Urban rail transit communication informatization monitoring device

Abstract

The invention provides an urban rail transit communication informatization monitoring device which comprises a rail health monitoring module which combines acoustic CT scanning and electromagnetic eddy current detection to generate a steel rail three-dimensional defect image and obtain rail defect data. The electromagnetic environment sensing and monitoring module extracts quantum noise features, establishes an electromagnetic field-signal system coupling model, and predicts interference of quantum noise on the CBTC system. And the communication signal quality monitoring module monitors signal strength abnormity by using a wireless spectrum analysis algorithm. And the data processing center fuses and analyzes various data and generates a monitoring report. And the visualization module displays the report. The integration technology improves the accuracy and reliability of track defect detection, and enhances the support of track maintenance data. The electromagnetic environment sensing and monitoring module improves the anti-interference capability of the communication system. The communication signal quality monitoring improves the monitoring precision and signal integrity verification, and reduces the false alarm rate.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit, and particularly to an urban rail transit communication informatization monitoring device. Background Art

[0002] With the rapid development of urban rail transit systems, the requirements for their operation safety, efficiency, and intelligent level have been significantly improved. However, current monitoring technologies still have many technical bottlenecks in aspects such as track health assessment, electromagnetic environment perception, and communication signal quality analysis, making it difficult to meet the accurate monitoring requirements in complex scenarios.

[0003] Traditional track monitoring methods mostly rely on single technologies, such as ultrasonic testing or eddy current testing, which have obvious limitations. Although ultrasonic testing can detect internal defects in materials, it is insufficiently sensitive to surface cracks; eddy current testing is good at capturing surface defects but difficult to obtain internal damage information. The application of single technologies leads to an incomplete assessment of track defects, with a relatively high risk of missed and false detections. At the same time, existing monitoring systems lack the ability to perform multi-physical field coupling analysis and are difficult to integrate the advantageous data of different detection technologies. Existing communication signal monitoring technologies mostly focus on single-frequency band or signal strength analysis and lack the refined monitoring ability for multi-frequency band co-interference and signal integrity damage. In a complex electromagnetic environment, problems such as signal interference between different frequency bands and signal integrity damage (such as bit errors caused by quantum noise) are becoming increasingly prominent. Traditional monitoring technologies are difficult to comprehensively identify abnormal features and lack quantum enhancement means to verify signal integrity, resulting in a high false alarm rate. Summary of the Invention

[0004] The present invention aims to at least solve the technical problem in the prior art that traditional monitoring technologies are difficult to comprehensively identify abnormal features and lack quantum enhancement means to verify signal integrity, resulting in a high false alarm rate, and particularly innovatively proposes an urban rail transit communication informatization monitoring device.

[0005] To achieve the above object of the present invention, the present invention provides an urban rail transit communication informatization monitoring device, which includes:

[0006] A track health monitoring module, configured to fuse acoustic CT scanning and electromagnetic eddy current detection to construct a three-dimensional defect image of the rail, and obtain track defect data based on the three-dimensional defect image of the rail;

[0007] An electromagnetic environment perception monitoring module, configured to extract quantum noise characteristics and establish an electromagnetic field-signal system coupling model, and predict the interference data of the quantum noise characteristics on the CBTC system based on the above electromagnetic field-signal system coupling model;

[0008] A communication signal quality monitoring module, configured to use a wireless spectrum analysis algorithm to monitor the signal strength abnormal data within the communication frequency band;

[0009] A data processing center, connected to the track health monitoring module, the electromagnetic environment perception monitoring module, and the communication signal quality monitoring module, is used to fuse and analyze track defect data, interference data, and signal strength anomaly data, and generate a monitoring report on the informatization of urban rail transit communication;

[0010] A visualization module, connected to the data processing center, is used to visually display the monitoring report on the informatization of urban rail transit communication.

[0011] As an alternative embodiment of the present invention, optionally, the communication signal quality monitoring module includes:

[0012] A multi-band collaborative monitoring unit, used to monitor the signal quality within different communication bands;

[0013] A quantum-enhanced monitoring unit, used to inject entangled photons at the receiving end to verify the integrity of the signal;

[0014] A spectrum analysis unit, connected to the multi-band collaborative monitoring unit and the quantum-enhanced monitoring unit, is used to identify the signal quality within different communication bands and the integrity of the signal, analyze the abnormal characteristics in the signal, and obtain signal strength anomaly data within the communication band.

[0015] As an alternative embodiment of the present invention, optionally, the multi-band collaborative monitoring unit includes:

[0016] An ultra-wideband receiver array, which uses a multi-channel ADC to synchronously collect signals in different bands;

[0017] A spectrum sensing engine, connected to the ultra-wideband receiver array, is used to extract the spectrum characteristics of signals in different bands;

[0018] A stitching network, connected to the spectrum sensing engine, is used to stitch the spectrum characteristics extracted from different bands to obtain a spectrum characteristic map;

[0019] An analysis network, connected to the stitching network, is used to analyze the co-channel interference situation between bands according to the spectrum characteristic map and obtain the signal quality within different communication bands.

[0020] As an alternative embodiment of the present invention, optionally, the quantum-enhanced monitoring unit includes:

[0021] A quantum probe, used to inject entangled photons at the receiving end;

[0022] A quantum channel encoder, connected to the quantum probe, is used to encode the entangled photons injected by the quantum probe and map them to the target band;

[0023] A single-photon detector array, connected to the quantum channel encoder, for detecting entangled photons within a target frequency band and obtaining the fidelity of the entangled photons;

[0024] A quantum state tomography instrument, connected to the single-photon detector array, for verifying the integrity of a signal based on the fidelity of the entangled photons. If the fidelity of the entangled photons is lower than a preset threshold, it is determined that the signal integrity is impaired.

