CN111325977A - Tunnel intelligence edge calculation management and control system - Google Patents
Tunnel intelligence edge calculation management and control system Download PDFInfo
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Abstract
The invention discloses an intelligent tunnel edge computing management and control system, which belongs to the technical field of tunnel edge computing and comprises a management and control center, a risk dynamic early warning subsystem and a monitoring and controlling subsystem, wherein the risk dynamic early warning subsystem is connected with the management and control center and is used for monitoring the running state of execution equipment in a tunnel and the acquired data of sensing equipment in real time and carrying out abnormal warning and equipment inspection; the electromechanical integrated subsystem is used for linking execution equipment in the tunnel and executing an emergency plan; a traffic state perception subsystem for visually perceiving the traffic state of the tunnel and detecting traffic events through radar and video fusion detection technologies; the management and control center receives the monitored running states of the execution equipment and the sensing equipment, issues a control command to the electromechanical integrated subsystem, receives the sensed traffic state, analyzes the traffic event and gives an alarm. The invention solves the problems of non-integration, low degree of association, lack of effective and normative informatization means and low emergency disposal efficiency of the existing tunnel management and control system.
Description
Technical Field
The invention belongs to the technical field of tunnel edge calculation, and relates to an intelligent tunnel edge calculation management and control system.
Background
Tunnels are engineering structures buried in the ground and are a form of human use of underground space. In China, the expressway is universal, and the tunnel is indispensable for complex terrain change in China. For the traffic tunnel, it is not only necessary to prevent the entry of non-motor vehicles, pedestrians and animals, but also to monitor various conditions in the tunnel and take countermeasures. The tunnel is used as the 'throat' of the highway, and the operation level directly influences the safety and the traffic efficiency of the highway. In order to actually improve the safe operation level of the tunnel and guarantee the life and property safety of people, the tunnel is required to be subjected to tunnel electromechanical safety integrated improvement engineering according to the notice on the action scheme for printing and upgrading the road tunnel quality improvement of the office hall of the department of transportation, and the tunnel in service is subjected to relevant standard specifications such as the traffic engineering and the auxiliary setting of the second volume of the design specification of the road tunnel, the lighting design rule of the road tunnel, the ventilation design rule of the road tunnel, the maintenance technical specification of the road tunnel and the like.
The edge calculation is a distributed open platform which integrates network, calculation, storage and application core capabilities at the edge side of a network close to an object or a data source, edge intelligent services are provided nearby, and key requirements of industry digitization on aspects of agile connection, real-time business, data optimization, application intelligence, safety, privacy protection and the like are met. It can be used as a bridge to connect physical and digital worlds, enabling intelligent assets, intelligent gateways, intelligent systems and intelligent services.
At present, the highway tunnel management station has too much software, the software is mutually independent, each software independently controls each system, so that when an accident happens, linkage and cooperative treatment of each system cannot be realized, and the problems of non-integration and low association degree of a management and control system exist; moreover, the emergency plan for highway tunnel operation management is in a paper form, traffic guidance and personnel evacuation in a fire scene are mostly dependent on subjective judgment of a commander, an effective and standard informatization means is lacked, and the emergency disposal efficiency is low.
Therefore, the invention provides an intelligent edge computing management and control system for a tunnel, which aims at the above problems.
Disclosure of Invention
The invention aims to: the intelligent edge computing management and control system for the tunnel solves the problems that an existing tunnel management and control system is not integrated, low in association degree, lack of effective and standard informatization means and low in emergency disposal efficiency.
The technical scheme adopted by the invention is as follows:
an intelligent tunnel edge calculation management and control system comprises a management and control center, a risk dynamic early warning subsystem, an electromechanical integration subsystem and a traffic state perception subsystem, wherein the risk dynamic early warning subsystem, the electromechanical integration subsystem and the traffic state perception subsystem are connected with the management and control center;
the risk dynamic early warning subsystem is used for monitoring the running state of execution equipment in the tunnel and the acquired data of the sensing equipment in real time, and performing abnormal warning and equipment inspection;
the electromechanical integrated subsystem is used for linking execution equipment in the tunnel and executing an emergency plan;
the traffic state perception subsystem visually perceives the traffic state of the tunnel through radar and video fusion detection technology, and detects traffic events;
the management and control center receives the running states of the execution equipment and the sensing equipment monitored by the risk dynamic early warning subsystem, issues a control command to the mechatronic subsystem, receives the traffic state sensed by the traffic state sensing subsystem, analyzes the traffic event and gives an alarm.
Furthermore, the mechatronic subsystem, the risk dynamic early warning subsystem and the traffic state perception subsystem are connected with the management and control center through an internet of things gateway.
