A highway tunnel detection system for highway engineering

Abstract

The present invention relates to the field of spectral data processing technology, and in particular to a highway tunnel detection system for highway engineering. The system first obtains the mineral alteration response degree at the wavelength corresponding to each band of mixed spectral data, obtains the reflectivity correction value at the wavelength corresponding to other bands in the neighborhood of each band, obtains the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points, and then further obtains the upper envelope of the mixed spectral data, and finally performs mineral alteration anomaly detection on the mixed spectral data after the envelope removal result, and obtains the location of defects in the tunnel. The present invention can ensure that the preprocessing of the highway tunnel spectrum data is more reliable, avoid the loss of some key information, and further improve the accuracy of subsequent highway tunnel detection.

Description

Technical Field

[0001] The present invention relates to the technical field of spectral data processing, and more specifically, to a highway tunnel detection system for highway engineering. Background Art

[0002] As an important part of transportation infrastructure, the structural safety and operation status of highway tunnels are directly related to the smooth transportation and public safety. With the increase in traffic volume and the extension of tunnel service life, the aging and damage problems of tunnel structures have become increasingly prominent, and regular inspection and maintenance of tunnels are particularly important. At present, tunnel inspection mainly relies on manual inspection, image processing technology, and spectral analysis technology. Among them, spectral analysis technology has been widely used in highway tunnel inspection for highway engineering due to its high precision and ability to explore the interior of rocks.

[0003] Spectral analysis technology can identify the composition and state of materials by collecting and analyzing the spectral data of materials at different wavelengths. In highway tunnel inspection, spectral data can be used to detect cracks, corrosion and other defects on the tunnel surface. However, in practical applications, spectral data often need to undergo complex preprocessing operations to remove noise and interference, so as to extract useful characteristic information. For example, in addition to the characteristic signals of the sample, spectral data may also contain background signals from the environment, such as scattered light, reflected light, etc. If these background signals are not properly eliminated, they may cause a slope effect on the baseline of the spectrum graph. Therefore, the envelope removal method is generally used to remove the background noise in the spectral data. However, in the traditional spectral data preprocessing method for highway tunnels, only the shape characteristics of the spectral data are usually considered, and the relationship between the spectral data and the material to be detected in different bands is not fully considered, which will affect the subsequent detection accuracy. Summary of the invention

[0004] In order to solve the technical problem that the spectral data preprocessing method for highway tunnels in the prior art usually only considers the shape characteristics of the spectral data, but does not fully consider the relationship between the spectral data in different bands and the substances to be detected, which affects the accuracy of spectral data monitoring in highway tunnels, the purpose of the present invention is to provide a highway tunnel detection system for highway engineering, and the technical scheme adopted is as follows:

[0005] A highway tunnel detection system for highway engineering, the system comprising:

[0006] A spectral data acquisition module, used to acquire mixed spectral data in the tunnel and standard spectral data of different minerals in the tunnel;

[0007] A mineral alteration response degree acquisition module is used to obtain the mineral alteration response degree at the corresponding wavelength of each band of the mixed spectral data based on the minimum reflectance value of the standard spectral data;

[0008] A reflectivity correction module is used to obtain reflectivity correction values ​​at corresponding wavelengths of other bands in the neighborhood of each band according to the mineral alteration response degree at corresponding wavelengths of other bands in the neighborhood of each band;

[0009] The drift correction degree acquisition module is used to obtain the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points according to the reflectivity correction values ​​of other bands in the neighborhood of each band at the corresponding wavelengths;

[0010] An upper envelope acquisition module is used to obtain the upper envelope of the mixed spectrum data according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points;

[0011] The alteration detection module is used to perform mineral alteration anomaly detection on the mixed spectral data after the envelope is removed based on the upper envelope, so as to obtain the location of defects in the tunnel.

