CN112446077A - Comprehensive pipe rack operation and maintenance risk assessment system and method based on big data - Google Patents
Comprehensive pipe rack operation and maintenance risk assessment system and method based on big data Download PDFInfo
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Abstract
The invention relates to a big data-based comprehensive pipe rack operation and maintenance risk assessment system which comprises a cloud server, a city big data center, an AI-based data processing server, a third-party server platform, a pipe rack remote operation and maintenance terminal, a pipe rack on-site monitoring terminal, an Internet of things communication service network and an Internet service network, wherein the AI-based data processing server is respectively in data connection with the pipe rack remote operation and maintenance terminal and the pipe rack on-site monitoring terminal through the Internet of things communication service network; and the AI-based data processing server is respectively in data connection with the cloud server, the urban big data center and the third-party server platform through an Internet service network. On one hand, the system expansibility, compatibility and fault resistance of the invention are greatly improved; on the other hand, the system can monitor and manage data to acquire comprehensively and high in precision, can comprehensively early warn and monitor the running state of the pipe gallery system, and can timely find potential safety hazards in the running process of the pipe gallery system.
Description
Technical Field
The invention relates to a management corridor system monitoring and management system and method, in particular to a comprehensive corridor operation and maintenance risk assessment system and method based on big data.
Background
The city comprehensive pipe gallery system bears a great amount of city power, gas and other power systems, communication network systems, water supply and drainage systems and other city equipment facility installation, operation, management and maintenance works, plays an increasingly important role in current city construction and planning, and is developed and applied in pipe gallery construction and maintenance based on GIS and BIM three-dimensional modeling technology in the daily maintenance and management work of the pipe gallery system, so that the need of three-dimensional modeling and visual monitoring work of the pipe gallery equipment is effectively realized, but in the actual operation and maintenance of the pipe gallery, the current pipe gallery supervision system can only realize supervision on the internal environment information, equipment operation information and personnel state of the pipe gallery, and can not comprehensively monitor the operating state of the pipe gallery by factors such as city surface building change, pipe gallery peripheral geological structure change, pipe gallery self structure deformation and precipitation, underground water level, city energy supply scheduling and the like, and the operation safety hidden danger caused by external factors and internal factors in the pipe gallery cloud cannot be pre-judged and pre-warned in time, so that the current stability of the operation of the pipe gallery equipment and the great hidden danger in the reliability management and maintenance work exist.
Therefore, aiming at the current situation, a brand-new pipe rack operation and maintenance risk early warning system and method are urgently needed to be developed so as to meet the requirement of actual operation, maintenance and management operation of a pipe rack system.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a brand-new explosion venting device applied to a container top cover, so as to overcome the defects of the traditional equipment in operation and improve the stability, safety and reliability of the equipment in operation. In order to achieve the purpose, the invention is realized by the following technical scheme:
a big data-based comprehensive pipe rack operation and maintenance risk assessment system comprises a cloud server, a city big data center, an AI-based data processing server, a third-party server platform, a pipe rack remote operation and maintenance terminal, a pipe rack on-site monitoring terminal, an Internet of things communication service network and an Internet service network, wherein the AI-based data processing server is respectively in data connection with the pipe rack remote operation and maintenance terminal and the pipe rack on-site monitoring terminal through the Internet of things communication service network and constructs a pipe rack operation and maintenance data service network layer; the AI-based data processing server establishes data connection with the cloud server, the urban big data center and the third-party server platform through an Internet service network respectively and forms a remote early warning data service network layer; the pipe gallery site monitoring terminal is a plurality of, and each pipe gallery site monitoring terminal is all through thing networking communication service network thoughtlessly and with the long-range fortune of pipe gallery terminal connection, constitutes the pipe gallery site data acquisition layer.
Furthermore, the AI-based data processing servers are at least two, and the AI-based data processing servers are connected with each other through an Internet service network.