Further, the risk dynamic early warning subsystem comprises an execution device, a sensing device, a PLC (programmable logic controller) and a fire alarm controller;
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and sends self running state data and feedback data to the PLC;
the sensing equipment comprises a CO/VI detector, a wind speed and direction detector, a light intensity detector, a liquid level detector, a manual alarm button, a temperature sensing optical fiber/optical grating and a dual-wavelength detector, and sends self running state data and acquired data to the PLC and the fire alarm controller;
and the PLC and the fire alarm controller receive data information of the execution equipment and the sensing equipment and send the data information to the control center for analysis and processing.
Furthermore, the risk dynamic early warning subsystem is connected with an alarm management module and a risk defense module which are arranged in a management and control center;
after receiving the data of the PLC, the alarm management module performs risk identification according to a preset alarm threshold value and provides alarm management;
after the risk defense module receives the data of the PLC, a troubleshooting suggestion is provided for risks based on a built-in risk defense expert knowledge base.
Further, the mechatronic subsystem comprises an execution device and a PLC controller;
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and is automatically controlled by a PLC (programmable logic controller);
and the PLC receives a control command issued by the control center and controls the execution equipment to perform corresponding operation.
Furthermore, the mechatronic subsystem is connected with an emergency plan configuration module and a one-key emergency plan module which are arranged in the management and control center;
the emergency plan configuration module divides the tunnel into a plurality of tunnel accident areas according to the driving crosshole, each accident area configures different execution equipment linkage control schemes according to the position or the accident type, and sends corresponding control commands to the PLC;
the one-key emergency plan module configures a corresponding execution equipment linkage control scheme according to a tunnel high-incidence accident and sends a corresponding control command to the PLC, wherein the tunnel high-incidence accident comprises a fire accident and a traffic accident.
Further, the traffic state perception subsystem comprises a millimeter wave radar, a video camera and a vehicle detector;
the millimeter wave radar converts the running state of the running vehicle in the tunnel into a group of data representing the position, speed and length of the vehicle, obtains the traffic flow statistics, average speed, headway and road space occupancy data of lane division and vehicle division types of the detection area, and sends the data to the control center;
the video camera monitors real-time video in the tunnel, displays detection information of the millimeter wave radar on the video by using a video fusion technology, and then sends the detection information to the control center.
Furthermore, the traffic state perception subsystem is connected with a vehicle behavior analysis module, an event detection module and a linkage control module which are arranged in a management and control center, and the vehicle behavior analysis module and the event detection module are connected with the linkage control module;
the vehicle behavior analysis module is used for carrying out behavior analysis on the driving state data of the vehicle and analyzing whether the conditions of parking, slow running, overspeed, reverse running and long-time occupation of an emergency parking zone exist or not;
the event detection module is used for carrying out event detection on the driving state data of the vehicle, so that detection of pedestrians, animals, sprinkles, traffic jam and vehicle detour is realized;
the linkage control module is connected with the video camera, the variable information board, the vehicle detector, the emergency telephone and the broadcast, and issues corresponding early warning information and traffic guidance information according to the accident types analyzed and obtained by the vehicle behavior analysis module and the event detection module.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. an intelligent tunnel edge calculation management and control system monitors the running state of execution equipment in a tunnel and the acquired data of sensing equipment in real time through a risk dynamic early warning subsystem, carries out warning and risk identification in time, actively carries out early warning and accurate diagnosis, and provides a troubleshooting treatment suggestion according to a diagnosis result; then, a control command is issued to the mechatronic subsystem through the pipe control center to control the operation of executing equipment in the tunnel, an emergency plan is also set in an emergency situation, corresponding control is carried out according to the emergency plan, the time required for emergency after an accident occurs is shortened, the operation steps of monitoring personnel are reduced, and the work efficiency is improved; the traffic state of the tunnel is visually perceived through a radar and video fusion detection technology of the traffic state perception subsystem, traffic events are analyzed, warning is given, reliability of single video detection is enhanced, further deterioration of adverse events is effectively avoided, and automatic monitoring inside and outside the tunnel hole is achieved. The invention realizes the monitoring of the tunnel electromechanical equipment through edge calculation, and has important significance for ensuring the safety of the vehicle passing in the tunnel.
2. The electromechanical integration subsystem, the risk dynamic early warning subsystem and the traffic state perception subsystem are connected with the control center through the internet of things gateway, diversified heterogeneous data generated by various electromechanical devices in the access tunnel can be compatible, and tunnel electromechanical integration and interconnection and intercommunication are achieved.
3. The traffic state sensing subsystem comprises a millimeter wave radar and a video camera, the millimeter wave radar converts the driving state of the vehicles running in the tunnel into a group of data representing the positions, speeds and lengths of the vehicles, realizes the datamation of the positions and speed information of the vehicles, obtains the lane dividing, vehicle dividing type vehicle flow statistics, average speed, head distance and road space occupancy data of the detection area, and sends the data to the control center.
