Foundation safety protection dynamic monitoring method based on sensor network

Abstract

The invention discloses a foundation safety protection dynamic monitoring method based on a sensor network, relates to the technical field of constructional engineering, and solves the problems that the monitoring range of a foundation detection system is limited, generally, a single-point sensor can only cover an area near a mounting point, the overall state of a foundation is difficult to reflect comprehensively, and the monitoring cost is low. Multi-dimensional sensors are arranged around a foundation and at key parts to form a sensor network with comprehensive coverage, comprehensive monitoring of foundation safety is realized by constructing the multi-dimensional sensor network, real-time transmission of data is ensured by using the Internet of Things technology, the timeliness and accuracy of monitoring are improved, and the safety of the foundation is improved. Monitoring parameters and monitoring frequency are dynamically adjusted, sensor layout is optimized, continuous and accurate monitoring of foundation safety is achieved, a data processing system based on big data analysis and an artificial intelligence algorithm can automatically recognize abnormal changes of the foundation safety state and give out early warning, the requirement for manual intervention is effectively reduced, and the safety of the foundation is improved. And the accuracy and timeliness of early warning are improved.

Description

Technical Field

[0001] The invention relates to the technical field of construction engineering, and in particular to a sensor network-based dynamic monitoring method for foundation safety protection. Background Art

[0002] In modern engineering construction and operation, foundation safety is a key factor in ensuring the stability and safety of the overall structure. At present, there are many foundation monitoring technologies on the market, among which the more common ones are static monitoring methods based on single-point sensors, such as strain gauges and inclinometers. These methods collect data regularly and analyze parameters such as foundation deformation and stress changes to evaluate the safety of the foundation. The existing foundation detection system has a limited monitoring range. Generally, single-point sensors can only cover the area near their installation points, which makes it difficult to fully reflect the overall status of the foundation. At the same time, they rely on regular manual inspections and data collection, and cannot achieve real-time monitoring of the foundation status, which may lead to delayed discovery of safety hazards. The data at each point are independent and there is a lack of a unified data management platform, making it difficult to achieve comprehensive analysis and early warning of multi-source data. The large-scale deployment of single-point sensors not only increases the installation and maintenance costs, but also increases the complexity of data analysis. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a dynamic monitoring method for foundation safety protection based on a sensor network, which is used to solve the problem that the existing foundation detection system has a limited monitoring range. Generally, a single-point sensor can only cover the area near its installation point, which is difficult to fully reflect the overall state of the foundation. At the same time, it relies on manual regular inspections and data collection, and cannot achieve real-time monitoring of the foundation state, which may lead to delayed discovery of safety hazards. The data of each point are independent and there is a lack of a unified data management platform, making it difficult to achieve comprehensive analysis and early warning of multi-source data. The large-scale deployment of single-point sensors not only increases the installation and maintenance costs, but also increases the complexity of data analysis.

[0004] To achieve the above-mentioned purpose, according to an embodiment of the first aspect of the present invention, a ground-based safety protection dynamic monitoring method based on a sensor network is proposed, comprising an information collection system, a data processing system, a data terminal and a multi-dimensional sensor network; The multi-dimensional sensor network is constructed by arranging multi-dimensional sensors including displacement sensors, stress sensors, osmometers, temperature sensors, etc. around the foundation and key parts to form a comprehensive sensor network to achieve synchronous monitoring of foundation deformation, stress state, seepage conditions and temperature changes; The information collection system includes: real-time data collection and transmission, data import module and data comparison module; The real-time data collection and transmission is used to collect multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network in real time, and transmit the collected information at the same time, using the Internet of Things technology to realize real-time collection of sensor network data; The data import module is used to import and store the threshold data set by the user, and compare the input threshold data with the real-time data collection and transmission; The data comparison module is used to compare the multi-dimensional information including displacement information, stress information, osmotic pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user; The data processing system includes: intelligent data analysis and early warning, dynamic monitoring and feedback adjustment, network communication module, log generation module and data storage module; The intelligent data analysis and early warning is based on the analysis of the collected data and the comparison with the imported data threshold, the collected data is integrated and analyzed, abnormal changes in the foundation safety status are automatically identified, and timely and accurate early warning information is issued through the preset early warning model; The dynamic monitoring and feedback adjustment is to dynamically adjust the monitoring parameters and monitoring frequency according to the monitoring results, optimize the sensor layout, form a closed-loop monitoring system, and achieve continuous and accurate monitoring of foundation safety; The network communication module transmits the feedback data and the early warning data to the data terminal, so that the staff can directly monitor the foundation data in real time; The log generation module stores the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored, which is convenient for subsequent reference; The data storage module stores data by wirelessly transmitting it to the cloud or a local data center, and can effectively review the data during subsequent calls and inquiries, ensuring the timeliness and integrity of the data.

