Multi-source data fusion highway bridge safety early warning system and method

Abstract

The invention relates to the technical field of highway bridges, and discloses a multi-source data fusion highway bridge safety early warning system and method, and the system comprises a hardware assembly. The hardware assembly comprises a vibration sensor, a pressure sensor, a load sensor, a radar detector, a 8-megapixel snapshot box camera and a light supplement lamp. According to the multi-source data fusion highway bridge safety early warning system and method, for convenient and flexible man-machine interaction, a plurality of communication interfaces (TCP / IP and serial ports) are adopted to establish a communication link between an embedded end server and an upper computer client, and a man-machine interaction function in a plurality of modes is realized, so that an operator can carry out multi-source data fusion through different communication modes, and the safety of the highway bridge safety early warning system and method is improved. According to the multi-interface man-machine interaction system, interaction with the system is conveniently carried out according to actual requirements and scenes, serial port communication can exert the advantages of the system, stability and reliability of interaction are ensured, the flexibility and convenience of man-machine interaction are greatly improved through the arrangement of multiple interfaces, and diversified operation requirements are met.

Description

Technical Field

[0001] The present invention relates to the technical field of highway bridges, and in particular to a multi-source data fusion highway bridge safety early warning system and method. Background Art

[0002] Bridges are large-scale infrastructures with huge investments and long service lives. Their safety has a significant impact on the national economy. With the advancement of science and technology, bridge design theory and construction technology have achieved new breakthroughs and developments, and their structural forms have become increasingly complex. However, during the operation of bridges, due to adverse factors such as load, fatigue, corrosion, and material aging, as well as the long-term impact of factors such as increasing traffic volume, the number of heavy and overweight vehicles crossing the bridge, and human accidents, the bridge structure will inevitably experience natural aging and damage accumulation, leading to accidents.

[0003] Most of the bridges in my country do not have a maintenance system to ensure safety and durability. There are two main reasons for this: on the one hand, due to the lack of a safety monitoring system for the entire bridge structure, any abnormalities in the structural status cannot be discovered in time and corresponding measures cannot be implemented; on the other hand, when repairing and reinforcing structures with severe local quality degradation, the current detection technology cannot make an accurate and objective assessment of the damage to the various components of the structure, and all components that may have problems often have to be replaced, resulting in a huge waste of materials and funds. It can be seen that the establishment and improvement of the bridge safety monitoring system not only affects the health and safety of the bridge and the normal operation of traffic, but is also closely related to economic benefits.

[0004] The UK has deployed sensor nodes on the Foyle, a 552-meter-long, three-span, variable-height, continuous steel box bridge. These sensors monitor the vibration, deflection, and strain of the main girder under vehicle and wind loads during operation. They also monitor environmental wind loads and structural temperature fields. This system, one of the earliest and most comprehensive, enables real-time monitoring, analysis, and data network sharing. Other examples of bridges with health monitoring systems include the Skarnsundet cable-stayed Bridge in Norway (1991, 530-meter main span), the Sunshine Skyway Bridge in Florida (1987, 440-meter main span), the Great Belt East Suspension Bridge in Denmark (1998, 1624-meter main span), the Flintshire single-pylon cable-stayed Bridge in the UK (1998, 194-meter main span), the 12.9-kilometer-long, 45-span prestressed concrete box girder Confederation Bridge in Canada (1997), and the Akashi Kaikyo Bridge in Japan (1998).

[0005] Research on bridge safety monitoring in my country began in the 1990s, and structural monitoring systems of varying sizes have been established on some large bridges, such as the Tsing Ma Bridge, Kap Shui Mun Bridge, and Ting Kau Bridge in Hong Kong, the Xupu Bridge in Shanghai, and the Jiangyin Yangtze River Bridge. In recent years, a health monitoring and assessment system has been established on the Sutong Bridge, and a bridge construction control and health monitoring system has been built on the Wuhan Yangluo Highway Bridge. In particular, the bridge health monitoring system of the Runyang Yangtze River Bridge in Jiangsu Province monitors traffic volume, vehicle loads, and the environment surrounding the bridge, while also providing long-term and continuous monitoring of some key bridge parameters.

