Millimeter wave detection anti-noise performance improvement method and system

Abstract

The invention discloses a millimeter wave detection anti-noise performance improvement method and a millimeter wave detection anti-noise performance improvement system, relates to the technical field of anti-noise performance improvement, and is used for solving the problem of defect discrimination sensitivity and positioning precision reduction caused by insufficient identification accuracy of sound wave or radar detection in a high-humidity and high-noise tunnel environment. Target echo power is calculated by transmitting millimeter wave signals and receiving tunnel wall surface echoes, noise is collected and noise power is extracted, a gain adjustment coefficient is obtained based on the ratio of the two echoes, target signals are amplified, and a judgment threshold value is generated by combining wall surface material reflection characteristics so as to identify structural defects and generate abnormal information. The method comprises the following steps: adjusting the bandwidth of a receiving filter to obtain an optimized echo signal, analyzing the type, position and severity of a defect, extracting a multi-path echo delay difference to realize accurate positioning, and finally judging whether to generate early warning information or not by combining the delay difference and abnormal information, thereby improving the detection precision and response speed of the system under noise interference.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anti-noise performance improvement, more particularly, to a millimeter wave detection anti-noise performance improvement method and system. BACKGROUND

[0002] As a key structure in traffic and infrastructure, the structural integrity of the tunnel is directly related to driving safety and engineering life. With the increase of tunnel service time and environmental impact, tunnel structures gradually appear structural defect problems such as cracks, hollowing, spalling, etc. If not discovered and handled in time, there will be a great safety hazard. Therefore, how to realize the rapid and accurate identification of tunnel structural defects has become the focus of current research.

[0003] The prior art has the following disadvantages:

[0004] At present, the structural health monitoring method mainly includes manual inspection, sound wave detection, laser radar and geological radar, etc. Among them, the sound wave or radar detection is easily disturbed in the high-humidity and high-noise tunnel environment, the signal-to-noise ratio of the echo signal is low, and the identification accuracy is insufficient, resulting in reduced sensitivity and positioning accuracy of defect identification. Therefore, a millimeter wave detection anti-noise performance improvement method and system are proposed.

[0005] The above information disclosed in the background section is only intended to enhance the understanding of the background of the present disclosure, and therefore it can include information that does not constitute the prior art known to those of ordinary skill in the art. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a millimeter wave detection anti-noise performance improvement method and system, which uses an adaptive gain adjustment mechanism based on the target echo and noise power ratio and a bandwidth adjustable filtering compensation algorithm to solve the problems raised in the above background.

[0007] To achieve the above object, the present application provides the following technical scheme, a millimeter wave detection anti-noise performance improvement method, comprising the following steps:

[0008] Step S1: transmitting a millimeter wave detection signal by a millimeter wave signal detector and receiving a target echo signal reflected by the tunnel wall to calculate the target echo power, and extracting the noise power after collecting the noise signal of the current environment;

[0009] Step S2: calculating a gain adjustment coefficient based on the target echo power and the noise power, amplifying the target echo signal according to the gain adjustment coefficient, and generating a judgment threshold from the reflection characteristics of the tunnel wall material called from the tunnel structure database;

[0010] Step S3: structure defect recognition is performed on the amplified target echo signal by a determination threshold, and abnormal information is generated, and the bandwidth of the receiving filter is adjusted to generate a target echo signal after bandwidth adjustment;

[0011] Step S4: filtering compensation is performed on the target echo signal after bandwidth adjustment, and a multi-path echo delay difference is extracted, and it is judged whether to generate a pre-warning information according to the multi-path echo delay difference.

[0012] In a preferred embodiment, in step S1, a preset acquisition period is divided into a plurality of acquisition time points, and a millimeter wave detection signal is emitted by a millimeter wave signal detector in the acquisition period, the millimeter wave detection signal propagates to the tunnel wall in the form of millimeter wave, and a target echo signal is generated;

[0013] The instantaneous power of the target echo signal at each acquisition time point is calculated, and the square of the amplitude of the target echo signal corresponding to the acquisition time point is taken as the instantaneous power;

[0014] In the acquisition period, the average of the instantaneous power at each acquisition time point is taken as the target echo power;

[0015] When the millimeter wave detection signal is not emitted, the noise signal in the current environment is collected by a noise detector and the noise power is calculated.

