CN115479634A - Bridge remote monitoring system and method based on Internet of things technology - Google Patents
Bridge remote monitoring system and method based on Internet of things technology Download PDFInfo
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Abstract
The invention provides a bridge remote monitoring system and method based on the technology of the Internet of things, and relates to the field of bridge monitoring. A bridge remote monitoring system based on the technology of the Internet of things comprises a data acquisition subsystem, a data transmission subsystem and a data background monitoring subsystem; the data acquisition subsystem is used for acquiring multiple pieces of bridge monitoring data through a plurality of sensors; the data transmission subsystem is used for collecting and transmitting multiple bridge monitoring data through the Internet of things; the data background monitoring subsystem is used for storing and displaying a plurality of bridge monitoring data, analyzing the plurality of bridge monitoring data to judge whether the bridge health condition is abnormal or not, and carrying out early warning according to the judgment result; outputting a bridge detection judgment result according to one or more abnormal bridge monitoring data, one or more bridge sensing positions of the sensor and a bridge maintenance method; the method can provide basis and guidance for decision making of bridge maintenance, repair and management, and makes safety early warning for potential safety hazards in advance.
Description
Technical Field
The invention relates to the field of bridge monitoring, in particular to a bridge remote monitoring system and method based on the technology of the Internet of things.
Background
In the prior art, most of the safety management and inspection of bridges are manual inspection or inspection of vehicles through bridge detection, time nodes of safety accidents are often omitted in irregular safety inspection, and bridge accidents still occur. The traditional research on bridge health monitoring mainly has the problems of integral design and systematized thinking of bridge health monitoring, less intelligent schemes such as Internet of things and mobile internet are introduced, in the aspect of remote transmission of bridge monitoring data, a wired network for optical fiber transmission is mostly adopted in the past, mobile network thinking and wireless network implementation schemes are rarely involved, and the defects of high wiring cost, limited wiring path, limited transmission distance and the like are caused. At present, a bridge remote monitoring system based on the internet of things technology is needed, which can monitor the safety condition and health condition of a bridge in real time by adopting the internet of things technology, provide basis and guidance for bridge maintenance, maintenance and management decision making, make safety early warning in advance for potential safety hazards, provide timely treatment for managers, and effectively avoid safety accidents.
Disclosure of Invention
One of the purposes of the invention is to provide a bridge remote monitoring system based on the internet of things technology, which can monitor the health condition of a bridge in real time by adopting the internet of things technology, provide basis and guidance for bridge maintenance, repair and management decisions, make safety early warning on potential safety hazards in advance, provide timely treatment for managers, and effectively avoid safety accidents.
One of the purposes of the invention is to provide a bridge remote monitoring system based on the internet of things technology, which can monitor the health condition of a bridge in real time by adopting the internet of things technology, provide basis and guidance for bridge maintenance, repair and management decisions, make safety early warning on potential safety hazards in advance for managers to handle in time, and effectively avoid safety accidents.
One of the objectives of the present invention is to provide an electronic device, which can monitor the health condition of a bridge in real time by using the technology of internet of things, provide basis and guidance for decision making of bridge maintenance, repair and management, and make a safety early warning on a potential safety hazard in advance for a manager to handle in time, thereby effectively avoiding occurrence of safety accidents.
One of the objectives of the present invention is to provide a computer storage medium, which can monitor the health status of a bridge in real time by using the internet of things technology, provide basis and guidance for bridge maintenance, repair and management decisions, and make a safety early warning on potential safety hazards in advance for managers to handle in time, thereby effectively avoiding safety accidents.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the application provides a bridge remote monitoring system based on an internet of things technology, which comprises a data acquisition subsystem, a data transmission subsystem and a data background monitoring subsystem; the data acquisition subsystem is used for acquiring multiple pieces of bridge monitoring data through a plurality of sensors; the data transmission subsystem is used for collecting and transmitting a plurality of bridge monitoring data through the Internet of things; the data background monitoring subsystem is used for storing and displaying a plurality of bridge monitoring data, analyzing the plurality of bridge monitoring data to judge whether the bridge health condition is abnormal or not, and carrying out early warning according to the bridge detection judgment result; the data background monitoring subsystem outputs the bridge detection judgment result according to one or more abnormal bridge monitoring data in early warning, one or more bridge sensing positions of one or more sensors corresponding to the abnormal bridge monitoring data and one or more bridge maintenance methods.
