CN217606278U - Tunnel operation abnormity detection device and system - Google Patents
Tunnel operation abnormity detection device and system Download PDFInfo
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- CN217606278U CN217606278U CN202222010717.7U CN202222010717U CN217606278U CN 217606278 U CN217606278 U CN 217606278U CN 202222010717 U CN202222010717 U CN 202222010717U CN 217606278 U CN217606278 U CN 217606278U
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Abstract
The application discloses unusual detection device of tunnel operation and system relates to tunnel fortune dimension safety device's technical field. The tunnel operation abnormity detection device comprises a shell and an integrated circuit substrate. The integrated circuit substrate is arranged in the shell and comprises a main control module, an electromechanical device signal acquisition module, an environmental parameter detection module, a wireless communication module and an edge calculation module. The main control module is used for outputting a control signal; the electromechanical equipment signal acquisition module is connected with the main control module and is used for acquiring real-time data of equipment; the environment parameter detection module is connected with the main control module and is used for acquiring environment real-time data; the edge calculation module is connected with the main control module and used for outputting a prediction result; the wireless communication module is connected with the main control module and used for sending the prediction result, the equipment real-time data and the environment real-time data. Therefore, the method and the device have the advantages of being strong in adaptability, high in working efficiency and reliability and capable of saving manpower and material resources.
Description
Technical Field
The application relates to the technical field of tunnel operation and maintenance safety facilities, in particular to a device and a system for detecting tunnel operation abnormity.
Background
With the rapid advance of the urbanization process, the urban traffic congestion problem is more serious, and the urban tunnel is an important part for solving the urban congestion problem. As a closed structure, a tunnel has a complex operation environment, is prone to traffic accidents, and has more serious consequences once an accident occurs, so that how to operate the tunnel more safely and efficiently is a very important problem. In order to manage the daily operation of the tunnel, how to quickly and efficiently detect the abnormal situation in the tunnel operation becomes an important research topic.
The unusual incident of current tunnel operation in-process detects still to stop in comparatively traditional mode, mainly relies on the real time monitoring of site management personnel to the control picture, has very big consumption to manpower, material resources, and the mode of artifical control is difficult to guarantee all-weather control, and the missed measure rate is very high, is difficult to guarantee the speed and the ageing of detecting. And once an accident occurs in the tunnel operation process, the transportation and management unit is difficult to take effective measures and start a related plan at the first time to prevent the accident scope from expanding.
SUMMERY OF THE UTILITY MODEL
The application aims to provide a tunnel operation abnormity detection device and system, which can quickly and accurately find out abnormal conditions in a tunnel and provide early warning prompts, so that manpower and material resources are saved; and can adapt to different tunnel field conditions.
The embodiment of the application is realized as follows:
the first aspect of the present application provides a device for detecting tunnel operation anomaly, which includes: the integrated circuit comprises a main control module, an electromechanical device signal acquisition module, an environmental parameter detection module, a wireless communication module and an edge calculation module. The main control module is used for outputting a control signal; the electromechanical equipment signal acquisition module is connected with the main control module and is used for acquiring real-time data of equipment; the environment parameter detection module is connected with the main control module and is used for acquiring environment real-time data; the edge calculation module is connected with the main control module and used for outputting a prediction result; the wireless communication module is connected with the main control module and used for sending the prediction result, the equipment real-time data and the environment real-time data.
In one embodiment, the integrated circuit substrate further comprises a power supply connected to the main control module, the electromechanical device signal acquisition module, the environmental parameter detection module, the wireless communication module, and the edge calculation module for providing current.
In one embodiment, the integrated circuit substrate further includes a heat dissipation module connected to the main control module for dissipating heat from the integrated circuit substrate.
In an embodiment, the integrated circuit substrate further includes a switch circuit connected to the main control module for controlling on/off of the circuit of the integrated circuit substrate.
In one embodiment, the electromechanical device signal acquisition module comprises ventilation equipment and lighting equipment, and is connected with the main control module, wherein the ventilation equipment is used for detecting forward rotation or reverse rotation of the fan blades, the rotating speed, the air volume, the air pressure or noise; and the lighting equipment is connected with the main control module and used for detecting the current lighting brightness value.
In one embodiment, the electromechanical device signal acquisition module further comprises fire fighting equipment and traffic equipment, the fire fighting equipment is connected with the main control module, and the fire fighting equipment is used for detecting whether a circuit of the fire fighting equipment is unblocked; the traffic equipment is connected with the main control module and used for detecting whether the signal lamp state is a passing state or a no passing state.
