CN209748604U - railway transportation coal dust suppression intelligent monitoring analysis system based on big data - Google Patents
railway transportation coal dust suppression intelligent monitoring analysis system based on big data Download PDFInfo
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Abstract
The utility model belongs to the technical field of coal transportation monitoring technique and specifically relates to a railway transportation coal presses down dirt intelligent monitoring analytic system based on big data, it includes: the system comprises laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring equipment, meteorological monitoring equipment and a coal dust suppression intelligent big data analysis platform; the utility model discloses plan from two visual angles of train coal-carrying volume and dust concentration and start, based on the data sources of equipment such as laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring facilities, meteorological monitoring equipment, through the analysis to the heterogeneous data of multisource, realize the integrated monitoring in the coal transportation.
Description
Technical Field
The utility model belongs to the technical field of coal transportation monitoring technique and specifically relates to a railway transportation coal presses down dirt intelligent monitoring analytic system based on big data.
Background
At present, the image recognition technology is applied to various fields such as security protection, traffic monitoring and the like, and is relatively mature. The scattering in the railway coal transportation process always exists, although surface curing agent measures are adopted, the scattering problem cannot be completely avoided, and the scattering is not a stable process, is high in randomness and is easily influenced by various factors such as external wind pressure, landform and vehicle meeting. The method is characterized in that the top surface of a coal transportation carriage is taken as a loss source, image identification technology is utilized to compare image differences of different places, factors such as vehicle speed, vehicle information, instantaneous atmospheric quality change and weather are combined and fused into big data, the relationship between the change rate of the surface state of the coal bed of the same carriage and each factor is finally obtained, the loss degree of different trains is judged, and the loss problem source is found out through sorting.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information constitutes prior art already known to a person skilled in the art.
SUMMERY OF THE UTILITY MODEL
An object of the utility model is to provide a railway transportation coal presses down dirt intelligent monitoring analytic system based on big data to solve the train in transportation coal process, because the diversity of macroscopic external environment, and the complexity of microcosmic coal dust diffusion motion, make the comprehensive assessment who reveals coal in the transportation in transit have certain challenge. Therefore, it is difficult to locate leaking vehicles and measure the concentration of coal dust by analyzing only the gas components in the local environment.
in order to achieve the above purpose, the utility model adopts the following technical scheme:
The utility model provides a railway transportation coal presses down dirt intelligent monitoring analytic system based on big data, it includes: the system comprises laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring equipment, meteorological monitoring equipment and a coal dust suppression intelligent big data analysis platform;
the laser radar monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and used for monitoring three-dimensional structural information data of the coal transport train and feeding the three-dimensional structural information data back to the intelligent coal dust suppression big data analysis platform; the radar speed measuring equipment is connected with the intelligent coal dust suppression big data analysis platform and used for measuring the speed data of the coal transport train and feeding the speed data back to the intelligent coal dust suppression big data analysis platform; the video monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for acquiring image data of a coal transport train in a video acquisition mode and feeding the image data back to the intelligent coal dust suppression big data analysis platform; the train number identification equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for identifying carriage number data of each carriage of the coal transport train and feeding the carriage number data back to the intelligent coal dust suppression big data analysis platform; the air quality monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for monitoring the air quality data around the railway line of the coal transport train and feeding the air quality data back to the intelligent coal dust suppression big data analysis platform; the meteorological monitoring equipment is connected with the intelligent big coal dust suppression data analysis platform and is used for monitoring meteorological data around the coal transport train railway line and feeding the meteorological data back to the intelligent big coal dust suppression data analysis platform; the coal dust suppression intelligent big data analysis platform is used for collecting, sorting and analyzing data of each device and performing three-dimensional data presentation.
as a further technical scheme, the intelligent coal dust suppression big data analysis platform comprises: the system comprises a transcoding server of a big data analysis platform, an analysis server of the big data analysis platform, a three-dimensional display server of the big data analysis platform and a display device;
the transcoding server of the big data analysis platform, the analysis server of the big data analysis platform and the three-dimensional display server of the big data analysis platform are respectively connected with the network switch;
The network switch is respectively connected with the laser radar monitoring equipment, the radar speed measuring equipment, the video monitoring equipment, the vehicle number identification equipment, the atmosphere quality monitoring equipment and the meteorological monitoring equipment;
the display device is respectively connected with the transcoding server of the big data analysis platform, the analysis server of the big data analysis platform and the three-dimensional display server of the big data analysis platform.
