WO2024065919A1 - 隧道诊断车中央控制***及方法 - Google Patents

隧道诊断车中央控制***及方法 Download PDF

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Publication number
WO2024065919A1
WO2024065919A1 PCT/CN2022/127480 CN2022127480W WO2024065919A1 WO 2024065919 A1 WO2024065919 A1 WO 2024065919A1 CN 2022127480 W CN2022127480 W CN 2022127480W WO 2024065919 A1 WO2024065919 A1 WO 2024065919A1
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WIPO (PCT)
Prior art keywords
tunnel
structural safety
disease
information
current
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PCT/CN2022/127480
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English (en)
French (fr)
Inventor
任伟新
赵杨平
王俊芳
杜彦良
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深圳大学
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Publication of WO2024065919A1 publication Critical patent/WO2024065919A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0423—Input/output
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
    • E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
    • E21F17/18—Special adaptations of signalling or alarm devices
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/25—Pc structure of the system
    • G05B2219/25257—Microcontroller
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • the present application relates to the technical field of traffic structure safety, and in particular to a central control system and method for a tunnel diagnostic vehicle.
  • the main purpose of this application is to propose a central control system and method for a tunnel diagnostic vehicle, aiming to optimize the detection effect of structural safety detection of structural safety defects in underground tunnels.
  • the present application provides a central control system for a tunnel diagnostic vehicle, the central control system for a tunnel diagnostic vehicle comprising: a central controller and a time-space synchronization subsystem and a tunnel detection subsystem connected to the central controller by signal;
  • a space-time synchronization subsystem used for outputting space-time synchronization signals
  • the central controller controls the tunnel detection subsystem to perform disease detection on the current tunnel based on the time-space synchronization signal
  • the tunnel detection subsystem is used to perform tunnel disease detection work and feed back the tunnel disease information of the detected tunnel to the central controller;
  • the central controller Based on the tunnel disease information, the central controller performs multi-dimensional information fusion on the tunnel disease information, obtains multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, determines the target structural safety disease of the current tunnel, and outputs the corresponding structural safety disease report.
  • the central control system of the tunnel diagnostic vehicle is also connected to a cloud-based precision diagnosis platform;
  • the method further includes:
  • the cloud-based precision diagnosis platform is used to accurately diagnose the safety defects of target structures of preset types
  • the central controller controls the cloud-based precision diagnosis platform to accurately diagnose preset types of target structural safety defects based on the multi-dimensional monitoring information, makes decision-making plans for the target structural safety defects, and generates corresponding precise diagnosis reports.
  • the tunnel detection subsystem includes: an apparent damage and water leakage detection module, a deformation and displacement detection module, and a hidden disease detection module;
  • Surface damage and water leakage detection module used to detect damage and cracks in the current tunnel
  • the deformation and displacement detection module is used to detect the deformation and displacement of the current tunnel
  • Hidden disease detection module used to detect hidden diseases in the current tunnel
  • the central controller controls the apparent damage and water leakage detection module, the deformation and displacement detection module and the hidden disease detection module in the tunnel detection subsystem to detect the current tunnel, and obtains the damage and crack conditions, deformation and displacement conditions and hidden diseases of the current tunnel respectively.
  • the tunnel detection subsystem further includes: an auxiliary detection module and a drone inspection module;
  • Auxiliary detection module used to collect basic tunnel information in the current tunnel
  • the drone inspection module is used to conduct a local inspection of a preset target location and collect specific disease conditions at the target location;
  • the central controller controls the auxiliary detection module to collect information on the current tunnel and obtain basic tunnel information in the current tunnel;
  • the central controller controls the preset device of the drone inspection module to conduct a local inspection on the preset target position in the current tunnel and collect the specific disease conditions of the target position.
  • the spatiotemporal synchronization subsystem includes: an encoder, a positioning and navigation module, and a data synchronization module;
  • a positioning and navigation module used for accurately positioning the tunnel diagnostic vehicle based on the pulse signal
  • Data synchronization module used to synchronize the time and space data between the central control system of the tunnel diagnostic vehicle and the current tunnel diagnostic vehicle;
  • the central controller controls the encoder of the space-time synchronization subsystem to generate a corresponding pulse signal, and based on the pulse signal, controls the positioning and navigation module to accurately locate the current tunnel diagnostic vehicle, obtain the space-time data of the current tunnel diagnostic vehicle, and the central controller synchronizes the space-time data to the data synchronization module.
  • the central controller includes: an information multi-dimensional fusion module, a front-end initial diagnosis module and a report feedback module;
  • An information multi-dimensional fusion module is used to perform multi-dimensional information fusion on the tunnel disease information obtained by the tunnel detection subsystem to obtain multi-dimensional detection information of the current tunnel;
  • a front-end initial diagnosis module is used to perform a front-end initial diagnosis of the current tunnel based on the multi-dimensional detection information of the current tunnel, and determine the target structural safety diseases in the current tunnel;
  • the report feedback module is used to generate a corresponding structural safety disease report according to the target structural safety disease in the current tunnel, and to feed back the structural safety disease report.
  • the central controller and the time-space synchronization subsystem and tunnel detection subsystem connected to the central controller by signal realize data transmission based on a preset data stream link;
  • the time-space synchronization subsystem realizes time-space synchronization signal transmission with the central controller through a preset time-space synchronization link;
  • the tunnel detection subsystem realizes data transmission with the central controller through a preset system software and hardware synchronization link.
  • the present application also provides a control method of a central control system of a tunnel diagnostic vehicle, the control method of the central control system of a tunnel diagnostic vehicle is applied to the central control system of a tunnel diagnostic vehicle, the central control system of a tunnel diagnostic vehicle comprises: a central controller for integrated control of various subsystems in the central control system of the tunnel diagnostic vehicle, a time-space synchronization subsystem for realizing electrical signal connection with the central controller, and a tunnel detection subsystem, wherein the control method of the central control system of a tunnel diagnostic vehicle comprises:
  • the central controller obtains a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem;
  • the central controller controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel;
  • multi-dimensional information fusion is performed on the tunnel disease information to obtain multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, the target structural safety disease of the current tunnel is determined, and the corresponding structural safety disease report is output.
  • the step of determining the target structural safety hazard of the current tunnel based on the multi-dimensional monitoring information and outputting a corresponding structural safety hazard report includes:
  • a front-end preliminary diagnosis is performed on the structural safety defects in the current tunnel, and the defect type of the structural safety defects in the current tunnel is determined;
  • the structural safety hazard is of a first preset type
  • matching a solution to the structural safety hazard of the first preset type is performed to determine a preliminary diagnosis report corresponding to the structural safety hazard of the first preset type
  • the structural safety hazard is of the second preset type, uploading the structural safety hazard information corresponding to the structural safety hazard of the second preset type to a preset cloud diagnosis platform;
  • the step of performing a front-end preliminary diagnosis on the structural safety defects in the current tunnel and determining the defect type of the structural safety defects in the current tunnel includes:
  • the structural safety defects are classified and the defect types of the structural safety defects are determined.
  • the present application proposes a central control system and method for a tunnel diagnostic vehicle.
  • the central control method for a tunnel diagnostic vehicle is applied to a central control system of a tunnel diagnostic vehicle.
  • the central control system of a tunnel diagnostic vehicle includes a central controller and a space-time synchronization subsystem and a tunnel detection subsystem connected to the central controller by signal; the space-time synchronization subsystem is used to output a space-time synchronization signal; the central controller controls the tunnel detection subsystem to perform disease detection on the current tunnel based on the space-time synchronization signal; the tunnel detection subsystem is used to perform tunnel disease detection and feed back tunnel disease information of the detected tunnel to the central controller; the central controller performs multi-dimensional information fusion on the tunnel disease information based on the tunnel disease information, obtains multi-dimensional monitoring information corresponding to the current tunnel, and determines the target structural safety disease of the current tunnel based on the multi-dimensional monitoring information, and outputs a corresponding structural safety disease report.
  • the central control method of the tunnel diagnostic vehicle comprises: the central controller obtains a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem; based on the synchronization signal, the central controller controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel; based on the tunnel disease information, multi-dimensional information fusion is performed on the tunnel disease information to obtain multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, the target structural safety disease of the current tunnel is determined, and the corresponding structural safety disease report is output.
