Real-time dynamic monitoring and early warning system for deep foundation pit

Abstract

The invention discloses a real-time dynamic monitoring and early warning system for a deep foundation pit. The real-time dynamic monitoring and early warning system comprises a multi-element sensor network, an intelligent data acquisition and processing unit, a cloud computing and big data analysis platform, a visual early warning system and a remote monitoring and emergency response center, according to the invention, a multi-element sensor network, cloud computing, big data analysis and Internet of Things communication technologies are deeply fused for the first time, and intelligence and comprehensiveness of deep foundation pit monitoring are realized. Meanwhile, monitoring data are analyzed in real time through a machine learning algorithm, early warning is achieved, and compared with a traditional method, a time window for risk discovery is greatly advanced. And a deep foundation pit stability evaluation model based on multi-dimensional parameters is constructed, so that the early warning accuracy and pertinence are improved. In addition, a rapid channel from early warning to emergency response is established, it is ensured that measures can be rapidly taken in emergency, and accidents are effectively prevented.

Description

Technical Field

[0001] The invention relates to the field of engineering construction technology, and in particular to a real-time dynamic monitoring and early warning system for a deep foundation pit. Background Art

[0002] Deep foundation pit refers to the earthwork excavation, support and dewatering engineering of foundation pit (trench) with excavation depth exceeding 5 meters (including 5 meters), or the depth not exceeding 5 meters but with complicated geological conditions, surrounding environment and underground pipelines, or affecting the safety of adjacent buildings (structures). Such projects have high risks and complexity in construction, and special attention should be paid to construction safety and quality. Their construction safety and stability are directly related to the safety of surrounding buildings, underground pipelines and personnel.

[0003] When carrying out deep foundation pit construction, many factors need to be considered, including geological conditions, groundwater level, surrounding environment, selection and operation of construction machinery, etc. In order to ensure the safety and smooth progress of construction, a series of technical measures are usually required, such as the setting of support structures, the formulation of precipitation plans, and the implementation of construction monitoring. Traditional monitoring methods mostly rely on manual measurement, and there are problems such as low monitoring frequency, data lag, and untimely early warning. With the development of information technology, although some automated monitoring systems have been introduced, most of them have single functions and limited data processing capabilities, which makes it difficult to fully meet the complex and changeable monitoring needs of deep foundation pit projects. Therefore, it is necessary to study a solution to the above problems. Summary of the invention

[0004] In view of this, the present invention aims to address the deficiencies in the prior art, and its main purpose is to provide a real-time dynamic monitoring and early warning system for deep foundation pits, which can effectively solve the problem that the existing automated monitoring systems have single functions and limited data processing capabilities, making it difficult to fully meet the complex and changeable monitoring needs of deep foundation pit projects.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] A real-time dynamic monitoring and early warning system for deep foundation pits includes a multi-sensor network, an intelligent data acquisition and processing unit, a cloud computing and big data analysis platform, a visual early warning system, and a remote monitoring and emergency response center; the multi-sensor network is arranged around and inside the deep foundation pit, and the multi-sensor network is used to collect various dynamic key parameters of the deep foundation pit in real time; the intelligent data acquisition and processing unit is wirelessly connected to the multi-sensor network through a wireless communication module, and the intelligent data acquisition and processing unit is responsible for collecting data collected by the multi-sensor network and performing preliminary preprocessing; the cloud computing and big data analysis platform is connected to the intelligent data acquisition and processing unit, and the cloud computing and big data analysis platform The platform is built on a cloud computing data center that integrates machine learning algorithms to conduct real-time analysis, trend prediction, and anomaly detection of massive monitoring data. The visual early warning system connects the cloud computing and big data analysis platforms. The visual early warning system has a Web / APP interface for displaying real-time monitoring data, historical trend charts, and risk assessment reports. The visual early warning system sets multi-level early warning thresholds. Once the monitoring data exceeds the safety range, it immediately triggers an early warning notification and provides emergency handling suggestions. The remote monitoring and emergency response center is connected to the visual early warning system. The remote monitoring and emergency response center is equipped with a professional team to respond quickly according to the early warning information and guide the on-site safety measures.