4. The video camera monitors videos in the tunnel in real time, detects information of the millimeter wave radar is displayed on the videos through a video fusion technology and then sent to the control center, a target detected by the radar and a target on the videos shot by the video camera are correspondingly matched through the radar and video fusion detection technology, and object motion information detected by the radar is directly displayed on the video target, so that radar detection data are visualized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that for those skilled in the art, other relevant drawings can be obtained according to the drawings without inventive effort, wherein:
FIG. 1 is a system block diagram of a tunnel intelligent edge computing management and control system;
fig. 2 is a sectional view of a tunnel monitoring facility according to a first embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described herein and illustrated in the figures may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The features and properties of the present invention are described in further detail below with reference to examples and the accompanying drawings.
Example one
The invention provides an intelligent tunnel edge computing management and control system, which comprises a management and control center, a risk dynamic early warning subsystem, an electromechanical integrated subsystem and a traffic state perception subsystem, wherein the risk dynamic early warning subsystem, the electromechanical integrated subsystem and the traffic state perception subsystem are connected with the management and control center as shown in figure 1;
the risk dynamic early warning subsystem is used for monitoring the running state of execution equipment in the tunnel and the acquired data of the sensing equipment in real time, and performing abnormal warning and equipment inspection;
the electromechanical integrated subsystem is used for linking execution equipment in the tunnel and executing an emergency plan;
the traffic state perception subsystem visually perceives the traffic state of the tunnel through radar and video fusion detection technology, and detects traffic events;
the management and control center receives the running states of the execution equipment and the sensing equipment monitored by the risk dynamic early warning subsystem, issues a control command to the mechatronic subsystem, receives the traffic state sensed by the traffic state sensing subsystem, analyzes the traffic event and gives an alarm.
Specifically, the management and control center performs data optimization on diversified heterogeneous data of a tunnel site, achieves data aggregation and unified presentation of the data, uploads the data to the cloud, provides data with higher value for the cloud, avoids uploading invalid and useless data, occupies bandwidth, wastes cloud computing capacity and increases cloud computing cost.
Furthermore, the mechatronics subsystem, the risk dynamic early warning subsystem and the traffic state perception subsystem are connected with the control center through the internet of things gateway, communication protocols are different due to different electromechanical equipment manufacturers in the tunnel, and diversified heterogeneous data generated by various electromechanical equipment in the tunnel can be compatibly accessed through a protocol stack built in the internet of things gateway, so that the mechatronics and interconnection of the tunnel are realized; the gateway of the Internet of things comprises an MODBUS serial communication protocol, a FINS communication protocol, a 645 protocol, an MQTT transmission protocol or a private protocol, and is used for data collection and protocol conversion.
Further, the risk dynamic early warning subsystem comprises an execution device, a sensing device, a PLC (programmable logic controller) and a fire alarm controller;
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and sends self running state data and feedback data to the PLC;
the sensing equipment comprises a CO/VI detector, a wind speed and direction detector, a light intensity detector, a liquid level detector, a manual alarm button, a temperature sensing optical fiber/grating and a dual-wavelength detector, and sends self running state data and collected data to a PLC (programmable logic controller) and a fire alarm controller;
and the PLC and the fire alarm controller receive data information of the execution equipment and the sensing equipment and send the data information to the control center for analysis and processing.
Furthermore, the risk dynamic early warning subsystem is connected with an alarm management module and a risk defense module which are arranged in a management and control center;
after receiving the data of the PLC, the alarm management module performs risk identification according to a preset alarm threshold value and provides alarm management; the behavior characteristics of abnormal operation of the equipment can be automatically refined by utilizing stream data processing and a machine learning algorithm, and accurate early warning can be timely realized before the abnormal behavior is influenced; the alarm management comprises alarm rules, alarm monitoring, alarm processing and alarm notification.
Specifically, the risks include equipment failure and potential safety hazards; the equipment faults comprise abnormal operation states of illumination and a fan, and blurred images and stripes of a video camera; the potential safety hazards comprise that the water level of a high-level water pool and a low-level water pool in the tunnel is too low or leaks, and power supply and distribution facilities leak electricity and the like.
After the risk defense module receives the data of the PLC, a troubleshooting suggestion is provided for risks based on a built-in risk defense expert knowledge base; in order to solve the problem that the operation and maintenance personnel can not inspect all electromechanical equipment in daily inspection, the risk defense module can further receive data information of the execution equipment and the sensing equipment through one key, the data information comprises self running state data of the execution equipment and the sensing equipment, the operation and maintenance personnel can carry out remote all-around detection on the equipment without going out, and then a detailed inspection report is issued to serve as internal work data of daily inspection, so that the operation and maintenance efficiency of the operation and maintenance personnel is greatly improved.