  • the present application controls the tunnel diagnostic vehicle through the tunnel diagnostic vehicle central control system to perform structural safety inspection on the current tunnel, determines the structural safety diseases of the current tunnel, and preliminarily classifies the structural safety diseases, determines the disease type of the structural safety disease, performs front-end diagnosis on the preset type of structural safety disease, and determines the corresponding initial diagnosis report.
  • the efficiency of diagnosing simple diseases in the current tunnel is improved, the diagnosis report is sent in time, and the efficiency of producing the detection report is improved; and real-time and accurate disease analysis is performed, which shortens the detection cycle of hidden diseases and improves the detection rate.
  • the present application implements a detection scheme for the central control system of the tunnel diagnostic vehicle by integrating the space-time synchronization subsystem, the tunnel detection subsystem, and the central controller.
  • the tunnel information of the current tunnel is obtained through multiple detection modules of the tunnel detection subsystem, thereby increasing the information sources for structural safety detection and improving the reliability of structural safety information for structural safety detection.
  • the multi-dimensional fusion of tunnel disease information is realized based on the central controller, thereby improving the targeted nature of structural safety detection, and achieving matching solutions and output of evaluation reports based on structural safety diseases, thereby improving the detection efficiency of the current tunnel and optimizing the detection effect of the structural safety detection of the current tunnel.
  • FIG1 is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the central control method of the tunnel diagnostic vehicle of the present application;
  • FIG2 is a schematic diagram of the system architecture of a tunnel diagnostic vehicle according to an embodiment of the central control method of the tunnel diagnostic vehicle of the present application;
  • FIG3 is a flow chart of a first embodiment of a central control method for a tunnel diagnostic vehicle of the present application
  • FIG4 is a flow chart of a second embodiment of the central control method for a tunnel diagnostic vehicle of the present application.
  • FIG5 is a schematic diagram of the functional modules of the central control system of the tunnel diagnostic vehicle of the central control method of the tunnel diagnostic vehicle of the present application.
  • FIG. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the central control method for a tunnel diagnostic vehicle of the present application.
  • the device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002.
  • the communication bus 1002 is used to realize the connection and communication between these components.
  • the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).
  • the memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory.
  • the memory 1005 may also be a storage device independent of the aforementioned processor 1001.
  • the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a system control program.
  • the operating system is a program for managing and controlling the hardware and software resources of the device, and supports the operation of the system control program and other software or programs;
  • the network communication module is used to manage and control the network interface 1004;
  • the user interface 1003 is mainly used for data communication with the client;
  • the network interface 1004 is mainly used to establish a communication connection with the server; and the processor 1001 can be used to call the system control program stored in the memory 1005.
  • the central controller obtains a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem;
  • the central controller controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel;
  • multi-dimensional information fusion is performed on the tunnel disease information to obtain multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, the target structural safety disease of the current tunnel is determined, and the corresponding structural safety disease report is output.
  • a front-end preliminary diagnosis is performed on the structural safety defects in the current tunnel, and the defect type of the structural safety defects in the current tunnel is determined;
  • the structural safety hazard is of a first preset type
  • matching a solution to the structural safety hazard of the first preset type is performed to determine a preliminary diagnosis report corresponding to the structural safety hazard of the first preset type
  • the structural safety hazard is of the second preset type, uploading the structural safety hazard information corresponding to the structural safety hazard of the second preset type to a preset cloud diagnosis platform;
  • the structural safety defects are classified and the defect types of the structural safety defects are determined.
  • FIG. 1 does not constitute a limitation on the device, and may include more or fewer components than shown, or a combination of certain components, or a different arrangement of components.
  • FIG. 2 is a schematic diagram of the system architecture of the central control system of a tunnel diagnostic vehicle involved in the embodiment of the tunnel diagnostic vehicle central control method of the present application.
  • the system of the central control system of the tunnel diagnostic vehicle at least includes: a central controller and a space-time synchronization subsystem and a tunnel detection subsystem connected to the central controller by signal, wherein the space-time synchronization subsystem is used to output a space-time synchronization signal; the central controller controls the tunnel detection subsystem to perform disease detection on the current tunnel based on the space-time synchronization signal; the tunnel detection subsystem is used to perform tunnel disease detection and feed back tunnel disease information of the detected tunnel to the central controller; the central controller performs multi-dimensional information fusion on the tunnel disease information based on the tunnel disease information, obtains multi-dimensional monitoring information corresponding to the current tunnel, and determines the target structural safety disease of the current tunnel based on the multi-dimensional monitoring information, and outputs the corresponding structural safety disease report.
  • the central control system of the tunnel diagnostic vehicle is also connected to a cloud-based precision diagnosis platform for accurately diagnosing preset types of target structural safety defects.
  • the central controller controls the cloud-based precision diagnosis platform to accurately diagnose preset types of target structural safety defects based on the multi-dimensional monitoring information, and makes decisions and plans for the target structural safety defects to generate a corresponding accurate diagnosis report.
  • the tunnel detection subsystem includes an apparent damage and water leakage detection module, a deformation and displacement detection module, and a hidden hazard detection module.
  • the apparent damage and water leakage detection module is used to detect the damage and crack conditions of the current tunnel;
  • the deformation and displacement detection module is used to detect the deformation and displacement conditions of the current tunnel;
  • the hidden disease detection module is used to detect the hidden diseases of the current tunnel.
  • the central controller controls the apparent damage and water leakage detection module, the deformation and displacement detection module, and the hidden disease detection module in the tunnel detection subsystem to detect the current tunnel, and obtain the damage and crack conditions, deformation and displacement conditions, and hidden diseases of the current tunnel respectively.
  • the tunnel detection subsystem further includes an auxiliary detection module and an unmanned aerial vehicle inspection module.
  • the auxiliary detection module is used to collect basic tunnel information in the current tunnel; the unmanned aerial vehicle inspection module is used to conduct a local inspection of a preset target location and collect specific disease conditions at the target location.
  • the central controller controls the auxiliary detection module to collect information on the current tunnel and obtain basic tunnel information in the current tunnel; the central controller controls the preset device of the unmanned aerial vehicle inspection module to conduct a local inspection of the preset target location in the current tunnel and collect specific disease conditions at the target location.
  • the space-time synchronization subsystem of the central control system of the tunnel diagnostic vehicle is used to obtain a synchronization signal for controlling the central control system of the tunnel diagnostic vehicle to perform tunnel detection based on a preset precise space-time synchronization technology;
  • the tunnel detection subsystem is used to detect the current tunnel based on each detection module of the preset monitoring and detection technology group, and obtain tunnel disease information of the current tunnel;
  • the central controller is used to perform multi-dimensional information fusion on the tunnel disease information of the current tunnel based on a preset multi-dimensional information fusion technology, obtain corresponding multi-dimensional monitoring information, and perform information fusion on the collected tunnel information of the current tunnel, obtain corresponding multi-dimensional monitoring information, and perform an initial diagnosis on the current tunnel based on the above multi-dimensional monitoring information, perform decision planning and feedback optimization, and obtain a corresponding initial diagnosis report.
  • the drone inspection module in the tunnel detection subsystem is used to conduct a local inspection of a preset target location and collect the specific disease conditions of the target location.
  • the auxiliary detection module in the tunnel detection subsystem is used to collect basic tunnel information in the current tunnel, specifically including: an information collection device, a vehicle body sub-electronic control device, an instrument and display device, and a visualization front end.
  • the information collection device includes vibration monitoring, scene monitoring, obstacle avoidance radar, and a positioning and attitude device, which are used to collect tunnel information for the current tunnel where the tunnel diagnosis vehicle is located;
  • the vehicle body sub-electronic control device is connected to each electronic control system connected to the power management module, and is used to manage each electronic control system that performs structural safety inspection in the system of the central control system of the tunnel diagnosis vehicle;
  • the instrument and display device is a visualization front end that realizes data connection with the cloud-based precision diagnosis platform and the central controller in the system of the central control system of the tunnel diagnosis vehicle, and the data of the structural safety inspection can be visualized through the instrument and display device.
  • the spatiotemporal synchronization subsystem of the central control system of the tunnel diagnostic vehicle comprises: an encoder, a positioning and navigation module, and a data synchronization module; wherein the encoder is used to generate a pulse signal; the positioning and navigation module is used to accurately locate the tunnel diagnostic vehicle based on the pulse signal; and the data synchronization module is used to synchronize the spatiotemporal data of the tunnel diagnostic vehicle central control system with the current tunnel diagnostic vehicle.
