Beidou-based high-precision monitoring bridge fabrication machine intelligent monitoring system

Abstract

The invention discloses a Beidou-based high-precision bridge fabrication machine intelligent monitoring system, and the system comprises a Beidou satellite positioning module, and the output end of the Beidou satellite positioning module is electrically connected with a construction progress analysis module and a data collection and transmission module. The output end of the data acquisition and transmission module is electrically connected with a data processing and analysis module, and the output end of the data processing and analysis module is electrically connected with an equipment health assessment module and a data storage and management module. According to the invention, high-precision monitoring of the position of the bridge fabrication machine is realized through the Beidou satellite positioning module, and the operation state of the bridge fabrication machine can be comprehensively and accurately mastered in combination with multi-dimensional data acquired by the stress sensor, the tilt angle sensor and the like; the construction progress analysis module can analyze the construction progress in real time, the equipment health evaluation module can predict the residual life of equipment, the early warning and decision making module makes a timely decision according to various data, and intelligent management of the bridge fabrication machine is achieved.

Description

Technical Field

[0001] This invention relates to the field of bridge-building machine monitoring technology, specifically a high-precision intelligent monitoring system for bridge-building machines based on the BeiDou Navigation Satellite System. Background Technology

[0002] In bridge construction, bridge-building machines are key equipment, and monitoring their operational status is crucial for ensuring construction safety, progress, and quality. Traditional bridge-building machine monitoring methods often suffer from low monitoring accuracy, untimely data processing, and the inability to achieve remote control and intelligent management. With the development of BeiDou satellite positioning technology, its application to bridge-building machine monitoring can effectively improve monitoring accuracy and reliability. However, there is currently no complete, high-precision bridge-building machine monitoring system based on BeiDou with intelligent functions, which cannot meet the needs of modern bridge construction for efficient, safe, and intelligent monitoring of bridge-building machines. Summary of the Invention

[0003] The purpose of this invention is to provide a high-precision intelligent monitoring system for bridge-building machines based on BeiDou, which has the advantages of high-precision monitoring of the operating status of bridge-building machines, intelligent management and remote control, and ensuring the safety and progress of bridge construction.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a high-precision intelligent monitoring system for bridge-building machines based on BeiDou, comprising a BeiDou satellite positioning module. The output terminals of the BeiDou satellite positioning module are electrically connected to a construction progress analysis module and a data acquisition and transmission module, respectively. The output terminal of the data acquisition and transmission module is electrically connected to a data processing and analysis module. The output terminals of the data processing and analysis module are electrically connected to an equipment health assessment module and a data storage and management module, respectively. Another output terminal of the data processing and analysis module is electrically connected to an early warning and decision-making module. The output terminal of the early warning and decision-making module is electrically connected to a remote control module. The output terminal of the remote control module is electrically connected to a collaborative communication module. The data processing and analysis module is also electrically connected to an environmental monitoring module.

[0005] As a preferred embodiment, the input end of the data acquisition and transmission module is electrically connected to a data encryption module, and the input end of the data encryption module is electrically connected to a user access control module.

[0006] As a preferred embodiment, the remote control module includes manual remote control, automatic remote control, and emergency control. The output of the emergency control is electrically connected to a remote control terminal, and the output of the remote control terminal is electrically connected to a controller. The automatic remote control is also electrically connected to the input of the early warning and decision-making module.

[0007] As a preferred embodiment, the data acquisition module is also electrically connected to a stress sensor and a tilt sensor, wherein the stress sensor acquires structural stress data and the tilt sensor acquires tilt angle data.

[0008] As a preferred embodiment, the output terminal of the early warning and decision-making module is electrically connected to an alarm module, and the output terminal of the alarm module is electrically connected to a mobile receiver. The alarm module can remind construction personnel through audible and visual alarms and SMS notifications.

[0009] As a preferred embodiment, the environmental monitoring module includes a wind speed sensor, a temperature and humidity sensor, and a rainfall sensor, and monitors the environmental parameters of the bridge-building machine in real time. It combines the environmental data with the bridge-building machine's operating data for analysis and assesses the impact of environmental factors on the operation of the bridge-building machine.