[0012] Furthermore, the mixed spectral data for obtaining the tunnel and the standard spectral data of different minerals in the tunnel are specifically:

[0013] Sampling points are set at equal distances along the highway tunnel, and mixed spectral data of minerals in the highway tunnel at different positions are collected using a spectrometer;

[0014] Analyze the geological conditions in the highway tunnel, obtain the mineral information in the highway tunnel, build a spectral library for the tunnel site, and obtain the standard spectral data corresponding to different minerals in the highway tunnel in the spectral library for the tunnel site.

[0015] Furthermore, the method of taking the minimum reflectivity value of the standard spectral data as the standard to obtain the mineral alteration response degree of different minerals in the tunnel at corresponding wavelengths in each band is specifically as follows: according to the ratio of the minimum reflectivity value of each mineral in the standard spectral data to the reflectivity of the mixed spectral data corresponding to the mineral in the highway tunnel at corresponding wavelengths in each band, the mineral alteration response degree at corresponding wavelengths in each band of the mixed spectral data is obtained.

[0016] Furthermore, the method of obtaining the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band according to the mineral alteration response degree at the corresponding wavelength of other bands in the neighborhood of each band is specifically as follows: according to the reflectivity at the corresponding wavelength of other bands in the neighborhood of each band of the mixed spectral data, the mineral alteration response degree, and the average reflectivity of multiple other bands corresponding wavelengths in the neighborhood of each band, the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band is obtained.

[0017] Furthermore, the greater the degree of mineral alteration response at the corresponding wavelengths of other bands in the neighborhood of each band, the greater the difference between the average reflectivity of multiple other bands in the neighborhood of each band and the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band, and the greater the correction of the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band of the mixed spectral data.

[0018] Furthermore, the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points is obtained according to the reflectivity correction values ​​of other bands corresponding to wavelengths in the neighborhood of each band:

[0019] According to the standard deviation of the first-order difference of the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band, the drift correction degree at the corresponding wavelength of each band is obtained;

[0020] According to the drift correction degree at the wavelength corresponding to the band where any two adjacent reflectivity maximum value points are located, the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum value points is obtained.

[0021] Furthermore, the upper envelope of the mixed spectrum data is obtained according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points:

[0022] According to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points and the number of two adjacent reflectivity maximum points in all bands, the overall average drift correction degree between any two adjacent reflectivity maximum points in all bands is obtained;

[0023] According to the relationship between the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectance maximum points and the overall average drift correction degree between any two maximum points in all bands, the connecting line segment of the upper envelope of the mixed spectral data is obtained.

[0024] Furthermore, the envelope removal result is specifically: obtaining the envelope removal result of the mixed spectral data according to the ratio between the reflectivity of the mixed spectral data at each wavelength and the upper envelope value of the mixed spectral data.

[0025] Furthermore, the upper envelope value of the mixed spectral data is specifically obtained by obtaining the upper envelope value of the mixed spectral data according to the slope of the connecting line segments of each upper envelope and the reflectivity of the mixed spectral data at each wavelength.

[0026] Furthermore, the method for performing mineral alteration anomaly detection on the spectral data after the envelope removal result based on the upper envelope to obtain the location of defects in the tunnel is specifically:

[0027] The spectral data after the envelope removal is subjected to the continuous projection algorithm to extract the features of multiple characteristic bands;

[0028] The extracted multiple spectral feature data are used for anomaly detection through isolation forest algorithm;

[0029] A first threshold value of the abnormality score is preset, and when the abnormality score corresponding to the spectral data feature at a certain position is greater than or equal to the first threshold value, the spectral data at the corresponding position is abnormal;

[0030] The position in the corresponding tunnel is marked as the defect position.