[0025] As an optional embodiment of the present invention, optionally, the track health monitoring module includes:

[0026] An acoustic CT scanning unit for acquiring tomographic images of defects in the rail using acoustic waves;

[0027] An electromagnetic eddy current detection unit for acquiring data on surface cracks in the rail using an alternating magnetic field;

[0028] A physical field coupling unit, connected to the acoustic CT scanning unit and the electromagnetic eddy current detection unit, for performing spatio-temporal synchronous physical field coupling on the tomographic image data obtained by the acoustic CT scanning unit and the crack data obtained by the electromagnetic eddy current detection unit to obtain a three-dimensional defect image of the rail;

[0029] A defect identification unit, connected to the physical field coupling unit, for identifying and analyzing defect features in the three-dimensional defect image of the rail and generating track defect data based on the defect features.

[0030] As an optional embodiment of the present invention, optionally, the electromagnetic environment perception and monitoring module includes:

[0031] A quantum noise acquisition unit for acquiring quantum noise;

[0032] A quantum noise feature extraction unit, connected to the quantum noise acquisition unit, for extracting feature information of the quantum noise;

[0033] An electromagnetic field simulation unit, connected to the quantum noise feature extraction unit, for constructing an electromagnetic field model based on the extracted quantum noise feature information and simulating the influence of the quantum noise on the electromagnetic field;

[0034] A signal system coupling unit, connected to the electromagnetic field simulation unit, for coupling the electromagnetic field model with the signal system to construct an electromagnetic field-signal system coupling model and predicting interference data of the quantum noise feature on the communication-based train CBTC system.

[0035] Advantages of the present invention: By integrating acoustic CT scanning and electromagnetic eddy current detection technologies, the present invention realizes a comprehensive assessment of track defects, significantly improving the accuracy and reliability of defect detection. The acoustic CT scanning technology can penetrate deep into the material interior to capture tiny defects that are difficult to detect by traditional ultrasonic testing, while electromagnetic eddy current detection is highly sensitive to surface cracks and minor damages. The combination of the two enables the track health monitoring module to generate high-precision three-dimensional defect images, providing strong data support for track maintenance. In addition, the electromagnetic environment perception and monitoring module in the present invention can accurately predict the interference of quantum noise on the CBTC system by extracting quantum noise characteristics and constructing an electromagnetic field-signal system coupling model. This improves the anti-interference ability of the communication system. In terms of communication signal quality monitoring, the present invention uses a wireless spectrum analysis algorithm to achieve real-time monitoring of signal strength within the communication frequency band and rapid identification of abnormal data. The introduction of the multi-band collaborative monitoring unit and the quantum-enhanced monitoring unit further improves the monitoring accuracy and signal integrity verification ability of the system, reducing the false alarm rate.

[0036] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0038] Figure 1 is a schematic structural diagram of an urban rail transit communication informatization monitoring device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0040] As Figure 1 shown, an urban rail transit communication informatization monitoring device, the device includes:

[0041] A track health monitoring module, configured to fuse acoustic CT scanning and electromagnetic eddy current detection, construct a three-dimensional defect image of the rail, and obtain track defect data based on the three-dimensional defect image of the rail;

[0042] It should be noted that the track health monitoring module includes an acoustic CT scanning unit and an electromagnetic eddy current detection unit to ensure accurate data acquisition and processing. The acoustic CT scanning unit can penetrate into the interior of the rail through high-precision acoustic wave transmitting and receiving devices, capture minute defect information, and form high-resolution tomographic images. The electromagnetic eddy current detection unit, on the other hand, uses an alternating magnetic field to induce eddy currents on the surface of the rail and identifies surface cracks and minute damages by detecting changes in the eddy currents, featuring high sensitivity and accuracy. The data from these two units are synchronously processed in terms of time and space through a physical field coupling unit, achieving in-depth fusion of defect information and thus constructing a high-precision three-dimensional defect image of the rail. This improves the comprehensiveness of track defect detection.

[0043] The electromagnetic environment perception and monitoring module is used to extract quantum noise characteristics and establish an electromagnetic field-signal system coupling model, and predict the interference data of the quantum noise characteristics on the CBTC system based on the above electromagnetic field-signal system coupling model;

[0044] It should be noted that the electromagnetic environment perception and monitoring module includes a quantum noise acquisition unit, a quantum noise characteristic extraction unit, an electromagnetic field simulation unit, and a signal system coupling unit. These units work together to achieve accurate extraction of quantum noise characteristics and comprehensive perception of the electromagnetic environment. The quantum noise acquisition unit is responsible for capturing quantum noise signals in the environment. The quantum noise characteristic extraction unit uses advanced signal processing algorithms to extract key characteristic information from the collected noise signals, and these characteristic information can reflect the statistical characteristics and spectral distribution of quantum noise. The electromagnetic field simulation unit constructs a mathematical model of the electromagnetic field based on the extracted characteristic information and simulates the influence of quantum noise on the electromagnetic field, thereby revealing the interaction mechanism between quantum noise and the electromagnetic field. Finally, the signal system coupling unit couples the electromagnetic field model with the train CBTC system to construct an electromagnetic field-signal system coupling model, which can predict the interference data of the quantum noise characteristics on the CBTC system.

