Tunnel data processing method and system

Abstract

The embodiment of the invention provides a tunnel data processing method and system, and the method comprises the steps: collecting and obtaining equipment construction data of construction equipment in a tunnel, and tunnel monitoring image data of a construction environment in the tunnel, the equipment construction data comprising track data and working condition data of the construction equipment; converting the equipment construction data and the tunnel monitoring image data into optical signals and transmitting the optical signals to the outside of the tunnel; analyzing the optical signal outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data; and identifying, classifying and analyzing the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data in the tunnel, thereby improving the effective transmission distance and transmission stability of the construction data in the tunnel.

Description

Technical Field

[0001] This application relates to the technical field of data processing. Specifically, it relates to a tunnel data processing method and system. Background Art

[0002] At present, with the booming development of transportation and water conservancy infrastructure construction, tunnel projects are increasingly widely used in fields such as highways, railways, and water conservancy energy storage. A large amount of data is generated during the tunnel construction stage, including the operation data of rock drilling jumbo, the working conditions information of wet concrete spraying machines, the video surveillance data at the construction site, and the environmental monitoring data, etc.

[0003] However, traditional data wireless transmission technology has exposed many drawbacks at the tunnel construction site. Due to the complex geological structure and narrow working space inside the tunnel, signal occlusion and interference are very common. The signal attenuation of conventional wireless transmission methods is severe, resulting in frequent problems such as data packet loss and excessive transmission delay, and it is difficult to meet the data timeliness requirements for real-time monitoring and precise control of equipment during the construction process. For example, rocks and metal structures in the tunnel will cause serious reflection and scattering effects on wireless signals, resulting in disordered signal transmission paths and a significant attenuation of signal strength, so that the effective transmission radius cannot meet the requirements of the spacing between construction equipment at the construction site. In addition, the commonly used 2.4GHz frequency band of wireless technology is extremely vulnerable to electromagnetic interference from many electromechanical devices at the construction site, such as the electromagnetic noise generated during the operation of equipment such as rock drilling jumbo and wet concrete spraying machines, resulting in an increase in the number of error frames of wireless transmission or data packet loss, etc., and it is difficult to ensure the continuity and integrity of key construction equipment data.

[0004] Therefore, how to improve the effective transmission distance and transmission stability of construction data in the tunnel is an urgent problem to be solved. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a tunnel data processing method and system to improve the effective transmission distance and transmission stability of construction data in the tunnel.

[0006] Combined with the first aspect of this application, a tunnel data processing method is provided. The method includes: Collect and obtain the equipment construction data of construction equipment in the tunnel, and the tunnel monitoring image data of the construction environment in the tunnel. The equipment construction data includes the trajectory data and working condition data of the construction equipment; Convert the equipment construction data and the tunnel monitoring image data into optical signals and transmit them outside the tunnel; Parse the optical signal outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data; Perform identification classification and parsing operations on the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data in the tunnel.

[0007] Optionally, the converting the equipment construction data and the tunnel monitoring image data into optical signals and transmitting them outside the tunnel includes: Perform a first conversion process on the equipment construction data and the tunnel monitoring image data to obtain first electrical signals corresponding to the equipment construction data and the tunnel monitoring image data; Perform a second conversion process on the first electrical signals to obtain optical signals corresponding to the equipment construction data and the tunnel monitoring image data; Transmit the optical signals outside the tunnel; The parsing the optical signals outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data includes: Perform a third conversion process on the optical signals to obtain first electrical signals corresponding to the equipment construction data and the tunnel monitoring image data; Perform a fourth conversion process on the first electrical signals to restore and obtain the equipment construction data and the tunnel monitoring image data.

[0008] Optionally, the collecting and obtaining the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel includes: Collect and obtain the initial equipment construction data of the construction equipment in the tunnel and the initial tunnel monitoring image data of the construction environment in the tunnel; Perform a first preprocessing operation on the initial equipment construction data to obtain the equipment construction data, and the first preprocessing operation includes at least one of the following: fault data diagnosis, abnormal data filtering, data packaging; Perform a second preprocessing operation on the initial tunnel monitoring image data to obtain the initial tunnel monitoring image data, and the second preprocessing operation includes at least one of the following: image denoising, image enhancement, image filtering, image compression.

[0009] Optionally, after the collecting and obtaining the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel, it further includes: Determine the spatio-temporal characteristics of the equipment construction data according to the trajectory data in the equipment construction data and the time stamp of the equipment construction data; Determine the spatio-temporal characteristics of the tunnel monitoring image data according to the time stamp of the tunnel monitoring image data and the scene position in the tunnel monitoring image data; Determine the equipment construction data and tunnel monitoring image data that are mutually correlated based on spatio-temporal characteristics according to the spatio-temporal characteristics of the equipment construction data and the spatio-temporal characteristics of the tunnel monitoring image data; Perform associated summarization storage on the equipment construction data and the tunnel monitoring image data according to the equipment construction data and the tunnel monitoring image data that are mutually correlated based on spatio-temporal characteristics.

[0010] Optionally, it further includes: Obtain a remote control instruction related to the construction monitoring data according to the construction monitoring data in the tunnel, where the remote control instruction is used to remotely control a target construction equipment in the tunnel to perform a target construction operation; Convert the remote control instruction into an optical signal corresponding to the remote control instruction and transmit it into the tunnel; Restore the optical signal corresponding to the remote control instruction into the remote control instruction in the tunnel, and control the target construction equipment to perform the target construction operation based on the remote control instruction.

[0011] Optionally, it further includes: Obtain the historical equipment construction data of the construction equipment in the tunnel and the historical tunnel monitoring image data of the construction environment in the tunnel; Convert the historical equipment construction data and the historical tunnel monitoring image data into optical signals and transmit them outside the tunnel; Parse the optical signal outside the tunnel to obtain the historical equipment construction data and the historical tunnel monitoring image data; Restore the historical equipment construction data and the historical tunnel monitoring image data according to the historical equipment construction data, the time stamp of the historical equipment construction data, the historical tunnel monitoring image data, and the time stamp of the historical tunnel monitoring image data, and generate a digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data.

[0012] Optionally, it further includes: Respond to a user's operation to obtain a simulation construction operation instruction; Based on the simulation construction operation instruction, simulate and execute the simulation construction operation instruction in the digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data, and generate simulation construction process data and simulation construction image data; Display or output the simulation construction process data and the simulation construction image data.

[0013] Optionally, after transmitting the optical signal outside the tunnel, it further includes: When receiving the optical signal outside the tunnel, perform a transmission integrity check on the optical signal to generate an optical signal check result; Extract the data packet sequence number set and check code set carried in the optical signal; Compare the data packet sequence number set with a pre-generated standard transmission sequence template to identify the characteristic information of the missing data packets; Perform data integrity verification on the completely received data packets according to the check code set to generate a data packet check result; When the optical signal check result indicates that there are missing data packets or data corruption, generate an optical signal retransmission request containing the characteristic information of the missing data packets; Convert the optical signal retransmission request into a retransmission instruction optical signal and send it to the equipment inside the tunnel; Receive the optical signal retransmitted according to the optical signal retransmission request, and perform secondary integrity check on the retransmitted optical signal until the preset transmission integrity threshold is met.

[0014] Optionally, after performing the first preprocessing operation on the initial equipment construction data, it further includes: Perform a data validity verification operation on the equipment construction data that has completed the first preprocessing operation to generate an equipment construction data verification result; Compare the equipment construction data verification result with the original check code of the initial equipment construction data to generate a data integrity comparison result; When the data integrity comparison result indicates that the equipment construction data meets the preset data integrity condition, store the equipment construction data in the tunnel local cache queue; When the data integrity comparison result indicates that the equipment construction data does not meet the preset data integrity condition, generate a data missing feature set, and the data missing feature set includes the timestamp field of the missing data and the equipment identification field corresponding to the missing data; Send a data re-collection instruction to the corresponding construction equipment according to the data missing feature set to trigger the re-collection of the initial equipment construction data; The data validity verification operation includes a three-level verification process of data field integrity check, data timestamp continuity verification, and data value range compliance detection.

[0015] Combined with the second aspect of the present application, a tunnel data processing system is provided. The tunnel data processing system includes a machine-readable storage medium and a processor. The machine-readable storage medium stores machine-executable instructions. When the processor executes the machine-executable instructions, the tunnel data processing system implements the foregoing tunnel data processing method.

[0016] In combination with the third aspect of the present application, there is provided a computer-readable storage medium storing computer-executable instructions, which when executed, implement the foregoing tunnel data processing method.

[0017] In combination with the fourth aspect of the present application, there is provided a computer program product, which when executed by a processor, implements the foregoing tunnel data processing method.

[0018] In combination with any of the foregoing aspects, by collecting the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel, converting the equipment construction data and the tunnel monitoring image data into optical signals and transmitting them outside the tunnel. Parsing the optical signals outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data, and performing identification classification and parsing operations on the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data in the tunnel. Thus, by converting the construction-related data in the tunnel into optical signals with a longer effective transmission distance and stronger transmission stability for transmission inside and outside the tunnel, the effective transmission distance and transmission stability of the construction data in the tunnel are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained in combination with these drawings without creative efforts.

[0020] Figure 1 Schematic flowchart of a tunnel data processing method provided by an embodiment of the present application Figure 2 Schematic flowchart of another tunnel data processing method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0022] In the description, claims and the above drawings of the present invention, terms such as "first", "second", etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal comprising a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or terminals.

[0023] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0024] Figure 1 The flowchart of a tunnel data processing method provided for an embodiment of the present application should be understood that in other embodiments, the order of some steps of the tunnel data processing method in this embodiment can be shared according to actual needs, or some of the steps can be omitted or maintained. The details of the tunnel data processing method include: S101. Collect and obtain the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel.