[0010] As a preferred option, the data encryption module employs advanced encryption algorithms, such as the AES encryption algorithm, to encrypt all data collected, transmitted, and stored by the system.

[0011] As a preferred embodiment, the construction progress analysis module uses the location data of the bridge-building machine obtained by the Beidou satellite positioning module, combined with the preset construction route and schedule, and uses a dynamic time series analysis algorithm to generate a visual construction progress Gantt chart, and compares the actual progress with the planned progress in real time. When the progress deviation exceeds the preset threshold, an abnormal signal is sent to the early warning and decision-making module.

[0012] As a preferred embodiment, the equipment health assessment module uses machine learning algorithms to construct an equipment health status assessment model based on the equipment operation data processed by the data processing and analysis module. It predicts the remaining life of key components of the bridge building machine, such as the hydraulic system and transmission device, and classifies the health status level. When the equipment health status drops to a dangerous level, it issues an equipment maintenance warning to the early warning and decision-making module.

[0013] As a preferred solution, the data storage and management module adopts a distributed storage architecture, which classifies and stores the collected data on different storage nodes, and performs data backup and archiving regularly. At the same time, it sets up a data retrieval index to support fast retrieval based on multiple dimensions such as time, device number, and data type, making it convenient for users to query historical monitoring data.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0015] 1. This invention achieves high-precision monitoring of the bridge-building machine's position through a BeiDou satellite positioning module. Combined with multi-dimensional data collected by stress sensors, tilt sensors, etc., it can comprehensively and accurately grasp the operating status of the bridge-building machine. The construction progress analysis module can analyze the construction progress in real time, the equipment health assessment module can predict the remaining lifespan of the equipment, and the early warning and decision-making module can make timely decisions based on various data, realizing intelligent management of the bridge-building machine and improving construction efficiency and quality. The remote control module has multiple control methods, enabling remote operation of the bridge-building machine. In case of dangerous situations or when remote adjustments are needed, timely control can be performed to ensure the safety of construction personnel and the smooth progress of construction. The data encryption module and user permission management module ensure the security and privacy of system data, preventing data leakage and unauthorized operation.

[0016] 2. This invention, through the combined design of a data acquisition and transmission module, a data encryption module, a user access control module, a remote control module, and stress and tilt sensors, offers significant advantages. The data encryption and user access control modules ensure data security from the data source to the transmission process. Advanced AES encryption prevents data leakage, and strict access control avoids unauthorized operations, ensuring the confidentiality of monitoring data and the security of the system. The remote control module's manual, automatic, and emergency control modes provide operators with flexible and diverse control methods. The automatic remote control and early warning decision-making module work together to respond quickly to abnormal situations, while emergency control enables remote intervention in emergency situations, effectively ensuring the safety of construction personnel and the smooth progress of construction. The stress and tilt sensors collect real-time data on the structural stress and tilt angle of the bridge-building machine, which, in conjunction with other data such as BeiDou positioning, provides the system with rich information on equipment operating status. This allows the system to comprehensively and accurately grasp the operating status of the bridge-building machine, providing strong data support for equipment health assessment and early warning decision-making, thus improving the comprehensiveness and accuracy of monitoring. Attached Figure Description

[0017] Figure 1 This is the main schematic diagram of the system principle of the present invention;

[0018] Figure 2 This is a system connection diagram of the remote control module of the present invention;

[0019] Figure 3 This is a system diagram of the data acquisition and transmission module of the present invention;

[0020] Figure 4 This is a system diagram of the early warning and decision-making module of the present invention;

[0021] Figure 5 This is a system diagram of the environmental monitoring module of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0024] Example 1:

[0025] Please see Figure 1 As shown, this invention provides a high-precision intelligent monitoring system for bridge-building machines based on BeiDou, including a BeiDou satellite positioning module. The output of the BeiDou satellite positioning module is electrically connected to a construction progress analysis module and a data acquisition and transmission module. The output of the data acquisition and transmission module is electrically connected to a data processing and analysis module. The output of the data processing and analysis module is electrically connected to an equipment health assessment module and a data storage and management module. Another output of the data processing and analysis module is electrically connected to an early warning and decision-making module. The output of the early warning and decision-making module is electrically connected to a remote control module. The output of the remote control module is electrically connected to a collaborative communication module. The data processing and analysis module is also electrically connected to an environmental monitoring module.