[0045] The communication signal quality monitoring module is used to monitor the abnormal data of signal intensity in the communication frequency band by using a wireless spectrum analysis algorithm;

[0046] It should be noted that the communication signal quality monitoring module includes a multi-band collaborative monitoring unit, a quantum-enhanced monitoring unit, and a spectrum analysis unit. The three cooperate closely to jointly improve the monitoring accuracy of communication signal quality and the verification ability of signal integrity. The multi-band collaborative monitoring unit has ultra-wideband receiving capabilities and can simultaneously monitor the signal quality within multiple communication bands. It uses an ultra-wideband receiver array and synchronously collects signals in different bands through a multi-channel ADC, ensuring the comprehensiveness and real-time nature of the data. Subsequently, the spectrum sensing engine extracts the spectral characteristics of signals in different bands, and the stitching network stitches these characteristics to form a spectral feature map. The analysis network then deeply analyzes the co-channel interference situation between bands based on the spectral feature map and accurately evaluates the signal quality within different communication bands. The quantum-enhanced monitoring unit injects entangled photons at the receiving end and uses the entanglement characteristics of quantum states to verify signal integrity. The quantum channel encoder encodes the injected entangled photons and maps them to the target band, and the single-photon detector array detects the entangled photons in the target band to obtain the fidelity of the entangled photons. The quantum state tomography verifies signal integrity based on the fidelity of the entangled photons. If the fidelity of the entangled photons is lower than the preset threshold, it is determined that the signal integrity is damaged. This mechanism greatly reduces the false alarm rate and improves the accuracy of monitoring. The spectrum analysis unit uses advanced wireless spectrum analysis algorithms to quickly identify abnormal characteristics in the signal and obtain abnormal data on signal strength within the communication band.

[0047] The data processing center, connected to the track health monitoring module, the electromagnetic environment perception monitoring module, and the communication signal quality monitoring module, is used to fuse and analyze track defect data, interference data, and signal strength abnormal data, and generate a monitoring report on the informatization of urban rail transit communication;

[0048] It should be noted that the data processing center includes a classification unit, a correlation analysis unit, and a report generation unit. The classification unit is responsible for classifying and sorting the data from each monitoring module to ensure the accuracy and orderliness of the data. The correlation analysis unit then uses advanced data analysis algorithms to deeply explore the internal relationships between track defect data, interference data, and signal strength abnormal data, revealing the interaction laws and potential risks between them. The report generation unit then automatically generates a monitoring report on the informatization of urban rail transit communication based on the results of the correlation analysis. This report details all the data and analysis results during the monitoring process and provides an important reference for the safe operation of rail transit.

[0049] The visualization module, connected to the data processing center, is used to visually display the urban rail transit communication informatization monitoring report. The visualization module adopts an intuitive graphical interface and rich chart forms to present complex monitoring data and analysis results in an easy-to-understand way, enabling operation and maintenance personnel to quickly grasp the operation status and potential risks of rail transit, and take corresponding maintenance and management measures in a timely manner to ensure the safe and efficient operation of rail transit.

[0050] As Figure 1 shown, when an urban rail transit communication informatization monitoring device of this embodiment is in use, first, the track health monitoring module monitors the tracks of urban rail transit in real time. This module combines acoustic CT scanning and electromagnetic eddy current detection technologies, can penetrate into the interior of the rail and capture minute defect information, and simultaneously monitor cracks and minute damages on the surface of the rail, thereby constructing a high-precision three-dimensional defect imaging of the rail. This imaging technology improves the accuracy and reliability of defect detection. Then, the electromagnetic environment perception monitoring module starts to work. This module is mainly responsible for extracting quantum noise characteristics and constructing an electromagnetic field-signal system coupling model. Through this model, the interference situation of quantum noise on the communication-based train CBTC system can be accurately predicted, and corresponding measures can be taken in advance to improve the anti-interference ability of the communication system. At the same time, the communication signal quality monitoring module is also monitoring the abnormal data of the signal intensity in the communication frequency band in real time. The introduction of the multi-band collaborative monitoring unit and the quantum-enhanced monitoring unit in this module not only improves the monitoring accuracy of the system, but also enhances the signal integrity verification ability, effectively reducing the false alarm rate. Subsequently, the data processing center starts to fuse and analyze the data from each monitoring module. Through steps such as classification and sorting, correlation analysis, and report generation, the data processing center can deeply explore the internal connections between the data, reveal potential risks, and automatically generate an urban rail transit communication informatization monitoring report. Finally, the visualization module visually displays the monitoring report. Through an intuitive graphical interface and rich chart forms, operation and maintenance personnel can quickly grasp the operation status and potential risks of rail transit, and thus take corresponding maintenance and management measures in a timely manner to ensure the safe and efficient operation of rail transit.

[0051] In summary, an urban rail transit communication informatization monitoring device of the present invention realizes comprehensive monitoring and analysis of track defects, electromagnetic environment, and communication signal quality by integrating a variety of advanced technologies, providing a strong guarantee for the safe operation of rail transit.

[0052] As an optional embodiment of the present invention, optionally, the communication signal quality monitoring module includes:

[0053] A multi-band collaborative monitoring unit for monitoring the signal quality in different communication frequency bands;

[0054] It should be noted that the multi-band collaborative monitoring unit monitors the signal quality in different communication bands synchronously. Specifically, for the 5G FR2 band (24.25 GHz - 52.6 GHz), a harmonic mixer is used; for the leaky cable communication system (800 MHz - 960 MHz), a superheterodyne receiver is deployed; for the millimeter wave radar band (77 GHz - 81 GHz), an SISL waveguide structure is integrated. A 100 dB dynamic range is achieved through digital pre-distortion (DPD) technology, 10 ns-level synchronization is achieved by using a rubidium atomic clock + GPS-tamed clock, and a clock distribution network based on a broadband phase-locked loop (PLL) ensures that the clock synchronization error between monitoring units in each band is less than 1 ps, thus realizing high-precision multi-band signal quality monitoring.

[0055] A quantum-enhanced monitoring unit, used to inject entangled photons at the receiving end to verify the integrity of the signal;

[0056] It should be noted that when the quantum-enhanced monitoring unit verifies the signal integrity, it adopts advanced quantum communication technology. By injecting entangled photons and utilizing the entanglement characteristics of quantum states, it can accurately detect any tiny interference or damage during the signal transmission process. If the fidelity of the entangled photons is lower than a preset threshold, the system immediately determines that the signal integrity is damaged and triggers an alarm mechanism to notify the operation and maintenance personnel to take timely measures for repair.