Specifically, the dynamic risk early warning subsystem realizes real-time monitoring of the execution equipment in the tunnel by collecting control feedback data, power data and sensing data of the execution equipment and the sensing equipment in the tunnel and applying three core technologies of the internet of things, stream data processing and anomaly detection, and when abnormal data occurs to the equipment, the dynamic risk early warning subsystem actively warns and diagnoses accurately and provides a troubleshooting processing suggestion aiming at a diagnosis result.
Further, the mechatronic subsystem comprises an execution device and a PLC controller;
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and is automatically controlled by a PLC (programmable logic controller);
and the PLC receives a control command issued by the control center and controls the execution equipment to perform corresponding operation.
Specifically, various weather conditions outside the tunnel can be configured according to the light intensity and the traffic volume outside the tunnel, for example, various weather modes such as sunny days, cloudy days, heavy cloudy days, night, late night and the like, and then the illumination inside the tunnel can be controlled according to different weather conditions outside the tunnel, so that the light difference outside the tunnel inside the tunnel can be adjusted, the potential safety hazards such as 'black holes' and 'white holes' can be eliminated, and the energy conservation and consumption reduction can be realized;
the number of running fans, the steering and the running time of the fans can be controlled according to visibility data, CO concentration data and wind speed and wind direction data collected by sensing equipment in the tunnel, harmful gas and smoke in the tunnel are diluted, the good traffic environment of the tunnel is ensured, the fans with less running time can be started preferentially, and the control running of the fans with better service life is kept.
Furthermore, the mechatronic subsystem is connected with an emergency plan configuration module and a one-key emergency plan module which are arranged in the management and control center;
the emergency plan configuration module divides the tunnel into a plurality of tunnel accident areas according to the crossroads, each accident area configures different execution equipment linkage control schemes according to the position or the accident type, and sends corresponding control commands to the PLC, so that emergency plans can be configured for various conditions such as tunnel fire, traffic accidents, traffic jams and the like;
the one-key emergency plan module configures a corresponding execution equipment linkage control scheme according to a tunnel high-incidence accident and sends a corresponding control command to the PLC, wherein the tunnel high-incidence accident comprises a fire accident and a traffic accident.
Further, the traffic state perception subsystem comprises a millimeter wave radar, a video camera and a vehicle detector;
the millimeter wave radar converts the running state of the running vehicle in the tunnel into a group of data representing the position, speed and length of the vehicle, realizes the datamation of the position and speed information of the vehicle, obtains the traffic flow statistics, average speed, headway and road space occupancy data of the lane and the vehicle type of the detection area and sends the data to the control center; millimeter wave radar compares with optical detector such as infrared, the video, laser, the ability that penetrates fog, cigarette, the dust is stronger, can work under various weather, weather and light condition, can appear conflagration dense smoke visibility extremely low adverse circumstances work in the tunnel, the interference killing feature is stronger, millimeter wave radar possesses four-dimensional (X, Y, Z three-dimensional coordinate and one-dimensional speed) imaging technique simultaneously, even under the conflagration dense smoke scene, also can show vehicle and personnel are visual in the tunnel, make things convenient for control personnel and fire fighter to guide personnel to evacuate through the broadcast pertinence, and rescue, a large amount of casualties and excessive rescue have been avoided.
Specifically, in the embodiment, in order to facilitate installation of the millimeter wave radar, and to connect power supply and network communication, the ideal installation position is the installation position of the fixed camera in the tunnel, the radar installed on one side of the tunnel can cover a plurality of lanes, the installation position of the fixed camera is as shown in fig. 2, the installation height of the camera is 4m away from the access way, the camera is installed on the right side wall of the tunnel, generally 150m, and the camera is arranged to fully cover and monitor all areas in the tunnel, the number of the radar waves is properly increased at the turning position of the tunnel, and the radar is installed at the position of the circumscribed line of the arc line of the tunnel hole to obtain the optimal coverage rate, so that the farthest position of each edge can be seen; the specific parameters of the millimeter wave radar are as follows:
the vehicle-mounted intelligent detection system is provided with two communication interfaces of an RS-485 serial port and an RJ-45 Ethernet simultaneously, is consistent with a video camera power supply, adopts a 12V direct-current power supply, can detect 3 or more lanes simultaneously, detects 64 targets simultaneously, detects the number of coming vehicles/going vehicles/two directions simultaneously, provides accurate real-time speed, has the speed range of 260-130 KM/h, provides accurate positioning distance, has the distance range of 1.5-200 m, has the protection grade of more than IP65 and has the temperature range of-40-55 ℃.