[0006] However, the current safety warning system lacks multiple communication interfaces (TCP / IP, serial port), so it is impossible to build an embedded server to communicate with the host computer client, and it is impossible to implement various human-computer interaction functions well; there is a lack of independent component analysis method: this is a new signal processing technology, its purpose is to represent the monitored data signal with a linear variable combination of component independent signals, that is, a method to recover independent basic source signals from mixed signals; there is a lack of sensor node layout method: it is impossible to apply the layout of sensor nodes in the diamond grid well, and arrange the nodes at the vertices of the diamond. For a given number of sensor nodes, each node can be moved to the vertex of the desired virtual diamond grid. This desired vertex is closest to all sensor nodes, so it is impossible to execute and manage the movement of nodes through the base station. In view of this, we propose a multi-source data fusion highway bridge safety warning system and method. Summary of the Invention

[0007] The purpose of the present invention is to provide a multi-source data fusion highway bridge safety early warning system and method to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A multi-source data fusion highway bridge safety early warning system, comprising:

[0010] Hardware components, including vibration sensors, pressure sensors, load sensors, radar detectors, 8-megapixel snapshot cameras, and fill lights;

[0011] The software module is responsible for receiving data collected from hardware components and performing data analysis, safety warnings, vehicle capture, and data statistics. Specifically, the software module includes the following submodules:

[0012] The data analysis module mainly uses the vibration sensors, pressure sensors, load sensors, radar detectors and other hardware equipment to collect data on multiple key indicators such as bridge vibration, pressure, load size, crack width, and bridge deformation. On this basis, the collected data is compared with historical data and compared and analyzed with reference to pre-set standard values ​​to achieve comprehensive detection and accurate evaluation of the bridge's operating status;

[0013] The safety warning module ensures that monitoring indicators are automatically and promptly transmitted to the management system. Once the monitored values ​​exceed the pre-set safety parameter range, an alarm message will be immediately triggered and accurately sent to the relevant responsible persons of the bridge maintenance unit so that they can quickly take appropriate measures to ensure the safe operation of the bridge.

[0014] The vehicle capture module activates when monitoring indicators exceed the established standard value, instructing the camera to start filming. If the filming time is at night, the fill light will be triggered at the same time to ensure that the license plate information of the suspected vehicle that triggered the warning can be clearly captured. In addition, the bridge warning information and related information such as the captured license plate number of the suspected vehicle will be sent to the bridge law enforcement supervision unit at the same time, providing a strong basis for subsequent law enforcement investigations.

[0015] The data statistics module is mainly used to conduct statistical analysis on the number of alarms according to the time and location dimensions based on historical alarm data, and then form corresponding statistical data. These statistical data can provide effective auxiliary support for decision-making in bridge safety management, help to predict possible safety risks in advance, and formulate more scientific and reasonable preventive measures.

[0016] Preferably, the safety warning module includes:

[0017] A preset parameter setting unit, used to set preset safety parameters for bridge operation conditions;

[0018] Monitoring indicator feedback unit, used to automatically transmit the collected monitoring indicators back to the management system;

[0019] The alarm trigger unit is used to trigger an alarm message and send it to the person in charge of the bridge maintenance unit when the monitoring indicators exceed the preset parameters.

[0020] Preferably, the vehicle capture module includes:

[0021] The shooting command unit is used to instruct the snapshot camera to shoot when the monitoring index exceeds the standard value; the flash trigger unit is used to trigger the fill light at the same time when shooting at night;

[0022] The information sending unit is used to capture the license plate of the suspected vehicle that triggered the warning, and simultaneously send the bridge warning information and the suspected vehicle license plate number and other information to the bridge law enforcement supervision unit.

[0023] Preferably, the data statistics module includes:

[0024] Historical alarm data recording unit, used to record historical alarm data;

[0025] The statistical analysis unit is used to generate alarm statistics by time and location based on historical alarm data to assist in decision-making and prevention of safety management.

[0026] Preferably, it also includes a clock synchronization module, which adopts link layer timestamp technology, completes the clock synchronization process of the entire network node through classification and synchronization, and applies two-way communication to reduce delay.

[0027] Preferably, a node positioning module is further included, which senses the arrival direction of the signal sent by the sending node through an antenna array or multiple receivers, and calculates the distance d and relative azimuth angle θ between the sending node and the receiving node. The calculation formula is:

[0028]

[0029] Where: c is the speed of light, Δt is the signal propagation time difference, (x1, y1) and (x2, y2) are the coordinates of the sending node and the receiving node respectively. The node positioning module uses an antenna array or multiple receivers to keenly sense the arrival direction of the signal sent by the sending node. According to the above precise calculation formula, it accurately calculates the distance and relative azimuth angle between the sending node and the receiving node.