[0005] Preferably, the operation steps of the information collection system are: S1. Multi-dimensional sensors including displacement sensors, stress sensors, osmometers, and temperature sensors are arranged around the foundation and at key locations to form a comprehensive sensor network to achieve simultaneous monitoring of foundation deformation, stress state, seepage conditions, and temperature changes. Multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network is collected in real time through data acquisition and transmission; S2. The collected information is transmitted, and the Internet of Things technology is used to realize the real-time collection of sensor network data. Then, the data import module is used to import and store the user-set threshold data, and the input set threshold data is compared with the real-time data collection and transmission; S3. Compare the multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user. By building a multi-dimensional sensor network, comprehensive monitoring of foundation safety is achieved. At the same time, the Internet of Things technology is used to ensure real-time transmission of data, greatly improving the timeliness and accuracy of monitoring.

[0006] Preferably, the steps of the data processing system are: P1. Using intelligent data analysis and early warning is to analyze the collected data and compare it with the imported data threshold, perform fusion analysis on the collected data, automatically identify abnormal changes in the foundation safety status, and issue timely and accurate early warning information through the preset early warning model; P2. Use dynamic monitoring and feedback adjustment to dynamically adjust monitoring parameters and monitoring frequency according to monitoring results, optimize sensor layout, form a closed-loop monitoring system, achieve continuous and accurate monitoring of foundation safety, and transmit feedback data and early warning data to the data terminal using the network communication module, so that staff can directly monitor the foundation data in real time; P3. Store the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored for easy subsequent reference. The data is stored by wirelessly transmitting it to the cloud or local data center, so that the data can be effectively reviewed during subsequent calls and queries to ensure the timeliness and integrity of the data. The data processing system based on big data analysis and artificial intelligence algorithms can automatically identify abnormal changes in the safety status of the foundation and issue early warnings, effectively reducing the need for manual intervention and improving the accuracy and timeliness of early warnings.

[0007] Compared with the prior art, the beneficial effects of the present invention are as follows: multi-dimensional sensors including displacement sensors, stress sensors, osmometers, temperature sensors, etc. are arranged around the foundation and at key positions to form a comprehensive sensor network to realize synchronous monitoring of foundation deformation, stress state, seepage conditions and temperature changes; information collected on the multi-dimensional sensor network is collected in real time by data collection and transmission, and the collected information is transmitted at the same time; multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network is compared with user-set threshold data by using the Internet of Things technology; comprehensive monitoring of foundation safety is realized by constructing a multi-dimensional sensor network; real-time transmission of data is guaranteed by using the Internet of Things technology, which greatly improves the timeliness and accuracy of monitoring; monitoring parameters and monitoring frequency are dynamically adjusted, sensor layout is optimized, a closed-loop monitoring system is formed, and continuous and accurate monitoring of foundation safety is realized; a data processing system based on big data analysis and artificial intelligence algorithms can automatically identify abnormal changes in the foundation safety status and issue early warnings, effectively reducing the need for manual intervention and improving the accuracy and timeliness of early warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 It is a schematic diagram of the principle framework of the ground-based security protection dynamic monitoring method based on the sensor network of the present invention; Figure 2 It is a flow chart of the information collection system of the ground safety protection dynamic monitoring method based on the sensor network of the present invention; Figure 3 It is a flow chart of the data processing system of the sensor network-based ground safety protection dynamic monitoring method of the present invention. DETAILED DESCRIPTION