Further, the third-party server platform comprises any one or more of a network payment platform, an identity recognition platform, a logistics information platform and an electronic commerce service platform.
Further, the remote operation and maintenance terminal of the pipe gallery comprises an intelligent communication gateway, a data processing server, a data output device and a console, wherein the console is respectively connected with the data processing server, the data output device and the communication service network of the internet of things through the intelligent communication gateway,
furthermore, the control platform is a circuit system based on one or two of an internet-of-things controller and a programmable controller; the data output device is any one or more of a loudspeaker, a display and a signal indicator lamp.
Further, piping lane on-site monitoring terminal includes access control system, surveillance camera head, three-dimensional scanning camera and on-site monitoring sensor, wherein access control system is a plurality of, inlays in each door department of piping lane system, in surveillance camera head, the three-dimensional scanning camera, a surveillance camera head and a three-dimensional scanning camera are parallelly connected and constitute a detection group, detection group is a plurality of, along piping lane axis direction equipartition at piping lane side lateral wall and top, on-site monitoring sensor is a plurality of, and 3-10 on-site monitoring sensor constitutes a work group, work group is a plurality of, along the piping lane axis direction equipartition on piping lane side lateral wall, top and horizon, and each on-site monitoring sensor in the same work group encircles piping lane axis equipartition.
Further, the on-site monitoring sensor comprises any one or more of a temperature and humidity sensor, a gas sensor, a water level sensor, a grating advance warning sensor, a stress strain sensor, an FBG displacement sensor, a water pressure sensor, a displacement sensor, a strain micro-vibration sensor, a flow velocity and flow rate sensor, a liquid level sensor, a current sensor, a voltage sensor, a COD sensor, a pH sensor and a concentration touch sensor.
Furthermore, the communication service network of the internet of things adopts any one or two of nested architectures of a C/S structure and a B/S structure.
A use method of a comprehensive pipe rack operation and maintenance risk assessment system based on big data comprises the following steps:
s1, system networking, namely, firstly, installing and fixing each pipe gallery field monitoring terminal at a designated working position of a pipe gallery system, then installing a data processing server and a pipe gallery remote operation and maintenance terminal based on an AI base at a designated pipe gallery operation and maintenance management working position, then establishing data connection among the data processing server, the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal based on the AI base through an Internet of things communication service network, finally establishing data connection among the data processing server based on the AI base, a cloud server, a city big data center and a third-party server platform, using the data processing server based on the AI base to coordinate a communication service protocol, and allocating independent communication addressing addresses for the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal, thereby completing the networking of the invention;
s2, three-dimensional modeling, completing S1 steps, firstly obtaining ground surface buildings, pipe network layout structures, geological structure basic data information, city basic geographic information and current pipe gallery system construction design drawing information around the current pipe gallery system construction range through a city big data center and a third-party server platform by an AI-based data processing server, then establishing a current pipe gallery system and a surrounding city facility basic three-dimensional model information database thereof through a BIM three-dimensional modeling system according to the obtained data, rendering and assigning values to each coordinate point in the three-dimensional model information database through a GIS system, finally inputting the pipe gallery system data collected by each pipe gallery field monitoring terminal into an integral three-dimensional model information database through the GIS system, obtaining a pipe gallery system three-dimensional visual data model, storing the pipe gallery system three-dimensional visual data model data in a cloud server on one hand, on the other hand, the display is output through a remote operation and maintenance terminal of the pipe gallery;
s3, actively carrying out risk early warning, and after the step S2 is completed, continuously monitoring the building structure of the pipe gallery system and the running states of equipment and facilities in the pipe gallery system by the pipe gallery on-site monitoring terminal in 24-hour continuous work and updating data; the AI-based data processing server is connected with the urban big data center and the third-party server platform in a period of 0.5-3 hours and performs data updating; finally, inputting the updated data into the three-dimensional visual data model of the pipe gallery system in the step S2, outputting and displaying the data, and meanwhile, caching and recording the updated data through a cloud server;
and S4, passive risk early warning, in the step S3 of executing active risk early warning, when the AI-based data processing server is in a standby state between two adjacent time contacts for data updating, and when threat data are generated in the city big data center and the third-party server platform for operation of the pipe gallery system, the city big data center and the third-party server platform actively push data to the AI-based data processing server through the Internet service network, the AI-based data processing server updates data according to the push data on the one hand to the three-dimensional visual data model of the pipe gallery system in the step S2, and the AI-based data processing server sends early warning to the pipe gallery remote operation and maintenance terminal on the other hand, and the pipe gallery remote operation and maintenance terminal drives the pipe gallery system to respond according to the push early warning data.