[0031] The present invention has the following beneficial effects: it can ensure that the preprocessing of the highway tunnel spectrum data is more reliable, avoid the loss of some key information, and further improve the accuracy of subsequent highway tunnel detection. The present invention deeply analyzes the relationship between the spectral data at different positions, and the detection system can identify the correlation strength between different bands and the material to be detected, retain the information of the spectral data of the altered area, and help to more accurately construct the envelope line, avoid mistakenly removing the key defect information as background noise, ensure that the constructed envelope line is more accurate, effectively avoid the loss of key defect information, and improve the accuracy of subsequent detection; in addition, by analyzing the relationship between the spectral data and the material to be detected, the parameters of the envelope line removal are dynamically adjusted to ensure the accuracy and flexibility of the envelope line removal process. This dynamic adjustment mechanism helps to adapt to different types of tunnel materials and environmental conditions, and enhances the robustness and adaptability of the detection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 A block diagram of a highway tunnel detection system for highway engineering provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation method, structure, characteristics and effects of a highway tunnel detection system for highway engineering proposed by the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. Unless otherwise defined, all technical and scientific terms used in this article have the same meaning as those commonly understood by technicians in the technical field of the present invention.

[0035] Example

[0036] A specific scheme of a highway tunnel detection system for highway engineering provided by the present invention is described in detail below with reference to the accompanying drawings.

[0037] The specific scenario targeted by the embodiments of the present invention is: in the process of highway tunnel detection, since the original spectral absorption characteristics are not obvious and there are background signals from the environment, such as scattered light, reflected light, etc., if these background signals are not properly eliminated, it may cause a slope effect on the baseline of the spectrum graph, that is, cause baseline drift. This embodiment corrects the baseline drift by fully considering the relationship between the spectral data and the material to be detected in different bands, thereby obtaining a more accurate envelope line, which has a better effect on removing the envelope line of the spectral data, thereby achieving the purpose of retaining only the spectral data information of the altered area and improving the accuracy of detection.

[0038] See also Figure 1 , which shows a block diagram of a highway tunnel detection system for highway engineering provided by an embodiment of the present invention, the system comprising:

[0039] Spectral data acquisition module 101, mineral alteration response degree acquisition module 102, reflectivity correction module 103, drift correction degree acquisition module 104, upper envelope acquisition module 105, alteration detection module 106.

[0040] The spectrum data acquisition module 101 is used to acquire mixed spectrum data in the tunnel and standard spectrum data of different minerals in the tunnel.

[0041] In order to analyze whether the mineral rock structure inside the highway tunnel is abnormal, it is generally necessary to obtain spectral data to analyze the data inside the highway tunnel. In this embodiment, the mixed spectral data in the tunnel and the standard spectral data of different minerals in the tunnel are obtained by the spectral data acquisition module 101.

[0042] For mixed spectral data, sampling points are set at equal distances along the direction of the highway tunnel, and a spectrometer is used to collect mixed spectral data of minerals in the highway tunnel at different positions. Specifically, along the direction of the highway tunnel to be detected, the spectral data in the tunnel is collected by uniform sampling. Considering the regional characteristics of different rock minerals, it is preferred to collect spectral data of the highway tunnel at different positions by sampling one point every 20m, and then detect the rock minerals inside the tunnel according to the spectral data obtained at various positions along the line, wherein the wavelength range of the spectral data obtained by the spectrometer is 350nm to 2500nm.

[0043] Based on the standard spectral data, the geological conditions in the highway tunnel are analyzed, the mineral information in the highway tunnel is obtained, the spectral library of the tunnel site area is constructed, and the standard spectral data corresponding to different minerals in the highway tunnel in the spectral library of the tunnel site area are obtained. Specifically, by analyzing the geological background in the road tunnel in detail, understanding the rock and mineral information in the area, determining the types of rock minerals contained in the current detection section, screening out the mineral spectral data that matches the predicted results from the standard spectral library, and establishing a regional spectral library of the tunnel site area. The main alteration type minerals include quartz, mica, chlorite, epidote and other types of rock mineral substances.

[0044] It should be further explained that because the standard spectral data corresponds to the spectral data of different minerals in the highway tunnel, its wavelength range is consistent with the wavelength range of the mixed spectral data, that is, the wavelength range is between 350nm and 2500nm. Therefore, the minimum wavelength of the standard spectral data is 350nm and the maximum wavelength is 2500nm. The minimum and maximum wavelengths correspond to different mineral types in the highway tunnel respectively.