The video camera monitors real-time video in the tunnel, displays detection information of the millimeter wave radar on the video by using a video fusion technology, and then sends the detection information to the control center; the millimeter wave radar has a four-dimensional imaging technology and a visual condition, so that the millimeter wave radar can be well fused with a video, a target detected by the radar is correspondingly matched with a target on the video shot by a video camera, and the motion information of an object detected by the radar, including a vehicle target, time, position, direction, speed, average speed, distance, lane number, flow, lane occupancy, queuing length and the like, is directly displayed on the video target, so that the visualization of radar detection data is realized.
Specifically, the traffic state sensing subsystem can realize the visual situation sensing of the tunnel traffic state by adopting radar and video fusion detection technology on the basis of the monitoring of the existing video camera, and solves the problems that the video detection is easily influenced by weather, light and climate, and the blind area exists in the fixed video camera of the tunnel, so that the detection data is inaccurate, and the problems of missing report, false report and the like are easily caused; the reliability of single video detection is enhanced, all areas of the tunnel are covered, and no blind area exists; by adopting multi-radar linkage, the same target can be tracked; the camera finely classifies the target object through deep learning, and the millimeter wave radar completes detection and identification of the movement speed, distance, angle and the like of the target object, so that the precision and the reliability of target detection are greatly improved, and the false alarm rate is reduced.
Furthermore, the traffic state perception subsystem is connected with a vehicle behavior analysis module, an event detection module and a linkage control module which are arranged in a management and control center, and the vehicle behavior analysis module and the event detection module are connected with the linkage control module;
the vehicle behavior analysis module is used for carrying out behavior analysis on the driving state data of the vehicle and analyzing whether the conditions of parking, slow running, overspeed, reverse running and long-time occupation of an emergency parking zone exist or not;
the event detection module is used for carrying out event detection on the driving state data of the vehicle, so that detection of pedestrians, animals, sprinkled objects, traffic jam and vehicle detour is realized, an alarm is given, special events of the tunnel are found in time, further deterioration of adverse events is effectively avoided, and automatic monitoring inside and outside the tunnel is realized;
the linkage control module is connected with the video camera, the variable information board, the vehicle detector, the emergency telephone and the broadcast, and issues corresponding early warning information and traffic guidance information according to the accident types analyzed and obtained by the vehicle behavior analysis module and the event detection module.
Specifically, a display interface of the control center is combined with a background tunnel simulation diagram, tracking tracks and event alarm are visually displayed, the control center has a background filtering function, fixed objects installed in the tunnel are filtered, and only moving and newly-added targets are monitored; the vehicle type is also identified by radar, including large, medium and small vehicles.
The working process is as follows:
because take place easily in the tunnel and cause the loss, influence serious emergency mainly for the fire incident, the fire incident is used as the example to this embodiment, disposes the emergent scheme of a key formula of fire incident, and specific work flow includes:
1. and (3) fire monitoring and alarming:
when a fire hazard occurs in the tunnel, a flame detector of the risk dynamic early warning subsystem sends acquired information to a PLC (programmable logic controller), the PLC sends fire hazard warning information to a control center, meanwhile, a video camera of the traffic state sensing subsystem uploads a monitoring picture of the control center, a fire hazard condition is automatically identified through an event detection module to give a warning, the warning can also be given through manual warning, the warning is sent to the control center, the control center gives a fire hazard warning in a unified mode, and sound and light warning is sent out to remind monitoring personnel of the fire hazard occurring in the tunnel;
2. and (3) fire disaster confirmation:
the method comprises the following steps that when receiving fire alarm information of a flame detector, a control center automatically switches to video pictures of video cameras of a fire alarm point, specifically, the pictures of two video cameras in front of and behind the fire alarm point and the pictures of two video cameras at a tunnel entrance, and monitoring personnel can confirm whether a tunnel has a fire or not and the true fire occurrence position through videos; after the confirmation, displaying a flow chart of popping up the emergency plan on the interface, guiding the monitoring personnel to carry out accident disposal, and executing all flows and tasks of the emergency plan; meanwhile, prompting a corresponding notice to a display interface, wherein the notice comprises alarm information and a contact way of an emergency rescue related mechanism, and monitoring personnel can report fire emergency information in time through the prompted alarm information and the contact way;
3. and (3) release or modification of a plan:
the emergency plan flow chart popped up from the display interface is manually confirmed or modified and then can be released; meanwhile, the control center also links the variable information board and the emergency broadcast by the linkage control module to release the early warning information and the traffic guidance information;
4. the plan execution process comprises the following steps:
after the plan is issued, the control center sends a corresponding control instruction to a PLC (programmable logic controller) of the mechatronic subsystem, and the PLC correspondingly controls the execution equipment to work, namely, the illumination, the fan, the video camera, the lane indicator, the traffic signal lamp and the crosshole roller shutter door are correspondingly subjected to preset operation; when the system executes the emergency plan, the risk dynamic early warning subsystem continuously uploads the running state of the execution equipment and the acquired data of the sensing equipment to the control center, and the execution process of the emergency plan is monitored; monitoring personnel can manually control the fan and issue traffic guidance information according to the video pictures and the tunnel site conditions;
5. accident treatment:
after the monitoring personnel confirm that the fire accident of the tunnel is completely processed, the monitoring personnel control the devices such as the lighting device, the fan, the lane indicating lamp, the cross-hole roller shutter door and the like of the tunnel to be recovered to a normal working state in the control center, and the tunnel is recovered to a normal traffic state; and the control center of the system automatically records the relevant information of the whole process of executing the emergency plan and records the video, thereby providing a basis for the improvement of the accident, the summary of the experience and the revision of the emergency plan.