[0026] Example 2:

[0027] Based on Embodiment 1, the present invention is as follows: Figure 3 As shown, the data acquisition and transmission module has an input terminal electrically connected to a data encryption module, and the input terminal of the data encryption module is electrically connected to a user access control module; the remote control module includes manual remote control, automatic remote control, and emergency control, the output terminal of the emergency control module is electrically connected to a remote control terminal, the output terminal of the remote control terminal is electrically connected to a controller, and the automatic remote control module is also electrically connected to the input terminal of the early warning and decision-making module; the data acquisition module is also electrically connected to a stress sensor and a tilt sensor, the stress sensor collects structural stress data, and the tilt sensor collects tilt angle data.

[0028] Adopting such Figure 1The technical solution presented, featuring a combined design of a data acquisition and transmission module, a data encryption module, a user access control module, a remote control module, and stress and tilt sensors, offers significant advantages. The data encryption and user access control modules ensure data security from the data source to the transmission process. Advanced AES encryption prevents data leakage, and strict access control avoids unauthorized operations, ensuring the confidentiality of monitoring data and the security of the system. The remote control module's manual, automatic, and emergency control modes provide operators with flexible and diverse control methods. The automatic remote control and early warning decision-making module work together to respond quickly to abnormal situations, while emergency control enables remote intervention in emergency situations, effectively ensuring the safety of construction personnel and the smooth progress of construction. The stress and tilt sensors collect real-time data on the structural stress and tilt angle of the bridge-building machine, which, in conjunction with other data such as BeiDou positioning, provides the system with rich information on equipment operating status. This allows the system to comprehensively and accurately grasp the operating status of the bridge-building machine, providing strong data support for equipment health assessment and early warning decision-making, thus improving the comprehensiveness and accuracy of monitoring.

[0029] Secondly, in the technical solution, the output end of the early warning and decision-making module is electrically connected to an alarm module, and the output end of the alarm module is electrically connected to a mobile receiver. The alarm module can remind construction personnel through audible and visual alarms and SMS notifications. The environmental monitoring module includes wind speed sensors, temperature and humidity sensors, and rainfall sensors, and monitors the environmental parameters of the bridge-building machine in real time. It combines environmental data with bridge-building machine operation data for analysis to assess the impact of environmental factors on the operation of the bridge-building machine. The data encryption module uses advanced encryption algorithms, such as AES encryption algorithm, to encrypt all data collected, transmitted, and stored by the system.

[0030] Its adoption is as follows Figure 1 The technical solution shown comprises an early warning and decision-making module, an alarm module, and a mobile receiver, forming a highly efficient safety early warning system. Audible and visual alarms immediately attract personnel's attention at the construction site, while SMS notifications overcome spatial limitations, ensuring that construction personnel can receive abnormal information promptly regardless of their location, effectively avoiding safety hazards caused by information delays. The environmental monitoring module uses wind speed, temperature, humidity, and rainfall sensors to capture environmental changes in real time, deeply integrating and analyzing environmental data with bridge-building machine operation data. This allows the system to predict potential threats to bridge-building machine operation from severe weather such as strong winds and heavy rains, and make corresponding decisions, greatly enhancing the system's adaptability to complex environments. The data encryption module uses the AES encryption algorithm, like adding a robust digital lock to the system data. Encryption is provided throughout the entire process from acquisition and transmission to storage, preventing data from being stolen or tampered with during the transfer process, building a solid defense for system data security, and ensuring the integrity and confidentiality of monitoring data.