[0025] Among them, the equipment construction data includes the trajectory data and working condition data of the construction equipment. The equipment construction data refers to the data generated by the construction equipment in the tunnel during operation, reflecting the operation state and working conditions in the tunnel. The trajectory data describes the information of the spatial position of the construction equipment in the tunnel changing with time, such as the longitude, latitude, elevation and other coordinate information of the shield machine at different times during the tunnel excavation process. The working condition data reflects various parameters of the working state of the construction equipment, such as the propulsion speed, cutter head torque, and jack pressure of the shield machine.

[0026] The tunnel monitoring image data can be collected by devices such as cameras installed in the tunnel, and is image information reflecting the construction environment in the tunnel, such as the excavation surface condition in the tunnel, the working state of construction workers, and the running position of construction equipment.

[0027] In this step, various sensors can be installed on the construction equipment in the tunnel to collect equipment construction data. For example, a GPS positioning sensor can be installed to obtain trajectory data, and pressure sensors, speed sensors, etc. can be installed to obtain working condition data. Alternatively, motion acquisition sensors can be added at the positions of the respective moving joints of the construction equipment, and the motion trajectory, working condition data, etc. of the construction equipment can be detected through the respective sensors.

[0028] Exemplarily, taking the construction equipment as a shield machine, torque sensors, rotational speed sensors, inclination sensors, etc. can be installed on the rotating joints of the shield machine (such as the edge of the cutter head and the main drive bearing seat), a displacement sensor (for controlling the tunneling distance of the shield machine by measuring the telescopic amount of the cylinder) and a pressure sensor (for monitoring the cylinder pressure to judge the propulsion resistance), etc. can be installed on the telescopic joint (such as the connection between the propulsion cylinder and the piston rod), an angle sensor can be installed on the swing joint (such as the hinge between the front shield and the middle shield of the shield machine) to determine the turning radius of the shield machine, and a rotational speed sensor can be installed on the walking joint (such as the crawler drive wheel) to monitor the crawler rotational speed to determine the traveling speed, etc.

[0029] Meanwhile, cameras can be installed at appropriate positions in the tunnel, such as the tunnel top, side walls, etc., or a mobile communication monitoring trolley can be added in the tunnel, and several groups of pan-tilt cameras can be installed to monitor the tunnel construction environment through the cameras to collect tunnel monitoring image data of the construction environment in the tunnel.

[0030] The equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel can be automatically collected at a preset time interval, or can be collected in response to a received data collection instruction, etc.

[0031] S102. Convert the equipment construction data and the tunnel monitoring image data into optical signals and transmit them outside the tunnel.

[0032] Among them, an optical signal refers to a signal that uses light as a carrier and carries information through parameter changes such as the intensity, frequency, and phase of light. In data transmission, optical signals have the advantages of fast transmission speed, strong anti-interference ability, etc.

[0033] In this step, the collected equipment construction data and tunnel monitoring image data can be digitally processed first to convert them into digital signals. Then, an optical emission device is used to convert the digital signals into optical signals. The optical signals are transmitted outside the tunnel through optical transmission media such as optical fibers laid in the tunnel.

[0034] For example, the data to be converted can be input into the laser driver circuit in the form of an electrical signal. The laser driver circuit precisely controls the operating state of the laser according to the input electrical signal, enabling it to emit corresponding optical signals in accordance with the variation law of the electrical signal. For example, the high and low level changes of the electrical signal can correspond to the on and off of the optical signal or different light intensity changes, thereby realizing the optical signal encoding of the data. The laser emits optical signals carrying data information according to the control of the driver circuit, and this optical signal can be injected into the optical fiber for transmission.

[0035] Exemplarily, for instance, the trajectory data and working condition data collected by the shield machine, as well as the tunnel monitoring image data collected by the camera, can first be converted into digital signals through the data processing module. Then, these digital signals are loaded onto the laser beam by the optical emission module and converted into optical signals. Through the optical fiber pre-laid on the sidewall of the tunnel, the optical signals are quickly and stably transmitted to the data receiving center outside the tunnel.

[0036] S103. Parse the optical signal outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data.

[0037] Parsing the optical signal refers to the process of restoring the received optical signal to the original equipment construction data and tunnel monitoring image data, which usually requires the conversion from optical signal to electrical signal and subsequent data processing.

[0038] In this step, an optical receiving device such as a photodetector can be set outside the tunnel to convert the received optical signal into an electrical signal. Then, the electrical signal is decoded, filtered, etc. to remove noise and interference, and the original equipment construction data and tunnel monitoring image data are restored.

[0039] S104. Perform identification classification and parsing operations on the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data inside the tunnel.

[0040] Among them, identification classification means dividing the equipment construction data and the tunnel monitoring image data into different categories according to the characteristics and attributes of the data. For example, the trajectory data and the working condition data are classified separately, and the tunnel monitoring image data is classified according to different scenarios.

[0041] The parsing operation refers to deeply analyzing and processing the classified data to extract valuable information. For example, analyzing whether the operating state of the equipment is normal from the working condition data, and identifying whether the operations of the construction workers are standardized from the tunnel monitoring image data.

[0042] The construction monitoring data refers to the comprehensive data that can reflect the overall construction situation inside the tunnel after identification classification and parsing operations, and can be used for construction management and decision-making.

[0043] In this step, data analysis algorithms and image recognition technologies can be used to process the equipment construction data and tunnel monitoring image data. For the equipment construction data, methods such as statistical analysis and machine learning can be adopted for identification classification and analysis. For example, by judging the threshold of the working condition data, it can be identified whether the equipment has a fault. For the tunnel monitoring image data, computer vision algorithms can be used for image recognition and analysis. For example, it can be identified whether the construction workers in the image wear safety equipment. Finally, the processed data is integrated into construction monitoring data and output, which can be displayed in the form of a display screen, report, etc.

[0044] The method provided by the embodiment of the present application acquires the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel, and converts the equipment construction data and the tunnel monitoring image data into optical signals for transmission outside the tunnel. The optical signals are analyzed outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data, and identification classification and analysis operations are performed on the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data in the tunnel. Therefore, by converting the construction-related data in the tunnel into optical signals with a longer effective transmission distance and stronger transmission stability for transmission inside and outside the tunnel, the effective transmission distance and transmission stability of the construction data in the tunnel are improved.

[0045] Next, a detailed introduction will be given on how to specifically convert the equipment construction data and the tunnel monitoring image data into optical signals for transmission outside the tunnel in the foregoing step S102. The foregoing step S102 can be implemented through the following sub-steps: S1021. Perform a first conversion process on the equipment construction data and the tunnel monitoring image data to obtain first electrical signals corresponding to the equipment construction data and the tunnel monitoring image data.

[0046] The first conversion process refers to the process of converting the original data forms of the collected equipment construction data and tunnel monitoring image data into electrical signals. Electrical signals usually have certain voltage and current change rules, which are convenient for subsequent processing and transmission.

[0047] The first electrical signals are the electrical signals obtained after the first conversion process, which carry the information of the equipment construction data and the tunnel monitoring image data.

[0048] Specifically, an analog-to-digital converter can be used to complete the first conversion process. The trajectory data and working condition data in the equipment construction data are generally analog signals. For example, the analog voltage signal output by a pressure sensor is proportional to the pressure working condition of the equipment; the analog current signal output by a temperature sensor reflects the temperature situation of the equipment. For these analog equipment construction data, they are converted into digital electrical signals through an analog-to-digital converter.

[0049] For tunnel monitoring image data, the images captured by the camera enter the camera internally in the form of optical signals. The image sensor inside the camera can convert the optical signals into analog electrical signals, which are then converted into digital electrical signals by an analog-to-digital converter.

[0050] Exemplarily, assume that in a highway tunnel construction, the range of the analog voltage signal output by the pressure sensor on the shield machine is 0 - 5V, corresponding to different pressure values of the shield machine jacks. This analog voltage signal is converted into a digital electrical signal by a 12-bit analog-to-digital converter. The digital electrical signal is represented in binary form, with a range of 0 - 4095, thus converting the equipment construction data collected by the pressure sensor into a digital electrical signal. At the same time, after the high-definition camera installed in the tunnel captures an image, it first converts the optical signal into an analog electrical signal inside the camera, and then into a digital electrical signal through an analog-to-digital converter. These digital electrical signals constitute the first electrical signal corresponding to the tunnel monitoring image data.

[0051] S1022. Perform a second conversion process on the first electrical signal to obtain an optical signal corresponding to the equipment construction data and the tunnel monitoring image data.

[0052] The second conversion process refers to the process of converting the first electrical signal into an optical signal, which can usually be achieved by means of optical modulation technology. An optical signal is a signal that uses light as a carrier and carries information through changes in parameters such as the intensity, frequency, and phase of light.

[0053] Specifically, an optical modulator can be used to complete the second conversion process. Common optical modulation methods include intensity modulation, that is, representing the information of the electrical signal by changing the intensity of light. For example, using a semiconductor laser as the light source, loading the first electrical signal onto the drive current of the laser. When the electrical signal changes, the intensity of the light emitted by the laser also changes accordingly, thus realizing the conversion from an electrical signal to an optical signal.

[0054] For example, the digital electrical signal obtained after the first conversion process can be input into a Mach-Zehnder modulator (MZM). The MZM uses a continuous laser beam as the light source. The digital electrical signal controls the phase of the light wave in the MZM, and through the interference effect, the information of the electrical signal is modulated onto the intensity of the optical signal, and finally an optical signal corresponding to the equipment construction data and the tunnel monitoring image data is output.

[0055] S1023. Transmit the optical signal to the outside of the tunnel.

[0056] Optical signal transmission refers to the process of transmitting optical signals from inside the tunnel to outside the tunnel using an optical transmission medium. The optical transmission medium can effectively reduce the loss of optical signals during transmission, increase the effective transmission distance, and reduce packet loss caused by electromagnetic interference, etc.