The operation state of the execution equipment in the tunnel and the acquired data of the sensing equipment are monitored in real time through the risk dynamic early warning subsystem, warning and risk identification are carried out in time, active early warning and accurate diagnosis are carried out, and a troubleshooting treatment suggestion is provided according to a diagnosis result; then, a control command is issued to the mechatronic subsystem through the pipe control center to control the operation of executing equipment in the tunnel, an emergency plan is also set in an emergency situation, corresponding control is carried out according to the emergency plan, the time required for emergency after an accident occurs is shortened, the operation steps of monitoring personnel are reduced, and the work efficiency is improved; the traffic state of the tunnel is visually perceived through a radar and video fusion detection technology of the traffic state perception subsystem, traffic events are analyzed, warning is given, reliability of single video detection is enhanced, further deterioration of adverse events is effectively avoided, and automatic monitoring inside and outside the tunnel hole is achieved. The invention realizes the monitoring of the tunnel electromechanical equipment through edge calculation, and has important significance for ensuring the safety of the vehicle passing in the tunnel.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents and improvements made by those skilled in the art within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. The utility model provides a management and control system is calculated at tunnel intelligence edge which characterized in that: the system comprises a management and control center, a risk dynamic early warning subsystem, an electromechanical integrated subsystem and a traffic state perception subsystem, wherein the risk dynamic early warning subsystem, the electromechanical integrated subsystem and the traffic state perception subsystem are connected with the management and control center;
the risk dynamic early warning subsystem is used for monitoring the running state of execution equipment in the tunnel and the acquired data of the sensing equipment in real time, and performing abnormal warning and equipment inspection;
the electromechanical integrated subsystem is used for linking execution equipment in the tunnel and executing an emergency plan;
the traffic state perception subsystem visually perceives the traffic state of the tunnel through radar and video fusion detection technology, and detects traffic events;
the management and control center receives the running states of the execution equipment and the sensing equipment monitored by the risk dynamic early warning subsystem, issues a control command to the mechatronic subsystem, receives the traffic state sensed by the traffic state sensing subsystem, analyzes the traffic event and gives an alarm.
2. The intelligent edge computing management and control system for tunnels according to claim 1, wherein: the electromechanical integrated subsystem, the risk dynamic early warning subsystem and the traffic state perception subsystem are connected with the management and control center through the internet of things gateway.
3. The intelligent edge computing management and control system for tunnels according to claim 1, wherein: the risk dynamic early warning subsystem comprises execution equipment, sensing equipment, a PLC (programmable logic controller) and a fire alarm controller;
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and sends self running state data and feedback data to the PLC;
the sensing equipment comprises a CO/VI detector, a wind speed and direction detector, a light intensity detector, a liquid level detector, a manual alarm button, a temperature sensing optical fiber/optical grating and a dual-wavelength detector, and sends self running state data and acquired data to the PLC and the fire alarm controller;
and the PLC and the fire alarm controller receive data information of the execution equipment and the sensing equipment and send the data information to the control center for analysis and processing.
4. The intelligent edge computing management and control system for tunnels according to claim 3, wherein: the risk dynamic early warning subsystem is connected with an alarm management module and a risk defense module which are arranged in a management and control center;
after receiving the data of the PLC, the alarm management module performs risk identification according to a preset alarm threshold value and provides alarm management;
after the risk defense module receives the data of the PLC, a troubleshooting suggestion is provided for risks based on a built-in risk defense expert knowledge base.
5. The intelligent edge computing management and control system for tunnels according to claim 1, wherein: the mechatronic subsystem comprises execution equipment and a PLC (programmable logic controller);
the execution equipment comprises an illumination device, a fan, a lane indicator, a traffic signal lamp and a cross tunnel roller shutter door, and is automatically controlled by a PLC (programmable logic controller);
and the PLC receives a control command issued by the control center and controls the execution equipment to perform corresponding operation.
