CN214994149U - Subway deep and large foundation pit risk factor intelligent sensing system - Google Patents
Subway deep and large foundation pit risk factor intelligent sensing system Download PDFInfo
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- CN214994149U CN214994149U CN202120460836.5U CN202120460836U CN214994149U CN 214994149 U CN214994149 U CN 214994149U CN 202120460836 U CN202120460836 U CN 202120460836U CN 214994149 U CN214994149 U CN 214994149U
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Abstract
The utility model discloses an intelligent sensing system for risk factors of deep and large foundation pits of a subway, which comprises a wireless sensor, a wireless intelligent gateway, an edge computing intelligent mobile terminal and an edge cloud server; the wireless sensors are of different types and are arranged at different positions in the deep and large foundation pit, and are used for acquiring monitoring data of different types in real time and transmitting the monitoring data to the wireless intelligent gateway; the wireless intelligent gateway is respectively in communication connection with the wireless sensor and the edge computing intelligent mobile terminal and is used for sending the received monitoring data to the edge computing intelligent mobile terminal after being in a unified format; the edge computing intelligent mobile terminals are provided with a plurality of edge computing intelligent mobile terminals, and the edge computing intelligent mobile terminals are in communication connection; the edge cloud server is in communication connection with the edge computing intelligent mobile terminal. The utility model discloses can perceive the risk factor in the deep and big foundation ditch of subway fast.
Description
Technical Field
The utility model relates to a building engineering technical field, concretely relates to dark big foundation ditch risk factor intelligent sensing system of subway.
Background
In recent years, with the advance of urbanization, urban subway construction is in a high-speed development stage. In subway construction, a deep and large foundation pit (a foundation pit with an excavation depth of 5 meters or more or a complex environment) is a key link of subway construction, and the structural stability of the deep and large foundation pit is most easily influenced by various uncertain factors, so that the deep and large foundation pit has the most safety risks, is also a place with the most casualties and economic losses, and has a severe safety situation. The sensing of the risk factors of the subway deep and large foundation pit is a key research direction in the field of safety management of the subway deep and large foundation pit. The risk factor perception in the deep and large foundation pit construction process must be comprehensive, objective and rapid, and the safety accidents can be effectively reduced. However, the existing perception of the risk factors of the deep and large foundation pit of the subway is mainly realized by studying and judging and looking up past documents by virtue of experts before construction, and the former determines the risk types based on the knowledge and experience of the experts, so that the defects that the existing perception is only unstructured and has the problems of large subjectivity, incomplete risk types and the like are overcome; the method can not continuously sense the risks and take corresponding measures along with the change of the construction environment, so that the uncertainty of the safety management of the deep and large foundation pits of the subway deep and large foundation pits is greatly increased, and great construction potential safety hazards exist.
SUMMERY OF THE UTILITY MODEL
The embodiment of the utility model provides a deep and big foundation ditch risk factor intelligent sensing system of subway aims at carrying out intelligent perception to deep and big foundation ditch safety risk factor of subway fast, accurately, improves the early warning ability to the safety risk of the deep and big foundation ditch of subway.
The embodiment of the utility model provides a deep and big foundation ditch risk factor intelligent sensing system of subway, including wireless sensor, wireless intelligent gateway, edge calculation intelligent mobile terminal and edge cloud server;
the wireless sensors are of different types and are arranged at different positions in the deep and large foundation pit, and are used for acquiring monitoring data of different types in real time and transmitting the monitoring data to the wireless intelligent gateway;
the wireless intelligent gateway is respectively in communication connection with the wireless sensor and the edge computing intelligent mobile terminal and is used for sending the received monitoring data to the edge computing intelligent mobile terminal after being in a unified format;
the edge computing intelligent mobile terminals are provided with a plurality of edge computing intelligent mobile terminals, and the edge computing intelligent mobile terminals are in communication connection;
the edge cloud server is in communication connection with the edge computing intelligent mobile terminal.
