the position of the rail vehicle in a rail route, extracting historical position information of a plurality of groups of rail vehicles which are not used, inputting the historical position information into a mathematical model for verifying the correctness of the mathematical model, and marking the mathematical model which is verified to be correct as a rail model;
the safety early warning module is used for early warning passengers on a platform before a railway vehicle enters the station, and the specific method is that a warning safety line and a dissuading unit are arranged, the warning safety line can use the position of the safety line on the platform to obtain the condition that the railway vehicle detects the passengers in the warning safety line N minutes before the railway vehicle enters the station, N is a proportionality coefficient and is more than or equal to 3 and less than or equal to 10, when no passenger exists in the safety line, the safety line is not operated, when the passenger exists in the safety line, the position of the passenger in the safety line is obtained to generate a dissuading signal, the dissuading signal and the position of the passenger in the safety line are sent to a server, the server sends the dissuading signal and the position of the passenger in the safety line to the dissuading unit, the dissuading unit is used for dissuading the passenger in the safety line according to the server signal and the position information, the dissuading unit controls the position of the passenger in the safety line to be irradiated by light, and sends dissuading voice, passengers in the safety line are persuaded, and the preferred persuaded unit can not only control light, but also use laser to inform the passengers of managers and display on a screen;
the fault early warning module is used for early warning the fault of the rail vehicle, and the specific method comprises the steps of acquiring detection data of the rail vehicle, the running time of the rail vehicle and the running environment of the rail vehicle in real time, integrating and marking as input data; the method comprises the steps that a rail vehicle runs in any environment, weather and temperature, detection data of the rail vehicle are data of daily detection of the rail vehicle, a prediction model is obtained, input data are input into the prediction model, an output result is obtained and marked as a prediction label, the prediction label is a state label corresponding to the input data, when the state label is in failure, the prediction label is sent to a server, and when the state label is not in failure, operation is not carried out;
further, the specific acquisition method of the prediction model comprises the following steps:
step S11: acquiring historical data of the rail vehicle through a data storage module, wherein the historical data of the rail vehicle comprises detection data of D minutes before the rail vehicle breaks down, the running time of the rail vehicle and the running environment of the rail vehicle; wherein D is a proportionality coefficient and is more than or equal to 5;
step S12: setting status labels for the historical data of the rail vehicle, wherein the status labels comprise fault and non-fault;
step S13: constructing an artificial intelligence model; the artificial intelligence model comprises an error reverse propagation neural network, an RBF neural network and a deep convolution neural network, historical data of the rail vehicle and corresponding state labels are divided into a training set, a test set and a check set according to a set proportion, and the set proportion comprises 2: 1: 1. 3: 2: 1 and 3: 1: 1;
step S14: training, testing and checking the artificial intelligence model through a training set, a testing set and a checking set, and marking the trained artificial intelligence model as a prediction model;
the passenger flow early warning module is used for early warning the number of passengers in a rail transit station, and the specific method is that a plurality of chip areas are divided in the rail transit station, passenger warning density is set, the passenger warning density is discussed and set by an expert group according to station safety management specifications, disease environment, weather, temperature and seasons, the passenger warning density comprises primary warning density and secondary warning density, the primary warning density is used for passenger density warning in the chip areas, the secondary warning density is used for whole passenger density warning in the station, the passenger density in each chip area and the passenger density in the station are obtained in real time, when the passenger density in the chip areas does not exceed the primary warning density, the corresponding chip areas are marked as unfilled chip areas, when the passenger density in the chip areas exceeds the primary warning density, a shunting signal is generated and sent to a server, and the server sends the shunting signal to the server, The positions of the over-warning sheet areas and the positions of the under-warning sheet areas closest to the over-warning sheet areas are sent to managers in a station, the managers shunt passengers in the corresponding sheet areas, and shunt the excessive passengers to the under-warning sheet areas closest to the over-warning sheet areas, preferably, the under-warning sheet areas closest to the over-warning sheet areas can be further analyzed, the under-warning sheet areas which can completely meet the over-standard passenger density in the over-warning sheet areas are selected according to the over-standard passenger density in the over-warning sheet areas and the passenger density which can be increased in the under-warning sheet areas, and preferably, the passengers who do not take a bus in the sheet areas are preferentially shunted during shunting; when the passenger density in the station exceeds the secondary warning density, an access limiting signal is generated, the access limiting signal is sent to a server, the server obtains rail vehicle information in X minutes before the departure, the rail vehicle information is the name of the rail vehicle which departs in X minutes, X is a proportionality coefficient, D is larger than or equal to 30, the rail vehicle information in X minutes before the departure is sent to a station entrance for display, the rail vehicle information shows that only the rail vehicle which is displayed on the rail vehicle entrance can enter the station, further, the rail vehicle information in X minutes before the departure is sent to an entrance guard system at the station entrance, and passengers who do not take the rail vehicle in X minutes before the departure do not let the rail vehicle enter the station.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