[0057] A spectrum analysis unit, connected to the multi-band collaborative monitoring unit and the quantum-enhanced monitoring unit, is used to identify the signal quality in different communication bands and the integrity of the signal, analyze the abnormal characteristics in the signal, and obtain the abnormal data of the signal strength in the communication band.

[0058] It should be noted that the spectrum analysis unit adopts a wireless spectrum analysis algorithm, which can quickly and accurately extract signal characteristics from a complex communication environment, identify and analyze abnormal characteristics in the signal, such as frequency offset, amplitude fluctuation, etc., so as to obtain the abnormal data of the signal strength in the communication band. These data help the operation and maintenance personnel to discover and solve potential problems in a timely manner and ensure the normal operation of the communication system.

[0059] As an optional embodiment of the present invention, optionally, the expression for the spectrum analysis unit to identify and analyze the abnormal characteristics in the signal is:

[0060]

[0061] Γ ref (f)=H ideal (f)·P env (f)

[0062] A Q (f)=A(f)·(1 + α·E(ρ))

[0063] Among them, A(f) represents the degree of abnormality at frequency point f;

[0064] represents the estimated value of the power spectral density of the current frequency point f (unit: dBm / Hz);

[0065] represents the mean value of the power spectral density of historical same-frequency points (statistical by sliding window);

[0066] represents the standard deviation of the power spectral density of historical same-frequency points;

[0067] exp() represents the exponential function;

[0068] f c represents the center frequency of the communication system (such as the center frequency of the LTE-M frequency band);

[0069] β represents the frequency-domain focusing coefficient (controlling the Gaussian window width, typical value β = 0.1B, B is the system bandwidth);

[0070] Γ(f) represents the measured channel frequency response function (estimated by pilot signals);

[0071] Γ ref (f) represents the reference channel frequency response function;

[0072] H ideal (f) represents the frequency response of the ideal hardware system (provided by the device specification);

[0073] P env (f) represents the electromagnetic propagation path loss (including track structure, material properties, etc.);

[0074] A Q (f) represents the quantum enhanced score;

[0075] α represents the experimentally calibrated value of the quantum correction coefficient, typical range (0.1 - 0.3);

[0076] E(ρ) represents the entanglement fidelity (measured by quantum state tomography);

[0077] If A(f) > η, then it is determined that the frequency f is abnormal, where η (adaptively adjusted according to the environment, typical value range 5 - 8) represents the dynamic threshold adaptively adjusted according to the environment.

[0078] As an optional embodiment of the present invention, optionally, the multi-band cooperative monitoring unit includes:

[0079] Ultra-wideband receiver array, using multi-channel ADC to synchronously collect signals in different frequency bands;

[0080] It should be noted that the ultra-wideband receiver array has extremely high sensitivity and a wide receiving bandwidth, capable of covering multiple communication frequency bands from low frequency to high frequency. This characteristic enables the ultra-wideband receiver array to simultaneously monitor signals in multiple frequency bands, ensuring the comprehensiveness and real-time nature of data. Through the synchronous acquisition of a multi-channel ADC (analog-to-digital converter), the ultra-wideband receiver array can quickly convert analog signals into digital signals. In addition, the ultra-wideband receiver array also adopts advanced signal processing technologies, such as digital down-conversion, filtering, and noise reduction, etc., to further improve the signal quality and monitoring accuracy. The ultra-wideband receiver array realizes the directional reception and enhancement of signals in different directions through multiple antenna elements and a phased array beamforming network. Each antenna element is connected to a phased array beamforming network, which can dynamically adjust the phase and amplitude of each antenna element according to the direction of the incoming signal, thereby realizing the directional transmission and reception of the beam. This technology not only improves the sensitivity and anti-interference ability of the receiver but also enables the system to accurately identify and track target signals in a complex multipath propagation environment.

[0081] A spectrum sensing engine, connected to the ultra-wideband receiver array, for extracting the spectrum characteristics of signals in different frequency bands;

[0082] It should be noted that the spectrum sensing engine is responsible for extracting the spectrum characteristics from the collected digital signals. The spectrum sensing engine adopts advanced signal processing algorithms, such as fast Fourier transform (FFT), short-time Fourier transform (STFT), or wavelet transform, etc., to perform spectrum analysis on the signals, thereby revealing the signal characteristics in different frequency bands. These characteristics include the frequency components of the signal, power spectral density, bandwidth, and the mutual relationship between signals, etc. Through the processing of the spectrum sensing engine, the system can accurately identify the signals in the communication frequency band.

[0083] A splicing network, connected to the spectrum sensing engine, for splicing the spectrum characteristics extracted from different frequency bands to obtain a spectrum characteristic map;

[0084] It should be noted that the splicing network is responsible for splicing these spectrum characteristics to form a spectrum characteristic map. The spectrum characteristic map visually shows the signal distribution in different frequency bands, enabling the operation and maintenance personnel to quickly grasp the signal status in the communication frequency band. Specifically, the spectrum characteristics extracted from each frequency band are arranged in frequency order, and visual elements such as color and brightness are used to represent characteristics such as the signal strength and frequency components. In this way, the operation and maintenance personnel can visually understand the signal distribution and changes in the communication frequency band by observing the spectrum characteristic map, so as to discover and solve potential problems in a timely manner.

[0085] An analysis network, connected to the splicing network, is used to analyze the co-channel interference situation between frequency bands according to the spectral feature map and obtain the signal quality within different communication frequency bands.

[0086] It should be noted that the analysis network uses deep learning algorithms to perform intelligent analysis on the spectral feature map. The analysis network can automatically identify abnormal regions and patterns in the spectral feature map, such as spectral holes, frequency conflicts, or signal interference, etc., so as to accurately evaluate the signal quality within different communication frequency bands. This function is of great significance for optimizing the allocation of spectral resources, reducing co-channel interference between frequency bands, and improving the overall performance of the communication system.