Further, the wireless sensor comprises a pressure sensor, a water level induction sensor and a displacement sensor.
Furthermore, the displacement sensors are arranged at the top of the enclosure structure of the deep and large foundation pit, the middle part of the periphery of the foundation pit and the external corner, the horizontal distance between every two adjacent displacement sensors is smaller than or equal to 20m, and the vertical distance is smaller than or equal to 3 m.
Further, the number of the displacement sensors in the horizontal direction is greater than or equal to 3, and the number of the displacement sensors in the vertical direction is greater than or equal to 2.
Furthermore, the water level induction sensors are arranged in the water level monitoring wells at the periphery of the deep and large foundation pit, and the distance between every two adjacent water level monitoring wells is 15-25 m.
Further, the pressure sensors are arranged inside the supporting structure of the deep and large foundation pit, and the number of the pressure sensors is greater than or equal to 10% of the number of the rods of the supporting structure.
Further, the pressure sensors are arranged in an internal soil layer structure of the deep and large foundation pit, the horizontal distance between every two horizontally adjacent pressure sensors is 2m, and the vertical distance between every two vertically adjacent pressure sensors is 0.5 m.
Further, the edge computing intelligent mobile terminal comprises a wireless signal processor, a storage module, an AI core processor, a controller, a display module, a mechanical vibration module, a loudspeaker and a UPS power supply, wherein the AI core processor is respectively connected with the wireless signal processor, the storage module and the controller, the controller is respectively connected with the display module, the mechanical vibration module and the loudspeaker, and the UPS power supply is respectively electrically connected with the wireless signal processor, the storage module, the AI core processor, the controller, the display module, the mechanical vibration module and the loudspeaker.
Further, the display module is an LCD display screen.
Further, the mechanical vibration module includes a vibrator.
The embodiment of the utility model provides a deep and big foundation ditch risk factor intelligent sensing system of subway, including wireless sensor, wireless intelligent gateway, edge calculation intelligent mobile terminal and edge cloud server; the wireless sensors are of different types and are arranged at different positions in the deep and large foundation pit, and are used for acquiring monitoring data of different types in real time and transmitting the monitoring data to the wireless intelligent gateway; the wireless intelligent gateway is respectively in communication connection with the wireless sensor and the edge computing intelligent mobile terminal and is used for sending the received monitoring data to the edge computing intelligent mobile terminal after being in a unified format; the edge computing intelligent mobile terminals are provided with a plurality of edge computing intelligent mobile terminals, and the edge computing intelligent mobile terminals are in communication connection; the edge cloud server is in communication connection with the edge computing intelligent mobile terminal. The embodiment of the utility model provides a pass through wireless sensor, wireless intelligent gateway, edge calculation intelligent Mobile terminal and the linkage of marginal cloud server can perceive the risk factor in the deep and big foundation ditch of subway fast.
Compared with the prior art, the real-time engineering big data are utilized, subjectivity caused by artificial factors is eliminated, monitoring of potential risk sources is more comprehensive, meanwhile, due to the fact that the data are derived from specific deep and big foundation pit construction environments, the method has strong pertinence to the perceived risk factors, and making of support decisions can be effectively achieved. In addition, the embodiment is based on the distributed edge computing network, and compared with a traditional data processing mode of central computing, the embodiment greatly reduces delay caused by network bandwidth in the aspect of large data transmission, so that risks can be sensed more quickly, and high cost caused by deployment of a data computing center can be reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without any creative effort.