In some embodiments of the present invention, the data background monitoring subsystem includes a human-machine interface software system, a data storage server system and a monitoring hall display screen system; the human-computer interface software system is respectively connected with the data storage server system and the display screen system; the man-machine interface software system is used for carrying out man-machine conversation and interface display on a plurality of pieces of bridge monitoring data; the data storage server system is used for storing, inquiring and analyzing a plurality of bridge monitoring data; the monitoring hall display screen system is used for amplifying the pictures displayed on the interface and synchronously displaying the pictures through the screen.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes a monitoring model training subsystem; the data background monitoring subsystem analyzes multiple bridge health indexes according to one or more bridge monitoring data and judges the bridge health condition according to the multiple bridge health indexes; the monitoring model training subsystem comprises a monitoring data acquisition module and a monitoring model training module; the monitoring data acquisition module is used for acquiring a plurality of groups of model training data, and each group of model training data comprises one or more sensors, one or more bridge monitoring data, one or more bridge health indexes and the bridge health condition; the monitoring model training module is used for performing machine learning training on a plurality of groups of model training data to obtain a bridge monitoring training model; the bridge monitoring training model is used for outputting the bridge health condition of the model data to be detected.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes an early warning model training subsystem, where the early warning model training subsystem includes an early warning data acquisition module and an early warning model training module; the early warning data acquisition module is used for acquiring a plurality of groups of early warning training data, and each group of early warning training data comprises one or more abnormal bridge monitoring data and a bridge detection judgment result during early warning; the early warning model training module is used for carrying out machine learning training on a plurality of groups of early warning training data to obtain a bridge early warning training model; the bridge early warning training model is used for outputting the bridge detection judgment result of the early warning data to be detected.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes a maintenance model training subsystem, where the maintenance model training subsystem includes a maintenance data acquisition module and a maintenance model training module; the maintenance data acquisition module is used for acquiring a plurality of groups of maintenance training data, each group of maintenance training data comprises one or more abnormal bridge monitoring data during early warning, one or more bridge sensing positions of one or more sensors corresponding to the abnormal bridge monitoring data, and one or more used bridge maintenance methods; the maintenance model training module is used for obtaining a maintenance early warning training model by performing machine learning training on a plurality of groups of maintenance training data; the maintenance early warning training model is used for outputting one or more bridge maintenance methods of maintenance data to be detected.
In some embodiments of the present invention, the bridge monitoring data includes any one or more of deflection monitoring, settlement monitoring, horizontal displacement monitoring, vibration monitoring, inclination monitoring, stress monitoring, cable force monitoring, expansion joint monitoring, load monitoring, environment monitoring, wind speed and wind direction monitoring.
In some embodiments of the invention, the sensor comprises any one or more of a dynamic level, a static level, a GPS locator, a vibration sensor, an inclination sensor, a surface strain gauge, a magnetic flux sensor, a displacement sensor, a dynamic weighing sensor, a temperature sensor and a wind speed/direction sensor.
In a second aspect, an embodiment of the present application provides a bridge remote monitoring method based on an internet of things technology, which is implemented based on the system in any one of the first aspect.