Further, in the steps S1 and S4, the city big data center provides any one or more of data of energy supply distribution, rainfall, air temperature, ground water, earthquake, building construction, and the like to the AI-based data processing server.
On one hand, the system has simple structure and strong data communication processing capacity, and has good modularization and integration capacity, thereby greatly improving the expansibility, compatibility and fault resistance of the system, and being beneficial to reducing the cost and labor intensity of daily management maintenance operation of the system and daily management polling operation of a pipe gallery system; on the other hand can effectively satisfy the needs of the daily control management operation of all kinds of piping lane equipment, and control management data acquisition is comprehensive and the precision is high to very big improvement the flexibility convenience when the daily supervision operation data of piping lane system acquire and read, thereby reach the comprehensive early warning control to piping lane system running state, in time discover that there is the potential safety hazard in the piping lane system operation process, thereby effectively improve the reliability and the stability of piping lane system operation.
Drawings
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a schematic structural diagram of a schematic diagram of a pipe gallery remote operation and maintenance terminal system;
FIG. 3 is a schematic structural view of a pipe gallery on-site monitoring terminal;
FIG. 4 is a flow chart illustrating a method of using the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained by taking hydrogen as an example in combination with the specific implementation mode.
As shown in fig. 1-3, a big data-based utility tunnel operation and maintenance risk assessment system includes a cloud server 1, a city big data center 2, an AI-based data processing server 3, a third-party server platform 4, a pipe gallery remote operation and maintenance terminal 5, a pipe gallery on-site monitoring terminal 6, an internet of things communication service network 7 and an internet service network 8, wherein the AI-based data processing server 3 establishes data connections with the pipe gallery remote operation and maintenance terminal 5 and the pipe gallery on-site monitoring terminal 6 through the internet of things communication service network 7, and constructs a pipe gallery operation and maintenance data service network layer; the AI-based data processing server 3 establishes data connection with the cloud server 1, the city big data 2 center and the third-party server platform 4 through the Internet service network 8 respectively, and forms a remote early warning data service network layer; pipe gallery on-site monitoring terminal 6 is a plurality of, and each pipe gallery on-site monitoring terminal 6 all mixes and is connected with the long-range fortune of pipe gallery terminal connection through thing networking communication service network, constitutes the on-site data acquisition layer of pipe gallery.
In this embodiment, there are at least two AI-based data processing servers 3, and the AI-based data processing servers 3 are connected to each other through an internet service network 8; the third-party server platform comprises any one or more of a 4-network payment platform, an identity recognition platform, a logistics information platform and an electronic commerce service platform.
Meanwhile, the pipe gallery remote operation and maintenance terminal 5 includes an intelligent communication gateway 51, a data processing server 52, a data output device 53 and a console 54, wherein the console 54 establishes data connection with the data processing server 52, the data output device 53 and the internet of things communication service network 7 through the intelligent communication gateway 51,
preferably, the control platform 54 is a circuit system based on one or two of an internet-of-things controller and a programmable controller; the data output device 53 is any one or more of a loudspeaker, a display and a signal indicator lamp.