As a further technical solution, the display device includes: displays or tiled large screens.
as a further technical scheme, the laser radar monitoring equipment is C32-151A in model.
as a further technical scheme, the model of the radar speed measuring equipment is STJ 1-12.
as a further technical scheme, the type of the snapshot device of the video monitoring equipment is iDS-TCV 300-AEM/1236.
As a further technical scheme, the model of the terminal server of the video monitoring equipment is DS-TP50-12 DH/S.
As a further technical scheme, the model of the car number identification equipment is AEI-S1.
As a further technical scheme, the model of the atmosphere quality monitoring equipment is BPM-200M.
as a further technical scheme, the model of the intelligent coal dust suppression big data analysis platform is DANA.
adopt above-mentioned technical scheme, the utility model discloses following beneficial effect has:
The utility model discloses plan from two visual angles of train coal-carrying volume and dust concentration and start, based on the data sources of equipment such as laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring facilities, meteorological monitoring equipment, through the analysis to the heterogeneous data of multisource, realize the integrated monitoring in the coal transportation.
drawings
in order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the technical solutions in the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a control flow chart of an intelligent monitoring and analyzing system for dust suppression of railway transportation coal based on big data provided by the embodiment of the utility model;
FIG. 2 is a circuit connection diagram of the railway transportation coal dust suppression intelligent monitoring and analyzing system based on big data provided by the embodiment of the utility model;
FIG. 3 is a control flow chart of the intelligent monitoring and analyzing method for dust suppression of railway transportation coal based on big data provided by the embodiment of the utility model;
FIG. 4 is a schematic view of a control interface of the intelligent big data analysis platform for suppressing dust in coal provided by the embodiment of the present invention.
icon: 1-radar speed measuring equipment; 2-lidar monitoring equipment; 3-video monitoring equipment; 4-a car number identification device; 5-atmospheric quality monitoring equipment; 6-meteorological monitoring equipment; 7-a network switch; 8, a three-dimensional display server of the big data analysis platform; 9-an analysis server of the big data analysis platform; 10-a transcoding server of a big data analysis platform; 11-splicing a large screen; 12-display.
Detailed Description
The technical solution of the present invention will be described clearly and completely with reference to the accompanying drawings, and obviously, the described embodiments are some, but not all embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood according to specific situations by those skilled in the art.
The following detailed description of the embodiments of the present invention will be made with reference to the accompanying drawings. It is to be understood that the description of the embodiments herein is for purposes of illustration and explanation only and is not intended to limit the invention.
example one
With reference to fig. 1 to 4, the present embodiment provides a big data based intelligent monitoring and analyzing system for dust suppression of coal transported by railways, which includes: the system comprises a laser radar monitoring device 2, a radar speed measuring device 1, a video monitoring device 3, a vehicle number identification device 4, an atmospheric quality monitoring device 5, a meteorological monitoring device 6 and a coal dust suppression intelligent big data analysis platform; the laser radar monitoring equipment 2 is connected with the coal dust suppression intelligent big data analysis platform and used for monitoring three-dimensional structural information data of the coal transport train and feeding the three-dimensional structural information data back to the coal dust suppression intelligent big data analysis platform; the radar speed measuring equipment 1 is connected with the intelligent big coal dust suppression data analysis platform and used for measuring the speed data of the coal transport train and feeding the speed data back to the intelligent big coal dust suppression data analysis platform; the video monitoring equipment 3 is connected with the intelligent coal dust suppression big data analysis platform and is used for acquiring image data of a coal transport train in a video acquisition mode and feeding the image data back to the intelligent coal dust suppression big data analysis platform; the train number identification equipment 4 is connected with the coal dust suppression intelligent big data analysis platform and is used for identifying carriage number data of each carriage of the coal transport train and feeding the carriage number data back to the coal dust suppression intelligent big data analysis platform; the air quality monitoring equipment 5 is connected with the coal dust suppression intelligent big data analysis platform and is used for monitoring the air quality data around the railway line of the coal transport train and feeding back the air quality data to the coal dust suppression intelligent big data analysis platform; the meteorological monitoring equipment 6 is connected with the coal dust suppression intelligent big data analysis platform and is used for monitoring meteorological data around the coal transport train railway line and feeding the meteorological data back to the coal dust suppression intelligent big data analysis platform; the coal dust suppression intelligent big data analysis platform is used for collecting, sorting and analyzing data of each device and performing three-dimensional data presentation.