[0057] In this step, an optical fiber can be used as the optical transmission medium. Optical fibers have the characteristics of low loss and high bandwidth, and are very suitable for long-distance optical signal transmission. Lay optical fibers inside the tunnel, couple the optical signals into the optical fibers, and transmit the optical signals to the data receiving end outside the tunnel through the optical fibers.

[0058] Alternatively, optical cables with different length specifications can be used to construct the transmission path. First, use a relatively short optical cable that is easy to arrange flexibly, such as a 50m optical cable, to lead out the converted optical signals from the data acquisition point. This optical cable can have good flexibility and mobility, facilitating connection and adjustment in the complex construction environment inside the tunnel. Then, connect this 50m optical cable to a long-distance transmission optical cable, such as a 1200m optical cable, through a quick connection joint. This quick connection joint can achieve quick and stable connection, reducing the loss of optical signals at the connection part. The long-distance transmission optical cable should have the characteristics of low loss and high bandwidth to ensure that optical signals can maintain good transmission quality over a long distance. As the tunnel construction progresses, the long-distance transmission optical cable can be moved and retracted according to the construction progress. When the construction moves forward, release the optical cable to extend the transmission distance; when the construction area changes or needs to be reduced, part of the optical cable can be retracted.

[0059] For example, continuing with the example of urban subway tunnel construction, the converted optical signals can be led out from the data acquisition point near the shield machine through a 50m optical cable. The 50m optical cable is connected to a 1200m portable optical cable through a quick aviation plug. As the shield machine continues to dig forward, the 1200m optical cable can be released synchronously with the construction progress to ensure that optical signals can be continuously and stably transmitted from inside the tunnel to outside the tunnel. If the position of the shield machine needs to be adjusted or the excavation needs to be temporarily stopped during the construction process, part of the 1200m optical cable can be retracted according to the situation to avoid the optical cable piling up or causing obstacles inside the tunnel. Finally, the optical signals are transmitted outside the tunnel through this transmission path composed of optical cables of different lengths for subsequent processing.

[0060] In a possible implementation manner, after transmitting the optical signal to outside the tunnel, the method may further include: When receiving the optical signal outside the tunnel, perform a transmission integrity check on the optical signal to generate an optical signal check result. Extract the set of data packet sequence numbers and the set of check codes carried in the optical signal. Compare the set of data packet sequence numbers with a pre-generated standard transmission sequence template to identify the characteristic information of the missing data packets. Perform a data integrity verification on the completely received data packets according to the set of check codes to generate a data packet check result. When the optical signal check result indicates that there are missing data packets or data corruption, generate an optical signal retransmission request containing the characteristic information of the missing data packets. Convert the optical signal retransmission request into a retransmission instruction optical signal and send it to the equipment inside the tunnel. Receive the optical signal retransmitted according to the optical signal retransmission request, and perform a secondary integrity check on the retransmitted optical signal until the preset transmission integrity threshold is met.

[0061] In this implementation, first, when receiving the optical signal outside the tunnel, its transmission integrity can be checked to generate an optical signal check result. The transmission integrity check is a key operation to check whether the optical signal is complete during transmission and whether there are missing data packets or data corruption. For example, the cyclic redundancy check (CRC) algorithm can be used to implement it. Specifically, the received optical signal can be first converted into an electrical signal through a photodetector, and then the CRC algorithm is used to calculate the check value of the received data and compare it with the original check value carried in the optical signal. If the two are the same, it indicates that the optical signal is transmitted completely; if they are different, it indicates that there may be missing data packets or data corruption. For example, in a certain tunnel construction project, the CRC check value carried by the original optical signal is 0x1234, and the calculated check value is the same as it, and the optical signal check result is that the transmission is complete; if the calculated value is 0x5678, it indicates that there may be a problem.

[0062] Next, extract the set of data packet sequence numbers and the set of check codes carried in the optical signal. After receiving the optical signal and converting it into an electrical signal, extract it according to the pre-set protocol format. For example, if the protocol stipulates that the data packet sequence number is located in the first 4 bytes of the data frame and the check code is located in the last 2 bytes, by parsing the electrical signal, the sequence number and check code of each data packet are extracted respectively to form the corresponding sets. In the above tunnel project, if 3 data packets are received, the set of data packet sequence numbers extracted may be [1, 2, 3], and the set of check codes is [0xABCD, 0xEF01, 0x2345].

[0063] After that, compare the set of data packet sequence numbers with a pre-generated standard transmission sequence template to identify the characteristic information of the missing data packets. The standard transmission sequence template is the standard order of pre-set data packet sequence numbers. By comparing one by one, find the sequence numbers that exist in the standard template but are missing in the set of data packet sequence numbers. These missing sequence numbers are the characteristic information of the missing data packets. For example, if the standard transmission sequence template is [1, 2, 3, 4, 5], and the received set of data packet sequence numbers is [1, 3, 5], then the characteristic information of the missing data packets is sequence numbers 2 and 4.

[0064] Then, perform data integrity verification on the completely received data packets according to the set of check codes to generate data packet check results. Recalculate the check code for the completely received data packet and compare it with the corresponding check code in the set of check codes. If they are the same, it indicates that the data in the data packet is complete; if they are different, it indicates that the data is damaged. In this tunnel project, if the recalculated check code for the data packet with sequence number 1 is 0xABCD, which is the same as the corresponding value in the set, its check result is that the data is complete; if the recalculated value for sequence number 3 is 0x6789, which is different from 0xEF01 in the set, then the data in this data packet is damaged.

[0065] When the optical signal check result indicates that there are missing data packets or data damage, an optical signal retransmission request containing the characteristic information of the missing data packets needs to be generated. Package the characteristic information such as the sequence numbers of the missing data packets in a certain format and add necessary information such as a request identifier to form a request. For example, in this project, if the data packets with sequence numbers 2 and 4 are missing, package them with the request identifier "RETRANSMIT" to form an optical signal retransmission request.

[0066] Subsequently, convert the optical signal retransmission request into a retransmission instruction optical signal and send it to the equipment in the tunnel. Use an optical modulator, such as a Mach-Zehnder modulator, to input the optical signal retransmission request in the form of an electrical signal. The modulator loads the electrical signal onto a laser beam to generate a retransmission instruction optical signal, which is sent through the optical fiber laid in the tunnel.

[0067] Finally, receive the optical signal retransmitted according to the optical signal retransmission request and perform secondary integrity verification on it until the preset transmission integrity threshold is met. Use the same verification method as the first time. If the secondary verification result shows that the transmission integrity of the optical signal meets the preset threshold (such as the data packet integrity rate reaches 100%), it is considered that the optical signal transmission is successful; otherwise, continue to send the optical signal retransmission request until the requirement is met. In this tunnel project, if the retransmitted optical signal still does not meet the preset threshold, continuously repeat the above request retransmission and verification process to ensure that the final optical signal is accurately and completely transmitted.

[0068] In a possible implementation, after performing a secondary integrity check on the retransmitted optical signal until the preset transmission integrity threshold is met, the number of optical signal retransmissions can also be counted and a transmission quality evaluation index can be generated. Among them, the transmission quality evaluation index can include, for example, the number of optical signal retransmissions and the transmission path stability index. The transmission path stability index can be reflected, for example, by monitoring the changes in the signal attenuation coefficient and the data packet loss rate of the alternative transmission path (after switching paths when the number of retransmissions exceeds the threshold). The signal attenuation coefficient reflects the intensity loss of the signal during transmission, and the data packet loss rate reflects the proportion of data lost during transmission.

[0069] The signal attenuation coefficient can be obtained by installing special monitoring devices (such as optical power meters, optical time domain reflectometers, etc.) at key nodes of the transmission path. The monitoring devices can measure the intensity of the signal in real time and calculate the signal attenuation coefficient based on the difference between the input and output signal intensities.

[0070] The data packet loss rate can be calculated by marking each sent data packet during data transmission and counting the number of received data packets at the receiving end. By comparing the number of data packets sent by the sending end and the number of data packets received by the receiving end, the data packet loss rate can be calculated. For example, if the sending end sends 1000 data packets and the receiving end only receives 950, then the data packet loss rate is (1000 - 950) / 1000 = 5%.

[0071] When the number of optical signal retransmissions exceeds the preset retransmission threshold (which can be set according to actual needs and is not limited in this application), a transmission path optimization strategy is initiated. Among them, the transmission path optimization strategy can include the following steps: a. Detect the path characteristic parameters of the currently used optical signal transmission path.

[0072] Among them, the path characteristic parameters can include, for example, the signal attenuation coefficient that reflects the intensity loss of the optical signal during transmission (the larger the attenuation coefficient, the faster the signal intensity drops, resulting in a decrease in the signal quality at the receiving end and affecting communication reliability), and the data packet loss rate that represents the proportion of lost data packets in the total sent data packets, etc.

[0073] Specifically, an optical power meter or an optical time domain reflectometer (OTDR) can be used to measure the optical power at the sending end and the receiving end of the optical signal on the transmission path, and the signal attenuation coefficient can be obtained by calculating the difference between the two. The packet loss rate can be calculated by setting monitoring points, capturing and analyzing the data packets on the transmission path, and counting the number of sent and received data packets.

[0074] b. Select the alternative transmission path with the optimal channel quality from the set of alternative transmission paths.

[0075] For each path in the set of backup transmission paths, measure its path characteristic parameters using the same method as in step a. According to the preset evaluation criteria (such as the minimum signal attenuation coefficient, the lowest data packet loss rate, the minimum delay, etc.), select the path with the best channel quality from the backup paths as the alternative transmission path.

[0076] In this step, specifically, multiple optical fiber sensor nodes can be arranged in the tunnel to collect the optical signal intensity data of each transmission path in real time. A transmission path quality evaluation matrix is constructed, and the matrix includes the real-time signal intensity, historical interruption times, and current load rate of each path. Based on the transmission path quality evaluation matrix, calculate the priority scores of each path, and dynamically adjust the priority ranking of the optical signal transmission path according to the priority scores to determine the alternative transmission path with the best channel quality.