[0016] In a preferred embodiment, in step S2, the gain adjustment coefficient is calculated by the target echo power and the noise power: Wherein, P target is the target echo power, P noise is the noise power, G dyn is the gain adjustment coefficient;

[0017] The target echo signal is amplified according to the gain adjustment coefficient;

[0018] The reflection coefficient of the tunnel wall material is retrieved from the tunnel structure database, and the reflection coefficient of the tunnel wall material is taken as the reflection characteristic of the tunnel wall material.

[0019] In a preferred embodiment, in step S2, the transmission power of the millimeter wave detection signal is obtained by the millimeter wave signal detector, and the transmission power of the millimeter wave detection signal is multiplied by the reflection characteristic of the tunnel wall material to obtain the expected reflection power;

[0020] The expected reflection power is subtracted from the preset offset correction factor to obtain the determination threshold.

[0021] In a preferred embodiment, in step S3, the amplified target echo signal is taken as a gain target echo signal, the gain target echo signal is subjected to signal amplitude square processing to obtain an instantaneous power at each time, and a maximum value of the instantaneous power is taken as a detection echo characteristic power;

[0022] If the detection echo characteristic power is greater than a judgment threshold, it is judged that the tunnel structure is normal;

[0023] Otherwise, it is judged that the tunnel structure has a defect.

[0024] In a preferred embodiment, in step S3, the gain target echo signal is used to judge a defect type of the tunnel structure, and a type bandwidth adjustment coefficient is preset according to the defect type of the tunnel structure;

[0025] The gain target echo signal is used to judge the defect type of the tunnel structure, and a type bandwidth adjustment coefficient is preset according to different types;

[0026] A defect position of the tunnel structure is calculated according to a propagation time of the gain target echo signal, and a position bandwidth adjustment coefficient is preset according to the defect position of the tunnel structure;

[0027] The bandwidth of the receiving filter is adjusted according to the preset type bandwidth adjustment coefficient and the preset position bandwidth adjustment coefficient.

[0028] In a preferred embodiment, in step S3, after the bandwidth is adjusted, the gain target echo signal is subjected to filtering processing according to the bandwidth of the adjusted receiving filter, so as to generate a bandwidth-adjusted target echo signal, and the bandwidth-adjusted target echo signal is taken as a bandwidth target echo signal.

[0029] In a preferred embodiment, in step S4, different filters are selected according to the bandwidth target echo signal to perform filtering compensation processing, and the filters include a low-pass filter, a high-pass filter and a band-pass filter;

[0030] The filters are selected according to a start frequency and an end frequency of a frequency range of the bandwidth target echo signal to perform filtering compensation on the bandwidth target echo signal;

[0031] A plurality of peak values in the gain target echo signal after the filtering compensation are extracted as different echo paths;

[0032] A time difference between adjacent peak values is taken as a multi-path echo delay difference;

[0033] When the multi-path echo delay difference exceeds a delay difference threshold, it is judged that a warning information is generated;

[0034] Otherwise, it is judged that the warning information is not generated.

[0035] The application discloses a millimeter wave detection anti-noise performance improving system.

[0036] The information capturing module transmits a detection signal through a millimeter wave signal detector, receives a target echo signal reflected by a tunnel wall, calculates target echo power and noise power, and transmits the target echo power and the noise power to the gain adjusting module.

[0037] The gain adjusting module calculates a gain adjusting coefficient according to the ratio of the target echo power to the noise power, dynamically amplifies the target signal, and generates a judgment threshold.

[0038] The defect identifying module compares the amplified echo signal with the judgment threshold, identifies structural defects, generates abnormal information, and adjusts the bandwidth.

[0039] The early warning processing module filters and compensates the signal after the bandwidth adjustment, judges whether to trigger early warning after extracting the multi-path echo delay difference.