What point explain, piping lane on-site monitoring terminal 6 includes access control system 61, surveillance camera head 62, three-dimensional scanning camera 63 and on-site monitoring sensor 64, wherein access control system 61 is a plurality of, inlays in each door department of piping lane system, in surveillance camera head 62, the three-dimensional scanning camera 63, a surveillance camera head 62 and a three-dimensional scanning camera 63 are parallelly connected and constitute a detection group, detection group is a plurality of, along piping lane axis direction equipartition at piping lane lateral wall and top, on-site monitoring sensor 64 is a plurality of, and 3-10 on-site monitoring sensor 64 constitute a workgroup, workgroup is a plurality of, along the equipartition of piping lane axis direction on piping lane lateral wall, top and horizon, and each on-site monitoring sensor 64 in the same workgroup encircles the piping lane axis equipartition.
Further preferably, the on-site monitoring sensor 64 includes one or more of a temperature and humidity sensor, a gas sensor, a water level sensor, a grating advance warning sensor, a stress strain sensor, an FBG displacement sensor, a water pressure sensor, a displacement sensor, a strain micro-vibration sensor, a flow rate and flow sensor, a liquid level sensor, a current sensor, a voltage sensor, a COD sensor, a pH sensor and a concentration touch sensor.
In this embodiment, the internet of things communication service network 7 uses any one or two of the nested architectures of the C/S structure and the B/S structure.
As shown in fig. 4, a method for using a big data-based utility tunnel operation and maintenance risk assessment system includes the following steps:
s1, system networking, namely, firstly, installing and fixing each pipe gallery field monitoring terminal at a designated working position of a pipe gallery system, then installing a data processing server and a pipe gallery remote operation and maintenance terminal based on an AI base at a designated pipe gallery operation and maintenance management working position, then establishing data connection among the data processing server, the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal based on the AI base through an Internet of things communication service network, finally establishing data connection among the data processing server based on the AI base, a cloud server, a city big data center and a third-party server platform, using the data processing server based on the AI base to coordinate a communication service protocol, and allocating independent communication addressing addresses for the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal, thereby completing the networking of the invention;
s2, three-dimensional modeling, completing S1 steps, firstly obtaining ground surface buildings, pipe network layout structures, geological structure basic data information, city basic geographic information and current pipe gallery system construction design drawing information around the current pipe gallery system construction range through a city big data center and a third-party server platform by an AI-based data processing server, then establishing a current pipe gallery system and a surrounding city facility basic three-dimensional model information database thereof through a BIM three-dimensional modeling system according to the obtained data, rendering and assigning values to each coordinate point in the three-dimensional model information database through a GIS system, finally inputting the pipe gallery system data collected by each pipe gallery field monitoring terminal into an integral three-dimensional model information database through the GIS system, obtaining a pipe gallery system three-dimensional visual data model, storing the pipe gallery system three-dimensional visual data model data in a cloud server on one hand, on the other hand, the display is output through a remote operation and maintenance terminal of the pipe gallery;
s3, actively carrying out risk early warning, and after the step S2 is completed, continuously monitoring the building structure of the pipe gallery system and the running states of equipment and facilities in the pipe gallery system by the pipe gallery on-site monitoring terminal in 24-hour continuous work and updating data; the AI-based data processing server is connected with the urban big data center and the third-party server platform in a period of 0.5-3 hours and performs data updating; finally, inputting the updated data into the three-dimensional visual data model of the pipe gallery system in the step S2, outputting and displaying the data, and meanwhile, caching and recording the updated data through a cloud server;
and S4, passive risk early warning, in the step S3 of executing active risk early warning, when the AI-based data processing server is in a standby state between two adjacent time contacts for data updating, and when threat data are generated in the city big data center and the third-party server platform for operation of the pipe gallery system, the city big data center and the third-party server platform actively push data to the AI-based data processing server through the Internet service network, the AI-based data processing server updates data according to the push data on the one hand to the three-dimensional visual data model of the pipe gallery system in the step S2, and the AI-based data processing server sends early warning to the pipe gallery remote operation and maintenance terminal on the other hand, and the pipe gallery remote operation and maintenance terminal drives the pipe gallery system to respond according to the push early warning data.