[0030] Preferably, it also includes a data fusion module, which applies compressed sensing theory to reduce the amount of data transmission and removes redundant information through data fusion technology. The amount of information after data fusion is I fused Expressed as:

[0031] I fused =f(I1,I2,…,I n )

[0032] Where: I1, I2, …, I n is the amount of original information from different sensors, and f is the data fusion function.

[0033] Preferably, it also includes a communication interface module, which uses multiple communication interfaces such as TCP / IP and serial port to build an embedded terminal server to communicate with the host computer client and realize human-computer interaction functions in various ways.

[0034] Preferably, an independent component analysis module is also included, which is used to represent the monitored data signal as a linear variable combination of component independent signals, that is, to recover the independent basic source signals from the mixed signal. Its mathematical model is:

[0035] X=AS, where: X is the observation signal matrix, A is the mixing matrix, and S is the source signal matrix.

[0036] A multi-source data fusion highway bridge safety early warning system early warning method includes the following steps:

[0037] S1. Bridge Data Collection: Vibration sensors, pressure sensors, load sensors, radar detectors, and other equipment are used to comprehensively and meticulously collect key data such as bridge vibration, pressure, load size, crack width, and bridge deformation. During the collection process, the normal operation of the equipment and the accuracy and integrity of the data are ensured, providing a solid data foundation for subsequent analysis and evaluation.

[0038] S2. Data analysis and evaluation: Compare the collected data with historical data and standard values ​​to detect and evaluate the bridge operation status;

[0039] S3. Data feedback and alarm: The monitoring indicators are automatically transmitted back to the management system, and when the monitoring indicators exceed the preset parameters, an alarm message is triggered and sent to the person in charge of the bridge maintenance unit;

[0040] S4. Shooting when the monitoring index exceeds the standard value: When the monitoring index exceeds the standard value, the camera is instructed to shoot, and the fill light is triggered at the same time during night shooting to capture the license plate of the suspected vehicle that triggered the warning. The bridge warning information and the suspected vehicle license plate number and other information are simultaneously sent to the bridge law enforcement supervision unit;

[0041] S5. Analysis of historical alarm data: Based on historical alarm data, the number of alarms is deeply analyzed and counted according to the two dimensions of time and location, and then corresponding statistical data is formed. By using scientific and reasonable statistical methods and analysis tools, valuable information is extracted from these statistical data to provide strong auxiliary support for decision-making and prevention work in bridge safety management.

[0042] Compared with the existing technology, the present invention provides a multi-source data fusion highway bridge safety early warning system and method, which has the following beneficial effects:

[0043] 1. This multi-source data fusion highway bridge safety early warning system and method, in order to facilitate flexible human-computer interaction, uses multiple communication interfaces (TCP / IP, serial port) to build a communication link between the embedded end server and the host computer client, realizing multiple modes of human-computer interaction functions. This enables operators to interact with the system conveniently through different communication methods according to actual needs and scenarios. Serial port communication can give full play to its advantages and ensure stable and reliable interaction. This multi-interface setting greatly improves the flexibility and convenience of human-computer interaction and meets diverse operational needs.

[0044] 2. This multi-source data fusion highway bridge safety early warning system and method utilizes independent component analysis (ICA) for precise signal source separation. This new signal processing technique can represent monitored data signals as a linear variable combination of component-independent signals, thereby recovering mutually independent basic source signals from mixed signals. This technique helps to accurately separate individual signal sources in complex monitoring data environments, enabling separate analysis and processing of signals from different sources and properties. For example, in bridge monitoring, it can more clearly and accurately distinguish signals generated by different factors such as vehicle loads, wind forces, and structural deformation, providing a reliable data foundation for subsequent accurate judgment of the bridge structure status and effectively improving the accuracy of signal analysis.