  • the central controller generates a corresponding pulse signal by controlling the encoder of the spatiotemporal synchronization subsystem, and based on the pulse signal, controls the positioning and navigation module to accurately locate the current tunnel diagnostic vehicle, obtains the spatiotemporal data of the current tunnel diagnostic vehicle, and the central controller synchronizes the spatiotemporal data to the data synchronization module.
  • the central controller of the central control system of the tunnel diagnostic vehicle includes: an information multi-dimensional fusion module, a front-end initial diagnosis module and a report feedback module; wherein the information multi-dimensional fusion module is used to perform multi-dimensional information fusion on the tunnel disease information obtained by the tunnel detection subsystem to obtain multi-dimensional detection information of the current tunnel; the front-end initial diagnosis module is used to perform a front-end initial diagnosis of the disease on the current tunnel based on the multi-dimensional detection information of the current tunnel to determine the target structural safety disease in the current tunnel; the report feedback module is used to generate a corresponding structural safety disease report according to the target structural safety disease in the current tunnel, and to feedback the structural safety disease report.
  • the information multi-dimensional fusion module is used to perform multi-dimensional information fusion on the tunnel disease information obtained by the tunnel detection subsystem to obtain multi-dimensional detection information of the current tunnel
  • the front-end initial diagnosis module is used to perform a front-end initial diagnosis of the disease on the current tunnel based on the multi-dimensional detection information of the current tunnel to
  • each module unit in the above-mentioned tunnel diagnostic vehicle central control system realizes data transmission based on a preset data flow link.
  • the space-time synchronization subsystem realizes space-time synchronization signal transmission with the central controller through a preset space-time synchronization link;
  • the tunnel detection subsystem realizes data transmission with the central controller through a preset system software and hardware synchronization link.
  • FIG. 3 is a flow chart of a first embodiment of a central control method for a tunnel diagnostic vehicle of the present application, wherein the central control method for a tunnel diagnostic vehicle comprises:
  • Step S10 the central controller obtains a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem;
  • Step S20 based on the synchronization signal, the central controller controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel;
  • Step S30 based on the tunnel disease information, multi-dimensional information fusion is performed on the tunnel disease information to obtain multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, the target structural safety disease of the current tunnel is determined, and the corresponding structural safety disease report is output.
  • the central control method of a tunnel diagnostic vehicle in an embodiment of the present application controls the tunnel diagnostic vehicle to perform structural safety detection on the current tunnel, by determining the structural safety defects of the current tunnel, and preliminarily classifying the structural safety defects, determining the defect type of the structural safety defects, performing front-end diagnosis on preset types of structural safety defects, and determining a corresponding initial diagnosis report.
  • Step S10 the central controller obtains a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem;
  • the tunnel diagnostic vehicle central control system controls the tunnel detection subsystem carried by the tunnel diagnostic vehicle to collect tunnel information from tunnels within a preset range of the tunnel where the tunnel diagnostic vehicle is currently located, obtain tunnel information corresponding to the current tunnel, and then perform information fusion based on the information multi-dimensional fusion subsystem, and perform structural safety disease identification based on the tunnel information after information fusion to determine the structural safety diseases existing in the current tunnel.
  • the tunnel detection subsystem at least includes: an apparent damage and water leakage detection module, a deformation displacement detection module and a hidden hazard detection module, and based on the various modules of the tunnel detection subsystem, the tunnel information of the current tunnel is collected.
  • the tunnel diagnostic vehicle moves forward for dynamic detection, the data of the current tunnel of the tunnel diagnostic vehicle and the operation background are aligned based on the preset multi-system precise time and space synchronization.
  • the data alignment includes time synchronization, history synchronization and coordinate synchronization.
  • Step S20 based on the synchronization signal, the central controller controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel;
  • the tunnel detection subsystem of the central control system of the tunnel diagnostic vehicle further includes an apparent damage and water leakage detection module, a deformation displacement detection module and a hidden hazard detection module, and the structural safety hazards in the current tunnel are identified through the above modules.
  • this embodiment detects the apparent damage and water leakage-type structural safety hazards of the current tunnel through the above-mentioned apparent damage and water leakage detection module to determine whether the current tunnel has apparent damage and water leakage-type structural safety hazards. If the current tunnel has the above-mentioned apparent damage and water leakage-type structural safety hazards, the apparent damage and water leakage detection module collects the hazard parameters corresponding to the apparent damage and water leakage-type structural safety hazards.
  • the deformation and displacement type structural safety defects of the current tunnel are detected by the above-mentioned deformation and displacement detection module to determine whether the current tunnel has deformation and displacement type structural safety defects. If the current tunnel has the above-mentioned deformation and displacement type structural safety defects, the defect parameters corresponding to the deformation and displacement type structural safety defects are collected by the deformation and displacement detection module.
  • the hidden hazard detection module is used to detect the hidden hazard type structural safety defects of the current tunnel to determine whether the current tunnel has the hidden hazard type structural safety defects. If the current tunnel has the hidden hazard type structural safety defects, the hidden hazard detection module collects the defect parameters corresponding to the deformation and displacement type structural safety defects. It needs to be specifically explained that the hidden hazard can be defined as a non-fatal hazard that occurs in the current tunnel, that is, the hidden hazard will not cause a preset degree of impact on the structural safety of the current tunnel within a preset period of time, but as time goes by, the hidden hazard still has a certain degree of harmfulness. For the hidden hazard, further accurate defect analysis needs to be performed through the cloud-based precision diagnosis platform, and the corresponding defect parameters of the hidden hazard type structural safety defects are determined.
  • the tunnel detection subsystem of the central control system of the above-mentioned tunnel diagnostic vehicle includes an auxiliary detection module and an unmanned aerial vehicle inspection module.
  • the auxiliary detection module in the above-mentioned tunnel detection subsystem is used to perform structural safety disease detection on the overall tunnel space in the current tunnel based on a preset monitoring and detection technology group to obtain basic tunnel information of the current tunnel;
  • the unmanned aerial vehicle inspection module in the above-mentioned tunnel detection subsystem is used to perform local inspection on the target position corresponding to the structural safety disease in the current tunnel to obtain the specific disease condition of the above-mentioned target position.
  • the tunnel detection subsystem includes an auxiliary detection module and an unmanned aerial vehicle inspection module.
  • the auxiliary detection module in the tunnel detection subsystem performs structural safety disease detection on the overall tunnel space in the current tunnel based on a preset monitoring and detection technology group to obtain basic tunnel information of the current tunnel.
  • the unmanned aerial vehicle inspection module in the tunnel detection subsystem performs local inspection on the target position corresponding to the structural safety disease in the current tunnel to obtain the specific disease condition of the target position, wherein the local inspection may be performed by obtaining image information of the specific part of the target position, obtaining the specific structural texture of the target position, etc.
  • the monitoring and detection technology group included in the above-mentioned auxiliary detection module may include: deformation detection technology based on three-dimensional lidar, hidden disease detection technology based on ground penetrating radar, impact echo, and acoustic vibration method, apparent defect detection technology based on three-dimensional visual information, track geometry detection technology based on total station + inertial navigation, apparent disease detection technology based on visible light + infrared, and high-precision positioning and attitude determination methods and other detection technology groups.
  • the above-mentioned drone inspection module can perform local inspection in a manner that performs local inspection on the target location where the structural safety disease occurs in the current tunnel, obtains local disease information on the target location where the structural safety disease occurs in the current tunnel through a preset photographing device and a detection device in the drone inspection system, and determines the specific disease condition of the target location based on the above-mentioned local disease information.
  • the deformation and displacement detection module collects the disease parameters corresponding to the deformation and displacement type structural safety diseases, the tunnel information of the current tunnel, the disease parameters of the hidden hazard type structural safety diseases, the basic tunnel information of the current tunnel and the specific disease conditions of the current tunnel, the actual structural safety diseases in the current tunnel are determined.
  • Step S30 based on the tunnel disease information, multi-dimensional information fusion is performed on the tunnel disease information to obtain multi-dimensional monitoring information corresponding to the current tunnel, and based on the multi-dimensional monitoring information, the target structural safety disease of the current tunnel is determined, and the corresponding structural safety disease report is output.
  • the tunnel disease information in the current tunnel collected by the apparent damage and water leakage detection module, deformation and displacement detection module, hidden hazard detection module, auxiliary detection module and drone inspection module in the above-mentioned tunnel detection subsystem is fused, and the multi-dimensional monitoring information after information fusion is obtained through the central controller.