[0087] As an alternative embodiment of the present invention, optionally, the quantum-enhanced monitoring unit includes:

[0088] A quantum probe, used to inject entangled photons at the receiving end;

[0089] It should be noted that the quantum probe uses advanced quantum communication technologies. By precisely controlling the generation and injection of entangled photons, it realizes real-time monitoring of the signal transmission process. When the entangled photons are subjected to any form of interference or damage during the transmission process, the entanglement characteristics of their quantum states will change, and this change can be accurately detected by the system. By comparing the fidelity of the entangled photons before and after injection, the system can accurately determine whether the integrity of the signal is damaged.

[0090] A quantum channel encoder, connected to the quantum probe, is used to encode the entangled photons injected by the quantum probe and map them to the target frequency band;

[0091] It should be noted that after encoding the entangled photons, the quantum channel encoder can ensure that they maintain a stable quantum state during the transmission process, and at the same time map them to the target frequency band for synchronous transmission and monitoring with the communication signal. This step ensures that the entangled photons can accurately reflect the transmission state of the communication signal.

[0092] A single-photon detector array, connected to the quantum channel encoder, is used to detect the entangled photons within the target frequency band and obtain the fidelity of the entangled photons;

[0093] It should be noted that the single-photon detector array has the characteristics of high sensitivity and low noise, and can accurately detect the entangled photons within the target frequency band. By measuring the fidelity of the entangled photons, the system can accurately evaluate the integrity of the signal during the transmission process. If the fidelity of the entangled photons is lower than the preset threshold, it indicates that the signal may be interfered or damaged during the transmission process, and the system will immediately trigger an alarm mechanism to notify the operation and maintenance personnel for further inspection and maintenance. This function is of great significance for ensuring the stable transmission of communication signals and improving the reliability of the communication system.

[0094] A quantum state tomography device, connected to the single-photon detector array, is used to verify the integrity of the signal based on the fidelity of entangled photons. If the fidelity of the entangled photons is lower than a preset threshold, it is determined that the signal integrity is impaired.

[0095] It should be noted that the quantum state tomography device adopts the principle of quantum measurement. By analyzing the quantum state of entangled photons in detail, it can accurately reconstruct the quantum state changes of the signal during transmission. When the fidelity of the entangled photons is lower than the preset threshold, the quantum state tomography device can accurately identify the situation where the signal integrity is impaired and trigger the corresponding alarm mechanism. This function not only improves the accuracy of signal integrity verification but also provides a more reliable monitoring means for operation and maintenance personnel to ensure the stable operation of the communication system.

[0096] As an optional embodiment of the present invention, optionally, the track health monitoring module includes:

[0097] An acoustic CT scanning unit, used to collect tomographic images of defects in the rail using acoustic waves;

[0098] It should be noted that the acoustic CT scanning unit can penetrate the rail material and reflect back by emitting and receiving acoustic signals to form a tomographic image of the internal structure of the rail. This imaging technology can clearly show defects such as cracks, cavities, and inclusions in the rail, providing intuitive monitoring results for operation and maintenance personnel. The acoustic CT scanning unit not only has high-precision and high-resolution monitoring capabilities but also can monitor the health status of the rail in real time to ensure the safe operation of rail transit. Through regular or real-time acoustic CT scanning, operation and maintenance personnel can timely discover and repair defects in the rail to prevent safety accidents caused by track defects.

[0099] An electromagnetic eddy current detection unit, used to collect data on surface cracks of the rail using an alternating magnetic field;

[0100] It should be noted that the electromagnetic eddy current detection unit can induce eddy currents by generating an alternating magnetic field and acting on the surface of the rail. When these eddy currents flow inside the rail, they will be affected by the material properties of the rail and surface and internal defects, resulting in specific magnetic field changes. The electromagnetic eddy current detection unit captures these magnetic field changes through high-precision sensors and analyzes them using advanced signal processing techniques to achieve accurate detection and quantitative evaluation of surface cracks on the rail. This unit not only has high-sensitivity and high-accuracy detection capabilities but also can monitor minute cracks on the surface of the rail in real time, providing timely and reliable monitoring data for operation and maintenance personnel. Through the application of the electromagnetic eddy current detection unit, operation and maintenance personnel can more comprehensively understand the health status of the rail and take timely measures for repair and maintenance to ensure the safety and stability of rail transit.

[0101] A physical field coupling unit, connected to the acoustic wave CT scanning unit and the electromagnetic eddy current detection unit, is used to perform spatio-temporal synchronous physical field coupling on the tomography data obtained by the acoustic wave CT scanning unit and the crack data obtained by the electromagnetic eddy current detection unit, so as to obtain a three-dimensional defect image of the rail;

[0102] It should be noted that the specific coupling of the physical field coupling unit is to precisely match the tomography data obtained by the acoustic wave CT scanning unit and the crack data obtained by the electromagnetic eddy current detection unit in terms of time and space. First, using a high-precision time synchronization technology to ensure that the data acquisition times of the two units are the same; second, through the conversion and calibration of the spatial coordinate system, the data of the two units are aligned in space. In this way, the internal defects obtained by acoustic wave CT scanning can be precisely correlated with the surface cracks obtained by electromagnetic eddy current detection to form a three-dimensional stereoscopic image of the rail defects. This image can clearly show the defect conditions inside and on the surface of the rail, providing more accurate and comprehensive rail health monitoring information for maintenance personnel.

[0103] A defect recognition unit, connected to the physical field coupling unit, is used to identify and analyze the defect features in the three-dimensional rail defect image and generate track defect data based on the defect features.

[0104] It should be noted that the defect recognition unit uses advanced image recognition and artificial intelligence technologies to intelligently analyze the three-dimensional rail defect image output by the physical field coupling unit. This unit can automatically identify and analyze the defect features in the image, such as the length, width, depth, and position of the crack, etc., so as to generate detailed track defect data. These data provide accurate defect information for maintenance personnel. Specifically, the defect recognition unit compares and classifies through deep learning algorithms and a preset defect database, and can accurately identify different types of track defects, such as cracks, cavities, inclusions, etc.