it can be seen that the system is based on two visual angles of train coal carrying quantity and dust concentration, and based on data sources of laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, train number identification equipment, atmospheric quality monitoring equipment and meteorological monitoring equipment, comprehensive monitoring in the coal railway transportation process is realized through analysis of multi-source heterogeneous data, data of a plurality of systems are collected, sorted and analyzed in a big data mode, and finally a three-dimensional comparison graph of each data in the coal railway transportation process is displayed through a three-dimensional modeling mode by a coal dust suppression intelligent big data analysis platform, so that the condition of coal scattering in the railway transportation process can be visually judged.
in this embodiment, preferably, the coal dust suppression intelligent big data analysis platform includes: the system comprises a transcoding server 10 of a big data analysis platform, an analysis server 9 of the big data analysis platform, a three-dimensional display server 8 of the big data analysis platform and a display device; the transcoding server 10 of the big data analysis platform, the analysis server 9 of the big data analysis platform and the three-dimensional display server 8 of the big data analysis platform are respectively connected with the network switch 7; the network switch 7 is respectively connected with the laser radar monitoring equipment 2, the radar speed measuring equipment 1, the video monitoring equipment 3, the vehicle number identification equipment 4, the atmospheric quality monitoring equipment 5 and the meteorological monitoring equipment 6; the display device is respectively connected with the transcoding server 10 of the big data analysis platform, the analysis server 9 of the big data analysis platform and the three-dimensional display server 8 of the big data analysis platform.
In this embodiment, preferably, the display device includes: display 12 or tiled large screen 11.
As a further technical scheme, the laser radar monitoring device 2 is C32-151A in model. The laser radar monitoring equipment 2 directly obtains the three-dimensional coordinate information of the surface sampling point of the target object, so that the three-dimensional structure information data of the object is obtained. The laser radar monitoring device 2 is provided with 32 pairs of fixed laser emitting and receiving devices by adopting a 32-line laser radar, and performs 360-degree panoramic scanning at the rotating speed of 5hz (or 10hz and 20hz) through the rotation of an internal motor. The pulse type distance measurement mode is adopted, the distance measurement precision reaches +/-2cm, the data speed reaches 64 ten thousand points/second at most, and an Ethernet communication interface is adopted.
For example: lidar monitoring device 2
the model is as follows: C32-151A;
equipment parameters:
32 channels are scanned;
pulse type of distance measurement;
the laser band is 905 nm;
laser class 1 (eye safe);
Signal transmission mode wireless power and signal transmission;
the maximum measuring range is 150 meters (the reflectivity is 30%);
The minimum measuring range is 0.5 m;
the distance measurement precision is +/-2 cm;
The data acquisition speed is 64 ten thousand points/second at most;
the scanning frequency is vertical to the 32-path vertical direction;
scanning frequency levels of 5Hz, 10Hz and 20Hz (optional);
the field angle is vertical to 360 degrees from minus 16 degrees to plus 15 degrees;
the angular resolution is vertically the most dense, 1 degree, horizontal 5Hz, 0.09 degree, 10Hz, 0.18 degree, 20Hz, 0.36 degree;
Impact 500m/sec2, duration 11 ms;
vibrating for 5Hz to 2000Hz, 3G rms;
the protection level can reach IP 67.
as a further technical scheme, the model of the radar speed measuring equipment 1 is STJ 1-12. Narrow wave speed measuring radar that radar speed measuring equipment 1 adopted, frequency 24G, the distance that tests the speed: single lane 18 ~ 38m, the range of testing the speed: 20 km/h-400 km/h.