[0040] The technical effects and advantages of the application are as follows:

[0041] The application transmits a millimeter wave detection signal, receives a reflected echo signal, calculates target echo power, collects environmental noise, extracts noise power, calculates the ratio of the target echo power to the noise power to obtain a gain adjusting coefficient, amplifies the target echo signal through the gain adjusting coefficient, generates a judgment threshold according to the reflection characteristics of the tunnel wall material, identifies structural defects through the judgment threshold, generates abnormal information, adjusts the bandwidth of the receiving filter to generate a target echo signal after bandwidth adjustment, further analyzes the defect type, abnormal position and severity, adjusts the bandwidth of the echo signal and performs filtering compensation to optimize the signal quality, accurately locates the defect position by extracting the multi-path echo delay difference, finally, judges whether to generate early warning information according to the delay difference and the abnormal information, improves the detection precision and response speed of the millimeter wave detection system in a noise interference environment, enhances the identification ability of the system to the structural defects of the tunnel, improves the safety and stability of the system, and effectively reduces the misjudgment rate and the missed detection rate. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The application discloses a millimeter wave detection anti-noise performance improving system.

[0043] Figure 2 The application discloses a millimeter wave detection anti-noise performance improving system. DETAILED DESCRIPTION

[0044] Clearly, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present application.

[0045] The present application calculates the target echo power by emitting a millimeter wave detection signal and receiving the echo signal reflected by the tunnel wall, collects the environmental noise and extracts the noise power, calculates the gain adjustment coefficient by the ratio of the target echo power to the noise power, amplifies the target echo signal by the gain adjustment coefficient, generates a determination threshold combining the reflection characteristics of the tunnel wall material, identifies the structural defects of the amplified target echo signal by the determination threshold and generates abnormal information, adjusts the bandwidth of the receiving filter to generate the target echo signal after bandwidth adjustment, further analyzes the defect type, abnormal position and severity, adjusts the echo signal bandwidth and performs filtering compensation to optimize the signal quality, and accurately locates the defect position by extracting the multi-path echo delay difference, finally, judges whether to generate the early warning information combining the delay difference and the abnormal information, improves the detection precision and response speed of the millimeter wave detection system in the noise interference environment, enhances the identification ability of the system to the tunnel structural defects, and improves the safety and stability of the system.

[0046] Embodiment 1, a millimeter wave detection anti-noise performance improvement method, as shown in Figure 1 The method comprises the following steps:

[0047] Step S1: Calculate the target echo power by emitting a millimeter wave detection signal and receiving the target echo signal reflected by the tunnel wall through the millimeter wave signal detector, and extract the noise power after collecting the noise signal of the current environment;

[0048] Step S2: Calculate the gain adjustment coefficient based on the target echo power and the noise power, amplify the target echo signal according to the gain adjustment coefficient, and generate a determination threshold from the reflection characteristics of the tunnel wall material called from the tunnel structure database;

[0049] Step S3: Identify the structural defects of the amplified target echo signal by the determination threshold and generate abnormal information, and adjust the bandwidth of the receiving filter to generate the target echo signal after bandwidth adjustment;

[0050] Step S4: Perform filtering compensation processing on the target echo signal after bandwidth adjustment and extract the multi-path echo delay difference, and judge whether to generate the early warning information according to the multi-path echo delay difference.

[0051] The specific steps are as follows:

[0052] In step S1, a preset acquisition period is divided into multiple acquisition time points, and a millimeter wave signal detector is used to emit a millimeter wave detection signal in the acquisition period. The millimeter wave detection signal propagates to the tunnel wall in the form of millimeter wave and generates a target echo signal.

[0053] The instantaneous power of the target echo signal at each acquisition time point is calculated, and the square of the amplitude of the target echo signal corresponding to the acquisition time point is taken as the instantaneous power.

[0054] In the acquisition period, the average of the instantaneous power at each acquisition time point is taken as the target echo power.

[0055] When the millimeter wave detection signal is not emitted, the noise signal in the current environment is collected by a noise detector and the noise power is calculated, and the steps are as follows:

[0056] A preset time window is set, and the noise signal of the current environment is collected by the noise detector, and the noise power is calculated according to the noise signal. The noise power formula is:

[0057] Where T is the total duration of the preset time window, is the amplitude of the noise signal, and P noise is the noise power.

