CN110852458A - City pipe network supervision method based on big data - Google Patents
City pipe network supervision method based on big data Download PDFInfo
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Abstract
The invention discloses a city pipe network supervision method based on big data, which comprises the steps of carrying out grid type division on a city area to obtain a grid type city pipe network, and classifying the detection points of the existing pipe network into grid units at corresponding positions; respectively carrying out big data analysis on the uploaded detection information of the corresponding grid units in the urban pipe network model according to different grid modules to obtain a monitoring result of each grid unit; displaying the monitoring result on a monitoring large screen with a grid display; and transmitting the monitoring result to the corresponding management extension according to the grid unit position. According to the invention, the urban pipe network state is monitored in real time in a remote manner, so that the urban pipe network state can be intelligently and effectively monitored, the detection accuracy and the detection efficiency can be improved, the monitoring efficiency is improved, and the safe and reliable operation of a pipe network is ensured.
Description
Technical Field
The invention belongs to the technical field of urban pipe network detection, and particularly relates to a large data-based urban pipe network supervision method.
Background
Along with the depth of the urbanization process, the scale of the urban underground pipe network is continuously enlarged, but the laying time of a large number of pipelines is long, so that the pipelines reach or approach the service life at present, and even a plurality of pipelines are leaked and exploded due to aging when not reaching the service life, so that the operation of the pipe network is influenced. In addition, at present, the manual monitoring point site selection method is mostly adopted for monitoring the pipe network, judgment and rough point selection are carried out according to work experience and urban development conditions, randomness is obvious, so that the defects of uneven distribution, insufficient scientific basis for monitoring point distribution and poor rationalization of the pipe network monitoring points generally exist, the urban pipe network often has a fault problem, and normal operation of the urban pipe network is greatly influenced.
Disclosure of Invention
In order to solve the problems, the invention provides a city pipe network supervision method based on big data, which can intelligently and effectively supervise the state of the city pipe network by monitoring the state of the city pipe network in real time remotely, can improve the detection accuracy and the detection efficiency, improves the supervision efficiency, and ensures the safe and reliable operation of the pipe network.
In order to achieve the purpose, the invention adopts the technical scheme that: a city pipe network supervision method based on big data comprises the following steps:
carrying out grid type division on an urban area to obtain a grid type urban network management network, and classifying the detection points of the existing network management into grid units at corresponding positions; arranging detection equipment at a detection point of a pipe network, wherein the detection equipment remotely transmits real-time detection information to a management server through the Internet;
establishing an urban pipe network model in a management server according to a grid type urban pipe network, and respectively carrying out big data analysis on the uploaded detection information of the corresponding grid units in the urban pipe network model according to different grid modules to obtain a monitoring result of each grid unit;
displaying the monitoring result on a monitoring large screen with grid display, if the monitoring result is normal, only displaying the monitoring data in the display grid, and if the monitoring result is abnormal, sending a prompt warning in the display grid; transmitting the monitoring result to a corresponding management extension set through the internet according to the grid unit position;
when a city pipe network is newly built, pipe network detection point positions are established at actual positions corresponding to corresponding grid units according to the division of the grid type city pipe network, new detection equipment is set, and starting and data updating are carried out on corresponding grid modules in a city pipe network model.
Further, the urban area is divided in a grid mode, coordinate coding is carried out in each grid unit in a grid type urban network management network, the grid units are classified into existing underground pipeline inspection ports in the existing network, detection equipment is installed at each underground pipeline inspection port, and the detection equipment is in remote communication connection with a management server.
Further, the detection equipment comprises a sensor, a positioner, a network transmitter and a data processor, wherein the sensor is arranged on a pipeline detection point and transmits a collected signal to the data processor, and the positioner positions the detection equipment and transmits a positioning signal to the data processor, and detection information in the data processor of the network transmission device is transmitted to the server through the internet. The real-time online detection can be effectively carried out on the detection points of each grid unit, and real-time operation data can be effectively acquired. The sensor can adopt a pressure sensor, a flow sensor, a water temperature sensor and the like. The network transmitter is a network transmission device such as GPRS and 4G, WiFi.
Furthermore, the underground pipeline inspection port adopts an existing pipeline inspection well, and the monitoring equipment is installed in the existing pipeline inspection well. The grid type detection can be realized on the basis of not changing the mechanism of the existing city network management.
Further, be provided with photovoltaic electric power storage power supply unit on the well lid of pipeline inspection shaft, photovoltaic electric power storage power supply unit provides the operation electric energy for check out test set, just the transmission antenna embedding of network transmission ware is on the well lid. The uninterrupted operation of the detection equipment can be maintained, and the detection of real-time data is ensured; and the transmission performance of the communication of the Internet of things is ensured.