6. The intelligent edge computing management and control system for tunnels according to claim 5, wherein: the electromechanical integrated subsystem is connected with an emergency plan configuration module and a one-key emergency plan module which are arranged in a management and control center;
the emergency plan configuration module divides the tunnel into a plurality of tunnel accident areas according to the driving crosshole, each accident area configures different execution equipment linkage control schemes according to the position or the accident type, and sends corresponding control commands to the PLC;
the one-key emergency plan module configures a corresponding execution equipment linkage control scheme according to a tunnel high-incidence accident and sends a corresponding control command to the PLC, wherein the tunnel high-incidence accident comprises a fire accident and a traffic accident.
7. The intelligent edge computing management and control system for tunnels according to claim 1, wherein: the traffic state perception subsystem comprises a millimeter wave radar, a video camera and a vehicle detector;
the millimeter wave radar converts the running state of the running vehicle in the tunnel into a group of data representing the position, speed and length of the vehicle, obtains the traffic flow statistics, average speed, headway and road space occupancy data of lane division and vehicle division types of the detection area, and sends the data to the control center;
the video camera monitors real-time video in the tunnel, displays detection information of the millimeter wave radar on the video by using a video fusion technology, and then sends the detection information to the control center.
8. The intelligent edge computing management and control system for tunnels according to claim 7, wherein: the traffic state perception subsystem is connected with a vehicle behavior analysis module, an event detection module and a linkage control module which are arranged in a management and control center, and the vehicle behavior analysis module and the event detection module are connected with the linkage control module;
the vehicle behavior analysis module is used for carrying out behavior analysis on the driving state data of the vehicle and analyzing whether the conditions of parking, slow running, overspeed, reverse running and long-time occupation of an emergency parking zone exist or not;
the event detection module is used for carrying out event detection on the driving state data of the vehicle, so that detection of pedestrians, animals, sprinkles, traffic jam and vehicle detour is realized;
the linkage control module is connected with the video camera, the variable information board, the vehicle detector, the emergency telephone and the broadcast, and issues corresponding early warning information and traffic guidance information according to the accident types analyzed and obtained by the vehicle behavior analysis module and the event detection module.
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Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111752253A (en) * | 2020-07-28 | 2020-10-09 | 上海海得控制系统股份有限公司 | Tunnel illumination and exhaust control system and method based on intelligent gateway |
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| CN115148024A (en) * | 2022-06-23 | 2022-10-04 | 广州国交润万交通信息有限公司 | Novel tunnel safety monitoring method and system |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102023599A (en) * | 2010-02-11 | 2011-04-20 | 北京瑞华赢科技发展有限公司 | Tunnel monitoring system |
| CN103247125A (en) * | 2013-04-03 | 2013-08-14 | 昆明联诚科技有限公司 | Expressway tunnel fire control linkage system and control method |
| CN106228484A (en) * | 2016-07-14 | 2016-12-14 | 河北上元工控技术有限公司 | A kind of medium tunnel intelligent total management system and management method |
| CN107065730A (en) * | 2017-05-26 | 2017-08-18 | 安徽皖通科技股份有限公司 | Freeway tunnel safe operation intelligent monitor system |
| CN108038812A (en) * | 2017-12-29 | 2018-05-15 | 中铁局集团电务工程有限公司 | A kind of municipal tunnel intelligent comprehensive commander's managing and control system based on deep layer intergration model |
| KR101885682B1 (en) * | 2017-07-21 | 2018-08-06 | 주식회사 아이비테크 | Remote management system for tunnel |
| CN108376473A (en) * | 2018-04-28 | 2018-08-07 | 招商局重庆交通科研设计院有限公司 | Roads and tunnels traffic Warning System based on vehicle operational monitoring |
| CN109443440A (en) * | 2018-12-13 | 2019-03-08 | 江苏久创电气科技有限公司 | Tunnel comprehensive monitoring system |