Fig. 1 is a schematic structural diagram of an intelligent sensing system for risk factors of a deep and large foundation pit of a subway provided by an embodiment of the utility model;
fig. 2 is a schematic structural diagram of an edge computing intelligent mobile terminal in an intelligent sensing system for risk factors of deep and large foundation pits of a subway, which is provided by the embodiment of the utility model;
fig. 3 is the embodiment of the utility model provides a deep and big foundation ditch risk factor intelligent sensing system's of subway work flow chart.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, of the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1, an embodiment of the present invention provides an intelligent sensing system for risk factors of a deep and large foundation pit of a subway, including a wireless sensor 10, a wireless intelligent gateway 20, an edge computing intelligent mobile terminal 30 and an edge cloud server 40;
the wireless sensors 10 are of different types, and the wireless sensors 10 are arranged at different positions in the deep and large foundation pit and are used for acquiring monitoring data of different types in real time and transmitting the monitoring data to the wireless intelligent gateway 20;
the wireless intelligent gateway 20 is in communication connection with the wireless sensor 10 and the edge computing intelligent mobile terminal 30 respectively, and is used for sending the received monitoring data to the edge computing intelligent mobile terminal 30 after being in a unified format;
the edge calculation intelligent mobile terminals 30 are provided in plurality, and the edge calculation intelligent mobile terminals 30 are in communication connection;
the edge cloud server 40 is in communication connection with the edge computing intelligent mobile terminal 30.
In this embodiment, the monitoring data of the construction environment of the deep and large foundation pit are acquired in real time by the wireless sensors 10 of different types arranged at different positions in the deep and large foundation pit of the subway, and are sent to the corresponding wireless intelligent gateways 20, then based on an edge computing network (that is, the edge computing network is composed of a plurality of edge computing intelligent mobile terminals 30), that is, the plurality of edge computing intelligent mobile terminals 30 and the edge cloud server 40 coordinate and cooperate to obtain result parameters related to the monitoring data, and the result parameters are displayed on the edge computing intelligent mobile terminals 30, so that data sharing with other edge computing intelligent mobile terminals 30 is realized.
Compared with the prior art, the real-time engineering big data are utilized, subjectivity caused by artificial factors is eliminated, monitoring of potential risk sources is more comprehensive, meanwhile, due to the fact that the data are derived from specific deep and big foundation pit construction environments, the method has strong pertinence to the perceived risk factors, and making of support decisions can be effectively achieved. In addition, the embodiment is based on the distributed edge computing network, and compared with a traditional data processing mode of central computing, the embodiment greatly reduces delay caused by network bandwidth in the aspect of large data transmission, so that risks can be sensed more quickly, and high cost caused by deployment of a data computing center can be reduced.
In a specific embodiment, the wireless intelligent gateway 20 is provided with a plurality of gateways. When the wireless sensor 10 collects the monitoring data, the monitoring data is sent to the nearest wireless intelligent gateway 20. Further, the number of the wireless sensors 10 may be the same as the number of the wireless intelligent gateways 20, that is, the wireless sensors 10 and the wireless intelligent gateways 20 are arranged in a one-to-one correspondence.
In one embodiment, the wireless sensor 10 includes a pressure sensor, a water level sensor, and a displacement sensor.
In the embodiment, because the subway deep and large foundation pit engineering is mostly located in the station engineering, the peripheral people flow is large, the buildings are more, the underground water level is high, the pipelines are complex, various uncertain factors are interwoven together, the technical difficulty and the safety risk of the deep and large foundation pit engineering are high, therefore, in the embodiment, aiming at the construction characteristics of the deep and large foundation pit of the subway, the wireless sensor 10 is deployed at the corresponding position of the deep and large foundation pit, and different wireless sensors 10 are utilized to correspondingly monitor different conditions, such as the water level sensor is utilized to monitor the water content of the soil layer and the water leakage condition of the side wall, the pressure sensor is utilized to detect the soil pressure of the side wall and the stress of the supporting structure, the displacement sensor is utilized to monitor the displacement of the urban pipeline, the ground surface settlement and the like, therefore, a sensing node network of potential safety risk factors of the deep and large foundation pit of the subway is formed, namely the sensing node network is formed by utilizing different wireless sensors 10.