In one embodiment, the environmental parameter detecting module includes: the illumination detection unit is connected with the main control module and used for detecting the brightness value in the tunnel; the wind speed detection unit is connected with the main control module and used for detecting a wind speed value in the tunnel; the visibility detection unit is connected with the main control module and used for detecting the visibility value in the tunnel; and the temperature and humidity detection unit is connected with the main control module and is used for detecting the temperature and humidity value in the tunnel.
In one embodiment, the environmental parameter detecting module includes a toxic gas detecting unit connected to the main control module for detecting toxic and harmful gases in the tunnel.
A second aspect of the present application provides a system for detecting tunnel operation anomaly, where the system includes a tunnel operation anomaly detection apparatus and a data platform according to any embodiment of the first aspect of the present application; and the data platform is connected with the tunnel operation abnormity detection device and used for receiving the prediction result, the equipment real-time data and the environment real-time data.
In an embodiment, the system for detecting tunnel operation anomaly further comprises an early warning device, and the early warning device is connected with the data platform and used for sending an early warning prompt.
Compared with the prior art, the beneficial effect of this application is: the application provides a tunnel operation anomaly detection device and system can adapt to different tunnel site conditions to have electromechanical device and environment detecting instrument according to the tunnel, carry out timely accurate abnormal conditions and detect and early warning suggestion, manpower, material resources have been saved to this application, have better economic benefits. In addition, the method has the characteristics of multifunctional integration, personalized design, convenience in use and high cost performance of the product, and is suitable for large-scale popularization and application.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic structural diagram of a tunnel operation anomaly detection apparatus according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a tunnel operation anomaly detection apparatus according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a tunnel operation anomaly detection system according to an embodiment of the present application.
An icon: 1-tunnel operation anomaly detection system; 10-tunnel operation anomaly detection means; 11-a data platform; 100-a housing; 110-an integrated circuit substrate; 111-a master control module; 112-electromechanical device signal acquisition module; 1121-ventilation equipment; 1122-lighting devices; 1123-fire fighting equipment; 1124-a transportation device; 113-an environmental parameter detection module; 1131, a toxic gas detection unit; 1132-flammable and explosive gas detection unit; 1133, an illuminance detection unit; 1134, a wind speed detection unit; 1135 — visibility detection unit; 1136, a temperature and humidity detection unit; 114-an edge calculation module; 115-a wireless communication module; 116-a power supply; 117-heat dissipation module; 118-a switching circuit; 12-early warning device.
Detailed Description
The terms "first," "second," "third," and the like are used for descriptive purposes only and not for purposes of indicating or implying relative importance, and do not denote any order or order.
Furthermore, the terms "horizontal", "vertical", "suspended" and the like do not imply that the components are absolutely horizontal or suspended, but may be slightly inclined. For example, "horizontal" merely means that the direction is more horizontal than "vertical" and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present application, it should be noted that the terms "inside", "outside", "left", "right", "upper", "lower", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings or orientations or positional relationships that are conventionally arranged when products of the application are used, and are used only for convenience in describing the application and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the application.
In the description of the present application, unless expressly stated or limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may for example be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements.
The technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings.
Please refer to fig. 1, which is a schematic structural diagram of a tunnel operation anomaly detection apparatus 10 according to an embodiment of the present application. As shown in fig. 1, the present application provides a tunnel operation abnormality detection apparatus 10, which includes: a housing 100 and an integrated circuit substrate 110. The integrated circuit substrate 110 is disposed on the housing 100. The integrated circuit substrate 110 is provided with a main control module 111, an electromechanical device signal acquisition module 112, an environmental parameter detection module 113, a wireless communication module 115 and an edge calculation module 114, which are a series of hardware modules for realizing different functions.
The electromechanical device signal acquisition module 112 is connected with the main control module 111 and is used for acquiring device real-time data of electromechanical devices in the tunnel; the environment parameter detection module 113 is connected with the main control module 111 and is used for acquiring environment real-time data of each environment detection unit in the tunnel; the edge calculation module 114 is connected to the main control module 111, and is configured to run an anomaly determination algorithm according to the device real-time data and the environment real-time data, and output a prediction result of whether operation is abnormal; the wireless communication module 115 is connected to the main control module 111, and is configured to send the prediction result and the related device real-time data and environment real-time data based on the prediction result output by the edge calculation module 114.