[0045] In highway tunnel inspection, each band of spectral data usually represents the reflection characteristics of different materials or substances. If you want to analyze which bands need a higher degree of information retention in the wavelength range during the subsequent envelope removal process, you first need to analyze the response degree of the spectral data corresponding to each rock mineral based on the multiple standard spectral data in the above-mentioned standard spectral database, and then conduct subsequent analysis.

[0046] The mineral alteration response degree acquisition module 102 is used to acquire the mineral alteration response degree at the corresponding wavelength of each band of the mixed spectral data based on the minimum reflectance value of the standard spectral data.

[0047] Specifically, taking the minimum reflectivity value of the standard spectral data as the standard, the degree of mineral alteration response of different minerals in the tunnel at corresponding wavelengths in each band is obtained as follows: according to the ratio of the minimum reflectivity value of each mineral in the standard spectral data to the reflectivity of the mixed spectral data corresponding to the mineral in the highway tunnel at corresponding wavelengths in each band, the degree of mineral alteration response at corresponding wavelengths in each band of the mixed spectral data is obtained.

[0048] In the mixed spectral data, the horizontal axis is the wavelength of the spectral data, and the vertical axis is the reflectivity of the spectral data under a single substance. When the corresponding material content response is higher, the corresponding reflectivity should be smaller. Therefore, the minimum reflectivity value of the standard spectral data is used as the standard to calculate the degree of mineral alteration response in each band.

[0049] In this embodiment, the calculation formula for the mineral alteration response degree at the corresponding wavelength of each band of the constructed mixed spectral data can be expressed as:

[0050]

[0051] In the formula, Indicates Bands; Indicates Bands correspond to wavelengths; Indicates the tunnel a mineral; represents the wavelength of the mixed spectral data, ,in =2500nm; The standard spectral data Wavelength of minerals Minimum reflectance value in standard spectral data; Represents the mixed spectral data The mineral Bands correspond to wavelengths Reflectance in mixed spectral data; Indicates the total number of tunnels kinds of minerals; Indicates The degree of mineral alteration response at the corresponding wavelength of each band.

[0052] In the calculation formula for the mineral alteration response degree at the corresponding wavelengths of each band of the above-mentioned mixed spectral data, the minimum reflectivity value of each mineral in the standard spectral data is taken as the standard, and the mineral alteration response degree at the corresponding wavelengths of each band of the mixed spectral data is obtained according to the ratio of the minimum reflectivity value of each mineral in the standard spectral data to the reflectivity of the mixed spectral data corresponding to the mineral in the highway tunnel at the corresponding wavelengths in each band.

[0053] In this embodiment, the purpose of preprocessing the mixed spectral data is to eliminate the background noise and low-frequency trends in the spectral signal so as to more accurately identify and analyze various materials and defects in the tunnel. The above-mentioned background noise and low-frequency trends will cause the spectral data to have different degrees of slope effects in different wavelength ranges. Therefore, after obtaining the degree of mineral alteration response at the corresponding wavelengths of the above-mentioned each band, the changes in the spectral data within the corresponding wavelength neighborhood range of each band in the mixed spectral data obtained during the actual measurement process are considered to adjust the envelope lines within different wavelength ranges.

[0054] Before considering the influence of the slope effect on each band, the relationship between the reflectivity at different wavelengths and the reflectivity at adjacent wavelengths in a single spectral data should be considered, that is, the wavelength neighborhood should be analyzed. Since the bands with different alteration degrees contain different amounts of required information, it is necessary to make different corrections to the corresponding reflectivity in the neighborhood of each band of the mixed spectral data according to the degree of mineral alteration response. Therefore, the highway tunnel detection system of this embodiment is provided with the following modules:

[0055] The reflectivity correction module 103 is used to obtain the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band according to the mineral alteration response degree at the corresponding wavelength of other bands in the neighborhood of each band.