Further, the wireless sensor 10 in the sensing node network transmits various monitored potential risk source data to the nearest wireless intelligent gateway 20 in real time through wireless WIFI or 4G/5G technology and the like, the wireless intelligent gateway 20 performs operations such as cleaning and preprocessing on the received data, unifies data formats on the received data, and then transmits the unified data formats to the edge computing intelligent mobile terminal 30, and the number of the edge computing intelligent mobile terminals 30 forming the edge computing network is determined according to the relation between the communication distance of the edge computing intelligent mobile terminal 30 and the pit bottom area, so as to ensure the principle of full coverage of the pit bottom area.
In one embodiment, the displacement sensors are arranged at the top of a building enclosure of a deep and large foundation pit, the middle part of the periphery of the foundation pit and the external corner, the horizontal distance between every two adjacent displacement sensors is less than or equal to 20m, and the vertical distance is less than or equal to 3 m.
In this embodiment, the displacement sensor is arranged at the top of the support structure of the deep and large foundation pit, the middle part of the periphery of the foundation pit, the external corner and the like, and the displacement of the pipeline in the deep and large foundation pit and the like is monitored. Obviously, because the displacement sensors are arranged at different positions, the displacement sensors are arranged in a plurality of positions, and further, the distance between every two adjacent displacement sensors in the horizontal direction is not more than 20m, and the distance between every two adjacent displacement sensors in the vertical direction is not more than 3m, so that the effect of comprehensive monitoring can be achieved. In a specific application scenario, the horizontal spacing between adjacent displacement sensors is 25m, and the vertical spacing is 2 m.
Furthermore, in one embodiment, the number of the displacement sensors in the horizontal direction is greater than or equal to 3, and the number of the displacement sensors in the vertical direction is greater than or equal to 2. In this embodiment, the number of the displacement sensors in the horizontal direction is at least 3, such as 5, and so on, and the number in the vertical direction is at least 2, such as 3, and so on. In order to improve the monitoring comprehensiveness and accuracy, the number of the displacement sensors and the arrangement positions of the displacement sensors can be correspondingly increased according to the actual scene requirements.
In one embodiment, the water level sensor is arranged in the water level monitoring wells around the deep and large foundation pit, and the distance between the adjacent water level monitoring wells is 15-25 m.
In this embodiment, utilize the water level inductive transducer who sets up in the water level monitoring well to monitor the condition such as soil layer water content, lateral wall percolating water in the deep and large foundation ditch. Obviously, when a plurality of water level monitoring wells exist, in order to improve the monitoring accuracy, one water level sensing sensor may be installed in each water level monitoring well, and in order to ensure the monitoring comprehensiveness, the distance between adjacent water level monitoring wells may be set to 15m to 25m, that is, the distance between adjacent water level sensing sensors is set to 15m to 25 m. In a specific application scenario, the distance between adjacent water level monitoring wells is 20m, that is, the distance between adjacent water level sensing sensors is 20 m.
In one embodiment, the pressure sensors are arranged inside the supporting structure of the deep and large foundation pit, and the number of the pressure sensors is greater than or equal to 10% of the number of the rods of the supporting structure.
In this embodiment, the pressure sensor disposed inside the support structure of the deep and large foundation pit is used to monitor the conditions such as the sidewall soil pressure in the deep and large foundation pit. It will be appreciated that the support structure will typically comprise a rod support structure and that the pressure experienced by adjacent or adjacent rods will be substantially the same, so that the use of pressure sensors in quantities of not less than 10% of the number of rods can provide a significant cost reduction while ensuring monitoring accuracy and integrity. Of course, in order to improve the accuracy and comprehensiveness of the monitoring, the number of the pressure sensors may be increased appropriately, which may be determined according to the actual application scenario. In a specific application scenario, the number of the pressure sensors is 20% of the number of the rods of the support structure, that is, if there are 100 rods, 20 pressure sensors are correspondingly disposed. Further, a plurality of pressure sensors evenly distributed in the interior of the supporting structure.
In one embodiment, the pressure sensor is disposed within the support structure at a location 1/3 between adjacent pivot points of the support structure.
In another embodiment, the pressure sensors are arranged in the internal soil layer structure of the deep and large foundation pit, the horizontal distance between every two horizontally adjacent pressure sensors is 2m, and the vertical distance between every two vertically adjacent pressure sensors is 0.5 m.