In an application process, the electromechanical device signal acquisition module 112 and the environmental parameter detection module 113 are connected with the main control module 111, and the acquired data are directly or indirectly transmitted to the edge calculation module 114 through the main control module 111. The main control module 111 sends a control signal to control the edge calculation module 114 to run a machine learning-based tunnel operation anomaly detection algorithm at regular time, which is an expression mode of the data structure of the whole sample, and this expression mode usually grasps the general properties of the whole sample, and points which are completely inconsistent with the whole sample in these properties are called anomaly points. The generation mechanism of the abnormal points is completely inconsistent with that of the whole sample, and the abnormal detection algorithm is extremely sensitive to the abnormal points, so that abnormal data different from normal conditions can be captured better. After the algorithm is run, the edge calculation module 114 gives that the current tunnel operation state is in a normal or abnormal state.
When the algorithm model predicts an abnormal state, the main control module 111 controls the wireless communication module 115 to upload data related to the abnormality (including a prediction result of the abnormality and related equipment real-time data, environment real-time data, abnormal equipment number, and the like).
The tunnel operation anomaly detection apparatus 10 may detect the operation state and environmental parameters of the devices in the tunnel and operate a corresponding anomaly detection algorithm based on the integrated data on the edge calculation module 114. The running time of the algorithm can be freely set, for example, the algorithm is set to automatically run once every 30 seconds, and based on the continuous generation of data, the training data of the algorithm model is continuously updated, and the model is further updated completely. If the prediction result of the algorithm model is abnormal, the in-device wireless communication module 115 sends the data related to the abnormality (including the prediction result of the abnormality and the related real-time data of the equipment, the real-time data of the environment, the number of the abnormal equipment, etc.) to other devices.
Please refer to fig. 2, which is a schematic structural diagram of a tunnel operation anomaly detection apparatus 10 according to an embodiment of the present application. As shown in fig. 1 and fig. 2, the integrated circuit substrate 110 further includes a power supply 116, a heat dissipation module 117 and a switch circuit 118. The power supply 116 is connected to hardware modules such as the main control module 111, the electromechanical device signal acquisition module 112, the environmental parameter detection module 113, the wireless communication module 115, the edge calculation module 114, the heat dissipation module 117, and the switch circuit 118, and is configured to provide electric energy or current to each hardware module.
The heat dissipation module 117 and the switch circuit 118 are also connected to the main control module 111, and the heat dissipation module 117 is configured to dissipate heat of each hardware module and the housing 100 on the integrated circuit substrate 110 based on a heat dissipation instruction sent by the main control module 111, so as to prevent the integrated circuit substrate 110 and related devices from overheating during operation. The switch circuit 118 is used for controlling the on/off of the circuit of the integrated circuit substrate 110 based on a switch control command sent by the main control module 111. The main control module 111 mainly outputs a control signal to control the on/off of the switch circuit 118 and the heat dissipation module 117, so as to implement the heat dissipation function or the on/off function of the switch circuit 118.
The electromechanical device signal acquisition module 112 may be flexibly assembled according to the electromechanical device configuration conditions of different tunnel sites, and in an embodiment, the electromechanical device signal acquisition module 112 may select an optimized device networking mode according to the site conditions and also select a reliable data transmission mode according to the tunnel management requirements.
In one embodiment, the mechatronic device signal acquisition module 112 includes, but is not limited to, the following types of devices, and the types of devices can be freely combined according to the field configuration, and the mechatronic device signal acquisition module 112 includes a ventilation device 1121, a lighting device 1122, a fire fighting device 1123, and a traffic device 1124. Each device is connected to the main control module 111 through a network or other communication methods, so as to transmit real-time data of different types of devices detected by different devices.
The ventilation device 1121 is configured to detect whether a circuit of the ventilation device 1121 is unblocked, forward rotation or reverse rotation of blades of the ventilation device 1121, a device rotation speed, a device air volume, an air pressure, noise, and the like; the lighting device 1122 is used to detect whether the current device circuit is unblocked, the current lighting brightness value, etc.; the fire fighting equipment 1123 is used for detecting whether the circuit of the fire fighting equipment 1123 is unblocked; the transportation equipment 1124 is used to detect whether the circuit of the transportation equipment 1124 is clear, the signal lamp status is passing or no passing, the value of the speed limit board, etc.
In other embodiments of the present application, the mechatronic device signal acquisition module 112 may further include a video image device, a broadcast system device, and the like.