[0056] Among them, according to the mineral alteration response degree at the corresponding wavelength of other bands in the neighborhood of each band, the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band is obtained. Specifically, according to the reflectivity at the corresponding wavelength of other bands in the neighborhood of each band of the mixed spectral data, the mineral alteration response degree, and the average reflectivity of multiple other bands in the neighborhood of each band, the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band is obtained.

[0057] Furthermore, the greater the degree of mineral alteration response at the corresponding wavelengths of other bands in the neighborhood of each band, the greater the difference between the average reflectivity of multiple other bands in the neighborhood of each band and the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band, and the greater the correction of the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band of the mixed spectral data.

[0058] In this embodiment, the calculation formula for the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band can be expressed as:

[0059]

[0060] In the formula, Indicates Mixed spectral data of measurements; Indicates the mixed spectral data Band neighborhood Bands correspond to wavelengths; Indicates that the mixed spectral data is the first Band neighborhood The reflectivity of each band at the corresponding wavelength and the degree of mineral alteration response at the wavelength; Indicates that the mixed spectral data is the first Band neighborhood The reflectivity of each band at the corresponding wavelength; Indicates that the mixed spectral data is the first The average reflectivity of the corresponding wavelengths of multiple other bands in the band neighborhood; Indicates the mixed spectral data Band neighborhood The reflectivity correction value at the corresponding wavelength of each band.

[0061] In the above-mentioned calculation formula of reflectance correction value at the corresponding wavelength of other bands in the neighborhood of each band, the first Band neighborhood The reflectivity of the corresponding wavelength in each band is used as the correction reference. Indicates the correction amount, which is the correction amount for the mixed spectral data in the mixed spectral data. Band neighborhood The reflectance of the corresponding wavelength of each band is corrected. When the mixed spectral data is in the mixed spectral data, Band neighborhood The reflectivity of the corresponding wavelength in each band The degree of mineral alteration response at the wavelength The larger the value, the higher the mixed spectral data is in the mixed spectral data. The average reflectance of multiple other bands corresponding to wavelengths in the band neighborhood and the mixed spectral data are the first Band neighborhood The greater the difference in reflectance between the two bands at the corresponding wavelengths, the Band neighborhood Reflectivity correction value at the corresponding wavelength of each band The bigger.

[0062] The drift correction degree acquisition module 104 is used to obtain the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points according to the reflectivity correction values ​​of other bands corresponding to wavelengths in the neighborhood of each band.

[0063] Specifically, according to the reflectivity correction values ​​of other bands in the neighborhood of each band at the corresponding wavelengths, the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points is obtained as follows: first, according to the standard deviation of the first-order difference of the reflectivity correction values ​​of other bands in the neighborhood of each band at the corresponding wavelengths, the drift correction degree of each band at the corresponding wavelength is obtained.

[0064] Generally speaking, when the multiple reflectivity values ​​of the corrected mixed spectral data are closer to a straight line, it means that the efficiency of removing the envelope of multiple points in the neighborhood of the band is better. Therefore, in order to judge whether the spectral data in different band neighborhoods in the mixed spectral data are smooth, it is necessary to further process the reflectivity correction values ​​of other bands in the neighborhood of each band of the mixed spectral data at the corresponding wavelengths to quantify the degree of drift correction.

[0065] In order to obtain the degree of drift correction at the corresponding wavelength of each band, first of all, the standard deviation of the first-order difference of the reflectance correction values ​​at the corresponding wavelengths of other bands in the neighborhood of each band is needed to evaluate the discreteness of the reflectance correction value of the mixed spectral data, and further calculate the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectance maximum points.