for example: radar speed measuring equipment 1
the model is as follows: STJ 1-12;
Equipment parameters:
A narrow wave speed measuring radar;
A single lane speed measuring radar with the frequency of 24G;
Speed measurement distance: the single lane is 18-38 m (adjustable);
Speed measurement range: 20 km/h-400 km/h;
WIFI function: various parameters of the radar can be set through the WIFI of the radar, and the debugging is simple and rapid;
working voltage: 9-12V DC.
as a further technical scheme, the type of the snapshot device of the video monitoring equipment 3 is iDS-TCV 300-AEM/1236. The model of the terminal server of the video monitoring device 3 is DS-TP50-12 DH/S. The video monitoring equipment 3 comprises a high-definition integrated embedded camera, a high-definition lens, an outdoor protective cover, a camera built-in network signal lightning protector, an infrared white light flashing integrated lamp, an LED environment light supplementing lamp, a terminal server and the like.
For example: video monitoring device 3
the type of the snapshot unit: iDS-TCV300-AEM/1236
equipment parameters:
the high-definition integrated embedded video camera comprises a high-definition integrated embedded video camera, a high-definition lens, an outdoor protective cover, a camera built-in network signal lightning protector, a power adapter and the like;
A photosensitive device: two 1/1.8 inch global exposure CMOS
the lens is 12-36 mm;
The wide dynamic range can reach 107 dB;
The video compression supports H.265, H.264, M-JPEG and MPEG4, and can support TCP/IP, HTTP, HTTPS, FTP, DNS, RTP, RTSP, RTC, NTP, UpnP and IPv 6; network protocols such as DHCP, 802.1x, etc.;
the main code stream is supported to output no less than 30 paths of images of 25 frames/s of 2048 × 1536 and 2Mbps simultaneously so as to provide client browsing;
the storage automatic coverage is supported, and the maximum support of the storage card is 256G;
A deep learning chip is arranged in the equipment;
The two-way fusion function: two image sensors are arranged in the machine, black-white and color images can be output respectively, and a prototype can fuse and output video images and snap pictures;
for example: a video monitoring device 3 terminal server;
The model is as follows: DS-TP50-12DH/S (2T);
Equipment parameters:
the equipment adopts an embedded Linux real-time operating system, and the memory capacity is 2 GB;
16 10M/100M adaptive RJ45 interfaces, 2 10M/100M/1000M adaptive RJ45 interfaces (1 of which is 1000M opto-electronically switchable SFP interfaces and is in the same network segment with 16 100 Mm network ports);
1 piece of 3.5-inch 2T hard disk is arranged in the hard disk drive;
The method supports 2 paths of HD-TVI cameras to access coding transmission and video recording, and can carry out real-time loop-through output on the accessed 2 paths of HD-TVI video signals;
4 HD-TVI interfaces, 2 RS-232 interfaces, 4 RS-485 interfaces, 1 VGA interface, 1 HDMI interface, 1 CVBS output interface, 2 USB2.0 interfaces, 4 alarm input interfaces, 4 alarm output interfaces, 1 audio input interface, 1 audio output interface, 1 DC12V output interface, 1 DC5V output interface, 1 eSATA interface, and 4 SATA interfaces;
The method supports video picture splicing of any four video channels, and can support mixed splicing of an analog channel and a digital channel;
at most 16 IP cameras can be accessed (single path code rate 10M);
The equipment is provided with an LCD display screen for displaying and setting date and time, displaying the internal temperature of the equipment and displaying the working states of the four hard disks;
The local video preview and the menu parameter configuration can be carried out through VGA and HDMI, and the local video preview can be carried out through CVBS.
as a further technical solution, the model of the car number identification device 4 is AEI-S1 model, the car number identification device 4 adopts the car number identification device 4 composed of antenna, wheel sensor (magnetic steel), AEI host, front-end device, KVM (keyboard, mouse and display 12), signal lightning protection unit, temperature controller, UPS power supply and so on.
for example: vehicle number identification device 4
The model is as follows: AEI equipment model S1;
equipment parameters:
the ground identification equipment for the vehicle number comprises an antenna, a wheel sensor (magnetic steel), an AEI host, a front device, a KVM (keyboard, mouse and display 12), a signal lightning protection unit, a temperature controller, a UPS power supply and the like.