[0058] It should be noted that the millimeter wave signal detector is a device that emits millimeter wave signals and receives reflected target echo signals.

[0059] By presetting the acquisition period, the millimeter wave detection signal emitted by the millimeter wave signal detector is collected to collect the target echo signal at multiple acquisition time points, and the instantaneous power of the target echo signal at each time point is calculated, and then the target echo power is obtained. At the same time, when the millimeter wave signal is not emitted, the noise signal in the environment is collected by the noise detector and the noise power is calculated, so as to effectively distinguish and suppress the target signal and the noise, thereby significantly improving the detection accuracy of the tunnel wall structure defect and the anti-interference ability of the system, and enhancing the reliability and stability of the detection result.

[0060] In step S2, the gain adjustment coefficient is calculated by the target echo power and the noise power: Where P target is the target echo power, P noise is the noise power, and G dyn is the gain adjustment coefficient.

[0061] When the target echo power is larger and the noise power is smaller, the gain adjustment coefficient is smaller, and the quality of the target echo signal is better. When the target echo power is smaller and the noise power is larger, the gain adjustment coefficient is larger, and the target echo signal is difficult to be identified, and needs to be amplified.

[0062] amplify the target echo signal according to the gain adjustment coefficient: V echo ′=G dyn ·V echo , wherein V echo ' is the amplified target echo signal, V echo is the target echo signal.

[0063] Amplifying the target echo signal according to the gain adjustment coefficient ensures that the target echo signal is distinguished in the case of strong noise background.

[0064] The reflection coefficient of the tunnel wall material is retrieved from the tunnel structure database, and the reflection coefficient of the tunnel wall material is taken as the reflection characteristic of the tunnel wall material. By combining the reflection characteristic of the tunnel wall material with the target echo signal intensity and the noise power, the adjustment of the determination threshold is realized.

[0065] The transmission power of the millimeter wave detection signal is obtained by the millimeter wave signal detector, and the transmission power of the millimeter wave detection signal is multiplied by the reflection characteristic of the tunnel wall material to obtain the expected reflection power, which is the reflection power generated when the tunnel structure is defect-free.

[0066] The expected reflection power is subtracted from the preset offset correction factor to obtain the determination threshold.

[0067] It should be noted that the preset offset correction factor is used to enhance the sensitivity and adaptability of defect identification, which is specifically set by professionals.

[0068] The gain adjustment coefficient is obtained by calculating the ratio of the target echo power to the noise power, and the target echo signal is dynamically amplified according to the coefficient, which effectively improves the recognition ability of the signal in the noise background. Combined with the reflection coefficient of the tunnel wall material and the transmission power of the millimeter wave detection signal, the determination threshold is dynamically adjusted, and the preset offset correction factor is introduced to enhance the sensitivity and adaptability of defect identification.

[0069] In step S3, the amplified target echo signal is taken as the gain target echo signal, and the gain target echo signal and the determination threshold are compared to determine whether there is a structural defect and generate abnormal information.

[0070] The gain target echo signal is subjected to signal amplitude square processing to obtain the instantaneous power at each time, and the maximum value of the instantaneous power is taken as the detection echo characteristic power.

[0071] If the detection echo characteristic power is greater than the determination threshold, it is judged that the tunnel structure is normal.

[0072] Otherwise, it is judged that the tunnel structure has defects.

[0073] When the echo characteristic power is greater than the determination threshold, it indicates that the tunnel structure reflection performance is normal, and the tunnel structure is complete, dense, continuous, and has no obvious structural damage or defects. Otherwise, it indicates that the reflection ability is lower than expected, which may be caused by local cracks, cavities, shedding and other structural abnormalities leading to reflection energy attenuation.

[0074] The millimeter wave detection system determines whether it is one of the following three types of structural defects according to the gain target echo signal:

[0075] Crack defect: the gain target echo signal shows a relatively obvious amplitude change and delay;

[0076] Corrosion or wear defect: the gain target echo signal is weak, the frequency or phase is offset, the amplitude is small and irregular;

[0077] Object collision: the gain target echo signal is strong, there is obvious multi-path reflection and high signal peak.