[0066] In this embodiment, the calculation formula for calculating the drift correction degree at the wavelength corresponding to each band can be expressed as:

[0067]

[0068] In the formula, Indicates the mixed spectral data Band neighborhood The bands correspond to wavelengths; z represents the The mixed spectral data measured; n represents the number of mixed spectral data measured; represents the mean function; It represents the standard deviation function; Indicates the size of the neighborhood radius of the selected multiple spectral data. In this implementation, The recommended value is 20nm; Indicates The mixed spectral data of the measured Band neighborhood Reflectivity correction value at the corresponding wavelength of each band; express about The first difference of Represents the mixed spectral data The degree of drift correction at the corresponding wavelength of the band.

[0069] In the above-mentioned drift correction degree calculation formula for each band corresponding to the wavelength, The mixed spectral data of the measured Band neighborhood The reflectivity correction value at the corresponding wavelength of each band is about The first-order difference of the mixed spectrum data is used to discretize the data after the reflectivity correction value is obtained. The degree of dispersion is obtained after the standard deviation is calculated. The degree of dispersion is related to the first-order difference of the mixed spectrum data. The degree of drift correction at the corresponding wavelength of the band Negative correlation, the higher the degree of dispersion, the less smooth the mixed spectral data is, and the smaller the corresponding drift correction is; on the contrary, the lower the standard deviation of the first-order difference of the reflectance correction value at the corresponding wavelength of other bands in the neighborhood of a band, the lower the degree of dispersion, which means that the mixed spectral data is smoother and the corresponding drift correction is greater.

[0070] Since the spectral reflectance characteristics of different materials in highway tunnels vary in different wavelength ranges, some materials may show strong absorption or reflection characteristics in specific wavelength ranges, resulting in a more obvious slope effect in these wavelength ranges. In the traditional envelope removal method, it only obtains the maximum points of each reflectance in a single spectral data, and uses the line between any two maximum points as the upper envelope of the spectral data for analysis. This method does not take into account the amount of information contained in the spectral data in different bands. When there are many maximum points in the band interval with a high degree of mineral alteration response, the envelope will be too close to the original spectral data, making it impossible to display the reflectance information of the band with a high degree of mineral alteration response after removing the envelope.

[0071] Therefore, after obtaining the drift correction degree at the corresponding wavelength of each band, further, according to the drift correction degree at the corresponding wavelength of the band where any two adjacent reflectivity maximum points are located, the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points is obtained.

[0072] The envelope acquisition module 105 is used to acquire the upper envelope of the mixed spectrum data according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points.

[0073] Among them, according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points, the upper envelope of the mixed spectral data is obtained specifically as follows: first, according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points and the number of two adjacent reflectivity maximum points in all bands, the overall average drift correction degree between any two adjacent reflectivity maximum points in all bands is obtained; then, according to the relationship between the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points and the overall average drift correction degree between any two maximum points in all bands, the connecting line segment of the upper envelope of the mixed spectral data is obtained.

[0074] In this embodiment, the calculation formula for the overall average drift correction degree between any two adjacent reflectivity maximum points can be expressed as:

[0075]

[0076] In the formula, z represents the Mixed spectral data of measurements; Indicates the number of selected reflectivity maximum points; Represents the number of two adjacent reflectivity maximum points; Indicates The wavelength corresponding to the maximum reflectivity point; Indicates The wavelength corresponding to the maximum reflectivity point; Indicates band The degree of drift correction under Indicates band The degree of drift correction under It represents the overall average drift correction degree between any two adjacent reflectivity maximum points.

[0077] In the calculation formula for the overall average drift correction degree between any two adjacent reflectivity maximum points constructed above, Indicated in With The average drift correction degree within the wavelength interval corresponding to two adjacent maximum points is traversed through the average drift correction degrees of all wavelength intervals corresponding to two adjacent reflectivity maximum points, and the overall average drift correction degree between any two adjacent reflectivity maximum points can be obtained.