  • the method for obtaining the multi-dimensional monitoring information after information fusion through the central controller can be to fuse the tunnel information of the current tunnel according to the multi-dimensional monitoring information through the central controller, specifically, by inputting the multi-dimensional monitoring information after multi-source heterogeneous fusion processing into the corresponding identification and diagnosis algorithm.
  • the structural safety defects are matched with solutions through the above-mentioned report output subsystem to determine the corresponding solutions, wherein the corresponding solutions can be determined by matching the structural safety defects through historical big data and querying the solutions in the historical data; or the tunnel defect information corresponding to the structural safety defects in the current tunnel can be uploaded to a preset cloud-based precision diagnosis platform for accurate diagnosis and determining the corresponding solutions.
  • tunnel disease information in the current tunnel is collected through a preset tunnel detection subsystem, and the disease information of the current tunnel is collected based on a preset monitoring and detection technology group, thereby increasing the data source for structural safety disease judgment, improving the accuracy of structural safety disease identification, and improving the accuracy of structural safety disease identification, thereby optimizing the detection effect of structural safety detection of the current tunnel.
  • a second embodiment of the control method of the tunnel diagnostic vehicle of the embodiment of the present application is proposed.
  • the second embodiment of the control method of the tunnel diagnostic vehicle is different from the first embodiment of the control method of the tunnel diagnostic vehicle in that, in step S30, the present embodiment refines "determining the target structural safety hazard of the current tunnel based on the multi-dimensional monitoring information and outputting the corresponding structural safety hazard report", with reference to FIG. 4, and specifically includes:
  • the step of performing a front-end preliminary diagnosis on the structural safety hazard in the current tunnel and determining the hazard type of the structural safety hazard in the current tunnel comprises:
  • the structural safety defects are classified and the defect types of the structural safety defects are determined.
  • S34 based on the cloud-based precision diagnosis platform, perform precise disease analysis on the second preset type of structural safety disease, and determine a precision diagnosis assessment report and maintenance recommendations corresponding to the second preset type of structural safety disease.
  • the tunnel disease information in the current tunnel collected by the apparent damage and water leakage detection module, deformation and displacement detection module, hidden hazard detection module, auxiliary detection module and drone inspection module in the above-mentioned tunnel detection subsystem is fused, and the multi-dimensional monitoring information after the information fusion is obtained through the central controller.
  • the structural safety diseases existing in the current tunnel are diagnosed at the front end to determine the types of the above-mentioned structural safety diseases.
  • the method of performing front-end preliminary diagnosis of the structural safety hazards of the current tunnel based on the multi-dimensional monitoring information by the central controller can be by inputting the multi-dimensional monitoring information that has been processed by multi-source heterogeneous fusion into the corresponding identification and diagnosis algorithm, first identifying the structural safety hazards existing in the current tunnel based on the multi-dimensional monitoring information, and then performing a front-end preliminary diagnosis of the structural safety hazards based on the historical diagnosis data in the identification and diagnosis algorithm.
  • feature extraction is performed on the structural safety defects existing in the current tunnel determined by the recognition and diagnosis algorithm of the above-mentioned central controller to determine the corresponding structural safety defect features, and the structural safety defects are classified according to the above-mentioned structural safety defect features to determine the defect type of the structural safety defect.
  • the above method of determining the type of structural safety disease can be to extract complementary features, fuse the features collected by each system, vector stack the fused multivariate features, extract the characteristic parameters of the unified disease from them, and determine the type of the structural safety disease based on the characteristic parameters.
  • the disease type of the structural safety disease existing in the current tunnel is the first preset type, that is, the hazard level of the structural safety disease existing in the current tunnel reaches the preset standard, and if the structural safety disease is not handled in time, it will cause fatal harm, that is, the structural safety disease is a fatal hazard, then it is necessary to conduct a preliminary diagnosis of the first preset type of fatal hazard through the central controller of the central control system of the tunnel diagnostic vehicle, match the solution according to the disease type and disease parameters of the structural safety disease, determine the corresponding solution, and avoid the fatal hazard in time.
  • the above-mentioned first preset type of structural safety hazard is matched with a solution to determine a corresponding solution.
  • the above-mentioned method of determining the corresponding solution can be to match the structural safety hazard through historical big data, query the solution in the historical data, and perform real-time alarm and structural safety hazard alarm based on the solution.
  • the disease type of the structural safety disease existing in the current tunnel is the second preset type, that is, the hazard level of the structural safety disease existing in the current tunnel has not reached the preset standard, and the structural safety disease will not cause fatal harm if it is not handled in time after the problem occurs, that is, the structural safety disease is a non-fatal hazard
  • the structural safety disease is a non-fatal hazard
  • the method of performing accurate disease analysis based on the disease parameters corresponding to the second preset type of non-fatal hazards through the cloud-based precision diagnosis platform can be to obtain tunnel disease information collected by the tunnel detection subsystem in the central control system of the tunnel diagnosis vehicle, make a hazard inference on the non-fatal hazards of the second preset type, determine the structural safety disease changes that will occur in the non-fatal hazards of the second preset type over time, generate a corresponding assessment report based on the corresponding structural safety disease changes, and determine corresponding maintenance recommendations based on the historical big data matching through the cloud-based precision diagnosis platform based on the assessment report.
  • This embodiment obtains tunnel information of the current tunnel through multiple detection methods, increases the information sources of structural safety detection, improves the reliability of structural safety information for structural safety detection, refines the structural safety diseases of the current tunnel through front-end diagnosis of structural safety defects and classification of defect types, improves the targeted nature of structural safety detection, and implements matching solutions based on structural safety defects through the cloud-based precision diagnosis platform, thereby optimizing the detection effect of structural safety detection on the current tunnel.
  • the embodiment of the present application also proposes a tunnel diagnostic vehicle central control system, referring to FIG5 , which is a schematic diagram of the functional modules of the tunnel diagnostic vehicle central control system involved in the embodiment of the tunnel diagnostic vehicle central control method of the present application.
  • the tunnel diagnostic vehicle central control system includes:
  • the time-space synchronization subsystem 10 is used for the central controller to obtain a synchronization signal for controlling the tunnel diagnostic vehicle to perform tunnel detection from the time-space synchronization subsystem;
  • the tunnel detection subsystem 20 controls the tunnel detection subsystem to detect the current tunnel and obtain tunnel disease information of the current tunnel;
  • the central controller 30 is used to perform multi-dimensional information fusion on the tunnel disease information based on the tunnel disease information, obtain multi-dimensional monitoring information corresponding to the current tunnel, and determine the target structural safety disease of the current tunnel based on the multi-dimensional monitoring information, and output the corresponding structural safety disease report.
  • an embodiment of the present application also proposes a device, which includes a memory, a processor, and a system control program stored in the memory and executable on the processor.
  • the system control program is executed by the processor, the steps of the central control method of the tunnel diagnostic vehicle as described in the above embodiment are implemented.
  • the present application also provides a medium, which is a computer-readable storage medium, on which a system control program is stored, and when the system control program is executed by a processor, the steps of the central control method of the tunnel diagnostic vehicle as described above are implemented.
  • system control program adopts all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the functions brought by all the technical solutions of all the aforementioned embodiments, which will not be described one by one here.