[0078] By identifying these characteristics, the tunnel structure defect types can be effectively distinguished.

[0079] The propagation time of the gain target echo signal and the time delay Δt of the echo signal can be used to deduce the distance d of the defect, and thus the defect position:

[0080]

[0081] Where c is the speed of millimeter wave detection signal propagation, Δt is the time difference between the emission and reception of the millimeter wave detection signal, and d is the distance of the defect.

[0082] It should be explained that the defect type refers to the type of defects or abnormal phenomena found in the structure; the defect position refers to the specific position of the structural defect; and the defect severity refers to the severity of the defect.

[0083] Through analysis of the gain target echo signal, the appropriate bandwidth adjustment strategy is determined according to the defect type, defect position and defect severity of the defect. The calculation formula for bandwidth adjustment is:

[0084] BW = BW base · (1 + a + b);

[0085] Where BW is the adjusted bandwidth, BW base is the base bandwidth of the receiving filter, a is the bandwidth adjustment coefficient related to the defect type, and b is the bandwidth adjustment coefficient related to the defect position.

[0086] After adjusting the bandwidth, the millimeter wave detector system filters the gain target echo signal according to the adjusted bandwidth, thereby generating a bandwidth-adjusted target echo signal, and taking the bandwidth-adjusted target echo signal as the bandwidth target echo signal.

[0087] It should be noted that the defect type refers to the type of defects or abnormal phenomena found in the structure, the defect position refers to the specific position of the structural defect, the defect severity refers to the severity of the defect, the bandwidth adjustment coefficient is set by professionals according to experiments or experience, and the standardization processing mode includes but is not limited to standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. Here, the application method of standardization processing is not described.

[0088] By performing amplitude squaring processing on the amplified gain target echo signal, extracting the detection echo characteristic power and comparing it with the judgment threshold, the accurate judgment of the tunnel structure defect is realized; in combination with the amplitude change, frequency and phase characteristics of the echo signal, the defect types such as cracks, corrosion wear and object collision are effectively distinguished, and the defect position is accurately positioned based on the millimeter wave signal propagation delay; further, according to the defect type, position and severity, the filter bandwidth is dynamically adjusted to realize adaptive filtering processing of the target echo signal, and the sensitivity and accuracy of defect detection are significantly improved.

[0089] In step S4, after the bandwidth target echo signal is standardized, the quality of the bandwidth target echo signal is further improved through filtering compensation processing to ensure that the bandwidth target echo signal can be accurately restored in the case of multipath propagation.

[0090] According to the bandwidth target echo signal, different filters are selected for filtering compensation processing, including low-pass filter, high-pass filter and band-pass filter.

[0091] The start frequency and end frequency of the bandwidth target echo signal frequency range are obtained by the spectrum analyzer, the median of the start frequency and end frequency is taken as the center frequency, and the start frequency and end frequency are respectively subtracted from the center frequency. If the result of the start frequency subtraction is close to the center frequency, it represents that the bandwidth target echo signal frequency range is concentrated in the low frequency band, and if the result of the end frequency subtraction is far away from the center frequency, it represents that the bandwidth target echo signal frequency range is concentrated in the high frequency band.

[0092] When the frequency range of the bandwidth target echo signal is concentrated in a lower frequency band, and the high frequency component is noise, a low-pass filter is selected;

[0093] When the frequency range of the bandwidth target echo signal is concentrated in a higher frequency band, and the low frequency component is noise, a high-pass filter is selected;

[0094] When the bandwidth target echo signal frequency range is between high frequency and low frequency, a band-pass filter is selected.

[0095] The filtering compensation removes noise and optimizes signal quality, ensuring that the bandwidth echo signal can be accurately restored in the case of multipath propagation.

[0096] A preset fixed time window is set, and the millimeter detector system collects gain target echo signals of different paths and calculates corresponding peak values according to the gain target echo signals.

[0097] After obtaining the gain target echo signal after bandwidth adjustment and filtering compensation, a plurality of peak values of the signal are extracted within a preset time, representing different echo paths. Each peak value corresponds to the arrival time of the propagation path, and the multipath echo delay difference is obtained by measuring the time difference between adjacent peak values.