In a third aspect, an embodiment of the present application provides an electronic device, which includes: a memory for storing one or more programs; a processor; the one or more programs, when executed by the processor, implement the system as described in any of the first aspects.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements a system as described above in any one of the first aspects.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
with respect to the first to fourth aspects: in the application, the data acquisition subsystem acquires multiple pieces of bridge monitoring data through a plurality of sensors so as to detect the bridge in real time; the data transmission subsystem collects and transmits bridge monitoring data through the Internet of things, so that a data background monitoring system stores and displays multiple pieces of bridge monitoring data, and managers can monitor bridges in real time conveniently; the data background monitoring system judges whether the health condition of the bridge is abnormal or not by analyzing a plurality of pieces of bridge detection data, so that early warning is carried out according to the bridge detection judgment result, and the bridge detection efficiency can be improved; and the data background monitoring subsystem outputs a bridge detection judgment result according to the abnormal bridge monitoring data during early warning, the abnormal bridge sensing position detected by the sensor and the bridge maintenance method used after early warning, so that managers can maintain the bridge in time. The method and the system can provide basis and guidance for bridge maintenance, maintenance and management decisions, make safety early warning on potential safety hazards in advance, and effectively avoid safety accidents. The bridge health and safety monitoring system integrates the technologies of the Internet of things, sensors, wireless transmission, cloud computing and the like, and is developed into a set of bridge health and safety monitoring system integrating the functions of safety real-time monitoring, intelligent analysis and safety early warning.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed 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 for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic diagram of a bridge remote monitoring system based on internet of things in embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a data background monitoring subsystem in embodiment 1 of the present invention;
FIG. 3 is a flowchart illustrating a method for determining bridge health in embodiment 1 of the present invention;
FIG. 4 is a flowchart of analyzing a judgment result of bridge detection in embodiment 1 of the present invention;
fig. 5 is a schematic diagram of an electronic device according to embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description of the present application, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in this application will be understood to be a specific case for those of ordinary skill in the art.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Example 1
Referring to fig. 1 to 4, fig. 1 to 4 are schematic diagrams illustrating a bridge remote monitoring system based on internet of things according to an embodiment of the present application. The bridge remote monitoring system based on the technology of the Internet of things comprises a data acquisition subsystem, a data transmission subsystem and a data background monitoring subsystem; the data acquisition subsystem is used for acquiring multiple pieces of bridge monitoring data through a plurality of sensors; the data transmission subsystem is used for collecting and transmitting a plurality of bridge monitoring data through the Internet of things; the data background monitoring subsystem is used for storing and displaying a plurality of bridge monitoring data, analyzing the plurality of bridge monitoring data to judge whether the bridge health condition is abnormal or not, and carrying out early warning according to the bridge detection judgment result; the data background monitoring subsystem outputs the bridge detection judgment result according to one or more abnormal bridge monitoring data in early warning, one or more bridge sensing positions of one or more sensors corresponding to the abnormal bridge monitoring data and one or more bridge maintenance methods.
The data acquisition subsystem is used for carrying out real-time bridge monitoring through a plurality of sensors and acquiring a plurality of bridge monitoring data, and the sensors and the bridge monitoring data are all in conventional settings and are not specifically limited herein. The plurality of sensors comprise a plurality of sensors for detecting different bridge monitoring data and are arranged on the corresponding sensing positions of the bridge. Optionally, a plurality of sensors may be disposed at the same detection position to obtain related data, and a plurality of the same sensors may be disposed at different detection positions to obtain detection data of each region. The data transmission subsystem is used for collecting and transmitting multiple bridge monitoring data through the Internet of things, and can also realize data transmission through a 4G/5G network, so that the data background monitoring subsystem can store and display the data, and the data background monitoring subsystem can be realized through a computer. And the data background monitoring subsystem judges whether the health condition of the bridge is normal or not by analyzing a plurality of bridge detection data and carries out early warning according to a bridge detection judgment result, wherein the bridge detection judgment result can comprise whether the bridge is abnormal or not and an abnormal reason when the bridge is abnormal. And according to the bridge monitoring data which are abnormal during early warning and the detection position of the corresponding sensor and the bridge maintenance method used according to the abnormal condition, the data background monitoring subsystem records the bridge monitoring data, which are abnormal during early warning, so that a bridge detection judgment result is output for early warning. The bridge maintenance method can comprise manual operation and used maintenance equipment.
In some embodiments of the present invention, the data background monitoring subsystem includes a human-machine interface software system, a data storage server system and a monitoring hall display screen system; the human-computer interface software system is respectively connected with the data storage server system and the display screen system; the man-machine interface software system is used for carrying out man-machine conversation and interface display on a plurality of pieces of bridge monitoring data; the data storage server system is used for storing, inquiring and analyzing a plurality of bridge monitoring data; the monitoring hall display screen system is used for amplifying the pictures displayed on the interface and synchronously displaying the pictures through the screen.