[0077] Among them, the optical fiber sensor nodes are used to collect the optical signal intensity data of each transmission path in real time, and the optical signal intensity data can directly reflect the attenuation of the optical signal during the transmission process (for example, in a 10-kilometer-long tunnel, an optical fiber sensor node can be deployed every 500 meters to monitor the intensity of the optical signal in real time through these nodes).

[0078] The transmission path quality evaluation matrix is used to comprehensively evaluate the quality of the transmission path. For example, it can include information such as the real-time signal intensity, historical interruption times, and current load rate of each transmission path. Based on the transmission path quality evaluation matrix, the priority scores of each path can be calculated. The higher the score, the better the channel quality of the path, and the more suitable it is as an alternative transmission path. For example, according to the preset scoring rules, such as adding 1 point for every 1 dBm increase in the real-time signal intensity, adding 2 points for every 1 decrease in the historical interruption times, and adding 1 point for every 10% decrease in the current load rate, score the above three paths.

[0079] Specifically, based on the optical signal intensity data of each backup transmission path collected by the optical fiber sensor nodes, calculate and obtain the historical interruption times and current load rate data of each backup transmission path. Then, based on the optical signal intensity data, historical interruption times, and current load rate data of each backup transmission path, etc., integrate to obtain the transmission path quality evaluation matrix. Then, score each backup transmission path in the transmission path quality evaluation matrix according to the above preset scoring rules, and sort the scoring results. When the current transmission path fails or its quality deteriorates, the alternative transmission path with the best channel quality can be selected according to the sorting results.

[0080] c. Switch the subsequent optical signal transmission to the alternative transmission path.

[0081] d. Monitor the signal attenuation coefficient and data packet loss rate of the alternative transmission path in real time.

[0082] Deploy devices such as optical power meters and network performance analyzers at key nodes of the alternative transmission path to monitor the signal attenuation coefficient and data packet loss rate in real time. According to the monitoring results, dynamically adjust the transmission path or optimization strategy.

[0083] e. When the signal attenuation coefficient exceeds the safety threshold, trigger an alarm for transmission path switching.

[0084] Among them, the safety threshold can be set according to data transmission requirements and transmission path characteristics, and this application does not limit it. When it is monitored that the signal attenuation coefficient exceeds the threshold, it indicates that the performance of the transmission path is poor, and the transmission path can be switched, and the corresponding alarm information is output to prompt the user that the transmission path needs to be switched or has been switched.

[0085] Next, a detailed introduction will be given on how to parse the optical signal outside the tunnel to obtain the device construction data and the tunnel monitoring image data in the foregoing step S103. The foregoing step S103 can be implemented through the following sub-steps: S1031. Perform a third conversion process on the optical signal to obtain a first electrical signal corresponding to the device construction data and the tunnel monitoring image data.

[0086] The third conversion process refers to the process of converting the received optical signal back into an electrical signal, which is usually achieved through a photodetector.

[0087] The first electrical signal means that the first electrical signal here is essentially the same as the first electrical signal obtained in S1021, except that it is restored from the optical signal again after passing through the optical signal transmission.

[0088] Specifically, a photodetector such as a photodiode can be used for the third conversion process. The photodetector can convert the optical signal into a current signal, and then convert the current signal into a voltage signal through a subsequent circuit to obtain the first electrical signal.

[0089] For example, a PIN photodiode is installed as a photodetector in the data receiving center outside the tunnel. When the optical signal transmitted from inside the tunnel irradiates the PIN photodiode, the photodiode generates a current signal proportional to the intensity of the optical signal. This current signal is converted into a voltage signal through a transimpedance amplifier, thereby obtaining the first electrical signal corresponding to the device construction data and the tunnel monitoring image data.

[0090] S1032. Perform a fourth conversion process on the first electrical signal to restore and obtain the device construction data and the tunnel monitoring image data.

[0091] The fourth conversion process refers to the process of decoding, decompressing, etc. the first electrical signal to restore it to the original device construction data and tunnel monitoring image data.

[0092] Specifically, for the equipment construction data, since it has been digitized during the first conversion process, it can be decoded through digital signal processing algorithms to restore the binary digital electrical signals into specific trajectory data and working condition data. For example, using data parsing software, according to the pre-set coding rules, the digital electrical signals are converted into corresponding pressure values, speed values, etc.

[0093] For the tunnel monitoring image data, if operations such as image compression are performed during the first conversion process, decompression and image reconstruction can be carried out to achieve the fourth conversion process. For example, image decoding algorithms such as the JPEG decoding algorithm can be used to restore the compressed digital electrical signals into the original image data.

[0094] Next, a detailed introduction will be given on how to specifically collect and obtain the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel in the foregoing step S101. The foregoing step S101 can be implemented through the following sub-steps: S1011. Collect and obtain the initial equipment construction data of the construction equipment in the tunnel and the initial tunnel monitoring image data of the construction environment in the tunnel.

[0095] In this step, various sensors can be installed on the construction equipment in the tunnel to collect the initial equipment construction data. For example, a GPS positioning sensor is installed to obtain trajectory data, a pressure sensor, a speed sensor, etc. are installed to obtain working condition data, or at the positions of each moving joint of the construction equipment, action acquisition sensors are added, and the movement trajectory, working condition data, etc. of the construction equipment are detected through each sensor.

[0096] Meanwhile, cameras can be installed at appropriate positions in the tunnel, such as the tunnel top, side walls, etc., or a mobile communication monitoring trolley can be added in the tunnel, and several groups of pan-tilt cameras are installed to monitor the tunnel construction environment through the cameras to collect the initial tunnel monitoring image data of the construction environment in the tunnel.

[0097] The initial equipment construction data of the construction equipment in the tunnel and the initial tunnel monitoring image data of the construction environment in the tunnel can be automatically collected at a preset time interval or collected in response to a received data collection instruction, etc.

[0098] S1012. Perform a first preprocessing operation on the initial equipment construction data to obtain the equipment construction data.

[0099] Among them, the first preprocessing operation includes at least one of the following: fault data diagnosis, abnormal data filtering, data packaging.

[0100] Specifically, for fault data diagnosis, an anomaly detection model in machine learning algorithms can be adopted. For example, using a method based on statistical distribution, by calculating the mean and standard deviation of the data, a reasonable threshold range is set. When the data exceeds this threshold range, it is considered that the device may have a fault. Taking the torque data of a shield machine as an example, if the torque value fluctuates within a relatively stable range under normal conditions, when the torque value suddenly exceeds this range significantly at a certain moment, it may indicate that the cutter head of the shield machine has encountered an obstacle or there is a problem with mechanical components.

[0101] Anomaly data filtering can use a moving average filtering algorithm. This algorithm can calculate the average value of the data within a certain time window and use this average value to replace the original data within the window. For example, for the propulsion speed data of a shield machine, individual outliers may occur due to momentary interference of the sensor. Through moving average filtering, these outliers are smoothed out, making the data better reflect the true operating state of the device.

[0102] Data packing can be carried out according to the type and time sequence of the data. For example, the trajectory data and working condition data (such as pressure, temperature, etc.) of the shield machine within the same time period are packed into a data packet, and corresponding timestamps and data identifiers are added to facilitate subsequent transmission and processing.

[0103] Exemplarily, for the initial equipment construction data of the shield machine collected, first, an anomaly detection model can be used to conduct fault diagnosis on the torque data of the cutter head. When it is found that the torque value suddenly increases and exceeds the normal range, the system issues an alarm to indicate that there may be a fault. Then, the moving average filtering algorithm is used for the propulsion speed data of the shield machine to remove the outliers generated due to sensor jitter. Finally, the processed trajectory data, pressure data, speed data, etc. are packed into data packets every 10 minutes. Each data packet has a unique identifier and a corresponding timestamp.

[0104] S1013. Perform a second preprocessing operation on the initial tunnel monitoring image data to obtain the initial tunnel monitoring image data.

[0105] Among them, the second preprocessing operation includes at least one of the following: image denoising, image enhancement, image filtering, and image compression.

[0106] Specifically, median filtering algorithm can be used for image denoising. This algorithm can take the median value of the pixel values in the neighborhood of each pixel point in the image to replace the value of this pixel point, thereby removing random noises such as salt-and-pepper noise. For example, in tunnel monitoring images, due to unstable light or interference of the camera itself, there may be some random white or black noise points in the image. These noise points can be effectively removed through median filtering.

[0107] Image enhancement can adopt the histogram equalization method. This method adjusts the grayscale histogram of the image to make the grayscale distribution of the image more uniform, thereby enhancing the contrast of the image. For example, for an image taken in a relatively dark tunnel environment, the overall contrast is low, and the details in the image can be made clearer through histogram equalization.

[0108] Image filtering can use Gaussian filtering. Gaussian filtering is a linear smoothing filter. It makes the image smoother by performing a convolution operation on the image while retaining the main features of the image. For example, for the edge part in a tunnel surveillance image, Gaussian filtering can smooth the edge to a certain extent and reduce the jaggedness of the edge.

[0109] Image compression can use the JPEG compression algorithm. This algorithm removes redundant information in the image and significantly reduces the data volume of the image while ensuring a certain image quality. For example, for a large-sized tunnel surveillance image captured by a high-definition camera, using the JPEG compression algorithm can compress the image file size to one fraction or even smaller of the original size.

[0110] For example, for the initial tunnel surveillance image data, the median filtering algorithm can be first used to remove the salt-and-pepper noise in the image to make the image clearer. Then, the histogram equalization method is adopted to enhance the contrast of the image, making the construction scene in the tunnel more obvious. Next, Gaussian filtering is used to smooth the image to reduce the noise and jagged edges in the image. Finally, the JPEG compression algorithm is used to compress the processed image, compressing the image file size from several megabytes to several hundred kilobytes, which is convenient for subsequent transmission and storage.