In this embodiment, pressure sensor can also set up in the inside soil layer structure of big deep foundation ditch, can be used for monitoring the circumstances such as foundation ditch body soil pressure. Further, the distance between the horizontally adjacent pressure sensors is set to 2m, and the distance between the vertically adjacent pressure sensors is set to 0.5 m. Of course, the distance between the pressure sensors can be properly adjusted according to the actual scene to obtain more accurate monitoring data.
In one embodiment, as shown in fig. 2, the edge computing smart mobile terminal 30 includes a wireless signal processor 301, a storage module 302, an AI core processor 303, a controller 304, a display module 305, a mechanical vibration module 306, a speaker 307, and a UPS power supply 308, the AI core processor 303 is respectively connected to the wireless signal processor 301, the storage module 302, and the controller 304, the controller 304 is respectively connected to the display module 305, the mechanical vibration module 306, and the speaker 304, and the UPS power supply 308 is respectively electrically connected to the wireless signal processor 301, the storage module 302, the AI core processor 303, the controller 304, the display module 305, the mechanical vibration module 306, and the speaker 307.
In this embodiment, with reference to fig. 3, after receiving the data sent by the wireless intelligent gateway 20 through the wireless signal processor 301, the edge-computing intelligent mobile terminal 30 stores the data through the storage module 302 therein, and at the same time, the AI core processor 303 responds to send a data request to the edge cloud server 40, downloads a corresponding sensing model to process and analyze the data, and sends the obtained result parameters to other edge-computing intelligent mobile terminals 30 through the wireless signal processor 301, so as to implement sharing, so that only each parameter of the model is present in the entire edge-computing network, and there is no massive sensor monitoring source data, thereby greatly reducing delay of network transmission and being capable of quickly sensing risks. The edge computing network in fig. 3 is configured by a plurality of edge computing smart mobile terminals 30. It should be noted that the AI core processor 303 described in this embodiment is a common AI chip. In one embodiment, the wireless signal processor 301 shares data with other edge computing smart mobile terminals 30 according to the Zigbee protocol.
Further, a network configuration table is formed for all the edge computing intelligent mobile terminals 30, the edge computing intelligent mobile terminal 30 with the most front MAC address is automatically set as a center computing intelligent mobile terminal for bearing the work of the basic center node, and the center computing intelligent mobile terminal collects all parameters in the edge computing network and senses potential risks, so that the safety risk factors of the deep and large foundation pits of the subway can be comprehensively sensed. And if the security risk factor is sensed, sending the security risk factor to the controller 304, starting the display module 305, the mechanical vibration module 306 and the loudspeaker 304 immediately after the controller receives an instruction, visually displaying the received data result by the display module 305 so as to display the data result on the edge computing intelligent terminal 10, and simultaneously starting the terminal vibration device and the loudspeaker 306 respectively to give an alarm according to the received data result. If no security risk factor exists, the result parameters are sent to the edge cloud server 40 through the wireless signal processor 301 for storage, and parameters in the edge computing network are corrected and optimized in real time.
In a specific application scenario, perceived safety risk factors and risk source data sources are marked in a one-to-one correspondence mode, and are marked and displayed on a site plan corresponding to a deep and large foundation pit of the subway, for example, red small round point marking display is adopted, correspondingly, the safety risk factors which are not perceived can be marked and displayed, for example, green small round point display is adopted, and therefore field personnel can be helped to rapidly deal with safety risks, and economic property loss is reduced.