[0105] As an optional embodiment of the present invention, optionally, the track health monitoring module further includes a defect prediction unit, which is used to predict the possible defect types and positions of the future track according to the historical track defect data and the current track operation status, and generate track defect data based on the possible defect types and positions.

[0106] It should be noted that the defect prediction unit realizes the prediction function through the comprehensive analysis of historical track defect data and the current track operation status. It uses machine learning algorithms to mine and learn from historical data to find the laws of the occurrence and development of track defects. At the same time, combining the current track operation status, such as train operation frequency, load condition, track maintenance records, etc., it predicts the possible types and locations of future track defects. This function provides forward-looking maintenance guidance for operation and maintenance personnel, enabling them to take preventive measures in advance to prevent the occurrence of potential defects, thereby further improving the safety and stability of rail transit.

[0107] As an alternative embodiment of the present invention, optionally, the electromagnetic environment perception and monitoring module includes:

[0108] A quantum noise acquisition unit for acquiring quantum noise;

[0109] It should be noted that the quantum noise acquisition unit can capture weak quantum noise signals in the environment through highly sensitive quantum sensors. These quantum noise signals contain rich electromagnetic environment information, which is of great significance for evaluating the interference level of the electromagnetic environment and optimizing the performance of communication systems.

[0110] A quantum noise feature extraction unit connected to the quantum noise acquisition unit for extracting the feature information of quantum noise;

[0111] It should be noted that the quantum noise feature extraction unit uses signal processing algorithms to deeply analyze the acquired quantum noise signals. It can extract the feature information of quantum noise, such as the spectral distribution of the noise, intensity changes, and the mutual relationship with other signals. Through the processing of the quantum noise feature extraction unit, the system can more accurately understand the complexity and dynamics of the electromagnetic environment, thereby formulating more effective communication strategies and resource allocation schemes.

[0112] An electromagnetic field simulation unit connected to the quantum noise feature extraction unit for constructing an electromagnetic field model based on the extracted quantum noise feature information and simulating the influence of quantum noise on the electromagnetic field;

[0113] It should be noted that the electromagnetic field simulation unit uses advanced calculation methods and simulation technologies to be able to construct an accurate electromagnetic field model according to the extracted quantum noise feature information. The method for constructing the electromagnetic field model is as follows: First, based on the relevant theories of quantum physics, a mathematical model of the electromagnetic field is established, including parameters such as the distribution, intensity, and direction of the electromagnetic field. Then, the extracted quantum noise feature information is used as input parameters and added to the electromagnetic field model to simulate the interference and influence of quantum noise on the electromagnetic field. Through the simulation, the system can predict the changes in the electromagnetic field under different quantum noise conditions and the possible impacts on the communication system.

[0114] The steps to simulate the influence of quantum noise on the electromagnetic field are as follows: By adjusting the parameters in the electromagnetic field model, the interference effects of quantum noise with different frequencies, intensities, and directions on the electromagnetic field are simulated. These simulation results can provide important references for the design and optimization of communication systems, helping engineers better understand and cope with the influence of quantum noise on the electromagnetic environment. For example, it is found in the simulation that the quantum noise interference in certain frequency bands is relatively serious, and engineers can take corresponding measures, such as adjusting the communication frequency, enhancing the signal intensity, or adopting advanced signal processing algorithms, etc., to reduce the influence of quantum noise on the performance of the communication system.

[0115] The signal system coupling unit, connected to the electromagnetic field simulation unit, is used to couple the electromagnetic field model with the signal system to construct an electromagnetic field-signal system coupling model and predict the interference data of quantum noise characteristics on the communication-based train CBTC system.

[0116] It should be noted that the signal system coupling unit realizes the accurate simulation of the performance of the train communication system in a complex electromagnetic environment by deeply integrating the electromagnetic field model with the actual signal system. This coupling process not only considers the distribution and dynamic changes of the electromagnetic field but also deeply analyzes the influence of quantum noise characteristics on key indicators such as signal transmission quality, bit error rate, and system stability. By constructing the electromagnetic field-signal system coupling model, the system can predict the degree of interference that the CBTC system may suffer and the changes in data transmission performance under different quantum noise characteristic conditions. This function provides valuable simulation data for communication system designers and engineers, helping them better understand the interaction relationship between the electromagnetic environment and the communication system, so as to formulate more effective anti-interference strategies and performance optimization plans. For example, if it is found in the prediction results that certain quantum noise characteristics have relatively serious interference on the CBTC system, designers can optimize the communication protocol, enhance the signal processing ability, or adopt advanced quantum communication technologies to improve the anti-interference ability and stability of the system.

[0117] The specific steps to predict the interference data of quantum noise characteristics on the communication-based train CBTC system are as follows:

[0118] First, use the signal system coupling unit to match the parameters in the electromagnetic field model with the parameters of the actual CBTC system to ensure that the model can truly reflect the operating state of the system. Then, take the extracted quantum noise characteristic information as the input condition and add it to the coupling model to simulate the actual interference effect of quantum noise on the CBTC system. During the simulation process, the system will monitor and record the changes of various key indicators in real time, such as signal transmission quality, bit error rate, system response time, etc. By comparing and analyzing the simulation results under different quantum noise characteristic conditions, the system can identify the quantum noise characteristics that have the greatest impact on the performance of the CBTC system and evaluate the possible risks it may bring. For example, quantum noise with certain specific frequencies and intensities may cause a significant decrease in signal transmission quality or a sharp increase in the bit error rate, and this information is crucial for formulating targeted anti-interference measures.

[0119] Next, based on the simulation results, the system will generate a detailed interference data report. This report not only includes the specific parameters of the quantum noise characteristics but also analyzes the degree of influence of these characteristics on various performance indicators of the CBTC system. Maintenance personnel can intuitively understand the impact of quantum noise on the communication system according to this report, and thus formulate effective countermeasures. For example, for the quantum noise characteristics with greater influence, measures such as adjusting the communication frequency, enhancing the signal strength, optimizing the signal processing algorithm, or introducing advanced quantum communication technology can be taken to reduce its impact on the system performance.