[0031] Example 3:

[0032] The present invention is as follows Figures 1-5 As shown, the construction progress analysis module discloses the location data of the bridge-building machine obtained by the Beidou satellite positioning module. Combined with the preset construction route and schedule, it uses a dynamic time series analysis algorithm to generate a visualized Gantt chart of construction progress and compares the actual progress with the planned progress in real time. When the progress deviation exceeds a preset threshold, an abnormal signal is sent to the early warning and decision-making module. The equipment health assessment module, based on the equipment operation data processed by the data processing and analysis module, uses machine learning algorithms to build an equipment health status assessment model. It predicts the remaining life of key components of the bridge-building machine, such as the hydraulic system and transmission device, and classifies the health status levels. When the equipment health status drops to a dangerous level, it issues an equipment maintenance warning to the early warning and decision-making module. The data storage and management module adopts a distributed storage architecture, classifies and stores the collected data in different storage nodes, and performs regular data backup and archiving. At the same time, it sets up a data retrieval index to support fast retrieval based on multiple dimensions such as time, equipment number, and data type, making it convenient for users to query historical monitoring data.

[0033] Using the above technical solution, the construction progress analysis module uses Beidou positioning data and dynamic time series algorithms to transform the abstract construction progress into an intuitive and visual Gantt chart, allowing construction personnel and managers to clearly grasp the construction rhythm of the bridge-building machine, compare the actual and planned progress in real time, and provide timely warnings in case of deviations, providing a strong basis for adjusting the construction plan and ensuring that the bridge construction is completed on time.

[0034] The equipment health assessment module leverages machine learning algorithms to deeply mine equipment operating data, accurately predicting the remaining lifespan and classifying the health status of key bridge-building machine components. This proactively identifies potential failure risks, preventing downtime losses due to sudden equipment malfunctions and shifting from reactive to proactive maintenance. This effectively reduces maintenance costs and extends equipment lifespan. The data storage and management module employs a distributed storage architecture, improving data storage stability and reliability. Through categorized storage, regular backups and archiving, and multi-dimensional retrieval functions, it allows users to quickly and accurately retrieve historical monitoring data. Whether reviewing the construction process, analyzing equipment failure causes, or providing data references for subsequent projects, this can be easily achieved, improving data utilization efficiency and system management level.

[0035] The working principle of this invention is as follows: The Beidou satellite positioning module, as the core information source of the system, continuously receives satellite signals and synchronously transmits the high-precision position data of the bridge-building machine to the construction progress analysis module and the data acquisition and transmission module. The construction progress analysis module processes the position data using a dynamic time series analysis algorithm based on the preset construction route and schedule plan, generates a visual Gantt chart, and compares the actual and planned progress in real time. If the deviation exceeds the threshold, an abnormal signal is immediately sent to the early warning and decision-making module.

[0036] In addition to acquiring BeiDou data, the data acquisition and transmission module also collects structural stress and tilt angle data through stress sensors and tilt sensors. Combined with environmental parameter data such as wind speed, temperature, humidity, and rainfall collected by the environmental monitoring module, the data is encrypted by the data encryption module before being transmitted to the data processing and analysis module. This module decrypts and analyzes the data, providing the equipment operation data to the equipment health assessment module. The equipment health assessment module uses machine learning algorithms to build models, predict the remaining lifespan of key components, classify health levels, and send maintenance warnings to the early warning and decision-making module when anomalies occur. The processed data is stored in the data storage and management module, enabling categorized storage, regular backup and archiving, and multi-dimensional retrieval, while also providing comprehensive data support to the early warning and decision-making module.

[0037] The early warning and decision-making module judges the operating status of the bridge-building machine based on the received data. If abnormal construction progress, equipment health hazards, or excessive environmental parameters occur, it quickly makes a decision and sends instructions to the remote control module. The remote control module selects manual, automatic, or emergency control mode according to the instructions and accurately transmits the control instructions to each component of the bridge-building machine for execution through the collaborative communication module. At the same time, if an alarm is required, the early warning and decision-making module controls the alarm module to promptly remind construction personnel through audible and visual alarms and SMS notifications to mobile receivers. All modules of the entire system work closely together to achieve high-precision monitoring, intelligent management, and remote control of the bridge-building machine through data collection, transmission, processing, analysis, and feedback.