When the invention is used, the derailment of the rail vehicle is prevented through the derailment early warning module, the position information of the rail vehicle is acquired in real time, the acquired real-time position information of the rail vehicle is input into the rail model, the scanning unit and the camera unit are arranged at the front end of the rail vehicle, the scanning unit scans the front of the rail vehicle in real time in the running process of the rail vehicle, when an obstacle is scanned, the position of the obstacle is obtained according to the speed of scanning light, the speed of the rail vehicle and the angle of the scanning light, the position of the obstacle is input into the mathematical model, when the position of the obstacle is not in the rail range, the operation is not carried out, when the position of the obstacle is in the rail range, the obstacle early warning signal is generated and sent to the server, the server sends a shooting instruction and the position of the obstacle to the camera unit, the camera unit shoots a picture of the received position of the obstacle, the taken picture is sent to a server, the server generates an alarm signal, the picture, the alarm signal and the position of the obstacle are sent to an alarm module, and the alarm module gives an alarm sound and displays the picture and the position of the obstacle; the derailment early warning module is used for preventing the derailment of the rail vehicle, acquiring rail line information, wherein the rail line information comprises a safety section at which parts in a line are and a dangerous section at which parts in the line are, the safety section and the dangerous section have judgment standards of radian, angle of a turning and accident occurrence frequency of the rail line, and are set by expert group discussion according to rail traffic safety standards, setting the maximum running speeds of the rail vehicle in different dangerous sections, generating an alarm signal by the derailment early warning module when the running speed of the rail vehicle in the dangerous section exceeds the corresponding maximum running speed, generating the alarm signal to a server, sending the alarm signal to the alarm module by the server, and reminding the rail vehicle of overspeed;
acquiring track route information, establishing a mathematical model, inputting the track route information into the mathematical model, acquiring historical position information of the rail vehicles, selecting historical position information of a plurality of groups of rail vehicles, inputting the historical position information into the mathematical model, and matching the driving route names of the rail vehicles with the route names in the track route information; the method comprises the steps of bringing the position of the rail vehicle into matched rail route information, obtaining the position of the rail vehicle in a rail route, extracting historical position information of a plurality of groups of rail vehicles which are not used, inputting the historical position information into a mathematical model for verifying the correctness of the mathematical model, and marking the mathematical model which is verified to be correct as a rail model; the method comprises the steps that passengers on a platform are warned before a railway vehicle enters a station through a safety warning module, a warning safety line and a dissuading unit are arranged, the condition of the passengers in the warning safety line is detected N minutes before the railway vehicle enters the station, when no passenger exists in the safety line, operation is not carried out, when the passenger exists in the safety line, the position of the passenger in the safety line is obtained, a dissuading signal is generated, the dissuading signal and the position of the passenger in the safety line are sent to a server, the dissuading signal and the position of the passenger in the safety line are sent to the dissuading unit by the server, the dissuading unit controls light to irradiate the position of the passenger in the safety line, dissuading voice is sent out, and the passenger in the safety line is dissuaded;
the method comprises the steps that a fault early warning module is used for early warning faults of the rail vehicle, detection data of the rail vehicle, the running time of the rail vehicle and the running environment of the rail vehicle are obtained in real time, and the detection data, the running time and the running environment of the rail vehicle are integrated and marked as input data; acquiring a prediction model, inputting input data into the prediction model to acquire an output result, and marking the output result as a prediction tag, wherein the prediction tag is a state tag corresponding to the input data, when the state tag fails, the prediction tag is sent to a server, and when the state tag does not fail, the operation is not carried out; the passenger quantity in the rail transit station is pre-warned through a passenger flow pre-warning module, a plurality of areas are divided in the rail transit station, the passenger density in each area and the passenger density in the station are obtained in real time, when the passenger density in the area does not exceed the first-level warning density, the corresponding area is marked as an under-filled area, when the passenger density in the area exceeds the first-level warning density, a shunting signal is generated and sent to a server, the server sends the shunting signal, the position of the over-warning area and the position of the under-filled area closest to the over-warning area to a manager in the station, the manager shunts the passengers in the corresponding area, shunts the extra passengers to the under-filled area closest to the over-warning area, when the passenger density in the station exceeds the second-level warning density, a limit signal is generated and sent to the server to obtain the rail vehicle information in X minutes before sending, and transmitting the rail vehicle information of X minutes before departure to a station entrance for displaying, wherein the rail vehicle information is only displayed on the upper surface of the station entrance, and transmitting the rail vehicle information of X minutes before departure to an access control system at the station entrance, so that passengers who do not take the rail vehicle of X minutes before departure do not get into the station.