[0098] A preset delay difference threshold is set. When the multipath echo delay difference is greater than or equal to the delay difference threshold, it indicates that the propagation path of the gain target echo signal has changed significantly, and there is a defect, and the millimeter wave detection system triggers a warning.

[0099] When the multipath echo delay difference is less than the delay difference threshold, it indicates that the propagation path of the gain target echo signal is stable, and the millimeter wave detection system ignores the warning.

[0100] The multipath echo delay difference reflects the complexity of the tunnel or target structure. A significant increase in the multipath echo delay difference indicates the presence of irregular surfaces or structural defects in the tunnel.

[0101] It should be noted that the delay difference threshold is preset by experimenters based on experience and data, and the spectrum analyzer is an electronic instrument for measuring the spectrum of the bandwidth target echo signal, which can display the power or amplitude of the bandwidth target echo signal at different frequencies.

[0102] Through standardization and targeted filtering compensation of the bandwidth target echo signal, noise interference in multipath propagation is effectively removed, and signal restoration accuracy is improved; combined with spectrum analysis to determine the appropriate filter type, adaptive selection of low-pass, high-pass and band-pass filtering is realized; based on dynamic monitoring of multipath echo peak values and delay difference, the complexity and abnormal changes of the tunnel structure are accurately reflected, and defect warning is triggered in time, significantly enhancing the resistance of the system to multipath effect and the sensitivity of defect detection, and improving the reliability and intelligent level of tunnel structure safety monitoring.

[0103] Embodiment 2, a millimeter wave detection anti-noise performance improvement system, as shown in Figure 2 for realizing a millimeter wave detection anti-noise performance improvement method, including an information acquisition module, a gain adjustment module, a defect identification module, and a warning processing module;

[0104] The information capturing module transmits a detection signal through a millimeter wave signal detector, receives a target echo signal reflected by a tunnel wall, and calculates a target echo power and a noise power;

[0105] The gain adjusting module calculates a gain adjusting coefficient based on a ratio of the target echo power and the noise power, dynamically amplifies the target signal, and generates a determination threshold;

[0106] The defect identifying module compares the amplified echo signal with the determination threshold, identifies a structural defect, generates abnormal information, and adjusts a bandwidth;

[0107] The early warning processing module filters and compensates the signal after the bandwidth adjustment, judges whether to trigger early warning after extracting a multi-path echo delay difference.

[0108] The above embodiments can be realized wholly or partially by software, hardware, firmware, or any combination thereof. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product.

[0109] Those skilled in the art can realize that the modules and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software depends on the specific application of the technical solution and the constraints of the invention. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0110] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0111] The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0112] Finally, the above is merely a preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for improving the noise resistance of millimeter-wave detection, characterized in that: Includes the following steps: Step S1: Transmit millimeter-wave detection signals through a millimeter-wave signal detector and receive the target echo signals reflected from the tunnel wall to calculate the target echo power. Collect the noise signal of the current environment and extract the noise power. Step S2: Calculate the gain adjustment coefficient based on the target echo power and noise power, amplify the target echo signal according to the gain adjustment coefficient, and generate a judgment threshold by calling the reflection characteristics of the tunnel wall material from the tunnel structure database; Step S3: Identify structural defects in the amplified target echo signal and generate abnormal information by judging the threshold, and adjust the bandwidth of the receiving filter to generate the target echo signal with adjusted bandwidth. Step S4: Perform filtering compensation on the target echo signal after bandwidth adjustment and extract the multipath echo delay difference. Determine whether to generate early warning information based on the multipath echo delay difference.

2. The method for improving the noise resistance of millimeter-wave detection according to claim 1, characterized in that: In step S1, a preset acquisition period is divided into multiple acquisition times. During the acquisition period, a millimeter-wave detection signal is emitted through a millimeter-wave signal detector. The millimeter-wave detection signal propagates to the tunnel wall in the form of millimeter waves and generates a target echo signal. Calculate the instantaneous power of the target echo signal at each acquisition time, and take the square of the target echo signal amplitude at the acquisition time as the instantaneous power; Within the acquisition period, the average instantaneous power at each acquisition moment is taken as the target echo power; When no millimeter-wave detection signal is emitted, noise signals in the current environment are collected by a noise detector and the noise power is calculated.