As a further technical scheme, the model of the atmosphere quality monitoring equipment 5 is BPM-200M. The air quality monitoring equipment 5 adopts a dynamic heating dehumidification and humidity compensation method, solves the problem of influence of high humidity conditions on measurement in rainy days, measures the measurement in all weather and high precision, refreshes concentration measurement values in minutes, and can select concentration limit values within any time ranges of 15min, 30min and the like to alarm.
For example: atmospheric quality monitoring equipment 5
The model is as follows: BPM-200M
Equipment parameters:
Measurement principle beta ray absorption method;
Performance indexes are as follows:
resolution 0.0001mg/m 3;
The lowest detection limit is 0.005mg/m 3;
The measurement range is (0-10) mg/m3, (0-20) mg/m3, (0-50) mg/m3 (0-100) mg/m3 (optional);
the sampling flow is 2L/min;
Flow error ± 2% f.s.;
the flow stability is less than or equal to +/-2 percent of the flow of the working point/24 h;
the repeatability of the calibration film is less than or equal to +/-2 percent of a standard value;
Sampling period (1-360) min or continuous sampling;
Sampling dust for 1-300 min or continuously sampling;
counting time (1-60) min by a detector;
The time resolution is 1 min;
technical parameters;
a dynamic heating control system;
The concentration alarm carries out concentration alarm according to the setting;
the paper-saving mode is designed, so that the maintenance amount is reduced;
the source C14 radioactive source, activity 10 μ Ci, belongs to exemption source;
the filter paper is provided with a glass fiber paper tape;
interface parameters:
communication interfaces RS232 and 4G wireless transmission (three-network communication, mobile communication and telecommunication).
as a further technical scheme, the meteorological monitoring equipment 6 is used for automatically monitoring the visibility, the wind direction, the wind speed, the air temperature, the humidity, the rainfall and the like of the railway line and transmitting the monitoring information to the monitoring center in time.
Equipment parameters:
the visibility, wind direction, wind speed, air temperature, humidity, rainfall and the like along the railway are automatically monitored, and monitoring information is timely transmitted to a monitoring center. The system has the functions of display, automatic storage, real-time lightning protection, data communication and the like.
1. the device can reliably operate in various severe field environments, has low power consumption, high stability and high precision, and can be unattended.
2. perfect lightning protection, corrosion resistance, anti-interference and other protection measures.
3. The wired connection and wireless network communication functions can be connected with a computer, and remote network distribution or remote measurement can be realized to realize data monitoring.
4. the recorder can work independently, is provided with an LCD display screen and a clock, can be expanded, displays various element data and realizes mass storage of the data. The storage time is required, and the customization can be contacted with a client.
5. The power supply system comprises an AC/DC power supply system, a solar battery and other various power supply modes.
As a further technical scheme, the model of the intelligent coal dust suppression big data analysis platform is DANA.
through a data platform developed by Germany, the existing laser radar monitoring equipment 2, radar testing equipment, video monitoring equipment 3, vehicle number identification equipment 4, atmospheric quality monitoring equipment 5 and meteorological monitoring equipment 6 are collected and extracted in a unified format, and the service barrier is broken through, so that the data are communicated. After the gathered data is cleaned and sorted to obtain effective data which accords with the business process, data modeling is carried out through DataStaudio, model training and correction are carried out, a final 'coal scattering' data model which is attached to the production environment is obtained, the surface variability of coal on different stations of a specified train number and a carriage can be determined, and a result set is formed and stored. The result set is finally visually presented by the pandabi software or the three-dimensional presentation server.