[0045] 3. The multi-source data fusion highway bridge safety early warning system and method, in order to efficiently optimize the sensor layout, divides the sensor area into a virtual diamond grid through the sensor node layout method, and arranges the nodes at the diamond vertices. It can move the sensor nodes to the desired vertex closest to all nodes based on a given number of sensor nodes. The base station is responsible for managing the node movement. This layout method can achieve efficient and optimized layout of sensor nodes in the monitoring area, so that the sensors can cover the monitoring area more evenly and reasonably, reducing monitoring blind spots. At the same time, the nodes can flexibly adjust their positions according to actual conditions, further improving the comprehensiveness and accuracy of the monitoring data, ensuring that more complete and valuable monitoring information can be obtained, thereby better monitoring and evaluating the status of the monitored objects (such as bridges and other infrastructure) in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is an overall schematic diagram of the multi-source data fusion highway bridge safety early warning system of the present invention;

[0047] Figure 2 This is a schematic diagram of the safety warning module of the present invention;

[0048] Figure 3 This is a schematic diagram of the vehicle capture module of the present invention;

[0049] Figure 4This is a schematic diagram of the data statistics module of the present invention;

[0050] Figure 5 Schematic diagram of the early warning method of the present invention;

[0051] Figure 6 Schematic diagram of the early warning process of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] See also Figure 1 - Figure 6 , the present invention provides a technical solution:

[0054] A multi-source data fusion highway bridge safety early warning system, including hardware components, including vibration sensors, pressure sensors, load sensors, radar detectors, 8-megapixel snapshot cameras and fill lights;

[0055] The software module is responsible for receiving data collected from hardware components and performing data analysis, safety warnings, vehicle capture, and data statistics. Specifically, the software module includes the following submodules:

[0056] The data analysis module uses hardware devices such as vibration sensors, pressure sensors, load sensors, and radar detectors to collect data on key indicators such as bridge vibration, pressure, load size, crack width, and bridge deformation. The module then compares the collected data with historical data and analyzes them against pre-set standard values ​​to achieve comprehensive detection and accurate evaluation of bridge operating conditions.

[0057] The safety warning module ensures that monitoring indicators are automatically and promptly transmitted to the management system. Once the monitored values ​​exceed the pre-set safety parameter range, an alarm message will be immediately triggered and accurately sent to the relevant responsible persons of the bridge maintenance unit so that they can quickly take appropriate measures to ensure the safe operation of the bridge.

[0058] The vehicle capture module activates when monitoring indicators exceed the established standard value, instructing the camera to start filming. If the filming time is at night, the fill light will be triggered at the same time to ensure that the license plate information of the suspected vehicle that triggered the warning can be clearly captured. In addition, the bridge warning information and related information such as the captured license plate number of the suspected vehicle will be sent to the bridge law enforcement supervision unit at the same time, providing a strong basis for subsequent law enforcement investigations.

[0059] The data statistics module is mainly used to conduct statistical analysis on the number of alarms according to the time and location dimensions based on historical alarm data, and then form corresponding statistical data. These statistical data can provide effective auxiliary support for decision-making in bridge safety management, help to predict possible safety risks in advance, and formulate more scientific and reasonable preventive measures.

[0060] In one embodiment of the present invention, the security warning module includes:

[0061] A preset parameter setting unit, used to set preset safety parameters for bridge operation conditions;

[0062] Monitoring indicator feedback unit, used to automatically transmit the collected monitoring indicators back to the management system;

[0063] The alarm trigger unit is used to trigger an alarm message and send it to the responsible person of the bridge maintenance unit when the monitoring indicators exceed the preset parameters. In addition, the vehicle capture module includes:

[0064] The shooting command unit is used to instruct the snapshot camera to shoot when the monitoring index exceeds the standard value; the flash trigger unit is used to trigger the fill light at the same time when shooting at night;

[0065] The information sending unit is used to capture the license plate of the suspected vehicle that triggered the warning, and simultaneously send the bridge warning information and the suspected vehicle license plate number and other information to the bridge law enforcement supervision unit. In addition, the data statistics module includes:

[0066] Historical alarm data recording unit, used to record historical alarm data;

[0067] The statistical analysis unit is used to generate alarm statistics by time and location based on historical alarm data to assist in decision-making and prevention of safety management.

[0068] In one embodiment of the present invention, a clock synchronization module is further included, which uses link layer timestamp technology to complete the clock synchronization process of the entire network node through hierarchical and synchronous methods, and uses two-way communication to reduce latency. In addition, a node positioning module is also included, which uses an antenna array or multiple receivers to sense the arrival direction of the signal sent by the sending node and calculate the distance d and relative azimuth angle θ between the sending node and the receiving node. The calculation formula is:

[0069]

[0070] Where: c is the speed of light, Δt is the signal propagation time difference, (x1, y1) and (x2, y2) are the coordinates of the sending node and the receiving node respectively. The node positioning module uses an antenna array or multiple receivers to keenly sense the arrival direction of the signal sent by the sending node. According to the above precise calculation formula, it accurately calculates the distance and relative azimuth angle between the sending node and the receiving node.