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Abstract

本申请涉及交通结构安全技术领域，公开了一种隧道诊断车中央控制***及方法，所述隧道诊断车中央控制***包括，中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***；其中，通过所述隧道检测子***的多个检测模块获取当前隧道的隧道病害信息，通过所述中央控制器实现隧道诊断车中央控制***的集成控制。

Description

隧道诊断车中央控制***及方法
本申请要求于2022年9月27号申请的、申请号为202211187555.2的中国专利申请的优先权。
技术领域
本申请涉及交通结构安全技术领域，尤其涉及一种隧道诊断车中央控制***及方法。
 背景技术
随着城市交通的不断发展，城市交通基础设施在空间布局上也不断得到延伸发展，其中，通过地下隧道实现城市交通基础设施向地面以下的延伸，实现了新型的城市交通方式。
然而，在上述通过地下隧道实现一种城市交通方式的过程中，地下隧道仍存在许多结构安全问题，而在对这些地面以下的结构安全病害进行结构安全检测的过程中，现有的结构安全检测设备无法准确识别地下隧道中的结构安全问题，且在检测到结构安全问题后，无法对各种结构安全问题提出有针对性的解决方案，对地下隧道出现的结构安全病害进行结构安全检测的效果差。
 技术问题
本申请的主要目的在于提出一种隧道诊断车中央控制***及方法，旨在优化对地下隧道的结构安全病害进行结构安全检测的检测效果。
 技术解决方案
为实现上述目的，本申请提供一种隧道诊断车中央控制***，所述隧道诊断车中央控制***包括：中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***；
时空同步子***，用于输出时空同步信号；
中央控制器基于所述时空同步信号控制所述隧道检测子***执行对当前隧道进行病害检测的工作；
所述隧道检测子***，用于执行隧道病害检测工作，并将检测的隧道的隧道病害信息反馈至所述中央控制器；
中央控制器基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
在一实施方式中，所述隧道诊断车中央控制***还连接云端精诊平台；
在所述基于所述多维度监测信息，确定当前隧道的目标结构安全病害之后，还包括：
云端精诊平台，用于对预设类型的目标结构安全病害进行精确诊断；
中央控制器基于所述多维度监测信息控制所述云端精诊平台对预设类型的目标结构安全病害进行精确诊断，并对所述目标结构安全病害进行决策规划，生成对应的精确诊断报告。
在一实施方式中，所述隧道检测子***包括：表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽病害检测模块；
表观损伤和渗漏水检测模块，用于检测当前隧道的损伤裂缝情况；
变形位移检测模块，用于检测当前隧道的变形位移情况；
隐蔽病害检测模块，用于检测当前隧道的隐蔽病害；
中央控制器控制所述隧道检测子***中的表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽病害检测模块对当前隧道进行检测，并分别获取当前隧道的损伤裂缝情况、变形位移情况和隐蔽病害。
在一实施方式中，所述隧道检测子***还包括：辅助检测模块和无人机细查模块；
辅助检测模块，用于采集当前隧道中的隧道基本信息；
无人机细查模块，用于对预设的目标位置进行局部细查，并采集所述目标位置的具体病害情况；
中央控制器控制所述辅助检测模块对当前隧道进行信息采集，获取当前隧道中的隧道基本信息；
中央控制器控制所述无人机细查模块的预设装置对当前隧道中预设的目标位置进行进行局部细查，采集目标位置的具体病害情况。
在一实施方式中，所述时空同步子***包括：编码器、定位导航模块和数据同步模块；
编码器，用于生成脉冲信号；
定位导航模块，用于基于所述脉冲信号对隧道诊断车进行精确定位；
数据同步模块，用于实现隧道诊断车中央控制***与当前隧道诊断车时空数据同步；
中央控制器控制所述时空同步子***的编码器生成对应的脉冲信号，并基于所述脉冲信号，控制所述定位导航模块对当前隧道诊断车进行精确定位，获取当前隧道诊断车的时空数据，中央控制器将所述时空数据同步至所述数据同步模块。
在一实施方式中，所述中央控制器包括：信息多维融合模块、前端初诊模块和报告反馈模块；
信息多维融合模块，用于将所述隧道检测子***获取的隧道病害信息进行多维信息融合，获取当前隧道的多维检测信息；
前端初诊模块，用于基于所述当前隧道的多维检测信息，对当前隧道进行病害前端初诊，确定当前隧道中的目标结构安全病害；
报告反馈模块，用于根据所述当前隧道中的目标结构安全病害，生成对应的结构安全病害报告，并将所述结构安全病害报告进行反馈。
在一实施方式中，所述中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***基于预设的数据流链路实现数据的传输；
所述时空同步子***，通过预设的时空同步链路实现与中央控制器的时空同步信号传输；
所述隧道检测子***，通过预设的***软硬同步链路实现与中央控制器的数据传输。
为实现上述目的，本申请还提供一种隧道诊断车中央控制***的控制方法，所述隧道诊断车中央控制***的控制方法应用于隧道诊断车中央控制***，所述隧道诊断车中央控制***包括：对所述隧道诊断车中央控制***中的各个子***进行集成控制的中央控制器、与所述中央控制器实现电信号连接的时空同步子***、隧道检测子***，其中，所述隧道诊断车中央控制***的控制方法包括：
所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
在一实施方式中，所述基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告的步骤，包括：
基于所述多维度监测信息，对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型；
若所述结构安全病害为第一预设类型，则对所述第一预设类型的结构安全病害进行解决方案匹配，确定所述第一预设类型的结构安全病害对应的初诊报告；
若所述结构安全病害为第二预设类型，则将所述第二预设类型的结构安全病害对应的结构安全病害信息上传至预设的云端精诊平台；
基于所述云端精诊平台，对所述第二预设类型的结构安全病害进行精确病害分析，确定所述第二预设类型的结构安全病害对应的精诊评估报告以及管养建议。
在一实施方式中，所述对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型的步骤，包括：
基于所述多维度监测信息，确定所述结构安全病害对应的病害信息；
根据所述病害信息对所述结构安全病害进行特征提取，确定当前隧道中结构安全病害对应的结构安全病害特征；
根据所述结构安全病害特征，对所述结构安全病害进行分类，并确定所述结构安全病害的病害类型。
本申请提出的隧道诊断车中央控制***及方法，所述隧道诊断车中央控制方法应用于隧道诊断车中央控制***，所述隧道诊断车中央控制***包括，中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***；时空同步子***，用于输出时空同步信号；中央控制器基于所述时空同步信号控制所述隧道检测子***执行对当前隧道进行病害检测的工作；所述隧道检测子***，用于执行隧道病害检测工作，并将检测的隧道的隧道病害信息反馈至所述中央控制器；中央控制器基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
所述隧道诊断车中央控制方法包括：所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
 有益效果
本申请通过隧道诊断车中央控制***控制隧道诊断车对当前隧道进行结构安全检测，通过确定当前隧道的结构安全病害，并对结构安全病害进行初步分类，确定该结构安全病害的病害类型，对预设类型的结构安全病害进行前端诊断，确定对应的初诊报告，在此过程中提升对当前隧道中的简易病害的诊断效率，及时发送诊断报告，提升检测报告产出效率；并进行实时的精确病害分析，缩短了隐蔽病害的检测周期，提升了检测速率。
另外，本申请通过对时空同步子***，隧道检测子***，中央控制器进行集成，实现了隧道诊断车中央控制***的检测方案，通过隧道检测子***的多个检测模块获取当前隧道的隧道信息，增加了结构安全检测的信息来源，提高了进行结构安全检测的结构安全信息的可靠性，并基于中央控制器实现隧道病害信息的多维融合，提高结构安全检测的针对性，实现根据结构安全病害匹配解决方案以及评估报告的输出，提升对当前隧道进行检测的检测效率，优化对当前隧道进行结构安全检测的检测效果。
 附图说明
图1为本申请隧道诊断车中央控制方法实施例方案涉及的硬件运行环境的设备结构示意图；
图2为本申请隧道诊断车中央控制方法实施例方案涉及的隧道诊断车的***架构示意图；
图3为本申请隧道诊断车中央控制方法第一实施例的流程示意图；
图4为本申请隧道诊断车中央控制方法第二实施例的流程示意图；
图5为本申请隧道诊断车中央控制方法的隧道诊断车中央控制***的功能模块示意图。
本申请目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
 本发明的实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
具体地，参照图1，图1为本申请隧道诊断车中央控制方法实施例方案涉及的硬件运行环境的设备结构示意图。
如图1所示，该设备可以包括：处理器1001，例如CPU，网络接口1004，用户接口1003，存储器1005，通信总线1002。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏（Display）、输入单元比如键盘（Keyboard），可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的有线接口、无线接口（如WI-FI接口）。存储器1005可以是高速RAM存储器，也可以是稳定的存储器（non-volatile memory），例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的存储装置。
如图1所示，作为一种计算机存储介质的存储器1005中可以包括操作***、网络通信模块、用户接口模块以及***控制程序。其中，操作***是管理和控制设备硬件和软件资源的程序，支持***控制程序以及其它软件或程序的运行；网络通信模块用于管理和控制网络接口1004；用户接口1003主要用于与客户端进行数据通信；网络接口1004主要用于与服务器建立通信连接；而处理器1001可以用于调用存储器1005中存储的***控制程序.