[0120] As an optional embodiment of the present invention, optionally, the expression for predicting the interference data of the quantum noise characteristics on the communication-based train CBTC system is:

[0121]

[0122] where I interference represents the total interference intensity of the quantum noise on the CBTC system, with the unit of decibel (dB) or dimensionless (depending on the specific normalization method);

[0123] α represents the frequency weighting coefficient, which is used to adjust the weight of different frequency components on the interference of the CBTC system, dimensionless;

[0124] ω min and ω max respectively represent the lowest and highest angular frequencies of the operating frequency band of the CBTC system, with the unit of radian per second (rad / s);

[0125] S q (ω) represents the power spectral density function of the quantum noise, with the unit of watt per hertz (W / Hz), which describes the energy distribution of the quantum noise at different frequencies;

[0126] H CBTC$(\omega)$ represents the frequency response function of the CBTC system, dimensionless, and describes the amplification or attenuation characteristics of the CBTC system for signals of different frequencies;

[0127] $\Gamma$ channel $(\omega)$ represents the transfer function of the communication channel, dimensionless, and describes the changes of the signal during transmission due to channel characteristics (such as multipath effect, attenuation, etc.);

[0128] $\beta$ represents the quantum noise intensity coefficient, dimensionless, and is used to quantify the direct impact of the quantum noise intensity on the interference of the CBTC system;

[0129] $\sigma$ quantum represents the standard deviation of the quantum noise, with the unit of tesla (T) or volt (V), depending on the specific manifestation form of the quantum noise;

[0130] SNR CBTC represents the signal-to-noise ratio of the CBTC system, dimensionless, and describes the relative intensity of the signal and the noise.

[0131] As an optional embodiment of the present invention, optionally, the data processing center includes:

[0132] A classification unit, configured to classify according to the characteristics of track defect data, interference data, and signal strength anomaly data;

[0133] It should be noted that the classification unit specifically classifies according to multiple dimensions such as the data source, type, severity, and urgency. First, according to the different data sources, the data can be divided into track defect data generated by the track health monitoring module, interference data generated by the electromagnetic environment perception monitoring module, and signal strength anomaly data generated by the signal strength monitoring system. Second, according to the type of data, it can be further subdivided into numerical data, image data, and text data for subsequent adoption of appropriate processing and analysis methods. Third, according to the severity of the data, the data can be divided into three levels: minor, medium, and severe to distinguish different levels of urgency. Finally, according to the urgency of the data, the data with a higher urgency can be evaluated and processed preferentially in real time to ensure the safe operation of the rail transit system is not affected. Through the comprehensive classification of the classification unit, the data processing center can efficiently manage and analyze various types of data.

[0134] An association analysis unit, connected to the classification unit, configured to analyze the association between the classified data and identify potential risk factors;

[0135] It should be noted that the association analysis unit specifically uses data mining and machine learning algorithms to deeply analyze the classified data. It can identify the internal connections and potential laws between different data, thereby revealing the key factors that may affect the safety of rail transit. For example, the association analysis unit can analyze the correlation between track defect data and electromagnetic environment interference data, and explore the possible impact of the electromagnetic environment on the track health status. At the same time, it can also combine the abnormal signal strength data to comprehensively evaluate the overall operation status of the rail transit system. Through association analysis, the system can discover potential safety hazards in advance, provide warning information for maintenance personnel, enabling them to take timely measures for intervention and avoid accidents.

[0136] A report generation unit, connected to the association analysis unit, is used to integrate the classified data and the association analysis results to generate a monitoring report on the informatization of urban rail transit communication.

[0137] It should be noted that the monitoring report on the informatization of urban rail transit communication generated by the report generation unit not only includes detailed track defect data, electromagnetic environment interference data, and abnormal signal strength data, but also conducts in-depth analysis and interpretation of these data. The report will clearly indicate the sources, characteristics, severity, and possible impacts of various types of data, providing comprehensive and accurate monitoring information for maintenance personnel. At the same time, the report will also propose potential risk factors and warning information based on the results of association analysis to help maintenance personnel timely discover and solve problems existing in the rail transit system. In addition, the report will be presented in various forms such as charts and images to make the data more intuitive and easy to understand, facilitating the understanding and application by maintenance personnel.

[0138] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and purposes of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. An information monitoring device for urban rail transit communication, characterized in that, The device includes: An orbital health monitoring module, which is used to fuse acoustic CT scanning and electromagnetic eddy current detection, construct a three-dimensional defect image of the rail, and obtain orbital defect data based on the three-dimensional defect image of the rail; An electromagnetic environment perception and monitoring module, which is used to extract quantum noise characteristics, establish an electromagnetic field-signal system coupling model, and predict the interference data of the quantum noise characteristics on the CBTC system based on the above electromagnetic field-signal system coupling model; A communication signal quality monitoring module, which is used to monitor the abnormal data of signal intensity in the communication frequency band by using a wireless spectrum analysis algorithm; A data processing center, which is connected to the orbital health monitoring module, the electromagnetic environment perception and monitoring module, and the communication signal quality monitoring module, and is used to fuse and analyze the orbital defect data, interference data, and signal intensity abnormal data, and generate a communication informatization monitoring report for urban rail transit; A visualization module, which is connected to the data processing center, and is used to visually display the communication informatization monitoring report for urban rail transit.

2. The urban rail transit communication informatization monitoring device according to claim 1, wherein The communication signal quality monitoring module includes: A multi-band collaborative monitoring unit, which is used to monitor the signal quality in different communication frequency bands; A quantum enhanced monitoring unit, which is used to inject entangled photons at the receiving end to verify the integrity of the signal; A spectrum analysis unit, which is connected to the multi-band collaborative monitoring unit and the quantum enhanced monitoring unit, and is used to identify the signal quality and the integrity of the signal in different communication frequency bands, analyze the abnormal characteristics in the signal, and obtain the abnormal data of signal intensity in the communication frequency band.