The model is as follows: DANA
equipment parameters:
example two
with reference to fig. 1 to 4, the present embodiment provides an intelligent monitoring and analyzing method for dust suppression of coal transported by railways based on big data, which includes the following steps:
Carrying out multi-point monitoring on the area passed by the coal transport train;
every monitoring point monitors the coal transportation train that passes through the intelligent monitoring analytic system that presses down dust of railway transportation coal in the embodiment one, include: the train passing data is sensed through the radar speed measuring equipment 1, the generated sensing data is transmitted to the laser radar monitoring equipment 2, the video monitoring equipment 3 and the train number identification equipment 4, and the laser radar monitoring equipment 2, the video monitoring equipment 3 and the train number identification equipment 4 are triggered to respectively perform radar scanning, video and picture recording and snapshot and train carriage number identification on the coal transport train; three-dimensional point cloud data of the whole train carriage, which are generated by scanning of the laser radar monitoring device 2, are transmitted to a transcoding server 10 end of the big data analysis platform for data transcoding; the video recorded by the video monitoring equipment 3 and the captured image data are input to a transcoding server 10 end of the big data analysis platform for data transcoding; the car number data of each carriage identified by the car number identification device 4 is input to a transcoding server 10 end of the big data analysis platform for data transcoding; the atmospheric monitoring equipment transmits the monitored particulate matter data in the atmosphere when the train passes through to a transcoding server 10 end of the big data analysis platform for data transcoding; the meteorological monitoring equipment 6 transmits the meteorological data monitored when the train passes through to a transcoding server 10 end of the big data analysis platform for data transcoding; the transcoding server 10 of the big data analysis platform transmits each item of transcoded data to the analysis server 9 of the big data analysis platform through a network for screening, sorting and analysis, and the analysis server 9 of the big data analysis platform transmits the final screened, sorted and analyzed data to the three-dimensional display server 8 end of the big data analysis platform for three-dimensional data presentation;
The change condition of each carriage coal in the railway transportation process is obtained by comparing the data generated by the equipment of each monitoring point, and the scattering condition of each carriage coal is obtained by point cloud data three-dimensional imaging and snapshot carriage picture comparison.
It is thus clear that the utility model discloses plan from two visual angles of train coal-carrying volume and dust concentration and start, based on the data sources of equipment such as laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring facilities, meteorological monitoring equipment, through the analysis to the heterogeneous data of multisource, realize the integrated monitoring in the coal transportation. And finally, data of a plurality of systems are acquired, sorted and analyzed in a big data mode, and a three-dimensional comparison graph of each item of data in the coal railway transportation process is displayed by a coal dust suppression intelligent big data analysis platform in a three-dimensional modeling mode, so that the coal scattering condition in the railway transportation process can be visually judged.
as a further technical solution, the multipoint monitoring of the area where the coal transportation train passes includes:
Monitoring an initial end along a coal transport train;
Monitoring a plurality of station ends along a coal transport train;
and monitoring the terminal end along the coal transport train.
As a further technical solution, the deployment position of each monitoring point includes:
the laser radar speed measuring equipment 1, the laser radar monitoring equipment 2 and the video monitoring equipment 3 are mainly deployed right above a coal transport train line or on two sides of the coal transport train line;
The atmospheric quality monitoring equipment 5, the meteorological monitoring equipment 6 and the train number identification equipment 4 are respectively arranged on two sides of the railway line.
as a further technical scheme, the radar speed measuring device 1 is used for measuring speed data of a coal transport train, transmitting the speed data to a network switch 7 through a network, transmitting the data to a transcoding server 10 end of a big data analysis platform through the network switch 7, transcoding the speed data through the transcoding server end to generate data which can be identified by a data analysis server, transmitting the data to a data analysis server end of the big data analysis platform through the network switch 7, analyzing and sorting the data through the data analysis server to generate final data to be presented, transmitting the data to be presented to a three-dimensional display server 8 end of the big data analysis platform through the network switch 7 to visually present the three-dimensional data, and finally displaying the three-dimensional data through a display 12 end or a spliced big screen 11 end.
as a further technical scheme, the three-dimensional point cloud data generated by the laser radar monitoring device 2 is transmitted to a network switch 7 through a network, then the network switch 7 transmits the data to a transcoding server 10 end of a big data analysis platform, then the three-dimensional point cloud data is transcoded by the transcoding server end to generate data which can be identified by the data analysis server, then the three-dimensional point cloud data is transmitted to a data analysis server end of the big data analysis platform through the network switch 7, finally the data which needs to be presented is generated after the data analysis server end analyzes and arranges the data, then the network switch 7 transmits the data which needs to be presented to a three-dimensional display server 8 end of the big data analysis platform to perform visual presentation of the three-dimensional data, and finally the data is displayed by a display 12 end or a spliced big screen 11 end.