其中，存储器1005中存储的***控制程序被处理器执行时还实现以下步骤：
所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
在一实施方式中，存储器1005中存储的***控制程序被处理器执行时还实现以下步骤：
基于所述多维度监测信息，对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型；
若所述结构安全病害为第一预设类型，则对所述第一预设类型的结构安全病害进行解决方案匹配，确定所述第一预设类型的结构安全病害对应的初诊报告；
若所述结构安全病害为第二预设类型，则将所述第二预设类型的结构安全病害对应的结构安全病害信息上传至预设的云端精诊平台；
基于所述云端精诊平台，对所述第二预设类型的结构安全病害进行精确病害分析，确定所述第二预设类型的结构安全病害对应的精诊评估报告以及管养建议。
在一实施方式中，存储器1005中存储的***控制程序被处理器执行时还实现以下步骤：
基于所述多维度监测信息，确定所述结构安全病害对应的病害信息；
根据所述病害信息对所述结构安全病害进行特征提取，确定当前隧道中结构安全病害对应的结构安全病害特征；
根据所述结构安全病害特征，对所述结构安全病害进行分类，并确定所述结构安全病害的病害类型。
本领域技术人员可以理解，图1中示出的设备结构并不构成对设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
为了更好的理解上述技术方案，下面将参照附图更详细地描述本公开的示例性实施例。虽然附图中显示了本公开的示例性实施例，然而应当理解，可以以各种形式实现本公开而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了能够更透彻地理解本公开，并且能够将本公开的范围完整的传达给本领域的技术人员。
参照图2，图2为本申请隧道诊断车中央控制方法实施例方案涉及的隧道诊断车中央控制***的***架构示意图。
如图2所示，该隧道诊断车中央控制***的***至少包括：中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***，其中，时空同步子***，用于输出时空同步信号；中央控制器基于所述时空同步信号控制所述隧道检测子***执行对当前隧道进行病害检测的工作；所述隧道检测子***，用于执行隧道病害检测工作，并将检测的隧道的隧道病害信息反馈至所述中央控制器；中央控制器基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
在一实施方式中，在所述基于所述多维度监测信息，确定当前隧道的目标结构安全病害之后，隧道诊断车中央控制***还连接云端精诊平台，用于对预设类型的目标结构安全病害进行精确诊断，中央控制器基于所述多维度监测信息控制所述云端精诊平台对预设类型的目标结构安全病害进行精确诊断，并对所述目标结构安全病害进行决策规划，生成对应的精确诊断报告。
在一实施方式中，上述隧道检测子***包括表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽危害检测模块，上述表观损伤和渗漏水检测模块用于检测当前隧道的损伤裂缝情况；上述变形位移检测模块用于检测当前隧道的变形位移情况；上述隐蔽病害检测模块用于检测当前隧道的隐蔽病害。中央控制器控制所述隧道检测子***中的表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽病害检测模块对当前隧道进行检测，并分别获取当前隧道的损伤裂缝情况、变形位移情况和隐蔽病害。
在一实施方式中，上述隧道检测子***还包括辅助检测模块和无人机细查模块，上述辅助检测模块，用于采集当前隧道中的隧道基本信息；无人机细查模块，用于对预设的目标位置进行局部细查，并采集所述目标位置的具体病害情况。中央控制器通过控制所述辅助检测模块对当前隧道进行信息采集，获取当前隧道中的隧道基本信息；中央控制器控制所述无人机细查模块的预设装置对当前隧道中预设的目标位置进行进行局部细查，采集目标位置的具体病害情况。
在一实施方式中，上述隧道诊断车中央控制***的时空同步子***用于基于预设的精准时空同步技术，获取控制所述隧道诊断车中央控制***进行隧道检测的同步信号；上述隧道检测子***用于基于预设的监检测技术群的各个检测模块对当前隧道进行检测，并获取当前隧道的隧道病害信息；上述中央控制器用于基于预设的多维信息融合技术，对当前隧道的隧道病害信息进行多维信息融合，获取对应的多维度监测信息，并对采集到的当前隧道的隧道信息进行信息融合，获取对应的多维度监测信息，并根据上述多维度监测信息对当前隧道进行初诊，进行决策规划以及反馈优化，获取对应的初诊报告。
在一实施方式中，上述隧道检测子***中的无人机细查模块用于对预设的目标位置进行局部细查，并采集所述目标位置的具体病害情况，上述隧道检测子***中的辅助检测模块用于采集当前隧道中的隧道基本信息，具体包括：信息采集装置，车体子电控装置、仪表与显示装置以及可视化前端。具体地，上述信息采集装置包括振动监测、场景监测、避障雷达以及定位定姿装置，用于对隧道诊断车所在的当前隧道进行隧道信息采集；上述车体子电控装置则与电源管理模块所连接的各个电控***实现连接，用于管理隧道诊断车中央控制***的***中进行结构安全检测的各个电控***；上述仪表与显示装置则是与云端精诊平台以及隧道诊断车中央控制***的***中的中央控制器实现数据连接的可视化前端，可通过该仪表与显示装置对结构安全检测的数据进行可视化管理。
在一实施方式中，上述隧道诊断车中央控制***的时空同步子***包括：编码器、定位导航模块和数据同步模块；其中，编码器，用于生成脉冲信号；定位导航模块，用于基于所述脉冲信号对隧道诊断车进行精确定位；数据同步模块，用于实现隧道诊断车中央控制***与当前隧道诊断车时空数据同步。中央控制器通过控制所述时空同步子***的编码器生成对应的脉冲信号，并基于所述脉冲信号，控制所述定位导航模块对当前隧道诊断车进行精确定位，获取当前隧道诊断车的时空数据，中央控制器将所述时空数据同步至所述数据同步模块。
在一实施方式中，上述隧道诊断车中央控制***的中央控制器包括：信息多维融合模块、前端初诊模块和报告反馈模块；其中，信息多维融合模块，用于将所述隧道检测子***获取的隧道病害信息进行多维信息融合，获取当前隧道的多维检测信息；前端初诊模块，用于基于所述当前隧道的多维检测信息，对当前隧道进行病害前端初诊，确定当前隧道中的目标结构安全病害；报告反馈模块，用于根据所述当前隧道中的目标结构安全病害，生成对应的结构安全病害报告，并将所述结构安全病害报告进行反馈。
在一实施方式中，上述隧道诊断车中央控制***中的各个模块单元都基于预设的数据流链路实现数据的传输，所述时空同步子***，通过预设的时空同步链路实现与中央控制器的时空同步信号传输；所述隧道检测子***，通过预设的***软硬同步链路实现与中央控制器的数据传输。
基于上述终端设备架构但不限于上述架构，提出本申请隧道诊断车中央控制方法实施例。
具体地，参照图3，图3为本申请隧道诊断车中央控制方法第一实施例的流程示意图，所述隧道诊断车中央控制方法包括：
步骤S10，所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
步骤S20，基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
步骤S30，基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
本申请实施例隧道诊断车中央控制方法本申请控制隧道诊断车对当前隧道进行结构安全检测，通过确定当前隧道的结构安全病害，并对结构安全病害进行初步分类，确定该结构安全病害的病害类型，对预设类型的结构安全病害进行前端诊断，确定对应的初诊报告。
以下将对各个步骤进行详细说明：
步骤S10，所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
在一具体实施例中，当隧道诊断车在一地下隧道行驶，并通过隧道诊断车中央控制***控制隧道诊断车搭载的隧道检测子***对隧道诊断车当前所在隧道预设范围内的隧道进行隧道信息采集，获取当前隧道对应的隧道信息，再基于信息多维融合子***进行信息融合，并根据信息融合后的隧道信息进行结构安全病害识别，确定当前隧道所存在的结构安全病害。
具体地，上述隧道检测子***至少包括：表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽危害检测模块，并基于上述隧道检测子***的各个模块实现对当前隧道的隧道信息进行采集。当上述隧道诊断车向前移动进行动态检测时，则基于预设的多***精准时空同步，实现该隧道诊断车当前隧道与操作后台的数据对齐，具体地，上述数据对齐包括时间同步、历程同步以及坐标同步。
步骤S20，基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