[0009] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention. Example

[0010] See also Figure 1-3 , the embodiment provided by the present invention: a ground-based safety protection dynamic monitoring method based on a sensor network, including an information collection system, a data processing system, a data terminal and a multi-dimensional sensor network; The multi-dimensional sensor network is constructed by arranging multi-dimensional sensors including displacement sensors, stress sensors, osmometers, temperature sensors, etc. around the foundation and key parts to form a comprehensive sensor network to achieve synchronous monitoring of foundation deformation, stress state, seepage conditions and temperature changes; The information collection system includes: real-time data collection and transmission, data import module and data comparison module; The real-time data collection and transmission is used to collect multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network in real time, and transmit the collected information at the same time, using the Internet of Things technology to realize real-time collection of sensor network data; The data import module is used to import and store the threshold data set by the user, and compare the input threshold data with the real-time data collection and transmission; The data comparison module is used to compare the multi-dimensional information including displacement information, stress information, osmotic pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user; The data processing system includes: intelligent data analysis and early warning, dynamic monitoring and feedback adjustment, network communication module, log generation module and data storage module; The intelligent data analysis and early warning is based on the analysis of the collected data and the comparison with the imported data threshold, the collected data is integrated and analyzed, abnormal changes in the foundation safety status are automatically identified, and timely and accurate early warning information is issued through the preset early warning model; The dynamic monitoring and feedback adjustment is to dynamically adjust the monitoring parameters and monitoring frequency according to the monitoring results, optimize the sensor layout, form a closed-loop monitoring system, and achieve continuous and accurate monitoring of foundation safety; The network communication module transmits the feedback data and the early warning data to the data terminal, so that the staff can directly monitor the foundation data in real time; The log generation module stores the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored, which is convenient for subsequent reference; The data storage module stores data by wirelessly transmitting it to the cloud or a local data center, and can effectively review the data during subsequent calls and inquiries, ensuring the timeliness and integrity of the data.

[0011] Furthermore, the operation steps of the information collection system are: S1. Multi-dimensional sensors including displacement sensors, stress sensors, osmometers, and temperature sensors are arranged around the foundation and at key locations to form a comprehensive sensor network to achieve simultaneous monitoring of foundation deformation, stress state, seepage conditions, and temperature changes. Multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network is collected in real time through data acquisition and transmission; S2. The collected information is transmitted, and the Internet of Things technology is used to realize the real-time collection of sensor network data. Then, the data import module is used to import and store the user-set threshold data, and the input set threshold data is compared with the real-time data collection and transmission; S3. Compare the multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user. By building a multi-dimensional sensor network, comprehensive monitoring of foundation safety is achieved. At the same time, the Internet of Things technology is used to ensure real-time transmission of data, greatly improving the timeliness and accuracy of monitoring.

[0012] Furthermore, the steps of the data processing system are: P1. Using intelligent data analysis and early warning is to analyze the collected data and compare it with the imported data threshold, perform fusion analysis on the collected data, automatically identify abnormal changes in the foundation safety status, and issue timely and accurate early warning information through the preset early warning model; P2. Use dynamic monitoring and feedback adjustment to dynamically adjust monitoring parameters and monitoring frequency according to monitoring results, optimize sensor layout, form a closed-loop monitoring system, achieve continuous and accurate monitoring of foundation safety, and transmit feedback data and early warning data to the data terminal using the network communication module, so that staff can directly monitor the foundation data in real time; P3. Store the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored for easy subsequent reference. The data is stored by wirelessly transmitting it to the cloud or local data center, so that the data can be effectively reviewed during subsequent calls and queries to ensure the timeliness and integrity of the data. The data processing system based on big data analysis and artificial intelligence algorithms can automatically identify abnormal changes in the safety status of the foundation and issue early warnings, effectively reducing the need for manual intervention and improving the accuracy and timeliness of early warnings. Example

[0013] Multi-dimensional sensors including displacement sensors, stress sensors, piezometers, temperature sensors, etc. are arranged around the foundation and at key locations to form a comprehensive sensor network to achieve synchronous monitoring of foundation deformation, stress state, seepage conditions and temperature changes. Multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network is collected in real time by data acquisition and transmission. Multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network is compared with user-set threshold data. By constructing a multi-dimensional sensor network, comprehensive monitoring of foundation safety is achieved. At the same time, the Internet of Things technology is used to ensure real-time data transmission, which greatly improves the timeliness and accuracy of monitoring. At the same time, the data processing system based on big data analysis and artificial intelligence algorithms can automatically identify abnormal changes in the foundation safety status and issue early warnings, effectively reducing the need for manual intervention and improving the accuracy and timeliness of early warnings.