In an embodiment, the wireless signal processor 301 is embedded in the edge computing intelligent mobile terminal 30, and configured to receive the monitoring data sent by the wireless intelligent gateway 20 and send result parameters to other edge computing intelligent mobile terminals 30; the storage module 302 is used for completing data storage and calling; after receiving the monitoring data, the AI core processor 303 requests the edge cloud server 10 to download a corresponding sensing model to perform calculation processing on the monitoring data, and shares the obtained result parameters with other edge-calculation intelligent mobile terminals 30 through the wireless signal processor 301; the controller 304 is connected to the display module 305, the mechanical vibration module 306 and the speaker 307 respectively, and immediately displays on the display module 305 after receiving the risk result signal, and activates the mechanical vibration module 306 and the speaker 307 to alarm; the display module 305 is an LCD display screen for displaying the risk result; the mechanical vibration module 306 comprises a vibrator, and the mechanical vibration module 306 is configured to receive a data instruction sent by the controller, start the vibrator according to the data instruction, and perform an early warning prompt; the speaker 307 is configured to activate according to the received data command sent by the controller 304, so as to sound an alarm.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. The intelligent sensing system for the risk factors of the deep and large foundation pit of the subway is characterized by comprising a wireless sensor, a wireless intelligent gateway, an edge computing intelligent mobile terminal and an edge cloud server;
the wireless sensors are of different types and are arranged at different positions in the deep and large foundation pit, and are used for acquiring monitoring data of different types in real time and transmitting the monitoring data to the wireless intelligent gateway;
the wireless intelligent gateway is respectively in communication connection with the wireless sensor and the edge computing intelligent mobile terminal and is used for sending the received monitoring data to the edge computing intelligent mobile terminal after being in a unified format;
the edge computing intelligent mobile terminals are provided with a plurality of edge computing intelligent mobile terminals, and the edge computing intelligent mobile terminals are in communication connection;
the edge cloud server is in communication connection with the edge computing intelligent mobile terminal.
2. The system according to claim 1, wherein the wireless sensor comprises a pressure sensor, a water level sensor and a displacement sensor.
3. The system for intelligently sensing the risk factors of the subway deep and large foundation pit according to claim 2, wherein the displacement sensors are arranged at the top of the enclosure structure of the deep and large foundation pit, the middle part of the periphery of the foundation pit and the external corner, and the horizontal spacing between adjacent displacement sensors is less than or equal to 20m and the vertical spacing is less than or equal to 3 m.
4. The intelligent sensing system for risk factors of deep and large foundation pits of a subway according to claim 3, wherein the number of the displacement sensors in the horizontal direction is greater than or equal to 3, and the number of the displacement sensors in the vertical direction is greater than or equal to 2.
5. The system for intelligently sensing the risk factors of the subway deep and large foundation pit as claimed in claim 2, wherein said water level induction sensors are arranged in water level monitoring wells around the deep and large foundation pit, and the distance between adjacent water level monitoring wells is 15-25 m.
6. The intelligent sensing system for risk factors of underground deep and large foundation pits according to claim 2, wherein the pressure sensors are arranged inside the supporting structure of the deep and large foundation pits, and the number of the pressure sensors is greater than or equal to 10% of the number of the rods of the supporting structure.
7. The system according to claim 2, wherein the pressure sensors are arranged in an internal soil structure of the deep and large foundation pit, the horizontal spacing between horizontally adjacent pressure sensors is 2m, and the vertical spacing between vertically adjacent pressure sensors is 0.5 m.
8. The system according to claim 1, wherein the edge-computing intelligent mobile terminal comprises a wireless signal processor, a storage module, an AI core processor, a controller, a display module, a mechanical vibration module, a speaker and a UPS, the AI core processor is respectively connected with the wireless signal processor, the storage module and the controller, the controller is respectively connected with the display module, the mechanical vibration module and the speaker, and the UPS is respectively electrically connected with the wireless signal processor, the storage module, the AI core processor, the controller, the display module, the mechanical vibration module and the speaker.
9. The subway deep and large foundation pit risk factor intelligent sensing system as claimed in claim 8, wherein said display module is an LCD display screen.
10. The system according to claim 8, wherein the mechanical vibration module comprises a vibrator.
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| CN202120460836.5U CN214994149U (en) | 2021-03-03 | 2021-03-03 | Subway deep and large foundation pit risk factor intelligent sensing system |
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