在一具体实施例中，上述隧道诊断车中央控制***的隧道检测子***还包含表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽危害检测模块，通过上述各个模块对当前隧道中的结构安全病害进行结构安全识别。
在一实施方式中，本实施例通过上述表观损伤和渗漏水检测模块对当前隧道的表观损伤和渗漏水类结构安全病害进行检测，判断当前隧道是否出现表观损伤和渗漏水类结构安全病害，若当前隧道存在上述表观损伤和渗漏水类的结构安全病害，则通过该表观损伤和渗漏水检测模块采集该表观损伤和渗漏水类的结构安全病害对应的病害参数。
在一实施方式中，通过上述变形位移检测模块对当前隧道的变形位移类结构安全病害进行检测，判断当前隧道是否出现变形位移类结构安全病害，若当前隧道存在上述变形位移类结构安全病害，则通过该变形位移检测模块采集该变形位移类结构安全病害对应的病害参数。
在一实施方式中，通过上述隐蔽危害检测模块对当前隧道的隐蔽危害类结构安全病害进行检测，判断当前隧道是否存在隐蔽危害类结构安全病害，若当前隧道存在上述隐蔽危害类结构安全病害，则通过该隐蔽危害检测模块采集该变形位移类结构安全病害对应的病害参数，需进行具体解释的是，上述隐蔽危害可以定义为在当前隧道中出现的非致命性危害，即该隐蔽危害在一段预设时间内并不会对当前隧道的结构安全造成预设程度影响，但随着时间的推移，该隐蔽危害仍存在一定的危害性，针对上述隐蔽危害需通过云端精诊平台进行进一步地精确病害分析，并确定对应的隐蔽危害类结构安全病害的病害参数。
作为一种具体实施例，上述隧道诊断车中央控制***的隧道检测子***包括辅助检测模块和无人机细查模块，通过上述隧道检测子***中的辅助检测模块对当前隧道中的整体隧道空间进行基于预设的监检测技术群的结构安全病害检测，获取当前隧道的隧道基本信息；通过上述隧道检测子***中的无人机细查模块对当前隧道出现结构安全病害对应的目标位置进行局部细查，获取上述目标位置的具体病害情况。
在一实施方式中，上述隧道检测子***中的包括辅助检测模块和无人机细查模块，通过上述隧道检测子***中的辅助检测模块对当前隧道中的整体隧道空间进行基于预设的监检测技术群的结构安全病害检测，获取当前隧道的隧道基本信息；通过上述隧道检测子***中的无人机细查模块对当前隧道出现结构安全病害对应的目标位置进行局部细查，获取上述目标位置的具体病害情况，其中，上述进行局部细查的方式可以是通过获取目标位置的具体部位图像信息、获取目标位置的具体结构文理等。
在一实施方式中，上述辅助检测模块所包含的监检测技术群可以包括：基于三维激光雷达的变形检测技术、基于探地雷达、冲击回波、声振法的隐蔽病害检测技术、基于三维视觉信息的表观缺陷检测技术、基于全站仪+惯导的轨道几何形位检测技术、基于可见光+红外的表观病害检测技术以及高精度定位定姿方法等检测技术群。
在一实施方式中，上述无人机细查模块进行局部细查的方式可以是，对当前隧道出现结构安全病害的目标位置进行局部细查，通过该无人机细查***中预设的拍照装置以及检测装置，获取当前隧道出现结构安全病害的目标位置上的局部病害信息，并基于上述局部病害信息确定该目标位置的具体病害情况。
在一实施方式中，基于上述表观损伤和渗漏水类的结构安全病害对应的病害参数、变形位移检测模块采集该变形位移类结构安全病害对应的病害参数、当前隧道的隧道信息、隐蔽危害类结构安全病害的病害参数、当前隧道的隧道基本信息以及当前隧道的具体病害情况，确定当前隧道实际存在的结构安全病害。
步骤S30，基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
在一具体实施例中，通过上述隧道检测子***中的表观损伤和渗漏水检测模块、变形位移检测模块、隐蔽危害检测模块、辅助检测模块以及无人机细查模块采集到的当前隧道中的隧道病害信息进行信息融合，并通过中央控制器获取实现信息融合后的多维度监测信息。
在一实施方式中，通过中央控制器获取实现信息融合后的多维度监测信息的方式可以是通过中央控制器根据多维度监测信息对当前隧道的隧道信息进行信息融合，具体地，通过将经过多源异构融合处理的多维度监测信息输入到对应的识别诊断算法。
在一具体实施例中，通过上述报告输出子***将结构安全病害进行解决方案匹配，确定对应的解决方案，其中，确定对应的解决方案的方式可以是通过历史大数据根据该结构安全病害进行匹配，查询历史数据中的解决方案；也可以是将当前隧道中结构安全病害对应的隧道病害信息上传至预设的云端精诊平台进行精确诊断，并确定对应的解决方案。
在本实施例通过预设的隧道检测子***采集当前隧道中的隧道病害信息，基于预设的监检测技术群对当前隧道的病害信息进行采集，增加了进行结构安全病害判定的数据源，提升了结构安全病害识别的正确率，提升了结构安全病害识别的精确性，优化对当前隧道进行结构安全检测的检测效果。
在一实施方式中，基于本申请实施例隧道诊断车的控制方法的第一实施例，提出本申请实施例隧道诊断车的控制方法的第二实施例。
隧道诊断车的控制方法的第二实施例与隧道诊断车的控制方法的第一实施例的区别在于，本实施例在步骤S30，“基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告”的细化，参照图4，具体包括：
S31，基于所述多维度监测信息，对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型；
在一实施方式中，所述对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型的步骤，包括：
基于所述多维度监测信息，确定所述结构安全病害对应的病害信息；
根据所述病害信息对所述结构安全病害进行特征提取，确定当前隧道中结构安全病害对应的结构安全病害特征；
根据所述结构安全病害特征，对所述结构安全病害进行分类，并确定所述结构安全病害的病害类型。
S32，若所述结构安全病害为第一预设类型，则对所述第一预设类型的结构安全病害进行解决方案匹配，确定所述第一预设类型的结构安全病害对应的初诊报告；
S33，若所述结构安全病害为第二预设类型，则将所述第二预设类型的结构安全病害对应的结构安全病害信息上传至预设的云端精诊平台；
S34，基于所述云端精诊平台，对所述第二预设类型的结构安全病害进行精确病害分析，确定所述第二预设类型的结构安全病害对应的精诊评估报告以及管养建议。
在一具体实施例中，通过上述隧道检测子***中的表观损伤和渗漏水检测模块、变形位移检测模块、隐蔽危害检测模块、辅助检测模块以及无人机细查模块采集到的当前隧道中的隧道病害信息进行信息融合，并通过中央控制器获取实现信息融合后的多维度监测信息，根据该多维度监测信息，对当前隧道中存在的结构安全病害进行前端初诊，确定上述结构安全病害病害类型。
在一实施方式中，上述通过中央控制器根据多维度监测信息对当前隧道的结构安全病害进行前端初诊的方式可以是通过将经过多源异构融合处理的多维度监测信息输入到对应的识别诊断算法，先根据上述多维度监测信息识别出当前隧道中存在的结构安全病害，再根据识别诊断算法中的历史诊断数据对上述结构安全病害进行前端初步诊断。
在一实施方式中，根据上述中央控制器的识别诊断算法确定的当前隧道中存在的结构安全病害进行特征提取，确定对应的结构安全病害特征，并根据上述结构安全病害特征对该结构安全病害进行分类，确定该结构安全病害的病害类型。
在一实施方式中，上述确定结构安全病害的病害类型的方式可以是通过互补性的特征提取，对各个***采集到的特征进行多元特征融合，在将融合后的多元特征进行向量堆栈，并从中提取统一病害的特征参数，根据该特征参数确定该结构安全病害的病害类型。
在一具体实施例中，若当前隧道中存在的结构安全病害的病害类型为第一预设类型，即当前隧道中存在的结构安全病害的危害程度达到预设标准，若不及时处理该结构安全病害则会造成致命危害，即该结构安全病害为致命危害，则需要将该第一预设类型的致命危害通过隧道诊断车中央控制***的中央控制器进行初步诊断，根据该结构安全病害的病害类型以及病害参数进行解决方案匹配，确定对应的解决方案，及时避免致命危害。
在一实施方式中，上述将该第一预设类型的结构安全病害进行解决方案匹配，确定对应的解决方案，上述确定对应的解决方案的方式可以是通过历史大数据根据该结构安全病害进行匹配，查询历史数据中的解决方案，并基于该解决方案进行实时报警以及结构安全病害警报。
在一具体实施例中，若当前隧道中存在的结构安全病害的病害类型为第二预设类型，即当前隧道中存在的结构安全病害的危害程度并未达到预设标准，在问题出现后不及时处理该结构安全病害也不会造成致命危害，即该结构安全病害为非致命危害，则需要将该第二预设类型的非致命危害以及对应的病害参数上传至云端精诊平台，通过上述云端精诊平台根据该第二预设类型的非致命危害对应的病害参数基于云端大数据进行精确病害分析，确定第二预设类型的非致命危害的结构安全病害精确病害，基于该结构安全病害精确病害，生成对应的评估报告以及管养建议。
在一实施方式中，上述通过云端精诊平台根据该第二预设类型的非致命危害对应的病害参数进行精确病害分析的方式可以是，通过获取隧道诊断车中央控制***中的隧道检测子***所采集的隧道病害信息，对上述第二预设类型的非致命危害进行危害推测，确定该第二预设类型的非致命危害随着时间的推移会出现的结构安全病害变化，并根据其对应的结构安全病害变化生成对应的评估报告，并根据该评估报告通过上述云端精诊平台进行历史大数据匹配，确定对应的管养建议。