[0038] It is important to note that the constructions and arrangements of this application shown in several different exemplary embodiments are merely illustrative. Although only a few embodiments are described in detail in this disclosure, those who consult this disclosure will readily understand that many modifications are possible (e.g., changes in the size, dimensions, structure, shape, and proportions of various elements, as well as parameter values ​​(e.g., temperature, pressure, etc.), mounting arrangements, use of materials, color, orientation, etc.) without substantially departing from the novel teachings and advantages of the subject matter described in this application). For example, an element shown as integrally formed may be composed of multiple parts or elements, the position of elements may be inverted or otherwise altered, and the nature or number or position of discrete elements may be changed or altered. Therefore, all such modifications are intended to be included within the scope of the invention. The order or sequence of any process or method steps may be changed or rearranged according to alternative embodiments. In the claims, any "device plus function" clause is intended to cover the structure performing the function described herein, and not only structural equivalents but also equivalent structures. Other substitutions, modifications, alterations, and omissions may be made in the design, operation, and arrangement of the exemplary embodiments without departing from the scope of the invention. Therefore, the present invention is not limited to the specific embodiments, but extends to various modifications that still fall within the scope of the appended claims.

[0039] Furthermore, in order to provide a concise description of exemplary embodiments, not all features of actual embodiments (i.e., those features that are not relevant to the best mode of carrying out the invention as currently considered, or those features that are not relevant to implementing the invention) may be omitted.

[0040] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A high-precision intelligent monitoring system for bridge-building machines based on BeiDou, including a BeiDou satellite positioning module, characterized in that: The output terminals of the BeiDou satellite positioning module are electrically connected to a construction progress analysis module and a data acquisition and transmission module, respectively. The output terminal of the data acquisition and transmission module is electrically connected to a data processing and analysis module. The output terminals of the data processing and analysis module are electrically connected to an equipment health assessment module and a data storage and management module, respectively. Another output terminal of the data processing and analysis module is electrically connected to an early warning and decision-making module. The output terminal of the early warning and decision-making module is electrically connected to a remote control module. The output terminal of the remote control module is electrically connected to a collaborative communication module. The data processing and analysis module is also electrically connected to an environmental monitoring module.

2. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The input end of the data acquisition and transmission module is electrically connected to a data encryption module, and the input end of the data encryption module is electrically connected to a user access control module.

3. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The remote control module includes manual remote control, automatic remote control, and emergency control. The output of the emergency control is electrically connected to a remote control terminal, and the output of the remote control terminal is electrically connected to a controller. The automatic remote control is also electrically connected to the input of the early warning and decision-making module.

4. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The data acquisition module is also electrically connected to a stress sensor and a tilt sensor. The stress sensor collects structural stress data, and the tilt sensor collects tilt angle data.

5. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The output of the early warning and decision-making module is electrically connected to an alarm module, and the output of the alarm module is electrically connected to a mobile receiver. The alarm module can remind construction personnel through audible and visual alarms and SMS notifications.

6. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The environmental monitoring module includes a wind speed sensor, a temperature and humidity sensor, and a rainfall sensor. It monitors the environmental parameters of the bridge-building machine in real time, combines the environmental data with the bridge-building machine's operating data for analysis, and assesses the impact of environmental factors on the operation of the bridge-building machine.

7. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The data encryption module employs advanced encryption algorithms, such as AES encryption, to encrypt all data collected, transmitted, and stored by the system.

8. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The construction progress analysis module uses the location data of the bridge-building machine obtained by the Beidou satellite positioning module, combined with the preset construction route and schedule, and uses a dynamic time series analysis algorithm to generate a visual construction progress Gantt chart. It also compares the actual progress with the planned progress in real time. When the progress deviation exceeds the preset threshold, it sends an abnormal signal to the early warning and decision-making module.

9. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The equipment health assessment module uses machine learning algorithms to construct an equipment health status assessment model based on the equipment operation data processed by the data processing and analysis module. It predicts the remaining life of key components of the bridge building machine, such as the hydraulic system and transmission device, and classifies the health status level. When the equipment health status drops to the dangerous level, it issues an equipment maintenance warning to the early warning and decision-making module.

10. The intelligent monitoring system for high-precision bridge-building machines based on BeiDou as described in claim 1, characterized in that: The data storage and management module adopts a distributed storage architecture, which classifies and stores the collected data on different storage nodes, and performs data backup and archiving regularly. At the same time, it sets up a data retrieval index to support fast retrieval based on multiple dimensions such as time, device number, and data type, making it convenient for users to query historical monitoring data.

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