Further, an urban pipe network model is established in the management server according to an urban pipe network grid network, the urban pipe network model comprises a data dispatching module and array type grid modules, each grid module corresponds to one grid unit, and the data dispatching module receives uploaded detection information and dispatches the detection information to the corresponding network module according to the coordinate code of the grid unit where the monitoring information is located; each grid module is provided with an independent arithmetic unit, and the monitoring result of the grid unit is obtained by carrying out big data analysis on the detection information through the arithmetic unit. Through the parallel distributed detection of the grids, independent operation is carried out on each grid unit, the detection position can be effectively and accurately matched, the detection result can be effectively fed back, meanwhile, synchronous detection can be effectively carried out on numerous detection points in a city, and the detection efficiency is improved.
Furthermore, a pre-established big data analysis model is called in each grid module, the big data analysis model is formed by training according to pipe network state data and fault data, the pipeline state and the fault state of the existing grid unit point positions detected in the grid module are identified by inputting detection information into the big data analysis model, and the pipeline state and the fault state are output as detection results. By combining big data technical analysis, the operation state and the fault information of each grid unit can be accurately and efficiently identified, intelligent and effective supervision can be performed on the pipe network condition, and the supervision efficiency is improved.
Furthermore, an urban map is arranged on the monitoring large screen, urban network grids are merged on the urban map to form the urban map with display grids, each display grid corresponds to a grid unit of the corresponding coordinate code, and a monitoring result of the corresponding grid unit is displayed on each display grid and early warning prompt information is carried out. The monitoring state information and the faults are provided for the managers visually and efficiently, the maintenance efficiency is improved, and the safety and the reliability of the pipe network are guaranteed.
The beneficial effects of the technical scheme are as follows:
the invention can remotely monitor the state of each detection point in the urban network in real time, carry out distributed detection on the urban grid through the grid layout, effectively and accurately match the detection position and feed back the detection result, simultaneously and effectively carry out synchronous detection on numerous detection points in the city, and improve the detection efficiency. Meanwhile, the running state and fault information of each grid unit are identified by combining big data technology analysis, the urban pipe network is monitored in all directions in real time, intelligent effective supervision can be carried out on the water supply and drainage conditions of the pipe network, the supervision efficiency is improved, and the reliable and safe running of the urban pipe network is ensured. The invention can also intuitively and efficiently provide monitoring state information and generated faults for management personnel, improve the maintenance efficiency and ensure the safety and reliability of the pipe network.
Drawings
FIG. 1 is a schematic flow chart of a big data-based urban pipe network supervision method according to the present invention;
fig. 2 is a system architecture diagram of a big data-based city pipe network supervision method according to 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 further described with reference to the accompanying drawings.
In this embodiment, referring to fig. 1 and fig. 2, the present invention provides a method for monitoring an urban pipe network based on big data, including the steps of:
carrying out grid type division on an urban area to obtain a grid type urban network management network, and classifying the detection points of the existing network management into grid units at corresponding positions; arranging detection equipment at a detection point of a pipe network, wherein the detection equipment remotely transmits real-time detection information to a management server through the Internet;
establishing an urban pipe network model in a management server according to a grid type urban pipe network, and respectively carrying out big data analysis on the uploaded detection information of the corresponding grid units in the urban pipe network model according to different grid modules to obtain a monitoring result of each grid unit;
displaying the monitoring result on a monitoring large screen with grid display, if the monitoring result is normal, only displaying the monitoring data in the display grid, and if the monitoring result is abnormal, sending a prompt warning in the display grid; transmitting the monitoring result to a corresponding management extension set through the internet according to the grid unit position;
when a city pipe network is newly built, pipe network detection point positions are established at actual positions corresponding to corresponding grid units according to the division of the grid type city pipe network, new detection equipment is set, and starting and data updating are carried out on corresponding grid modules in a city pipe network model.
As an optimized scheme of the above embodiment, the urban area is divided into grids, coordinates are encoded in each grid unit in the grid urban network management network and are included in an existing underground pipeline inspection port in the existing network management network, a detection device is installed at each underground pipeline inspection port, and the detection device is in remote communication connection with the management server.
The detection device comprises a sensor, a positioner, a network transmitter and a data processor, wherein the sensor is arranged on a pipeline detection point and transmits a collected signal to the data processor, the positioner positions the detection device and transmits a positioning signal to the data processor, and detection information in the data processor of the network transmission device is transmitted to a server through the Internet. The real-time online detection can be effectively carried out on the detection points of each grid unit, and real-time operation data can be effectively acquired. The sensor can adopt a pressure sensor, a flow sensor, a water temperature sensor and the like. The network transmitter is a network transmission device such as GPRS and 4G, WiFi.
The underground pipeline inspection hole adopts the existing pipeline inspection well, and the monitoring equipment is installed in the existing pipeline inspection well. The grid type detection can be realized on the basis of not changing the mechanism of the existing city network management.
The well lid of pipeline inspection shaft is provided with photovoltaic power storage power supply unit, photovoltaic power storage power supply unit provides the operation electric energy for check out test set, just the transmission antenna embedding of network transmission ware is on the well lid. The uninterrupted operation of the detection equipment can be maintained, and the detection of real-time data is ensured; and the transmission performance of the communication of the Internet of things is ensured.