[0014] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A ground-based safety protection dynamic monitoring method based on a sensor network, characterized in that: Including information collection system, data processing system, data terminal and construction of multi-dimensional sensor network; The multi-dimensional sensor network is constructed by arranging multi-dimensional sensors including displacement sensors, stress sensors, osmometers, temperature sensors, etc. around the foundation and key parts to form a comprehensive sensor network to achieve synchronous monitoring of foundation deformation, stress state, seepage conditions and temperature changes; The information collection system includes: real-time data collection and transmission, data import module and data comparison module; The real-time data collection and transmission is used to collect multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network in real time, and transmit the collected information at the same time, using the Internet of Things technology to realize real-time collection of sensor network data; The data import module is used to import and store the threshold data set by the user, and compare the input threshold data with the real-time data collection and transmission; The data comparison module is used to compare the multi-dimensional information including displacement information, stress information, osmotic pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user; The data processing system includes: intelligent data analysis and early warning, dynamic monitoring and feedback adjustment, network communication module, log generation module and data storage module; The intelligent data analysis and early warning is based on the analysis of the collected data and the comparison with the imported data threshold, the collected data is integrated and analyzed, abnormal changes in the foundation safety status are automatically identified, and timely and accurate early warning information is issued through the preset early warning model; The dynamic monitoring and feedback adjustment is to dynamically adjust the monitoring parameters and monitoring frequency according to the monitoring results, optimize the sensor layout, form a closed-loop monitoring system, and achieve continuous and accurate monitoring of foundation safety; The network communication module transmits the feedback data and the early warning data to the data terminal, so that the staff can directly monitor the foundation data in real time; The log generation module stores the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored, which is convenient for subsequent reference; The data storage module stores data by wirelessly transmitting it to the cloud or a local data center, and can effectively review the data during subsequent calls and inquiries, ensuring the timeliness and integrity of the data.

2. The ground-based security protection dynamic monitoring method based on a sensor network according to claim 1 is characterized in that: The operation steps of the information collection system are as follows: S1. Multi-dimensional sensors including displacement sensors, stress sensors, osmometers, and temperature sensors are arranged around the foundation and at key locations to form a comprehensive sensor network to achieve simultaneous monitoring of foundation deformation, stress state, seepage conditions, and temperature changes. Multi-dimensional information including displacement information, stress information, seepage pressure information, and temperature information collected on the multi-dimensional sensor network is collected in real time through data acquisition and transmission; S2. The collected information is transmitted, and the Internet of Things technology is used to realize the real-time collection of sensor network data. Then, the data import module is used to import and store the user-set threshold data, and the input set threshold data is compared with the real-time data collection and transmission; S3. Compare the multi-dimensional information including displacement information, stress information, seepage pressure information and temperature information collected on the multi-dimensional sensor network with the threshold data set by the user. By building a multi-dimensional sensor network, comprehensive monitoring of foundation safety is achieved. At the same time, the Internet of Things technology is used to ensure real-time transmission of data, greatly improving the timeliness and accuracy of monitoring.

3. The ground-based security protection dynamic monitoring method based on a sensor network according to claim 1 is characterized in that: The steps of the data processing system are: P1. Using intelligent data analysis and early warning is to analyze the collected data and compare it with the imported data threshold, perform fusion analysis on the collected data, automatically identify abnormal changes in the foundation safety status, and issue timely and accurate early warning information through the preset early warning model; P2. Use dynamic monitoring and feedback adjustment to dynamically adjust monitoring parameters and monitoring frequency according to monitoring results, optimize sensor layout, form a closed-loop monitoring system, achieve continuous and accurate monitoring of foundation safety, and transmit feedback data and early warning data to the data terminal using the network communication module, so that staff can directly monitor the foundation data in real time; P3. Store the collected data in the form of text, so that the value of each set of data, the time of generation, and whether it is greater than the threshold and other information are stored for easy subsequent reference. The data is stored by wirelessly transmitting it to the cloud or local data center, so that the data can be effectively reviewed during subsequent calls and queries to ensure the timeliness and integrity of the data. The data processing system based on big data analysis and artificial intelligence algorithms can automatically identify abnormal changes in the safety status of the foundation and issue early warnings, effectively reducing the need for manual intervention and improving the accuracy and timeliness of early warnings.

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