[0111] In a possible implementation manner, after performing the first preprocessing operation on the initial device construction data, the method of the present application may further include: Perform a data validity verification operation on the equipment construction data that has completed the first preprocessing operation to generate an equipment construction data verification result. Compare the equipment construction data verification result with the original check code of the initial equipment construction data to generate a data integrity comparison result. When the data integrity comparison result indicates that the equipment construction data meets the preset data integrity condition, store the equipment construction data in the tunnel local cache queue. When the data integrity comparison result indicates that the equipment construction data does not meet the preset data integrity condition, generate a data missing feature set, which includes the timestamp field of the missing data and the equipment identification field corresponding to the missing data. Send a data re-collection instruction to the corresponding construction equipment according to the data missing feature set to trigger the re-collection of the initial equipment construction data. The data validity verification operation includes a three-level verification process of data field integrity verification, data timestamp continuity verification, and data numerical range compliance detection.

[0112] In this implementation, a data validity verification operation can be performed on the equipment construction data that has completed the first preprocessing operation to generate an equipment construction data verification result. This data validity verification operation includes a three-level verification process of data field integrity verification, data timestamp continuity verification, and data numerical range compliance detection.

[0113] Data field integrity verification means checking whether each field in the equipment construction data is complete and without omission. For example, in subway tunnel construction, the equipment construction data of a shield machine should include trajectory data (such as longitude, latitude, and elevation), working condition data (such as propulsion speed, cutter head torque), etc. If a certain piece of data is missing the propulsion speed field, then the data fails the field integrity check.

[0114] Data timestamp continuity verification is to check whether the timestamps of the data are arranged continuously in a reasonable order. For example, under normal circumstances, the data of a shield machine should be recorded in chronological order. If there are jumps or disorders in the timestamps, such as the timestamp of the previous piece of data is 9 am and the next one becomes 11 am without intermediate data, then it does not meet the timestamp continuity requirement.

[0115] Data numerical range compliance detection is to determine whether the numerical values of the data are within a reasonable range. Taking the cutter head torque of a shield machine as an example, there is a specific range for the cutter head torque during normal operation. If the collected data shows that the cutter head torque far exceeds this range, then the data is non-compliant in terms of the numerical range.

[0116] After completing the data validity verification, the verification result of the equipment construction data can be compared with the original check code of the initial equipment construction data to generate a data integrity comparison result. The original check code is generated during the collection of the initial equipment construction data and is used to verify the integrity of the data. By comparing the verification result with the original check code, it can be determined whether the data has been damaged or lost during the preprocessing process.

[0117] When the data integrity comparison result indicates that the equipment construction data meets the preset data integrity conditions, the equipment construction data can be stored in the tunnel local cache queue. This cache queue can serve as a temporary storage area to facilitate the further processing and transmission of subsequent data. For example, in the monitoring system of subway tunnel construction, the shield machine equipment construction data that meets the integrity conditions is stored in the local cache queue and waits to be transmitted to the server outside the tunnel for analysis.

[0118] When the data integrity comparison result indicates that the equipment construction data does not meet the preset data integrity conditions, a data missing feature set is generated. This set contains the timestamp field of the missing data and the equipment identification field corresponding to the missing data. For example, if it is found that the data of the shield machine is missing from 10:00 am to 10:15 am, the timestamp of this time period and the equipment identification of the shield machine are recorded in the data missing feature set.

[0119] Then, a data re - collection instruction can be sent to the corresponding construction equipment according to the data missing feature set to trigger the re - collection of the initial equipment construction data. In subway tunnel construction, if it is detected that some data of the shield machine is missing, the monitoring system can send a data re - collection instruction to the shield machine according to the equipment identification in the data missing feature set, allowing it to re - collect the initial equipment construction data for the specified time period to ensure the integrity and accuracy of the data and provide a reliable basis for subsequent construction monitoring and decision - making.

[0120] Figure 2 As a schematic flowchart of another tunnel data processing method provided by the embodiment of the present application, after collecting and obtaining the equipment construction data of the construction equipment in the tunnel and the tunnel monitoring image data of the construction environment in the tunnel, the method of the present application may further include the following steps: S201. Determine the spatio - temporal characteristics of the equipment construction data according to the trajectory data in the equipment construction data and the timestamp of the equipment construction data.

[0121] In this step, by analyzing the coordinate information and corresponding timestamps in the trajectory data, parameters such as the position change rate and direction of the device at different time points can be calculated, so as to determine the spatio-temporal characteristics of the device construction data. For example, by calculating the distance and time difference between the trajectory coordinates corresponding to adjacent timestamps, the moving speed of the device can be obtained; by comparing the direction changes of the trajectory coordinates at different time points, the turning situation of the device can be determined.

[0122] For example, assume that in the construction of a railway tunnel, the trajectory data of a shield machine records the coordinate information of its different positions in the tunnel, and each coordinate data is accompanied by a corresponding timestamp. By analyzing this data, it is found that the shield machine moved from the coordinate (X1, Y1, Z1) to the coordinate (X2, Y2, Z2) between 9:00 am and 9:30 am. According to the distance and time difference between these two coordinate points, the average moving speed of the shield machine during this period can be calculated. In addition, by comparing the directions of these two coordinate points, the tunneling direction of the shield machine during this period can be determined, and these speed and direction information constitute the spatio-temporal characteristics of the device construction data during this period.

[0123] S202. Determine the spatio-temporal characteristics of the tunnel monitoring image data according to the timestamp of the tunnel monitoring image data and the scene position in the tunnel monitoring image data.

[0124] Specifically, the scene position information can be first identified from the tunnel monitoring image data. For example, the specific coordinates of the scene in the tunnel can be determined by the tunnel wall markings in the image, the position of the construction equipment, etc. Then, combined with the timestamp of the image data, the state changes of the scene at different times can be determined, so as to obtain the spatio-temporal characteristics of the tunnel monitoring image data.

[0125] For example, assume that in the above-mentioned railway tunnel construction, a series of monitoring images are taken by cameras installed in the tunnel at different times. For an image taken at 2:00 pm, the specific coordinate position of the scene in the tunnel is determined by the position of the shield machine shown in the image and the mileage markings on the tunnel wall. At the same time, by comparing the images taken at adjacent times, it is found that the shield machine has advanced a certain distance between 2:00 pm and 2:15 pm, and the placement of the surrounding construction materials has changed. These scene position information and the state changes at different times constitute the spatio-temporal characteristics of the tunnel monitoring image data.

[0126] S203. Determine the device construction data and tunnel monitoring image data that are mutually correlated based on spatio-temporal characteristics according to the spatio-temporal characteristics of the device construction data and the spatio-temporal characteristics of the tunnel monitoring image data.

[0127] In this step, by comparing the timestamps and spatial location information of the equipment construction data and the tunnel monitoring image data, data at the same or similar time points and the same or similar spatial locations can be found. For example, when the equipment construction data shows that the shield machine is at a certain position in the tunnel at a certain moment, search for tunnel monitoring images taken at the same or a similar moment, and the scene position in the image matches the position of the shield machine. Then, these equipment construction data and tunnel monitoring image data can be considered to be correlated with each other based on spatio-temporal characteristics.

[0128] Specifically, this step can be implemented through the following sub-steps: S2031. Extract the set of timestamps and the set of three-dimensional spatial coordinates in the spatio-temporal characteristics of the equipment construction data.

[0129] The set of timestamps refers to the set of time records corresponding to when the equipment construction data is generated at different moments, and each timestamp precisely identifies the specific moment when the data is generated.

[0130] The set of three-dimensional spatial coordinates refers to the set of position coordinates of the construction equipment in the three-dimensional space recorded in the equipment construction data, usually represented by (x, y, z), which reflects the spatial position of the equipment in the tunnel.

[0131] Specifically, the equipment construction data can be traversed to extract the timestamp information therein to form a set of timestamps, and at the same time, the corresponding three-dimensional spatial coordinate information can be extracted to form a set of three-dimensional spatial coordinates. For example, in the construction of a subway tunnel, the equipment construction data of the shield machine includes its operating status and position information at different times. These data are parsed through program code, and timestamps (such as "2025-04-10 09:00:00", "2025-04-10 09:15:00", etc.) are extracted from each data record to form a set of timestamps; at the same time, the corresponding three-dimensional spatial coordinates (such as (100, 200, 30), (105, 202, 32), etc.) are extracted to form a set of three-dimensional spatial coordinates.

[0132] S2032. Extract the image acquisition time series and the image spatial positioning information in the spatio-temporal characteristics of the tunnel monitoring image data.

[0133] The image spatial positioning information refers to the specific spatial position information of the scene captured by the tunnel monitoring image in the tunnel, which can be determined by landmarks, equipment positions, etc. in the image.

[0134] Specifically, the image acquisition time can be extracted from the metadata of the tunnel monitoring image data and arranged in chronological order to form an image acquisition time series. For the image spatial positioning information, through image recognition technology, characteristic elements in the image (such as the numbers on the tunnel wall, the positions of specific construction equipment, etc.) can be recognized, and combined with the map information of the tunnel to determine the spatial position of the scene captured by the image. For example, in the above subway tunnel construction, by reading the image metadata recorded by the monitoring camera, the image acquisition time (such as "2025-04-10 09:02:00", "2025-04-10 09:18:00", etc.) is extracted to form an image acquisition time series. At the same time, the position of the shield machine in the image and the mileage identification on the tunnel wall are recognized by using the image recognition algorithm to determine the spatial coordinates of the scene captured by the image, forming the image spatial positioning information.

[0135] S2033. Perform dynamic time window alignment processing on the timestamp set and the image acquisition time series to generate a time synchronization feature set.

[0136] Dynamic time window alignment processing means matching and aligning the timestamp set and the image acquisition time series according to a certain time window range to find data pairs within a similar time range.