as a further technical scheme, the view data of the coal transport train acquired by the video monitoring device 3 is transmitted to a network switch 7 through a network, then the view data is transmitted to a transcoding server 10 end of a big data analysis platform by the network switch 7, then the data is transcoded by the transcoding server end to generate data which can be identified by a data analysis server, then the data is transmitted to a data analysis server end of the big data analysis platform by the network switch 7, finally the data which needs to be presented is generated after being analyzed and sorted by the data analysis server end, then the data which needs to be presented is transmitted to a three-dimensional display server 8 end of the big data analysis platform by the network switch 7 to be visually presented, and finally the data is displayed by a display 12 end or a spliced big screen 11 end.
As a further technical scheme, the car number data of the coal transport train generated by the car number recognition device 4 is transmitted to the network switch 7 through a network, then the car number data is transmitted to the transcoding server 10 end of the big data analysis platform through the network switch 7, then the data is transcoded by the transcoding server end to generate data which can be recognized by the data analysis server, then the data is transmitted to the data analysis server end of the big data analysis platform through the network switch 7, finally the data which needs to be presented is generated after being analyzed and sorted by the data analysis server end, then the data which needs to be presented is transmitted to the three-dimensional display server 8 end of the big data analysis platform through the network switch 7 to be visually presented, and finally the data is displayed by the display 12 end or the spliced big screen 11 end.
As a further technical scheme, peripheral air quality data along a coal transport train railway generated by the atmospheric quality monitoring device 5 is transmitted to a network switch 7 through a network, then the network switch 7 transmits the peripheral air quality data to a transcoding server 10 end of a big data analysis platform, then the data is transcoded by the transcoding server end to generate data which can be identified by a data analysis server, then the data is transmitted to a data analysis server end of the big data analysis platform through the network switch 7, the data which needs to be presented finally is generated after the data analysis server end analyzes and arranges, then the network switch 7 transmits the data which needs to be presented to a three-dimensional display server 8 end of the big data analysis platform to perform visual presentation of the three-dimensional data, and finally the data is displayed by a display 12 end or a spliced big screen 11 end.
as a further technical scheme, meteorological data around a coal transport train railway along the line generated by the meteorological monitoring equipment 6 are transmitted to a network switch 7 through a network, then the data are transmitted to a transcoding server 10 end of a big data analysis platform through the network switch 7, then the data are transcoded by the transcoding server end to generate data which can be identified by a data analysis server, then the data are transmitted to a data analysis server end of the big data analysis platform through the network switch 7, finally data which need to be displayed are generated after the data are analyzed and sorted by the data analysis server end, then the data which need to be displayed are transmitted to a three-dimensional display server 8 end of the big data analysis platform through the network switch 7 to be visually displayed, and finally the data are displayed by a display 12 end or a spliced big screen 11 end.
As a further technical scheme, data output by the laser radar equipment, the radar speed measuring equipment 1, the video monitoring equipment 3, the vehicle number identifying equipment 4, the air monitoring equipment and the weather monitoring equipment 6 are all transmitted to a transcoding server 10 end of a big data analysis platform through a network interface, the data are transmitted to an analysis server through a network for data analysis after being transcoded and sorted, and finally the analyzed data are transmitted to a three-dimensional display server end through the network for three-dimensional data presentation; the data generated by the laser radar equipment, the radar speed measuring equipment 1, the video monitoring equipment 3, the car number identification equipment 4, the air monitoring equipment and the meteorological monitoring equipment 6 are stored in a database form, and the big data analysis platform extracts the data in each equipment database through a network to carry out big data analysis.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention.