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A rail transit early warning system based on big data is characterized by comprising a server, a derailment early warning module, a safety early warning module, a fault early warning module, a passenger flow early warning module, an alarm module and a data storage module; the derailment early warning module is used for preventing derailment of a rail vehicle, and specifically the derailment of the rail vehicle is prevented by establishing a rail model, acquiring position information of the rail vehicle in real time, inputting the acquired real-time position information of the rail vehicle into the rail model, arranging a scanning unit and a camera unit at the front end of the rail vehicle, scanning the front of the rail vehicle by the scanning unit in real time in the running process of the rail vehicle, obtaining the position of an obstacle according to the speed of scanning light, the speed of the rail vehicle and the angle of the scanning light when the obstacle is scanned, inputting the position of the obstacle into a mathematical model, not operating when the position of the obstacle is not in the range of the rail, generating an obstacle early warning signal when the position of the obstacle is in the range of the rail, sending the obstacle early warning signal to a server, and sending a shooting instruction and the position of the obstacle to the camera unit by the server, the camera shooting unit shoots pictures at the received positions of the obstacles, the shot pictures are sent to the server, the server generates an alarm signal, the pictures, the alarm signal and the positions of the obstacles are sent to the alarm module, and the alarm module gives out alarm sound and displays the pictures and the positions of the obstacles.
2. The big data-based rail transit early warning system according to claim 1, characterized in that the rail model establishing method specifically comprises the steps of obtaining rail route information, the rail route information comprising a rail position, a rail range and a route name, establishing a mathematical model, inputting the rail route information into the mathematical model, obtaining historical position information of rail vehicles, selecting historical position information of a plurality of groups of rail vehicles to input into the mathematical model, and matching the driving route names of the rail vehicles with the route names in the rail route information; and the position of the rail vehicle is brought into the matched rail route information, historical position information of a plurality of groups of unused rail vehicles is extracted and input into the mathematical model to verify the correctness of the mathematical model, and the mathematical model which is verified to be correct is marked as the rail model.
3. The big data-based rail transit early warning system according to claim 1, wherein the safety early warning module is used for early warning passengers on a platform before a rail vehicle arrives at the station, and the method comprises the steps of arranging a warning safety line and a dissuading unit, detecting the condition of the passengers in the warning safety line N minutes before the rail vehicle arrives at the station, acquiring the position of the passengers in the safety line when the passengers exist in the safety line, generating a dissuading signal, sending the dissuading signal and the position of the passengers in the safety line to the server, sending the dissuading signal and the position of the passengers in the safety line to the dissuading unit by the server, controlling the position of the passengers in the safety line to be irradiated by light by the dissuading unit, and sending dissuading voice to dissuade the passengers in the safety line.
4. The big data-based rail transit early warning system according to claim 1, wherein the fault early warning module is used for early warning faults of rail vehicles, and the specific method comprises the steps of acquiring detection data of the rail vehicles, running time of the rail vehicles and running environments of the rail vehicles in real time, integrating and marking the detection data, the running time and the running environments of the rail vehicles as input data; and acquiring a prediction model, inputting input data into the prediction model to acquire an output result, and marking the output result as a prediction label, wherein the prediction label is a state label corresponding to the input data, when the state label is in a fault state, the prediction label is sent to a server, and when the state label is not in the fault state, the operation is not performed.
5. The big-data-based rail transit early warning system as claimed in claim 1, wherein the passenger flow early warning module is configured to perform early warning on the number of passengers in the rail transit station by dividing a plurality of parcel areas in the rail transit station, setting passenger warning densities including a primary warning density and a secondary warning density, obtaining the passenger density in each parcel area and the passenger density in the station in real time, when the passenger density in the parcel area does not exceed the primary warning density, marking the corresponding parcel area as a less-than-full parcel area, when the passenger density in the parcel area exceeds the primary warning density, generating a shunting signal, transmitting the shunting signal to the server, transmitting the shunting signal, the position of the more-than-warning parcel area and the position of the less-than-full parcel area nearest to the more-than-warning parcel area to a manager in the station, the manager shunting the passengers in the corresponding parcel area, and shunting the excessive passengers to an area which is not full and is closest to the area exceeding the warning area, generating an access limiting signal when the passenger density in the station exceeds the secondary warning density, sending the access limiting signal to a server, acquiring the rail vehicle information X minutes before departure, and sending the rail vehicle information X minutes before departure to a station entrance for display.
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| CN202210580320.3A CN115056821A (en) | 2022-05-26 | 2022-05-26 | Big data-based rail transit early warning system |
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