3. The urban rail transit communication informatization monitoring device according to claim 2, characterized in that, The expression for the spectrum analysis unit to identify and analyze the abnormal characteristics in the signal is: Γ ref (f) = H ideal (f)·P env (f) A Q (f) = A(f) · (1 + α · E(ρ)) Among them, A(f) represents the degree of abnormality at frequency point f, represents the estimated value of the power spectral density of the current frequency point f, represents the mean value of the power spectral density of historical same-frequency points, represents the standard deviation of the power spectral density of historical same-frequency points, exp() represents the exponential function, f c represents the center frequency of the communication system, β represents the frequency-domain focusing coefficient, Γ(f) represents the measured channel frequency response function, Γ ref (f) represents the reference channel frequency response function, H ideal (f) represents the frequency response of the ideal hardware system, P env (f) represents the electromagnetic propagation path loss, A Q (f) represents the quantum-enhanced score, α represents the quantum correction coefficient, E(ρ) represents the entanglement fidelity; If A(f)>η, it is determined that the frequency f is abnormal, where η represents a dynamic threshold adaptively adjusted according to the environment.

4. The urban rail transit communication informatization monitoring device according to claim 2, characterized in that, The multi-band collaborative monitoring unit includes: An ultra-wideband receiver array, which uses a multi-channel ADC to synchronously collect signals in different frequency bands; A spectrum sensing engine, which is connected to the ultra-wideband receiver array, and is used to extract the spectrum characteristics of signals in different frequency bands; A splicing network, which is connected to the spectrum sensing engine, and is used to splice the spectrum characteristics extracted from different frequency bands to obtain a spectrum characteristic map; An analysis network, which is connected to the splicing network, and is used to analyze the co-channel interference situation between frequency bands according to the spectrum characteristic map to obtain the signal quality in different communication frequency bands.

5. The urban rail transit communication informatization monitoring device according to claim 2, characterized in that, The quantum enhanced monitoring unit includes: A quantum probe, which is used to inject entangled photons at the receiving end; A quantum channel encoder, which is connected to the quantum probe, and is used to encode the entangled photons injected by the quantum probe and map them to the target frequency band; A single-photon detector array, which is connected to the quantum channel encoder, and is used to detect the entangled photons in the target frequency band to obtain the fidelity of the entangled photons; A quantum state tomography instrument, which is connected to the single-photon detector array, and is used to verify the integrity of the signal according to the fidelity of the entangled photons. If the fidelity of the entangled photons is lower than the preset threshold, it is determined that the signal integrity is damaged.

6. The urban rail transit communication informatization monitoring device according to claim 1, characterized in that, The orbital health monitoring module includes: An acoustic CT scanning unit, which is used to use sound waves to collect tomographic images of defects in the rail; An electromagnetic eddy current detection unit, which is used to use an alternating magnetic field to collect data on surface cracks in the rail; A physical field coupling unit, connected to the acoustic wave CT scanning unit and the electromagnetic eddy current detection unit, is used to perform spatio-temporal synchronous physical field coupling on the tomographic imaging data obtained by the acoustic wave CT scanning unit and the crack data obtained by the electromagnetic eddy current detection unit, so as to obtain a three-dimensional defect imaging of the rail; A defect identification unit, connected to the physical field coupling unit, is used to identify and analyze the defect characteristics in the three-dimensional defect imaging of the rail, and generate rail defect data based on the defect characteristics.

7. The urban rail transit communication informatization monitoring device according to claim 1 or 6, characterized in that The rail health monitoring module further includes a defect prediction unit, which is used to predict the possible defect types and positions of the future rail according to the historical rail defect data and the current rail operation status, and generate rail defect data based on the possible defect types and positions.

8. The urban rail transit communication informatization monitoring device according to claim 1, characterized in that The electromagnetic environment perception monitoring module includes: A quantum noise acquisition unit, used to acquire quantum noise; A quantum noise feature extraction unit, connected to the quantum noise acquisition unit, is used to extract the feature information of the quantum noise; An electromagnetic field simulation unit, connected to the quantum noise feature extraction unit, is used to construct an electromagnetic field model based on the extracted quantum noise feature information and simulate the influence of the quantum noise on the electromagnetic field; A signal system coupling unit, connected to the electromagnetic field simulation unit, is used to couple the electromagnetic field model with the signal system, construct an electromagnetic field-signal system coupling model, and predict the interference data of the quantum noise feature on the communication-based train CBTC system.

9. The urban rail transit communication informatization monitoring device according to claim 8, characterized in that, The expression for predicting the interference data of the quantum noise feature on the communication-based train CBTC system is: Among them, I interference represents the total interference intensity of quantum noise on the CBTC system, α represents the frequency weighting coefficient, ω min and ω max respectively represent the lowest and highest angular frequencies of the working frequency band of the CBTC system, S q (ω) represents the power spectral density function of quantum noise, H CBTC (ω) represents the frequency response function of the CBTC system, Γ channel (ω) represents the transfer function of the communication channel, β represents the quantum noise intensity coefficient, σ quantum represents the standard deviation of quantum noise, SNR CBTC represents the signal-to-noise ratio of the CBTC system.

10. The urban rail transit communication informatization monitoring device according to claim 1, characterized in that The data processing center includes: A classification unit, used to classify according to the characteristics of the rail defect data, the interference data, and the signal intensity anomaly data; An association analysis unit, connected to the classification unit, is used to analyze the correlation between the classified data and identify potential risk factors; A report generation unit, connected to the association analysis unit, is used to integrate the classified data and the association analysis results, and generate a monitoring report on the informatization of urban rail transit communication.

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