本实施例通过多种检测方式获取当前隧道的隧道信息，增加了结构安全检测的信息来源，提高了进行结构安全检测的结构安全信息的可靠性，通过对结构安全病害进行前端诊断以及病害类型分类，对当前隧道的结构安全病害进行细化，提高结构安全检测的针对性，通过云端精诊平台实现根据结构安全病害匹配解决方案，优化对当前隧道进行结构安全检测的检测效果。
此外，本申请实施例还提出一种隧道诊断车中央控制***，参照图5，图5为本申请隧道诊断车中央控制方法实施例方案涉及的隧道诊断车中央控制***的功能模块示意图。如图5所示，所述隧道诊断车中央控制***包括：
时空同步子***10，用于所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
隧道检测子***20，基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
中央控制器30，用于基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
本实施例实现物流运输的原理及实施过程，请参照上述各实施例，在此不再赘述。
此外，本申请实施例还提出一种设备，所述设备包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的***控制程序，所述***控制程序被所述处理器执行时实现如上述实施例所述的隧道诊断车中央控制方法的步骤。
此外，为实现上述目的，本申请还提供一种介质，所述介质为计算机可读存储介质，所述计算机可读存储介质上存储有***控制程序，所述***控制程序被处理器执行时实现如上所述的隧道诊断车中央控制方法的步骤。
由于本***控制程序被处理器执行时，采用了前述所有实施例的全部技术方案，因此至少具有前述所有实施例的全部技术方案所带来的所有功能，在此不再一一赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者***不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者***所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者***中还存在另外的相同要素。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品储存在如上所述的一个储存介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的可选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书与附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (10)

  1. 一种隧道诊断车中央控制***，其中，所述隧道诊断车中央控制***包括：中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***；
    时空同步子***，用于输出时空同步信号；
    中央控制器基于所述时空同步信号控制所述隧道检测子***执行对当前隧道进行病害检测的工作；
    所述隧道检测子***，用于执行隧道病害检测工作，并将检测的隧道的隧道病害信息反馈至所述中央控制器；
    中央控制器基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
  2. 如权利要求1所述的隧道诊断车中央控制***，其中，所述隧道诊断车中央控制***还连接云端精诊平台；
    在所述基于所述多维度监测信息，确定当前隧道的目标结构安全病害之后，还包括：
    云端精诊平台，用于对预设类型的目标结构安全病害进行精确诊断；
    中央控制器基于所述多维度监测信息控制所述云端精诊平台对预设类型的目标结构安全病害进行精确诊断，并对所述目标结构安全病害进行决策规划，生成对应的精确诊断报告。
  3. 如权利要求1所述的隧道诊断车中央控制***，其中，所述隧道检测子***包括：表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽病害检测模块；
    表观损伤和渗漏水检测模块，用于检测当前隧道的损伤裂缝情况；
    变形位移检测模块，用于检测当前隧道的变形位移情况；
    隐蔽病害检测模块，用于检测当前隧道的隐蔽病害；
    中央控制器控制所述隧道检测子***中的表观损伤和渗漏水检测模块、变形位移检测模块以及隐蔽病害检测模块对当前隧道进行检测，并分别获取当前隧道的损伤裂缝情况、变形位移情况和隐蔽病害。
  4. 如权利要求1所述的隧道诊断车中央控制***，其中，所述隧道检测子***还包括：辅助检测模块和无人机细查模块；
    辅助检测模块，用于采集当前隧道中的隧道基本信息；
    无人机细查模块，用于对预设的目标位置进行局部细查，并采集所述目标位置的具体病害情况；
    中央控制器控制所述辅助检测模块对当前隧道进行信息采集，获取当前隧道中的隧道基本信息；
    中央控制器控制所述无人机细查模块的预设装置对当前隧道中预设的目标位置进行进行局部细查，采集目标位置的具体病害情况。
  5. 如权利要求1所述的隧道诊断车中央控制***，其中，所述时空同步子***包括：编码器、定位导航模块和数据同步模块；
    编码器，用于生成脉冲信号；
    定位导航模块，用于基于所述脉冲信号对隧道诊断车进行精确定位；
    数据同步模块，用于实现隧道诊断车中央控制***与当前隧道诊断车时空数据同步；
    中央控制器控制所述时空同步子***的编码器生成对应的脉冲信号，并基于所述脉冲信号，控制所述定位导航模块对当前隧道诊断车进行精确定位，获取当前隧道诊断车的时空数据，中央控制器将所述时空数据同步至所述数据同步模块。
  6. 如权利要求1所述的隧道诊断车中央控制***，其中，所述中央控制器包括：信息多维融合模块、前端初诊模块和报告反馈模块；
    信息多维融合模块，用于将所述隧道检测子***获取的隧道病害信息进行多维信息融合，获取当前隧道的多维检测信息；
    前端初诊模块，用于基于所述当前隧道的多维检测信息，对当前隧道进行病害前端初诊，确定当前隧道中的目标结构安全病害；
    报告反馈模块，用于根据所述当前隧道中的目标结构安全病害，生成对应的结构安全病害报告，并将所述结构安全病害报告进行反馈。
  7. 如权利要求1至6所述的隧道诊断车中央控制***，其中，所述中央控制器及与所述中央控制器信号连接的时空同步子***和隧道检测子***基于预设的数据流链路实现数据的传输；
    所述时空同步子***，通过预设的时空同步链路实现与中央控制器的时空同步信号传输；
    所述隧道检测子***，通过预设的***软硬同步链路实现与中央控制器的数据传输。
  8. 一种隧道诊断车中央控制***的控制方法，所述隧道诊断车中央控制***包括：对所述隧道诊断车中央控制***中的各个子***进行集成控制的中央控制器、与所述中央控制器实现电信号连接的时空同步子***、隧道检测子***，其中，所述隧道诊断车中央控制***的控制方法包括：
    所述中央控制器从所述时空同步子***获取控制隧道诊断车进行隧道检测的同步信号；
    基于所述同步信号，所述中央控制器控制所述隧道检测子***对当前隧道进行检测，获取当前隧道的隧道病害信息；
    基于所述隧道病害信息，对所述隧道病害信息进行多维信息融合，获取当前隧道对应的多维度监测信息，并基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告。
  9. 如权利要求8所述的隧道诊断车中央控制***的控制方法，其中，所述基于所述多维度监测信息，确定当前隧道的目标结构安全病害，并输出对应的结构安全病害报告的步骤，包括：
    基于所述多维度监测信息，对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型；
    若所述结构安全病害为第一预设类型，则对所述第一预设类型的结构安全病害进行解决方案匹配，确定所述第一预设类型的结构安全病害对应的初诊报告；
    若所述结构安全病害为第二预设类型，则将所述第二预设类型的结构安全病害对应的结构安全病害信息上传至预设的云端精诊平台；
    基于所述云端精诊平台，对所述第二预设类型的结构安全病害进行精确病害分析，确定所述第二预设类型的结构安全病害对应的精诊评估报告以及管养建议。
  10. 如权利要求9所述的隧道诊断车中央控制***的控制方法，其中，所述对当前隧道中的结构安全病害进行前端初诊，并确定所述当前隧道中的结构安全病害的病害类型的步骤，包括：
    基于所述多维度监测信息，确定所述结构安全病害对应的病害信息；
    根据所述病害信息对所述结构安全病害进行特征提取，确定当前隧道中结构安全病害对应的结构安全病害特征；
    根据所述结构安全病害特征，对所述结构安全病害进行分类，并确定所述结构安全病害的病害类型。
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