| CN109887221A (en) * | 2019-03-13 | 2019-06-14 | 杭州图析同创科技有限公司 | A kind of fire disaster intelligently detection system and its control method |
| CN110473402A (en) * | 2019-08-20 | 2019-11-19 | 河北德冠隆电子科技有限公司 | A kind of accident detection early warning system based on target abnormal behaviour trajectory analysis |
| CN110570664A (en) * | 2019-09-23 | 2019-12-13 | 山东科技大学 | automatic detection system for highway traffic incident |
-
2020
- 2020-02-25 CN CN202010116732.2A patent/CN111325977A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102023599A (en) * | 2010-02-11 | 2011-04-20 | 北京瑞华赢科技发展有限公司 | Tunnel monitoring system |
| CN103247125A (en) * | 2013-04-03 | 2013-08-14 | 昆明联诚科技有限公司 | Expressway tunnel fire control linkage system and control method |
| CN106228484A (en) * | 2016-07-14 | 2016-12-14 | 河北上元工控技术有限公司 | A kind of medium tunnel intelligent total management system and management method |
| CN107065730A (en) * | 2017-05-26 | 2017-08-18 | 安徽皖通科技股份有限公司 | Freeway tunnel safe operation intelligent monitor system |
| KR101885682B1 (en) * | 2017-07-21 | 2018-08-06 | 주식회사 아이비테크 | Remote management system for tunnel |
| CN108038812A (en) * | 2017-12-29 | 2018-05-15 | 中铁局集团电务工程有限公司 | A kind of municipal tunnel intelligent comprehensive commander's managing and control system based on deep layer intergration model |
| CN108376473A (en) * | 2018-04-28 | 2018-08-07 | 招商局重庆交通科研设计院有限公司 | Roads and tunnels traffic Warning System based on vehicle operational monitoring |
| CN109443440A (en) * | 2018-12-13 | 2019-03-08 | 江苏久创电气科技有限公司 | Tunnel comprehensive monitoring system |
| CN109887221A (en) * | 2019-03-13 | 2019-06-14 | 杭州图析同创科技有限公司 | A kind of fire disaster intelligently detection system and its control method |
| CN110473402A (en) * | 2019-08-20 | 2019-11-19 | 河北德冠隆电子科技有限公司 | A kind of accident detection early warning system based on target abnormal behaviour trajectory analysis |
| CN110570664A (en) * | 2019-09-23 | 2019-12-13 | 山东科技大学 | automatic detection system for highway traffic incident |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111830924A (en) * | 2020-08-04 | 2020-10-27 | 郑州信大先进技术研究院 | Unified management and linkage control system and method for internal facilities of building engineering |
| CN111830924B (en) * | 2020-08-04 | 2021-06-11 | 郑州信大先进技术研究院 | Unified management and linkage control system and method for internal facilities of building engineering |
| CN111857082A (en) * | 2020-08-14 | 2020-10-30 | 昆山同日工业自动化有限公司 | Intelligent workshop remote diagnosis control system based on 5G network |
| CN112419629A (en) * | 2020-10-12 | 2021-02-26 | 航天科工广信智能技术有限公司 | Emergency parking area alarm system |
| CN112560610A (en) * | 2020-12-03 | 2021-03-26 | 西南交通大学 | Video monitoring object analysis method, device, equipment and readable storage medium |
| CN113296460A (en) * | 2021-01-22 | 2021-08-24 | 陕西交通电子工程科技有限公司 | A management and control system is synthesized in wisdom tunnel for highway |
| CN113299067A (en) * | 2021-05-24 | 2021-08-24 | 上海市政工程设计研究总院（集团）有限公司 | Tunnel access & exit safety control system based on video perception technology |
| CN113298400A (en) * | 2021-06-01 | 2021-08-24 | 江西锦路科技开发有限公司 | Based onWebGLIntelligent monitoring system for highway tunnel |
| CN113990018B (en) * | 2021-09-15 | 2024-01-12 | 上海腾盛智能安全科技股份有限公司 | Safety risk prediction system |
| CN113990018A (en) * | 2021-09-15 | 2022-01-28 | 上海腾盛智能安全科技股份有限公司 | Safety risk prediction system |
| CN113923414A (en) * | 2021-10-10 | 2022-01-11 | 浙江机电职业技术学院 | Three-section type tunnel vision comprehensive monitoring and control system |
| CN113936463A (en) * | 2021-10-19 | 2022-01-14 | 上海交通大学 | Tunnel traffic control method and system based on radar and video data fusion |
| CN113936463B (en) * | 2021-10-19 | 2022-08-16 | 上海交通大学 | Tunnel traffic control method and system based on radar and video data fusion |
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| CN113920744A (en) * | 2021-12-15 | 2022-01-11 | 陕西易合交通科技有限公司 | Tunnel portal traffic safety monitoring and early warning system based on Internet of things |
| CN114333303B (en) * | 2021-12-20 | 2022-12-16 | 武汉微创光电股份有限公司 | Highway tunnel monitoring data fusion processing system |
| CN114333303A (en) * | 2021-12-20 | 2022-04-12 | 武汉微创光电股份有限公司 | Highway tunnel monitoring data fusion processing system |
| CN114483195A (en) * | 2022-01-27 | 2022-05-13 | 青岛市城市规划设计研究院 | Long tunnel emergency evacuation safety early warning indicating system based on edge calculation |
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Application publication date: 20200623 |
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