[0007] Preferably, the multi-sensor network consists of a displacement sensor, a stress-strain sensor, a vibration sensor and a groundwater level sensor, which are used to respectively collect the displacement, stress, vibration and water level data of the deep foundation pit in real time.

[0008] Preferably, the displacement sensor is a laser displacement sensor.

[0009] Preferably, the groundwater level sensor is a vibrating-wire pore water pressure sensor.

[0010] Preferably, the intelligent data acquisition and processing unit is a data collector equipped with a low-power microprocessor and a wireless communication module.

[0011] Preferably, the intelligent data acquisition and processing unit is uploaded to the cloud server of the cloud computing and big data analysis platform via 4G / 5G, LoRa or NB-IoT communication protocol.

[0012] Preferably, the warning notification includes text message, email, or APP push.

[0013] Preferably, the remote monitoring and emergency response center is a 24-hour remote monitoring and emergency response center.

[0014] Compared with the prior art, the present invention has obvious advantages and beneficial effects. Specifically, it can be seen from the above technical solution that:

[0015] The present invention deeply integrates multi-sensor networks, cloud computing, big data analysis and Internet of Things communication technologies for the first time, realizing intelligent and comprehensive deep foundation pit monitoring. At the same time, the present invention uses machine learning algorithms to perform real-time analysis of monitoring data to achieve early warning, which greatly advances the time window for risk discovery compared to traditional methods. The present invention also constructs a deep foundation pit stability assessment model based on multi-dimensional parameters, which improves the accuracy and pertinence of early warning. In addition, the present invention establishes a fast channel from early warning to emergency response, ensuring that measures can be taken quickly in emergency situations to effectively prevent accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a structural schematic diagram of a preferred embodiment of the present invention.

[0017] Description of the accompanying drawings:

[0018] 10. Multi-sensor network; 20. Intelligent data acquisition and processing unit; 30. Cloud computing and big data analysis platform; 40. Visual early warning system; 50. Remote monitoring and emergency response center 50. DETAILED DESCRIPTION

[0019] Please refer to Figure 1 As shown, it shows the specific structure of the preferred embodiment of the present invention, including a multi-sensor network 10, an intelligent data acquisition and processing unit 20, a cloud computing and big data analysis platform 30, a visual early warning system 40 and a remote monitoring and emergency response center 50.

[0020] The multi-sensor network 10 is arranged around and inside the deep foundation pit, and is used to collect various dynamic key parameters of the deep foundation pit in real time. Specifically, the multi-sensor network 10 is composed of a variety of high-precision sensors such as displacement sensors, stress strain sensors, vibration sensors and groundwater level sensors. The displacement sensors, stress strain sensors, vibration sensors and groundwater level sensors are used to collect the displacement, stress, vibration and water level data of the deep foundation pit in real time. In addition, the displacement sensor is a laser displacement sensor with higher monitoring accuracy. The groundwater level sensor is a vibrating string pore water pressure sensor with higher monitoring accuracy.

[0021] The intelligent data acquisition and processing unit 20 is wirelessly connected to the multi-sensor network 10 through a wireless communication module. The intelligent data acquisition and processing unit 20 is responsible for collecting the data collected by the multi-sensor network 10 and performing preliminary preprocessing (such as filtering and calibration); in this embodiment, the intelligent data acquisition and processing unit 20 is a data collector equipped with a low-power microprocessor and a wireless communication module. In addition, the intelligent data acquisition and processing unit 20 is uploaded to the cloud server of the cloud computing and big data analysis platform 30 through 4G / 5G, LoRa or NB-IoT communication protocols.

[0022] The cloud computing and big data analysis platform 30 is connected to the intelligent data acquisition and processing unit 20. The cloud computing and big data analysis platform 30 is constructed based on a cloud computing data center and integrates machine learning algorithms to perform real-time analysis, trend prediction and anomaly detection on massive monitoring data. The cloud computing and big data analysis platform 30 realizes quantitative evaluation of engineering safety by constructing a deep foundation pit stability evaluation model.