As an optimization scheme of the above embodiment, an urban pipe network model is established in a management server according to an urban pipe network grid network, where the urban pipe network model includes a data dispatch module and array-type grid modules, each grid module corresponds to a grid unit, and the data dispatch module receives uploaded detection information and dispatches the detection information to a corresponding network module according to a coordinate code of the grid unit where the monitoring information is located; each grid module is provided with an independent arithmetic unit, and the monitoring result of the grid unit is obtained by carrying out big data analysis on the detection information through the arithmetic unit. Through the parallel distributed detection of the grids, independent operation is carried out on each grid unit, the detection position can be effectively and accurately matched, the detection result can be effectively fed back, meanwhile, synchronous detection can be effectively carried out on numerous detection points in a city, and the detection efficiency is improved.
And calling a pre-established big data analysis model in each grid module, wherein the big data analysis model is formed by training according to the state data and the fault data of the pipe network, identifying the pipeline state and the fault state of the existing grid unit point position detected in the grid module by inputting detection information into the big data analysis model, and outputting the pipeline state and the fault state as detection results. By combining big data technical analysis, the operation state and the fault information of each grid unit can be accurately and efficiently identified, intelligent and effective supervision can be performed on the pipe network condition, and the supervision efficiency is improved.
As an optimization scheme of the above embodiment, an urban map is arranged on the monitoring large screen, and urban network networks and grid networks are merged on the urban map to form an urban map with display grids, each display grid corresponds to a grid unit of a corresponding coordinate code, and a monitoring result of the corresponding grid unit is displayed on each display grid and early warning prompt information is performed. The monitoring state information and the faults are provided for the managers visually and efficiently, the maintenance efficiency is improved, and the safety and the reliability of the pipe network are guaranteed.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. A city pipe network supervision method based on big data is characterized by comprising the following steps:
carrying out grid type division on an urban area to obtain a grid type urban network management network, and classifying the detection points of the existing network management into grid units at corresponding positions; arranging detection equipment at a detection point of a pipe network, wherein the detection equipment remotely transmits real-time detection information to a management server through the Internet;
establishing an urban pipe network model in a management server according to a grid type urban pipe network, and respectively carrying out big data analysis on the uploaded detection information of the corresponding grid units in the urban pipe network model according to different grid modules to obtain a monitoring result of each grid unit;
displaying the monitoring result on a monitoring large screen with grid display, if the monitoring result is normal, only displaying the monitoring data in the display grid, and if the monitoring result is abnormal, sending a prompt warning in the display grid; transmitting the monitoring result to a corresponding management extension set through the internet according to the grid unit position;
when a city pipe network is newly built, pipe network detection point positions are established at actual positions corresponding to corresponding grid units according to the division of the grid type city pipe network, new detection equipment is set, and starting and data updating are carried out on corresponding grid modules in a city pipe network model.
2. The method as claimed in claim 1, wherein the urban area is divided into grids, coordinates are encoded in each grid cell in the grid urban network management system and are included in existing underground pipeline inspection ports of the existing network, a detection device is installed at each underground pipeline inspection port, and the detection device is in remote communication connection with the management server.
3. The big data-based city pipe network supervision method according to claim 2, wherein the detection device comprises a sensor, a locator, a network transmitter and a data processor, the sensor is installed on a pipeline detection point and transmits a collected signal to the data processor, the locator locates the position of the detection device and transmits a locating signal to the data processor, and detection information in the data processor of the network transmission device is transmitted to the server through the internet.
4. The big data-based urban pipe network supervision method according to claim 3, wherein the underground pipeline inspection opening is an existing pipeline inspection well, and the monitoring device is installed in the existing pipeline inspection well.
5. The big data-based urban pipe network supervision method according to claim 4, wherein a photovoltaic power storage power supply device is arranged on a well cover of the pipeline inspection well, the photovoltaic power storage power supply device provides operating electric energy for inspection equipment, and a transmission antenna of the network transmitter is embedded in the well cover.
6. The method according to any one of claims 2-5, wherein a city pipe network model is established in the management server according to a city pipe network grid network, the city pipe network model comprises a data dispatch module and array grid modules, each network module corresponds to a grid unit, the data dispatch module receives uploaded detection information and dispatches the detection information to the corresponding network module according to a coordinate code of the grid unit where the monitoring information is located; each grid module is provided with an independent arithmetic unit, and the monitoring result of the grid unit is obtained by carrying out big data analysis on the detection information through the arithmetic unit.
7. The method according to claim 6, wherein a pre-established big data analysis model is called in each grid module, the big data analysis model is formed by training pipe network state data and fault data, the pipeline state and fault state of the existing grid unit point location detected in the grid module are identified by inputting detection information into the big data analysis model, and the pipeline state and fault state are output as detection results.
8. The method according to claim 1, wherein a city map is provided on the monitoring large screen, and city network grids are merged on the city map to form a city map with display grids, each display grid corresponds to a grid unit of a corresponding coordinate code, and a monitoring result of the corresponding grid unit is displayed on each display grid, and an early warning prompt message is performed.
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| CN113221302A (en) * | 2021-05-26 | 2021-08-06 | 上海天麦能源科技有限公司 | Smart city detection data dynamic gridding processing method and system |
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