3. The method for improving the noise resistance of millimeter-wave detection according to claim 1, characterized in that: In step S2, the gain adjustment coefficient is calculated using the target echo power and noise power: Among them, P target For the target echo power, P noise For noise power, G dyn This is the gain adjustment coefficient; The target echo signal is amplified according to the gain adjustment coefficient; The reflection coefficient of the tunnel wall material is retrieved from the tunnel structure database and used as the reflection characteristic of the tunnel wall material.

4. The method for improving the noise resistance of millimeter-wave detection according to claim 3, characterized in that: In step S2, the transmission power of the millimeter-wave detection signal is obtained by the millimeter-wave signal detector, and the transmission power of the millimeter-wave detection signal is multiplied by the reflection characteristics of the tunnel wall material to obtain the expected reflection power. The difference between the expected reflection power and the preset offset correction factor is used as the judgment threshold.

5. The method for improving the noise resistance of millimeter-wave detection according to claim 4, characterized in that: In step S3, the amplified target echo signal is used as the gain target echo signal. The gain target echo signal is processed by squaring the signal amplitude to obtain the instantaneous power at each moment. The maximum value of the instantaneous power is used as the detection echo characteristic power. If the detected echo characteristic power is greater than the judgment threshold, the tunnel structure is judged to be normal. Conversely, if the tunnel structure does not have defects, it is determined that there are defects in the tunnel structure.

6. The method for improving the noise resistance of millimeter-wave detection according to claim 5, characterized in that: In step S3, the type of tunnel structural defect is determined by the gain target echo signal, and a type bandwidth adjustment coefficient is preset according to the type of tunnel structural defect. The type of tunnel structural defect is determined by the gain target echo signal, and the bandwidth adjustment coefficient is preset according to different types. The location of tunnel structural defects is calculated based on the propagation time of the target gain echo signal, and the location bandwidth adjustment coefficient is preset based on the location of the tunnel structural defects. The bandwidth of the receiving filter is adjusted according to the preset type bandwidth adjustment coefficient and the preset position bandwidth adjustment coefficient.

7. The method for improving the noise resistance of millimeter-wave detection according to claim 6, characterized in that: In step S3, after adjusting the bandwidth, the gain target echo signal is filtered according to the adjusted bandwidth of the receiving filter to generate the bandwidth-adjusted target echo signal, which is then used as the bandwidth target echo signal.

8. The method for improving the noise resistance of millimeter-wave detection according to claim 7, characterized in that: In step S4, different filters are selected for filtering compensation processing based on the target bandwidth echo signal. The filters include low-pass filters, high-pass filters, and band-pass filters. The filter is selected based on the start and end frequencies of the target bandwidth echo signal frequency range to perform filtering compensation on the target bandwidth echo signal; Multiple peak values ​​are extracted from the target gain echo signal after filtering and compensation, and used as different echo paths; The time difference between adjacent peaks is used as the multipath echo delay difference; When the multipath echo delay difference exceeds the delay difference threshold, an early warning message is generated. Conversely, if the condition is not met, then no warning message will be generated.

9. A millimeter-wave detection noise reduction system, used to implement the millimeter-wave detection noise reduction method according to any one of claims 1-8, characterized in that: It includes an information capture module, a gain adjustment module, a defect identification module, and an early warning processing module; The information acquisition module transmits a detection signal through a millimeter-wave signal detector, receives the target echo signal reflected from the tunnel wall, and calculates the target echo power and noise power. The gain adjustment module calculates the gain adjustment coefficient by combining the ratio of target echo power to noise power, dynamically amplifies the target signal, and generates a judgment threshold. The defect identification module compares the amplified echo signal with the judgment threshold to identify structural defects and generate abnormal information, and then adjusts the bandwidth. The early warning processing module filters and compensates the signal after bandwidth adjustment, extracts the multipath echo delay difference, and then determines whether an early warning is triggered.

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