[0137] The time synchronization feature set refers to the data feature set with time synchronization relationships obtained after dynamic time window alignment processing.

[0138] In this step, a dynamic time window can be set, such as ±5 minutes. For each timestamp in the timestamp set, search for the image acquisition time within the range of ±5 minutes of this timestamp in the image acquisition time series, and record these matching data pairs to form a time synchronization feature set. For example, there is a timestamp "2025-04-10 09:10:00" in the timestamp set of equipment construction data. After searching in the image acquisition time series, it is found that "2025-04-10 09:12:00" is within the range of ±5 minutes of this timestamp. Then these two times form a time synchronization feature pair, and all such feature pairs are summarized to form a time synchronization feature set.

[0139] S2034. Perform spatial grid matching processing on the three-dimensional space coordinate set and the image spatial positioning information to generate a spatial association feature set.

[0140] Spatial grid matching processing means dividing the space in the tunnel into several grids, mapping the three-dimensional space coordinate set and the image spatial positioning information into these grids respectively, and finding data pairs in the same or adjacent grids.

[0141] The spatial correlation feature set refers to a data feature set with spatial correlation relationship obtained after spatial grid matching processing.

[0142] In this step, the space in the tunnel can be divided into grids of uniform size, for example, each grid is 10m×10m×5m. Each coordinate point in the three-dimensional space coordinate set is mapped to the corresponding grid, and the image space positioning information is also mapped to the corresponding grid. For the equipment construction data coordinates and image space positioning information in the same grid or adjacent grids, they are recorded to form a spatial association feature set. For example, there is a coordinate point (102,203,31) in the three-dimensional space coordinate set mapped to grid A, and the coordinate corresponding to the image space positioning information is mapped to the adjacent grid B, then these two data form a spatial association feature pair, and all such feature pairs are aggregated to form a spatial association feature set.

[0143] S2035: Input the time synchronization feature set and the space correlation feature set into a spatiotemporal correlation calculation model to generate a spatiotemporal correlation weight coefficient matrix.

[0144] The spatiotemporal correlation calculation model is a mathematical model used to calculate the degree of correlation between equipment construction data and tunnel monitoring image data in time and space. The spatiotemporal correlation weight coefficient matrix is ​​a matrix output by the spatiotemporal correlation calculation model, and the elements in the matrix represent the spatiotemporal correlation weights between different data pairs.

[0145] In this step, a machine learning algorithm (such as a neural network) can be used to build a spatiotemporal correlation calculation model. The time synchronization feature set and the spatial correlation feature set are used as input. After training and calculation, the model outputs a matrix. The rows and columns of the matrix correspond to the equipment construction data and the tunnel monitoring image data, respectively. Each element in the matrix represents the spatiotemporal correlation weight between the corresponding data pairs. For example, the element (i, j) in the matrix represents the spatiotemporal correlation weight between the i-th equipment construction data and the j-th tunnel monitoring image data.

[0146] S2036. Screening the spatiotemporal correlation weight coefficient matrix based on a preset spatiotemporal correlation threshold to obtain a subset of equipment construction data and a subset of tunnel monitoring image data that meet correlation conditions.

[0147] The preset spatiotemporal correlation threshold is used to determine whether the spatiotemporal correlation between data pairs meets the requirements. The equipment construction data subset is a data set that has a strong spatiotemporal correlation with the tunnel monitoring image data, which is screened from the original equipment construction data. The tunnel monitoring image data subset is a data set that has a strong spatiotemporal correlation with the equipment construction data, which is screened from the original tunnel monitoring image data.

[0148] In this step, a spatio-temporal correlation threshold can be set, such as 0.8. Traverse the spatio-temporal correlation weight coefficient matrix. For the data pairs with element values greater than or equal to 0.8 in the matrix, extract the corresponding equipment construction data and tunnel monitoring image data respectively to form an equipment construction data subset and a tunnel monitoring image data subset. For example, if the value of the element (3,5) in the matrix is 0.9, then the 3rd equipment construction data and the 5th tunnel monitoring image data meet the correlation condition, and they are added to the equipment construction data subset and the tunnel monitoring image data subset respectively.

[0149] S2037. Perform data fusion processing on the equipment construction data subset and the tunnel monitoring image data subset to form a spatio-temporal correlation data group.

[0150] Among them, the spatio-temporal correlation data group includes the correlation relationship between the equipment construction data and the tunnel monitoring image data that are correlated based on spatio-temporal characteristics. Data fusion processing refers to integrating the equipment construction data subset and the tunnel monitoring image data subset and associating the relevant data together. The spatio-temporal correlation data group refers to the data set formed after data fusion processing, which contains the correlation relationship between the equipment construction data and the tunnel monitoring image data.

[0151] Specifically, the equipment construction data subset and the tunnel monitoring image data subset can be combined according to certain rules. For example, the identification information of the corresponding tunnel monitoring image can be added to each equipment construction data record, and the identification information of the corresponding equipment construction data can be added to each tunnel monitoring image record. Store the associated data in a new data structure to form a spatio-temporal correlation data group. For example, for a record in the equipment construction data subset, add the number of the associated tunnel monitoring image; for an image record in the tunnel monitoring image data subset, add the number of the associated equipment construction data, so as to establish the correlation relationship between the equipment construction data and the tunnel monitoring image data and form a spatio-temporal correlation data group.

[0152] S204. Perform associated summary storage on the equipment construction data and the tunnel monitoring image data according to the equipment construction data and the tunnel monitoring image data that are correlated based on spatio-temporal characteristics.

[0153] Specifically, a database can be established to store the associated data in the same data table or record. In the database, different fields can be set to store the relevant information of the equipment construction data and the tunnel monitoring image data, such as time stamp, spatial location, equipment working condition data, image file path, etc. At the same time, a unique identifier can be set for each associated data group to facilitate subsequent management and query.

[0154] Finally, after obtaining the construction monitoring data in the tunnel through the methods of the foregoing embodiments, it is possible to further realize applications such as real-time data monitoring, historical data traceback, and simulation data simulation based on the construction monitoring data in the tunnel. The following will separately introduce in detail the specific implementation methods for realizing these three applications of real-time data monitoring, historical data traceback, and simulation data simulation.

[0155] Real-time data monitoring: Store the construction monitoring data in the tunnel to a local host and / or a cloud server to monitor the construction environment in the tunnel and the operating conditions of construction equipment in real time. According to the construction monitoring data in the tunnel, obtain a remote control command related to the construction monitoring data, where the remote control command is used to remotely control a target construction equipment in the tunnel to perform a target construction operation. Convert the remote control command into an optical signal corresponding to the remote control command and transmit it into the tunnel. In the tunnel, restore the optical signal corresponding to the remote control command to the remote control command, and control the target construction equipment to perform the target construction operation based on the remote control command.

[0156] In this implementation method, first, the construction monitoring data in the tunnel can be stored to a local host and / or a cloud server. Among them, the local host can provide fast data access and processing capabilities, which are suitable for instant data analysis and monitoring. The cloud server, on the other hand, has powerful storage and computing capabilities and can be used for long-term data storage and complex data analysis. By storing the construction monitoring data in both the local host and the cloud server at the same time, it is possible to realize real-time monitoring of the construction environment in the tunnel and the operating conditions of construction equipment. For example, during the construction of a subway tunnel, the construction monitoring data includes information such as the propulsion speed of the shield machine, the cutter head torque, the temperature and humidity in the tunnel, etc. These data are stored in real time on the local monitoring host and the cloud server. Monitoring personnel can view the operating status of the shield machine in real time through the monitoring interface of the local host, and can also monitor through the remote access function of the cloud server anywhere with network access.

[0157] Next, according to the construction monitoring data in the tunnel, obtain a remote control command related to the construction monitoring data. These remote control commands are generated according to the actual situation reflected by the construction monitoring data and are used to remotely control a target construction equipment in the tunnel to perform a target construction operation. For example, when the construction monitoring data shows that the propulsion speed of the shield machine is too fast and may damage the tunnel wall, the monitoring system can generate a remote control command to reduce the propulsion speed according to preset rules. The purpose of this command is to control the shield machine to perform the operation of reducing the propulsion speed to ensure construction safety.

[0158] Then, convert the remote control instruction into an optical signal corresponding to the remote control instruction and transmit it into the tunnel. Since optical signals have advantages such as fast transmission speed and strong anti-interference ability, they are very suitable for transmitting data in complex environments like tunnels. An optical modulator can be used to load the remote control instruction onto an optical carrier in the form of an electrical signal to generate an optical signal. For example, in the above subway tunnel construction, the remote control instruction to reduce the propulsion speed of the shield machine is converted into an optical signal through a Mach-Zehnder modulator and then transmitted through the optical fiber laid in the tunnel to the receiving device in the tunnel.

[0159] Finally, restore the optical signal corresponding to the remote control instruction to the remote control instruction inside the tunnel, and control the target construction equipment to perform the target construction operation based on the remote control instruction. Set up an optical receiving device in the tunnel, such as a photodetector, to convert the received optical signal into an electrical signal, and then through decoding and other processing, restore the original remote control instruction. Then, send the remote control instruction to the control system of the target construction equipment to control the equipment to perform corresponding operations. For example, inside the subway tunnel, after the photodetector receives the optical signal, it converts it into an electrical signal, and through decoding, obtains the remote control instruction to reduce the propulsion speed of the shield machine. This instruction is sent to the control system of the shield machine, and the control system adjusts the propulsion speed of the shield machine according to the instruction, thereby realizing the remote control of the construction equipment and ensuring the safety and smooth progress of tunnel construction.