Preferably, in the steps S1 and S4, the city big data center provides any one or more of data of energy supply distribution, rainfall, air temperature, underground water, earthquake, building construction, and the like for the AI-based data processing server.
On one hand, the system has simple structure and strong data communication processing capacity, and has good modularization and integration capacity, thereby greatly improving the expansibility, compatibility and fault resistance of the system, and being beneficial to reducing the cost and labor intensity of daily management maintenance operation of the system and daily management polling operation of a pipe gallery system; on the other hand can effectively satisfy the needs of the daily control management operation of all kinds of piping lane equipment, control management data and acquire comprehensively and the precision is high to very big improvement the flexibility convenience when daily supervision operation data of piping lane system acquire and read, thereby reach to the comprehensive early warning control of piping lane system running state, in time discover that there is the potential safety hazard in the piping lane system operation process, thereby effectively improve reliability and the stability of piping lane system operation
It will be appreciated by persons skilled in the art that the present invention is not limited by the embodiments described above. The foregoing embodiments and description have been presented only to illustrate the principles of the invention. Various changes and modifications can be made without departing from the spirit and scope of the invention. Such variations and modifications are intended to be within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The utility model provides a utility tunnel fortune dimension risk assessment system based on big data which characterized in that: the comprehensive pipe rack operation and maintenance risk assessment system based on big data comprises a cloud server, a city big data center, a data processing server based on an AI base, a third-party server platform, a pipe rack remote operation and maintenance terminal, a pipe rack on-site monitoring terminal, an Internet of things communication service network and an Internet service network, wherein the data processing server based on the AI base is respectively in data connection with the pipe rack remote operation and maintenance terminal and the pipe rack on-site monitoring terminal through the Internet of things communication service network and constructs a pipe rack operation and maintenance data service network layer; the AI-based data processing server establishes data connection with the cloud server, the urban big data center and the third-party server platform through an Internet service network respectively and forms a remote early warning data service network layer; the pipe rack site monitoring terminal is a plurality of, and each pipe rack site monitoring terminal is connected with the long-range fortune of pipe rack maintenance terminal through thing networking communication service network thoughtlessly, constitutes the on-the-spot data acquisition layer of pipe rack.
2. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 1, characterized in that: the AI-based data processing servers are connected with each other through an Internet service network.
3. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 1, characterized in that: the third-party server platform comprises any one or more of a network payment platform, an identity recognition platform, a logistics information platform and an electronic commerce service platform.
4. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 1, characterized in that: the remote operation and maintenance terminal of the pipe rack comprises an intelligent communication gateway, a data processing server, a data output device and a console, wherein the console is respectively connected with the data processing server, the data output device and a communication service network of the Internet of things through the intelligent communication gateway to establish data connection.
5. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 4, wherein: the control platform is a circuit system based on any one or two public functions of an internet-of-things controller and a programmable controller; the data output device is any one or more of a loudspeaker, a display and a signal indicator lamp.
6. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 1, characterized in that: the utility model discloses a pipe gallery on-site monitoring terminal, including access control system, surveillance camera head, three-dimensional scanning camera and on-site monitoring sensor, wherein access control system is a plurality of, inlays in each door department of pipe gallery system, in surveillance camera head, the three-dimensional scanning camera head, a surveillance camera head and a three-dimensional scanning camera head are parallelly connected and constitute a detection group, detection group is a plurality of, along pipe gallery axis direction equipartition at pipe gallery lateral wall and top, on-site monitoring sensor is a plurality of, and 3-10 on-site monitoring sensor constitute a work group, work group is a plurality of, along pipe gallery axis direction equipartition on pipe gallery lateral wall, top and horizon, and each on-site monitoring sensor among the same work group encircles pipe gallery axis equipartition.
7. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 6, characterized in that: the on-site monitoring sensor comprises any one or more of a temperature and humidity sensor, a gas sensor, a water level sensor, a grating advanced early warning sensor, a stress strain sensor, an FBG displacement sensor, a water pressure sensor, a displacement sensor, a strain micro-vibration sensor, a flow velocity and flow sensor, a liquid level sensor, a current sensor, a voltage sensor, a COD sensor, a pH sensor and a concentration touch sensor.
8. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 1, characterized in that: the communication service network of the Internet of things adopts any one or two of nested architectures of a C/S structure and a B/S structure.
9. The utility model provides a utility tunnel fortune dimension risk assessment system's application method based on big data which characterized in that: the use method of the comprehensive pipe rack operation and maintenance risk assessment system based on big data comprises the following steps:
s1, system networking, namely, firstly, installing and fixing each pipe gallery field monitoring terminal at a designated working position of a pipe gallery system, then installing a data processing server and a pipe gallery remote operation and maintenance terminal based on an AI base at a designated pipe gallery operation and maintenance management working position, then establishing data connection among the data processing server, the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal based on the AI base through an Internet of things communication service network, finally establishing data connection among the data processing server based on the AI base, a cloud server, a city big data center and a third-party server platform, using the data processing server based on the AI base to coordinate a communication service protocol, and allocating independent communication addressing addresses for the pipe gallery remote operation and maintenance terminal and the pipe gallery field monitoring terminal, thereby completing the networking of the invention;
s2, three-dimensional modeling, completing S1 steps, firstly obtaining ground surface buildings, pipe network layout structures, geological structure basic data information, city basic geographic information and current pipe gallery system construction design drawing information around the current pipe gallery system construction range through a city big data center and a third-party server platform by an AI-based data processing server, then establishing a current pipe gallery system and a surrounding city facility basic three-dimensional model information database thereof through a BIM three-dimensional modeling system according to the obtained data, rendering and assigning values to each coordinate point in the three-dimensional model information database through a GIS system, finally inputting the pipe gallery system data collected by each pipe gallery field monitoring terminal into an integral three-dimensional model information database through the GIS system, obtaining a pipe gallery system three-dimensional visual data model, storing the pipe gallery system three-dimensional visual data model data in a cloud server on one hand, on the other hand, the display is output through a remote operation and maintenance terminal of the pipe gallery;
s3, actively carrying out risk early warning, and after the step S2 is completed, continuously monitoring the building structure of the pipe gallery system and the running states of equipment and facilities in the pipe gallery system by the pipe gallery on-site monitoring terminal in 24-hour continuous work and updating data; the AI-based data processing server is connected with the urban big data center and the third-party server platform in a period of 0.5-3 hours and performs data updating; finally, inputting the updated data into the three-dimensional visual data model of the pipe gallery system in the step S2, outputting and displaying the data, and meanwhile, caching and recording the updated data through a cloud server;
and S4, passive risk early warning, in the step S3 of executing active risk early warning, when the AI-based data processing server is in a standby state between two adjacent time contacts for data updating, and when threat data are generated in the city big data center and the third-party server platform for operation of the pipe gallery system, the city big data center and the third-party server platform actively push data to the AI-based data processing server through the Internet service network, the AI-based data processing server updates data according to the push data on the one hand to the three-dimensional visual data model of the pipe gallery system in the step S2, and the AI-based data processing server sends early warning to the pipe gallery remote operation and maintenance terminal on the other hand, and the pipe gallery remote operation and maintenance terminal drives the pipe gallery system to respond according to the push early warning data.
10. The big-data-based comprehensive pipe rack operation and maintenance risk assessment system according to claim 9, characterized in that: in the steps S1 and S4, the city big data center provides any one or more of data such as energy supply distribution, rainfall, air temperature, ground water, earthquake, building construction, and the like to the AI-based data processing server.
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