The man-machine interface software system is used for carrying out man-machine conversation and interface display according to a plurality of bridge monitoring data and is connected with the data storage server system, so that the data storage server system is used for providing storage, query and analysis functions of the plurality of bridge monitoring data. The man-machine interface software system is connected with the monitor hall display screen system, so that the picture displayed by the interface is amplified and then synchronously displayed through the screen.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes a monitoring model training subsystem; the data background monitoring subsystem analyzes multiple bridge health indexes according to one or more bridge monitoring data and judges the bridge health condition according to the multiple bridge health indexes; the monitoring model training subsystem comprises a monitoring data acquisition module and a monitoring model training module; the monitoring data acquisition module is used for acquiring a plurality of groups of model training data, and each group of model training data comprises one or more sensors, one or more bridge monitoring data, one or more bridge health indexes and the bridge health condition; the monitoring model training module is used for performing machine learning training on a plurality of groups of model training data to obtain a bridge monitoring training model; the bridge monitoring training model is used for outputting the bridge health condition of the model data to be detected.
The data background monitoring subsystem respectively analyzes one bridge health index according to one or more bridge detection data, so that a plurality of bridge health indexes are obtained according to a plurality of groups of bridge detection data. And judging whether each bridge health index reaches an index threshold value of the bridge health requirement, thereby obtaining the bridge health condition. The monitoring model training subsystem acquires a plurality of groups of model training data through the monitoring data acquisition module according to the sensors, the bridge monitoring data, the bridge health indexes and the bridge health conditions, so that the monitoring model training module obtains a bridge monitoring training model through machine learning training. The model data to be detected comprises one or more sensors, at least one bridge monitoring data collected by the one or more sensors, and a bridge health index obtained by analyzing the at least one bridge monitoring data. Therefore, the bridge monitoring training model obtains the health condition of the bridge by inputting the data of the model to be detected.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes an early warning model training subsystem, where the early warning model training subsystem includes an early warning data acquisition module and an early warning model training module; the early warning data acquisition module is used for acquiring multiple groups of early warning training data, and each group of early warning training data comprises one or more abnormal bridge monitoring data and the bridge detection judgment result during early warning; the early warning model training module is used for carrying out machine learning training on a plurality of groups of early warning training data to obtain a bridge early warning training model; the bridge early warning training model is used for outputting the bridge detection judgment result of the early warning data to be detected.
The early warning model training subsystem acquires multiple groups of early warning training data through the early warning data acquisition module according to abnormal bridge monitoring data during early warning and a bridge detection judgment result, and the early warning model training module performs machine learning training on the multiple groups of early warning training data to obtain a bridge early warning training model. The early warning data to be detected comprises one or more abnormal bridge monitoring data, so that a bridge detection judgment result is output through a bridge early warning training model, and a data background monitoring subsystem can quickly and automatically early warn abnormality according to the abnormal bridge monitoring data obtained when the health condition of the bridge is abnormal after performing abnormality analysis according to the multiple bridge monitoring data.
In some embodiments of the present invention, the bridge remote monitoring system based on the internet of things further includes a maintenance model training subsystem, where the maintenance model training subsystem includes a maintenance data acquisition module and a maintenance model training module; the maintenance data acquisition module is used for acquiring a plurality of groups of maintenance training data, wherein each group of maintenance training data comprises one or more abnormal bridge monitoring data during early warning, one or more bridge sensing positions of one or more sensors corresponding to the abnormal bridge monitoring data, and one or more used bridge maintenance methods; the maintenance model training module is used for obtaining a maintenance early warning training model by performing machine learning training on a plurality of groups of maintenance training data; the maintenance early warning training model is used for outputting one or more bridge maintenance methods of maintenance data to be detected.