[0160] Historical data backtracking: Obtain the historical equipment construction data of the construction equipment in the tunnel and the historical tunnel monitoring image data of the construction environment in the tunnel. Convert the historical equipment construction data and the historical tunnel monitoring image data into optical signals and transmit them outside the tunnel. Parse the optical signals outside the tunnel to obtain the historical equipment construction data and the historical tunnel monitoring image data. According to the historical equipment construction data, the timestamp of the historical equipment construction data, the historical tunnel monitoring image data, and the timestamp of the historical tunnel monitoring image data, restore the historical equipment construction data and the historical tunnel monitoring image data to generate a digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data.

[0161] In this implementation, the historical equipment construction data includes the operation information of the construction equipment in different time periods in the past, such as the historical trajectory data of the shield machine, which records its latitude, longitude and elevation at each time, reflecting the route of the shield machine in the tunnel; there are also working condition data, such as propulsion speed, cutter head torque, etc., which can reflect the working status of the shield machine at different construction stages. The historical tunnel monitoring image data is the images taken by the camera installed in the tunnel at different times. These images record the changes in the tunnel construction environment over time, such as the progress of the tunnel excavation surface, the work conditions of the construction personnel, etc. These historical data can be obtained through the data storage device of the construction equipment and the storage device of the monitoring camera. For example, in the construction of a subway tunnel, the control system of the shield machine can regularly store the equipment construction data in its internal hard disk, and the monitoring camera can also store the captured images on the local storage server.

[0162] Next, the acquired historical equipment construction data and historical tunnel monitoring image data are converted into optical signals and transmitted outside the tunnel. Since optical signals have the advantages of fast transmission speed and strong anti-interference ability, they are very suitable for data transmission over long distances and in complex environments. The historical data can be digitized and converted into digital signals suitable for transmission, and then an optical transmission device, such as a laser, is used to load the digital signal onto an optical carrier to realize the conversion of electrical signals to optical signals. The optical signal is then transmitted to the data receiving center outside the tunnel through the optical fiber laid in the tunnel. For example, in the above-mentioned subway tunnel construction, the historical data stored in the shield machine hard disk and the surveillance camera storage server are read out, and after digital processing, they are converted into optical signals using an optical transmission module and transmitted to the monitoring room outside the tunnel through optical fiber.

[0163] Then, the optical signal is analyzed outside the tunnel to obtain historical equipment construction data and historical tunnel monitoring image data. In the data receiving center outside the tunnel, an optical receiving device, such as a photodetector, is used to convert the received optical signal into an electrical signal. The electrical signal is then decoded, filtered, and processed to remove noise and interference that may be generated during the transmission process, and the original historical equipment construction data and historical tunnel monitoring image data are restored. For example, after the photodetector converts the optical signal into an electrical signal, the data processing software decodes and filters the electrical signal to finally obtain complete historical data.

[0164] Finally, based on the historical equipment construction data, the timestamps of the historical equipment construction data, the historical tunnel monitoring image data, and the timestamps of the historical tunnel monitoring image data, these historical data are restored to generate a digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data. The digital twin environment is a virtual reproduction of the tunnel construction process. Through timestamps, the historical equipment construction data and the historical tunnel monitoring image data can be arranged and associated in chronological order. Using these associated data, a virtual environment highly similar to the actual tunnel construction process can be constructed on a computer to reproduce the entire process of tunnel construction. For example, in the digital twin environment of subway tunnel construction, the traveling trajectory and working status of the shield machine can be simulated based on the historical equipment construction data, and at the same time, the construction scenes at different times in the tunnel can be displayed in combination with the historical tunnel monitoring image data, providing an intuitive retrospective of the historical construction process for construction management personnel to better analyze problems in construction and optimize subsequent construction plans.

[0165] Simulation data simulation: In response to the user's operation, obtain the simulation construction operation instruction. Based on the simulation construction operation instruction, simulate and execute the simulation construction operation instruction in the digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data to generate simulation construction process data and simulation construction image data. Display or output the simulation construction process data and the simulation construction image data.

[0166] In the processing and application of tunnel construction data, by using the digital twin environment constructed based on the historical equipment construction data and the historical tunnel monitoring image data, simulation construction can be carried out, providing strong support for construction planning and decision-making.

[0167] In this step, the user operation can be initiated, for example, through an interactive interface. This interactive interface can be a software interface specifically designed for tunnel construction simulation or a module integrated in a large construction management system. Various operation options and input boxes can be provided on the interactive interface to facilitate the user to input or select the required simulation construction operation instructions. For example, on the software interface of a subway tunnel construction simulation, the user can select different construction scenarios through a drop-down menu, such as normal tunneling of the shield machine, handling when encountering obstacles, etc.; or input specific parameters in the input box, such as the propulsion speed of the shield machine, the adjustment value of the cutter head torque, etc. When the user completes the operation and clicks the "Start Simulation" button, the system responds to this operation, extracts the information input by the user from the interface, and organizes it into a simulation construction operation instruction.

[0168] The digital twin environment is a virtual reproduction of the real tunnel construction scenario. It is constructed based on a large amount of historical equipment construction data and historical tunnel monitoring image data, and includes the geographical information of the tunnel, the models of construction equipment, and operation rules, etc. When receiving the simulation construction operation instructions, the system can input these instructions into the simulation engine of the digital twin environment. The simulation engine calculates and deduces according to the instructions and the models and rules in the digital twin environment. For example, if the instruction is to increase the propulsion speed of the shield machine by 10%, the simulation engine calculates the changes in these parameters after increasing the propulsion speed based on the relationship between the propulsion speed of the shield machine and other parameters (such as cutter head torque, jack pressure, etc.) in the historical data. At the same time, the influence of factors such as the geological conditions of the tunnel and the surrounding environment on the construction can also be considered.

[0169] During the process of simulating the execution of the operation instructions, the system can record the changes of various parameters in real time to form the simulation construction process data. These data include the operation parameters of construction equipment (such as the propulsion speed, cutter head rotation speed, torque, etc. of the shield machine), the deformation of the tunnel (such as the displacement, stress, etc. of the tunnel wall), the construction progress, etc. For example, during the process of simulating the increase in the propulsion speed of the shield machine, the system can record the actual propulsion speed of the shield machine, the change value of the cutter head torque, and the displacement data of the tunnel wall at different positions at regular intervals. These data are stored in chronological order to form a complete simulation construction process dataset.

[0170] In addition, in order to more intuitively display the simulation construction process, the system can generate simulation construction image data according to the simulation construction process data. Computer graphics technology can be used to visually render the virtual models and simulation processes in the digital twin environment. For example, through 3D modeling software and rendering engines, the position and attitude of the shield machine at different times, as well as the deformation of the tunnel, can be presented in the form of images. The image can be static, used to display the construction scenario at a specific moment; or it can be a dynamic video, used to continuously display the entire simulation construction process.

[0171] Optionally, the simulation construction process data and the simulation construction image data can be displayed on the interactive interface. For the simulation construction process data, it can be displayed in the form of tables, charts, etc., which is convenient for users to view and analyze. For example, the parameters such as the propulsion speed and cutter head torque of the shield machine are displayed in the form of a line chart, allowing users to intuitively see the change trends of these parameters during the simulation process. For the simulation construction image data, a dedicated area can be opened on the interface to display the image or video. Users can control the video by operating the controls on the interface, such as play, pause, fast forward buttons, etc., in order to carefully observe the details of the simulation construction process.

[0172] In addition to being displayed on the interface, the data of the simulated construction process and the data of the simulated construction images can also be output to other storage devices or files. For example, the data of the simulated construction process can be saved as a CSV file for subsequent in-depth analysis using data analysis software; the data of the simulated construction images can be saved as a video file for purposes such as reporting and training. The user can select the output file format and storage path through the "Export" button on the interface to complete the data output operation.

[0173] Through the above steps, the user can perform simulation of the construction in the digital twin environment, obtain the data of the simulated construction process and the data of the simulated construction images, and perform display and output, providing a strong basis for the planning and decision-making of tunnel construction.

[0174] Next, for the convenience of understanding, an exemplary introduction will be given to implement the above method with a possible tunnel data processing system. Among them, the tunnel data processing system includes: a first data acquisition unit, a second data acquisition unit, a first data processing unit, a second data processing unit, a signal transmission unit, a signal reception unit, a first signal conversion unit, a second signal conversion unit, and a processing unit. In a possible implementation manner, an operation unit and a display unit may also be included.

[0175] Among them, the first data acquisition unit is used to collect and obtain the equipment construction data of the construction equipment in the tunnel; the second data acquisition unit is used to collect the tunnel monitoring image data of the construction environment in the tunnel; the first data processing unit is used to preprocess and store the collected equipment construction data; the second data processing unit is used to preprocess and store the collected tunnel monitoring image data; the first signal conversion unit is used to convert the equipment construction data and the tunnel monitoring image data into optical signals; the signal transmission unit is used to transmit the optical signals outside the tunnel; the signal reception unit is used to receive the optical signals; the second signal conversion unit is used to analyze the optical signals to obtain the equipment construction data and the tunnel monitoring image data; the processing unit is used to perform identification classification and analysis operations on the equipment construction data and the tunnel monitoring image data, obtain and output the construction monitoring data in the tunnel, and based on the construction monitoring data in the tunnel, realize functions such as real-time data monitoring, historical data backtracking, and simulation data simulation.

[0176] The operation unit can include, for example, an operation handle, a touch screen, a button panel, a toggle switch, and a master switch in the control and command center outside the tunnel to provide remote control operation instructions in response to user operations. The display unit can be used to display the real-time construction monitoring data in the tunnel, the digital twin model, etc.

[0177] Optionally, the foregoing first data acquisition unit and second data acquisition unit may be integrated into the same data acquisition unit or may be two different data acquisition units.

[0178] Optionally, the foregoing first data processing unit and second data processing unit may be integrated into the same data processing unit, or may be two different data processing units.

[0179] The tunnel data processing system provided by the embodiments of the present application can execute the tunnel data processing method in the foregoing method embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0180] In the above embodiments, the tunnel data processing system for executing the above method embodiments has at least one processor, a control module (chipset) coupled to at least one of the (at least one) processors, a memory coupled to the control module, a non-volatile memory (NVM) / storage device coupled to the control module, at least one input / output device coupled to the control module, and a network interface coupled to the control module.