[0023] The visual warning system 40 is connected to the cloud computing and big data analysis platform 30. The visual warning system 40 has a Web / APP interface for displaying real-time monitoring data, historical trend charts and risk assessment reports. The visual warning system 40 sets multi-level warning thresholds. Once the monitoring data exceeds the safety range, a warning notification is immediately triggered and emergency handling suggestions are provided. The warning notification includes SMS, email, APP push, etc.

[0024] The remote monitoring and emergency response center 50 is connected to the visual warning system 40. The remote monitoring and emergency response center 50 is equipped with a professional team to quickly respond to the warning information and guide the site to take safety measures. In this embodiment, the remote monitoring and emergency response center 50 is a 24-hour remote monitoring and emergency response center.

[0025] The design focus of the present invention is: for the first time, the present invention deeply integrates multi-sensor networks, cloud computing, big data analysis and Internet of Things communication technology to achieve intelligent and comprehensive deep foundation pit monitoring. At the same time, the present invention uses machine learning algorithms to perform real-time analysis of monitoring data to achieve early warning, which greatly advances the time window for risk discovery compared to traditional methods. And the present invention constructs a deep foundation pit stability assessment model based on multi-dimensional parameters, which improves the accuracy and pertinence of early warning. In addition, the present invention establishes a fast channel from early warning to emergency response to ensure that measures can be taken quickly in emergency situations to effectively prevent accidents.

[0026] The technical principle of the present invention is described above in conjunction with specific embodiments. These descriptions are only for explaining the principle of the present invention and cannot be interpreted as limiting the scope of protection of the present invention in any way. Based on the explanations herein, those skilled in the art can associate other specific implementations of the present invention without paying creative labor, and these methods will fall within the scope of protection of the present invention.

Claims

1. A real-time dynamic monitoring and early warning system for deep foundation pits, characterized by: It includes a multi-sensor network, an intelligent data acquisition and processing unit, a cloud computing and big data analysis platform, a visual early warning system, and a remote monitoring and emergency response center; the multi-sensor network is arranged around and inside the deep foundation pit, and the multi-sensor network is used to collect various dynamic key parameters of the deep foundation pit in real time; the intelligent data acquisition and processing unit is wirelessly connected to the multi-sensor network through a wireless communication module, and the intelligent data acquisition and processing unit is responsible for collecting the data collected by the multi-sensor network and performing preliminary preprocessing; the cloud computing and big data analysis platform is connected to the intelligent data acquisition and processing unit, and the cloud computing and big data analysis platform is built based on a cloud computing data center, integrating machine learning algorithms, and performing real-time analysis, trend prediction, and anomaly detection on massive monitoring data; the visual early warning system is connected to the cloud computing and big data analysis platform, and the visual early warning system has a Web / APP interface for displaying real-time monitoring data, historical trend charts, and risk assessment reports. The visual early warning system sets multi-level early warning thresholds. Once the monitoring data exceeds the safety range, it immediately triggers an early warning notification and provides emergency handling suggestions; the remote monitoring and emergency response center is connected to the visual early warning system, and the remote monitoring and emergency response center is equipped with a professional team to respond quickly according to the early warning information and guide the site to take safety measures.

2. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 1, characterized in that: The multi-sensor network consists of a displacement sensor, a stress-strain sensor, a vibration sensor and a groundwater level sensor, which are used to respectively collect displacement, stress, vibration and water level data of a deep foundation pit in real time.

3. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 2, characterized in that: The displacement sensor is a laser displacement sensor.

4. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 2, characterized in that: The groundwater level sensor is a vibrating wire pore water pressure sensor.

5. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 1, characterized in that: The intelligent data acquisition and processing unit is a data collector equipped with a low-power microprocessor and a wireless communication module.

6. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 1, characterized in that: The intelligent data acquisition and processing unit is uploaded to the cloud server of the cloud computing and big data analysis platform through 4G / 5G, LoRa or NB-IoT communication protocol.

7. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 1, characterized in that: The warning notification includes SMS, email, and APP push.

8. The deep foundation pit real-time dynamic monitoring and early warning system according to claim 1, characterized in that: The remote monitoring and emergency response center is a 24-hour remote monitoring and emergency response center.

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