[0071] In one embodiment of the present invention, a data fusion module is further included, which applies compressed sensing theory to reduce the amount of data transmitted and removes redundant information through data fusion technology. The amount of information after data fusion is I fused Expressed as:

[0072] I fused =f(I1,I2,…,I n )

[0073] Where: I1, I2, …, I n is the amount of original information from different sensors, and f is the data fusion function.

[0074] In addition, it also includes a communication interface module, which uses multiple communication interfaces such as TCP / IP and serial port to build an embedded server to communicate with the host computer client, realize various human-computer interaction functions such as data query, parameter setting, and command issuance, greatly improving the system's operational convenience and flexibility.

[0075] In addition, it also includes an independent component analysis module, which is used to represent the monitored data signal as a linear variable combination of component independent signals, that is, to recover the independent basic source signals from the mixed signal. Its mathematical model is:

[0076] X = AS, where X is the observation signal matrix, A is the mixing matrix, and S is the source signal matrix. Based on this precise mathematical model, the independent component analysis module meticulously analyzes and processes the monitored data signals, converting them into a form represented by a linear variable combination of component-independent signals. This successfully recovers the mutually independent basic source signals from the mixed signals. This function is of great significance for in-depth analysis of monitoring data and accurate extraction of key information, helping to more accurately grasp the actual status of the bridge.

[0077] A multi-source data fusion highway bridge safety early warning system early warning method includes the following steps:

[0078] S1. Bridge Data Collection: Vibration sensors, pressure sensors, load sensors, radar detectors, and other equipment are used to comprehensively and meticulously collect key data such as bridge vibration, pressure, load size, crack width, and bridge deformation. During the collection process, the normal operation of the equipment and the accuracy and integrity of the data are ensured, providing a solid data foundation for subsequent analysis and evaluation.

[0079] S2. Data Analysis and Evaluation: Conduct a comprehensive and in-depth analysis and evaluation of the data collected in step S1. Specifically, compare and analyze the collected data with historical data and pre-set standard values. Through this dual comparison method, accurately grasp the changing trends of bridge operation conditions, promptly identify potential safety hazards, and provide a scientific basis for subsequent early warning and treatment work;

[0080] S3. Data feedback and alarms: Monitoring indicators collected by various sensors are automatically and promptly transmitted to the management system. Once a monitoring indicator is found to exceed the pre-set safety parameter range, an alarm message is immediately triggered and accurately sent to the relevant responsible person of the bridge management and maintenance unit so that they can quickly take appropriate measures to ensure the safe operation of the bridge.

[0081] S4. Shooting when the monitoring index exceeds the established standard value: When the monitoring index exceeds the established standard value, the 8-megapixel snapshot camera will be instructed to start shooting. If the shooting time is at night, the fill light will be triggered at the same time to ensure that the license plate information of the suspected vehicle that triggered the warning can be clearly captured. In addition, the bridge warning information and the captured suspected vehicle license plate number and other related information will be sent to the bridge law enforcement supervision unit at the same time, providing a strong basis for subsequent law enforcement investigations and other work;

[0082] S5. Analysis of historical alarm data: Based on historical alarm data, the number of alarms is deeply analyzed and counted according to the two dimensions of time and location, and then corresponding statistical data is formed. By using scientific and reasonable statistical methods and analysis tools, valuable information is extracted from these statistical data to provide strong auxiliary support for decision-making and prevention work in bridge safety management.

[0083] While the present invention has been generally described above, modifications and improvements are readily apparent to those skilled in the art. Therefore, modifications and improvements that do not depart from the spirit of the present invention are intended to be within the scope of the present invention.