The environment parameter detecting module 113 can be configured flexibly according to different tunnel site environment conditions. The environment parameter detecting module 113 selects an optimized detecting module networking mode according to the field situation, and also can select a reliable data transmission mode according to the tunnel management requirement. In one embodiment, the environmental parameter detecting module 113 includes a toxic gas detecting unit 1131, a flammable and explosive gas detecting unit 1132, an illuminance detecting unit 1133, a wind speed detecting unit 1134, a visibility detecting unit 1135, a temperature and humidity detecting unit 1136, and the like, each of the detecting units is connected to the main control module 111 through a network or other methods, respectively, for transmitting different types of environmental real-time data detected by different detecting units, and the types and the number of the detecting units can be freely combined according to the situation of the field environment.
The toxic gas detection unit 1131 is configured to detect toxic and harmful gases such as CO and NO2 in the tunnel, and may reflect the environmental safety in the tunnel to a certain extent, reflect the safety condition of the hazardous chemical transportation vehicle, and have a correlation with the operation data of the ventilation device 1121.
The illumination detection unit 1133 is configured to detect a brightness value in the tunnel, so as to reflect a view condition in the tunnel to a certain extent and reflect whether an abnormal light phenomenon, such as a fire, exists. The wind speed detection unit 1134 is configured to detect a wind speed value in the tunnel, which may reflect a ventilation condition in the tunnel and has a correlation with toxic and harmful gas data. The visibility detection unit 1135 is configured to detect a visibility value in the tunnel, reflect a view situation in the tunnel, and have a correlation with smoke and a fire situation in the tunnel. The temperature and humidity detection unit 1136 is configured to detect a temperature and humidity value in the tunnel, and may reflect, to a certain extent, whether a temperature abnormality such as a fire exists in the tunnel, and may also reflect a situation that an environment in the tunnel is affected by an weather.
Please refer to fig. 3, which is a schematic structural diagram of a tunnel operation anomaly detection system 1 according to an embodiment of the present application. As shown in fig. 3, the present application further provides a system 1 for detecting abnormal tunnel operation, which includes a device 10 for detecting abnormal tunnel operation provided in any of the above embodiments of the present application, and a data platform 11; the data platform 11 is connected to at least one tunnel operation anomaly detection device 10, and is configured to receive a prediction result, device real-time data, environment real-time data, and the like.
In the practical application process, the tunnel operation abnormity detection devices 10 are distributed on the tunnel wall at intervals of a preset distance along the tunnel direction, and are connected to the existing tunnel equipment and the detection unit in a wired or wireless mode to acquire real-time equipment data or real-time environment data; the tunnel operation anomaly detection apparatus 10 can detect the operation status and environmental parameters of the devices in the tunnel, and synthesize various data through the edge calculation module 114 to operate a corresponding anomaly detection algorithm and output a corresponding prediction result. The operation time of the abnormality detection algorithm can be freely set, for example, to be automatically operated every 30 seconds.
Based on the continuous generation of the real-time data of the equipment or the real-time data of the environment, the training data of the algorithm model is continuously updated, the anomaly detection algorithm model is further updated completely, and the prediction result output by the edge calculation module 114 is more accurate. If the prediction result is abnormal, the wireless communication module 115 in the tunnel operation abnormality detection device 10 sends abnormal data and abnormal equipment numbers to the data platform 11; the data platform 11 stores the tunnel device number, the tunnel position information corresponding to the device number, the normal value range of the device data and the normal value range of the environment detection data, and after receiving the abnormal data uploaded by the tunnel operation abnormality detection device 10, the data platform 11 provides preliminary analysis and judgment of the early warning information, provides a corresponding early warning disposal scheme according to detailed early warning data and the corresponding device measurement value range, and notifies tunnel operation managers.
In an embodiment, the system 1 for detecting tunnel operation anomaly further includes an early warning device 12, where the early warning device 12 is installed at a tunnel entrance or inside the tunnel, and is connected to the data platform 11 for sending an early warning prompt.
In the practical application process, after the tunnel operation manager confirms the early warning information, the tunnel prompt device receives the early warning information and the recommended plan measures sent by the data platform 11, executes the plan in a voice, image or signal lamp mode, and prompts vehicles entering the tunnel to take corresponding measures.
The tunnel operation abnormity detection device 10 and the tunnel operation abnormity detection system 1 can adapt to different tunnel field conditions, carry out abnormity detection according to electromechanical equipment and an environment detection instrument in a tunnel, and have stronger universality and adaptability. The tunnel operation abnormity detection device 10 is based on a machine learning algorithm, has the characteristics of self-learning and intelligent improvement, is more reliable and accurate in accuracy rate of abnormity detection in operation along with data accumulation and updating, has extremely strong real-time performance, can perform early warning in the first time of abnormity occurrence, and provides a precious time window for tunnel accident rescue.