In the maintenance model training subsystem, the maintenance data acquisition module acquires at least one corresponding sensor according to abnormal bridge monitoring data during early warning and according to the bridge monitoring data, so that the sensor is used for acquiring a sensing position, and the bridge maintenance method acquires multiple groups of maintenance training data. And then, the maintenance model training model carries out two maintenance early warning training models of machine learning training on a plurality of groups of maintenance training data. The maintenance data to be detected comprises one or more abnormal bridge monitoring data and the sensing position of at least one sensor, so that a bridge maintenance method is output, a bridge maintenance method is automatically output according to the detection result of the sensor, and managers can timely maintain the quality of the bridge according to the maintenance method. The various models can be used for a data background monitoring subsystem, so that data acquisition and training are completed in a matched mode, and more accurate and complete analysis data are obtained.
In some embodiments of the present invention, the bridge monitoring data includes any one or more of deflection monitoring, settlement monitoring, horizontal displacement monitoring, vibration monitoring, inclination monitoring, stress monitoring, cable force monitoring, expansion joint monitoring, load monitoring, environment monitoring, wind speed and wind direction monitoring. The monitoring data are multiple indexes representing bridge quality, so that various bridge health indexes are analyzed according to the multiple bridge monitoring data, and a result of whether the bridge health condition is abnormal is obtained.
In some embodiments of the invention, the sensor comprises any one or more of a dynamic level, a static level, a GPS locator, a vibration sensor, an inclination sensor, a surface strain gauge, a magnetic flux sensor, a displacement sensor, a dynamic weighing sensor, a temperature sensor and a wind speed/direction sensor. Different bridge monitoring data are obtained through corresponding sensor types, and the sensors are the prior art and are not particularly limited herein.
It will be appreciated that the configuration shown in fig. 1 is merely illustrative, and that a bridge remote monitoring system based on internet of things may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
Example 2
Referring to fig. 5, fig. 5 is a schematic structural block diagram of an electronic device according to an embodiment of the present disclosure. The electronic device comprises a memory 101, a processor 102 and a communication interface 103, wherein the memory 101, the processor 102 and the communication interface 103 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 101 may be configured to store software programs and modules, such as program instructions/modules corresponding to the bridge remote monitoring system based on the internet of things provided in embodiment 1 of the present application, and the processor 102 executes the software programs and modules stored in the memory 101, so as to execute various functional applications and data processing. The communication interface 103 may be used for communicating signaling or data with other node devices.
The Memory 101 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor 102 may be an integrated circuit chip having signal processing capabilities. The Processor 102 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
To sum up, the bridge remote monitoring system and method based on the internet of things provided by the embodiment of the application:
in the application, the data acquisition subsystem acquires multiple pieces of bridge monitoring data through a plurality of sensors so as to detect the bridge in real time; the data transmission subsystem collects and transmits bridge monitoring data through the Internet of things, so that a data background monitoring system can store and display multiple pieces of bridge monitoring data, and managers can monitor bridges in real time conveniently; the data background monitoring system judges whether the health condition of the bridge is abnormal or not by analyzing a plurality of bridge detection data, so that early warning is carried out according to the bridge detection judgment result, and the bridge detection efficiency can be improved; and the data background monitoring subsystem outputs a bridge detection judgment result according to the abnormal bridge monitoring data during early warning, the abnormal bridge sensing position detected by the sensor and the bridge maintenance method used after early warning, so that managers can maintain the bridge in time. The method and the system can provide basis and guidance for bridge maintenance, maintenance and management decisions, make safety early warning on potential safety hazards in advance, and effectively avoid safety accidents. The bridge health and safety monitoring system integrates the technologies of the Internet of things, sensors, wireless transmission, cloud computing and the like, and is developed into a set of bridge health and safety monitoring system integrating the functions of safety real-time monitoring, intelligent analysis and safety early warning.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A bridge remote monitoring system based on the technology of the Internet of things is characterized by comprising a data acquisition subsystem, a data transmission subsystem and a data background monitoring subsystem; the data acquisition subsystem is used for acquiring multiple pieces of bridge monitoring data through a plurality of sensors; the data transmission subsystem is used for collecting and transmitting a plurality of pieces of bridge monitoring data through the Internet of things; the data background monitoring subsystem is used for storing and displaying a plurality of pieces of bridge monitoring data, analyzing the plurality of pieces of bridge monitoring data to judge whether the bridge health condition is abnormal or not, and carrying out early warning according to the bridge detection judgment result; the data background monitoring subsystem outputs the bridge detection judgment result according to one or more abnormal bridge monitoring data in early warning, one or more bridge sensing positions of one or more sensors corresponding to the abnormal bridge monitoring data and one or more bridge maintenance methods.