[0181] The processor may include at least one single-core or multi-core processor, and the processor may include any combination of general-purpose processors or dedicated processors (such as graphics processors, application processors, baseband processors, etc.). For some alternative embodiments, the tunnel data processing system can be used as tunnel data processing system devices such as the gateway described in the embodiments of the present application.

[0182] For some alternative embodiments, the tunnel data processing system may include at least one computer-readable medium having instructions (e.g., a memory or an NVM / storage device) and at least one processor integrated with the at least one computer-readable medium and configured to execute the instructions to implement modules to perform the actions described in the present disclosure.

[0183] For one embodiment, the control module may include any suitable interface controller to provide any suitable interface to at least one of the (at least one) processors and / or any suitable device or component communicating with the control module.

[0184] The control module may include a memory controller module to provide an interface to the memory. The memory controller module may be a hardware module, a software module, and / or a firmware module.

[0185] The memory may be used, for example, to load and store data and / or instructions for the tunnel data processing system. For one embodiment, the memory may include any suitable volatile memory, such as a suitable DRAM.

[0186] For one embodiment, the control module may include at least one input / output controller to provide an interface to the NVM / storage device and the (at least one) input / output device.

[0187] For example, an NVM / storage device can be used to store data and / or instructions. The NVM / storage device can include any suitable non-volatile memory (e.g., flash memory) and / or can include any suitable (at least one) non-volatile storage device (e.g., at least one hard disk drive (HDD), at least one compact disc (CD) drive, and / or at least one digital versatile disc (DVD) drive).

[0188] The NVM / storage device can include storage resources that are physically part of a device on which a tunnel data processing system is installed, or it can be accessed by the device without necessarily being part of the device. For example, the NVM / storage device can be accessed via (at least one) input / output device according to a network.

[0189] (At least one) input / output device can provide an interface for the tunnel data processing system to communicate with any other suitable device. The input / output device can include communication components, phonetic components, sensor components, etc. The network interface can provide an interface for the tunnel data processing system to communicate according to at least one network. The tunnel data processing system can wirelessly communicate with at least one component of a wireless network according to any standard and / or protocol in at least one wireless network standard and / or protocol, such as accessing a wireless network according to a communication standard.

[0190] For one embodiment, at least one of the (at least one) processors can be logically loaded together with at least one controller of a control module (e.g., a memory controller module). For one embodiment, at least one of the (at least one) processors can be logically loaded together with at least one controller of a control module to form a system-level load. For one embodiment, at least one of the (at least one) processors can be logically integrated with at least one controller of a control module on the same die. For one embodiment, at least one of the (at least one) processors can be logically integrated with at least one controller of a control module on the same die to form a system-on-chip (SoC).

[0191] The embodiments of the present application have been introduced in detail above. Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

[0192] Embodiments of the present invention disclose a computer-readable storage medium that stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the tunnel data processing method described in the foregoing embodiments.

[0193] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the tunnel data processing method described in the foregoing embodiments.

[0194] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0195] Through the above specific descriptions of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other medium that can be used for a computer to have or store data.

[0196] Finally, it should be noted that what is disclosed above is only the preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A tunnel data processing method, characterized in that, Including: Collecting and obtaining the equipment construction data of the construction equipment in the tunnel, and the tunnel monitoring image data of the construction environment in the tunnel, where the equipment construction data includes the trajectory data and working condition data of the construction equipment; Converting the equipment construction data and the tunnel monitoring image data into optical signals and transmitting them outside the tunnel; Analyzing the optical signals outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data; Performing identification classification and analysis operations on the equipment construction data and the tunnel monitoring image data to obtain and output the construction monitoring data in the tunnel.

2. The tunnel data processing method according to claim 1, wherein The converting the equipment construction data and the tunnel monitoring image data into optical signals and transmitting them outside the tunnel includes: Performing a first conversion process on the equipment construction data and the tunnel monitoring image data to obtain first electrical signals corresponding to the equipment construction data and the tunnel monitoring image data; Performing a second conversion process on the first electrical signals to obtain optical signals corresponding to the equipment construction data and the tunnel monitoring image data; Transmitting the optical signals outside the tunnel; The analyzing the optical signals outside the tunnel to obtain the equipment construction data and the tunnel monitoring image data includes: Performing a third conversion process on the optical signals to obtain first electrical signals corresponding to the equipment construction data and the tunnel monitoring image data; Performing a fourth conversion process on the first electrical signals to restore and obtain the equipment construction data and the tunnel monitoring image data.

3. The tunnel data processing method according to claim 2, wherein The collecting and obtaining the equipment construction data of the construction equipment in the tunnel, and the tunnel monitoring image data of the construction environment in the tunnel includes: Collecting and obtaining the initial equipment construction data of the construction equipment in the tunnel, and the initial tunnel monitoring image data of the construction environment in the tunnel; Performing a first preprocessing operation on the initial equipment construction data to obtain the equipment construction data, where the first preprocessing operation includes at least one of the following: fault data diagnosis, abnormal data filtering, data packing; Performing a second preprocessing operation on the initial tunnel monitoring image data to obtain the initial tunnel monitoring image data, where the second preprocessing operation includes at least one of the following: image denoising, image enhancement, image filtering, image compression.

4. The tunnel data processing method according to any one of claims 1-3, characterized in that After the collecting and obtaining the equipment construction data of the construction equipment in the tunnel, and the tunnel monitoring image data of the construction environment in the tunnel, it further includes: Determining the spatio-temporal characteristics of the equipment construction data according to the trajectory data in the equipment construction data and the time stamp of the equipment construction data; Determining the spatio-temporal characteristics of the tunnel monitoring image data according to the time stamp of the tunnel monitoring image data and the scene position in the tunnel monitoring image data; Determining the equipment construction data and the tunnel monitoring image data that are mutually correlated based on spatio-temporal characteristics according to the spatio-temporal characteristics of the equipment construction data and the spatio-temporal characteristics of the tunnel monitoring image data; Performing associated summarization storage on the equipment construction data and the tunnel monitoring image data according to the equipment construction data and the tunnel monitoring image data that are mutually correlated based on spatio-temporal characteristics.

5. The tunnel data processing method according to any one of claims 1-3, characterized in that It also includes: Obtain a remote control instruction related to the construction monitoring data in the tunnel, where the remote control instruction is used to remotely control a target construction device in the tunnel to perform a target construction operation; Convert the remote control instruction into an optical signal corresponding to the remote control instruction and transmit it into the tunnel; Restore the optical signal corresponding to the remote control instruction to the remote control instruction in the tunnel, and control the target construction device to perform the target construction operation based on the remote control instruction.

6. The tunnel data processing method according to any one of claims 1-3, characterized in that Further include: Obtain the historical equipment construction data of the construction equipment in the tunnel and the historical tunnel monitoring image data of the construction environment in the tunnel; Convert the historical equipment construction data and the historical tunnel monitoring image data into optical signals and transmit them outside the tunnel; Analyze the optical signal outside the tunnel to obtain the historical equipment construction data and the historical tunnel monitoring image data; Restore the historical equipment construction data and the historical tunnel monitoring image data according to the historical equipment construction data, the timestamp of the historical equipment construction data, the historical tunnel monitoring image data, and the timestamp of the historical tunnel monitoring image data, and generate a digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data.

7. The tunnel data processing method according to claim 6, wherein Further include: In response to a user's operation, obtain a simulation construction operation instruction; Based on the simulation construction operation instruction, simulate and execute the simulation construction operation instruction in the digital twin environment based on the historical equipment construction data and the historical tunnel monitoring image data, and generate simulation construction process data and simulation construction image data; Display or output the simulation construction process data and the simulation construction image data.

8. The tunnel data processing method according to claim 2, wherein After transmitting the optical signal outside the tunnel, further include: When receiving the optical signal outside the tunnel, perform a transmission integrity check on the optical signal to generate an optical signal check result; Extract the set of data packet sequence numbers and the set of check codes carried in the optical signal; Compare the set of data packet sequence numbers with a pre-generated standard transmission sequence template to identify the characteristic information of the missing data packets; Perform a data integrity verification on the completely received data packets according to the set of check codes to generate a data packet check result; When the optical signal check result indicates that there are missing data packets or data corruption, generate an optical signal retransmission request including the characteristic information of the missing data packets; Convert the optical signal retransmission request into a retransmission instruction optical signal and send it to the equipment in the tunnel; Receive the optical signal retransmitted according to the optical signal retransmission request, and perform a secondary integrity check on the retransmitted optical signal until a preset transmission integrity threshold is met.

9. The tunnel data processing method according to claim 3, characterized in that, After performing the first preprocessing operation on the initial equipment construction data, further include: Perform a data validity verification operation on the equipment construction data after completing the first preprocessing operation to generate an equipment construction data verification result; Compare the equipment construction data verification result with the original check code of the initial equipment construction data to generate a data integrity comparison result; When the data integrity comparison result indicates that the equipment construction data meets the preset data integrity condition, store the equipment construction data in the tunnel local cache queue; When the data integrity comparison result indicates that the equipment construction data does not meet the preset data integrity condition, generate a data missing feature set, which includes a timestamp field of the missing data and an equipment identification field corresponding to the missing data; Send a data re-collection instruction to the corresponding construction equipment according to the data missing feature set, triggering the re-collection of the initial equipment construction data; The data validity verification operation includes a three-level verification process of data field integrity verification, data timestamp continuity verification, and data numerical range compliance detection.

10. A tunnel data processing system, characterized in that, It includes a processor and a computer-readable storage medium, and machine-executable instructions are stored in the computer-readable storage medium. When the machine-executable instructions are executed by a computer, the tunnel data processing method described in any one of claims 1-9 is implemented.

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