In addition, through automatic data analysis, missing detection of the real-time monitoring picture by human eyes in the application of the traditional operation anomaly detection system is avoided, the reliability of anomaly detection is improved, the investment of manpower and material resources is saved, and the method has better economic benefit. The multifunctional integrated circuit has the advantages of being multifunctional, individual in design, convenient to use and high in cost performance, and is suitable for large-scale popularization and application.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A tunnel operation abnormality detection apparatus, characterized by comprising:
a housing;
the integrated circuit substrate is arranged in the shell and comprises a main control module, an electromechanical device signal acquisition module, an environmental parameter detection module, a wireless communication module and an edge calculation module;
the main control module is used for outputting a control signal; the electromechanical equipment signal acquisition module is connected with the main control module and is used for acquiring real-time data of equipment; the environment parameter detection module is connected with the main control module and is used for acquiring environment real-time data; the edge calculation module is connected with the main control module and used for outputting a prediction result; the wireless communication module is connected with the main control module and used for sending the prediction result, the equipment real-time data and the environment real-time data.
2. The tunnel operation anomaly detection device according to claim 1, wherein said integrated circuit substrate further comprises:
and the power supply is connected with the main control module, the electromechanical equipment signal acquisition module, the environmental parameter detection module, the wireless communication module and the edge calculation module and is used for providing current.
3. The tunnel operation anomaly detection device according to claim 1, wherein said integrated circuit substrate further comprises:
and the heat dissipation module is connected with the main control module and used for dissipating heat of the integrated circuit substrate.
4. The tunnel operation abnormality detection apparatus according to claim 1, wherein said integrated circuit substrate further includes:
and the switch circuit is connected with the main control module and is used for controlling the on-off of the circuit of the integrated circuit substrate.
5. The tunnel operation anomaly detection device according to claim 1, wherein said mechatronic device signal acquisition module comprises:
the ventilation equipment is connected with the main control module and used for detecting the forward rotation or the reverse rotation of the fan blades, the rotating speed, the air volume, the air pressure and the noise;
and the lighting equipment is connected with the main control module and used for detecting the current lighting brightness value.
6. The tunnel operation anomaly detection device according to claim 5, wherein said mechatronic device signal acquisition module further comprises:
the fire fighting equipment is connected with the main control module and used for detecting whether a circuit of the fire fighting equipment is unblocked or not;
and the traffic equipment is connected with the main control module and used for detecting whether the state of the signal lamp is a passing state or a no passing state.
7. The tunnel operation anomaly detection device according to claim 1, wherein said environment parameter detection module comprises:
the illumination detection unit is connected with the main control module and is used for detecting the brightness value in the tunnel;
the wind speed detection unit is connected with the main control module and is used for detecting a wind speed value in the tunnel;
the visibility detection unit is connected with the main control module and used for detecting the visibility value in the tunnel;
and the temperature and humidity detection unit is connected with the main control module and used for detecting the temperature and humidity value in the tunnel.
8. The tunnel operation anomaly detection device according to claim 1, wherein said environment parameter detection module comprises:
and the toxic gas detection unit is connected with the main control module and used for detecting toxic and harmful gases in the tunnel.
9. A system for detecting tunnel operation anomaly, comprising:
the tunnel operation abnormality detection apparatus according to any one of claims 1 to 8;
and the data platform is connected with the tunnel operation abnormity detection device and is used for receiving the prediction result, the equipment real-time data and the environment real-time data.
10. The system according to claim 9, wherein the system further comprises:
and the early warning device is connected with the data platform and used for sending early warning prompts.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202222010717.7U CN217606278U (en) | 2022-07-29 | 2022-07-29 | Tunnel operation abnormity detection device and system |
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| CN202222010717.7U CN217606278U (en) | 2022-07-29 | 2022-07-29 | Tunnel operation abnormity detection device and system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116357400A (en) * | 2023-05-31 | 2023-06-30 | 山东高速信息集团有限公司 | Intelligent inspection system for expressway tunnel |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116357400A (en) * | 2023-05-31 | 2023-06-30 | 山东高速信息集团有限公司 | Intelligent inspection system for expressway tunnel |
| CN116357400B (en) * | 2023-05-31 | 2023-08-08 | 山东高速信息集团有限公司 | Intelligent inspection system for expressway tunnel |
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