2. The remote bridge monitoring system based on the internet of things technology as claimed in claim 1, wherein the data background monitoring subsystem comprises a human-computer interface software system, a data storage server system and a monitoring hall display screen system; the human-computer interface software system is respectively connected with the data storage server system and the display screen system; the human-computer interface software system is used for performing human-computer conversation and interface display on a plurality of pieces of bridge monitoring data; the data storage server system is used for storing, inquiring and analyzing a plurality of pieces of bridge monitoring data; and the monitoring hall display screen system is used for amplifying the pictures displayed on the interface and synchronously displaying the pictures through the screen.
3. The remote bridge monitoring system based on the internet of things technology as claimed in claim 1, further comprising a monitoring model training subsystem; the data background monitoring subsystem analyzes multiple bridge health indexes according to one or more bridge monitoring data and judges the bridge health condition according to the multiple bridge health indexes; the monitoring model training subsystem comprises a monitoring data acquisition module and a monitoring model training module; the monitoring data acquisition module is used for acquiring a plurality of groups of model training data, and each group of model training data comprises one or more sensors, one or more bridge monitoring data, one or more bridge health indexes and the bridge health condition; the monitoring model training module is used for carrying out machine learning training on a plurality of groups of model training data to obtain a bridge monitoring training model; the bridge monitoring training model is used for outputting the bridge health condition of the model data to be detected.
4. The remote bridge monitoring system based on the internet of things technology of claim 1, further comprising an early warning model training subsystem, wherein the early warning model training subsystem comprises an early warning data acquisition module and an early warning model training module; the early warning data acquisition module is used for acquiring multiple groups of early warning training data, and each group of early warning training data comprises one or more abnormal bridge monitoring data and a bridge detection judgment result during early warning; the early warning model training module is used for carrying out machine learning training on a plurality of groups of early warning training data to obtain a bridge early warning training model; the bridge early warning training model is used for outputting the bridge detection judgment result of the early warning data to be detected.
5. The remote bridge monitoring system based on the internet of things technology of claim 1, further comprising a maintenance model training subsystem, wherein the maintenance model training subsystem comprises a maintenance data acquisition module and a maintenance model training module; the maintenance data acquisition module is used for acquiring a plurality of groups of maintenance training data, each group of maintenance training data comprises one or more abnormal bridge monitoring data during early warning, one or more bridge induction positions of one or more sensors corresponding to the abnormal bridge monitoring data, and one or more used bridge maintenance methods; the maintenance model training module is used for carrying out machine learning training on a plurality of groups of maintenance training data to obtain a maintenance early warning training model; the maintenance early warning training model is used for outputting one or more bridge maintenance methods of maintenance data to be detected.
6. The system of claim 1, wherein the bridge monitoring data comprises any one or more of deflection monitoring, settlement monitoring, horizontal displacement monitoring, vibration monitoring, inclination monitoring, stress monitoring, cable force monitoring, expansion joint monitoring, load monitoring, environmental monitoring, wind speed and direction monitoring.
7. The internet of things technology-based bridge remote monitoring system of claim 1, wherein the sensor comprises any one or more of a dynamic level gauge, a static level gauge, a GPS locator, a vibration sensor, an inclination sensor, a surface strain gauge, a magnetic flux sensor, a displacement sensor, a dynamic weighing sensor, a temperature sensor, and a wind speed/direction sensor.
8. A bridge remote monitoring method based on the technology of the Internet of things is realized based on the system of any one of claims 1-7.
9. An electronic device, comprising: a memory for storing one or more programs; a processor; the one or more programs, when executed by the processor, implement the system of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the system according to any one of claims 1-7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117076928A (en) * | 2023-08-25 | 2023-11-17 | 中交路桥科技有限公司 | Bridge health state monitoring method, device and system and electronic equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117076928A (en) * | 2023-08-25 | 2023-11-17 | 中交路桥科技有限公司 | Bridge health state monitoring method, device and system and electronic equipment |
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