Claims

1. A multi-source data fusion highway bridge safety early warning system, characterized in that: include: Hardware components, including vibration sensors, pressure sensors, load sensors, radar detectors, 8-megapixel snapshot cameras, and fill lights; Software module, which is used to receive data from hardware components and perform data analysis, safety warning, vehicle capture and data statistics functions. The software module includes: A data analysis module is used to collect bridge vibration, pressure, load, crack width, bridge deformation and other indicators using the vibration sensor, pressure sensor, load sensor, and radar detector, and to detect and evaluate the bridge operation status through the dual standards of historical comparison and standard value comparison; Safety early warning module, used to automatically transmit monitoring indicators back to the management system. Once the value exceeds the preset parameters, the alarm information is triggered and sent to the person in charge of the bridge maintenance unit; The vehicle capture module is used to instruct the camera to take pictures when the monitoring index exceeds the standard value. For example, it triggers the flash light at night to capture the license plate of the suspected vehicle that triggered the warning, and simultaneously sends the bridge warning information and the suspected vehicle license plate number and other information to the bridge law enforcement supervision unit; The data statistics module is used to generate alarm data statistically calculated by time and location based on historical alarm data, to assist in decision-making and prevention of safety management.

2. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: The safety warning module includes: A preset parameter setting unit, used to set preset safety parameters of bridge operation conditions; A monitoring indicator feedback unit is used to automatically transmit the collected monitoring indicators back to the management system; The alarm trigger unit is used to trigger an alarm message to be sent to the person in charge of the bridge maintenance unit when the monitoring indicators exceed the preset parameters.

3. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: The vehicle capture module comprises: The shooting command unit is used to instruct the snapshot camera to shoot when the monitoring index exceeds the standard value; Flash trigger unit, used to trigger the fill light at the same time when shooting at night; The information sending unit is used to capture the license plate of the suspected vehicle that triggered the warning, and simultaneously send the bridge warning information and the suspected vehicle license plate number and other information to the bridge law enforcement supervision unit.

4. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: The data statistics module includes: A historical alarm data recording unit, used to record historical alarm data; The statistical analysis unit is used to generate alarm statistics by time and location based on historical alarm data to assist in decision-making and prevention of safety management.

5. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: It also includes a clock synchronization module, which uses link layer timestamping technology to complete the clock synchronization process of the entire network node through classification and synchronization, and uses two-way communication to reduce latency.

6. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: It also includes a node positioning module, which senses the arrival direction of the signal sent by the sending node through an antenna array or multiple receivers, and calculates the distance d and the relative azimuth angle θ between the sending node and the receiving node. The calculation formula is: Where: c is the speed of light, Δt is the signal propagation time difference, (x1, y1) and (x2, y2) are the coordinates of the sending node and the receiving node respectively. The node positioning module uses an antenna array or multiple receivers to keenly sense the arrival direction of the signal sent by the sending node.

7. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: It also includes a data fusion module, which uses compressed sensing theory to reduce the amount of data transmission and removes redundant information through data fusion technology. fused It is expressed as: I fused =f(I1,I2,…,I n ) Where: I1, I2, …, I n is the amount of original information from different sensors, and f is the data fusion function.

8. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: It also includes a communication interface module, which uses TCP / IP, serial port and other communication interfaces to build an embedded server to communicate with the host computer client and realize various human-computer interaction functions.

9. The multi-source data fusion highway bridge safety early warning system according to claim 1 is characterized by: It also includes an independent component analysis module, which is used to represent the monitored data signal with a linear variable combination of component independent signals, that is, to recover independent basic source signals from the mixed signal. Its mathematical model is: X=AS, where: X is the observation signal matrix, A is the mixing matrix, and S is the source signal matrix.

10. An early warning method of the highway bridge safety early warning system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Collect bridge data: collect bridge vibration, pressure, load, crack width and bridge deformation data through vibration sensors, pressure sensors, load sensors and radar detectors; S2. Data analysis and evaluation: conduct historical comparison and standard value comparison of the collected data to detect and evaluate the bridge operation status; S3, data feedback and alarm: the monitoring indicators are automatically transmitted back to the management system, and when the monitoring indicators exceed the preset parameters, the alarm information is triggered and sent to the responsible person of the bridge maintenance unit; S4, shooting beyond the standard value: when the monitoring index exceeds the standard value, instruct the camera to shoot, and trigger the fill light at the same time when shooting at night, capture the license plate of the suspected vehicle that triggered the warning, and simultaneously send the bridge warning information and the suspected vehicle license plate number and other information to the bridge law enforcement supervision unit; S5. Analysis of historical alarm data: Based on historical alarm data, generate alarm data statistically calculated by time and location to assist in decision-making and prevention of safety management.

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