Claims (10)
1. The utility model provides a railway transportation coal presses down dirt intelligent monitoring analytic system based on big data which characterized in that includes: the system comprises laser radar monitoring equipment, radar speed measuring equipment, video monitoring equipment, car number identification equipment, atmospheric quality monitoring equipment, meteorological monitoring equipment and a coal dust suppression intelligent big data analysis platform;
The laser radar monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and used for monitoring three-dimensional structural information data of the coal transport train and feeding the three-dimensional structural information data back to the intelligent coal dust suppression big data analysis platform; the radar speed measuring equipment is connected with the intelligent coal dust suppression big data analysis platform and used for measuring the speed data of the coal transport train and feeding the speed data back to the intelligent coal dust suppression big data analysis platform; the video monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for acquiring image data of a coal transport train in a video acquisition mode and feeding the image data back to the intelligent coal dust suppression big data analysis platform; the train number identification equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for identifying carriage number data of each carriage of the coal transport train and feeding the carriage number data back to the intelligent coal dust suppression big data analysis platform; the air quality monitoring equipment is connected with the intelligent coal dust suppression big data analysis platform and is used for monitoring the air quality data around the railway line of the coal transport train and feeding the air quality data back to the intelligent coal dust suppression big data analysis platform; the meteorological monitoring equipment is connected with the intelligent big coal dust suppression data analysis platform and is used for monitoring meteorological data around the coal transport train railway line and feeding the meteorological data back to the intelligent big coal dust suppression data analysis platform; the coal dust suppression intelligent big data analysis platform is used for collecting, sorting and analyzing data of each device and performing three-dimensional data presentation.
2. The big data based intelligent monitoring and analyzing system for coal dust suppression in railway transportation according to claim 1, wherein the intelligent big data analyzing platform for coal dust suppression comprises: the system comprises a transcoding server of a big data analysis platform, an analysis server of the big data analysis platform, a three-dimensional display server of the big data analysis platform and a display device;
the transcoding server of the big data analysis platform, the analysis server of the big data analysis platform and the three-dimensional display server of the big data analysis platform are respectively connected with the network switch;
The network switch is respectively connected with the laser radar monitoring equipment, the radar speed measuring equipment, the video monitoring equipment, the vehicle number identification equipment, the atmosphere quality monitoring equipment and the meteorological monitoring equipment;
The display device is respectively connected with the transcoding server of the big data analysis platform, the analysis server of the big data analysis platform and the three-dimensional display server of the big data analysis platform.
3. The big data based railway transportation coal dust suppression intelligent monitoring and analyzing system according to claim 2, wherein the display device comprises: displays or tiled large screens.
4. The big data based intelligent monitoring and analyzing system for dust suppression of railway transportation coal of claim 1, wherein the laser radar monitoring equipment is C32-151A in model number.
5. the big data based intelligent monitoring and analyzing system for dust suppression of railway transportation coal according to claim 1, wherein the model number of the radar speed measuring equipment is STJ 1-12.
6. The big data based railway transportation coal dust suppression intelligent monitoring and analysis system according to claim 1, wherein the video monitoring equipment is provided with a snapshot device of type iDS-TCV 300-AEM/1236.
7. The big data based intelligent monitoring and analyzing system for coal dust suppression in railway transportation is characterized in that the model of the terminal server of the video monitoring equipment is DS-TP50-12 DH/S.
8. the big data based intelligent monitoring and analyzing system for dust suppression of coal in railway transportation according to claim 1, wherein the model number of the train number identification equipment is AEI-S1.
9. the big data based intelligent monitoring and analyzing system for dust suppression of railway transportation coal of claim 1, wherein the model of the air quality monitoring equipment is BPM-200M.
10. the big data based intelligent monitoring and analyzing system for coal dust suppression in railway transportation according to claim 1, wherein the model of the intelligent big data analyzing platform for coal dust suppression is DANA.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247991A (en) * | 2019-07-19 | 2019-09-17 | 中交铁道设计研究总院有限公司 | Railway transportation coal dust suppression intellectual monitoring analysis system based on big data |
| CN112298283A (en) * | 2020-07-13 | 2021-02-02 | 上海悠络客电子科技股份有限公司 | Railway auxiliary system based on big data |
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2019
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247991A (en) * | 2019-07-19 | 2019-09-17 | 中交铁道设计研究总院有限公司 | Railway transportation coal dust suppression intellectual monitoring analysis system based on big data |
| CN112298283A (en) * | 2020-07-13 | 2021-02-02 | 上海悠络客电子科技股份有限公司 | Railway auxiliary system based on big data |
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