[0078] When the average drift correction degree of the wavelength interval corresponding to two adjacent reflectivity maximum points is large, it means that the discrete degree of the wavelength reflectivity correction value is lower, and a smaller envelope line segment length is selected within the interval, and the information loss is smaller, so a smaller envelope line segment length should be selected; conversely, if the average drift correction degree of the wavelength interval corresponding to two adjacent reflectivity maximum points is small, it means that the discrete degree of the wavelength reflectivity correction value is higher, and a larger envelope line length is selected within the interval, and the information loss is smaller, so a larger envelope line segment length should be selected.

[0079] In this embodiment, according to the relationship between the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points and the overall average drift correction degree between any two maximum points in all bands, the connecting line segment of the upper envelope of the mixed spectral data is obtained as follows: the wavelength intervals corresponding to the adjacent reflectivity maximum points of all mixed spectral data are obtained and these wavelength intervals are arranged in order from small to large according to the wavelength, and are respectively recorded as the first wavelength interval, the second wavelength interval...the Mth wavelength interval; if the average drift correction degree within the first wavelength interval is greater than or equal to the overall average drift correction degree between any two maximum points in all bands, the line between the reflectivity maximum points at both ends of the first wavelength interval is recorded as the connecting line segment of the first envelope; if the average drift correction degree within the first wavelength interval is less than the overall average drift correction degree between any two maximum points in all bands, the connecting line between the reflectivity maximum points at both ends of the first wavelength interval is recorded as the connecting line segment of the first envelope. Average drift correction degree, calculate the sum of the average drift correction degrees of the first wavelength interval and the second wavelength interval, if the sum of the average drift correction degrees is greater than or equal to the overall average drift correction degree between any two maximum points in all bands, record the line between the reflectivity maximum points at both ends of the first wavelength interval and the second wavelength interval as the connecting line segment of the first envelope; if the sum of the average drift correction degrees of the first wavelength interval and the second wavelength interval is less than the overall average drift correction degree between any two maximum points in all bands, further calculate the sum of the average drift correction degrees of the first wavelength interval, the second wavelength interval, and the third wavelength interval, and so on, until the sum of the average drift correction degrees in multiple intervals is greater than or equal to the overall average drift correction degree between any two maximum points in all bands, and then obtain the connecting line segment of the first envelope. For the multiple maximum points remaining after the above steps, continue to follow the above steps to obtain the connecting line segments of the second envelope line, the connecting line segments of the third envelope line...the connecting line segments of the Qth envelope line in sequence, and connect the connecting line segments of the first envelope line, the connecting line segments of the second envelope line, the connecting line segments of the third envelope line...the connecting line segments of the Qth envelope line in sequence to obtain the upper envelope line segments of the final spectral data.

[0080] For example, the multiple maximum points of a spectrum data are a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, and the corresponding wavelength ranges are , , , , , , , , According to the above-mentioned method for obtaining the upper envelope line segment of spectral data, the multiple envelope line segments obtained are [a1, a3], [a3, a6], [a6, a7], and [a7, a10] respectively. Then these four segments are connected in sequence to form the upper envelope line segment of the final spectral data.

[0081] Furthermore, it is necessary to obtain the upper envelope value of the mixed spectral data according to the upper envelope segment of the final spectral data.

[0082] The upper envelope value of the mixed spectral data is specifically obtained by: obtaining the upper envelope value of the mixed spectral data according to the slope of the connecting line segments of each upper envelope and the reflectivity of the mixed spectral data at each wavelength.

[0083] In this embodiment, the upper envelope value calculation formula of the constructed mixed spectrum data can be expressed as:

[0084]

[0085] In the formula, The first segment of the upper envelope of the final spectral data is represented by The wavelength of the band corresponding to the maximum value of each spectral data; The first segment of the upper envelope of the final spectral data is represented by The wavelength of the band corresponding to the maximum value of each spectral data; The wavelength representing the mixed spectral data; express The mixed spectral data of the measurements are at wavelength The reflectivity at express The mixed spectral data of the measurements are at wavelength The reflectivity at The wavelength representing the mixed spectral data The upper envelope value of the lower envelope.

[0086] In the above-mentioned upper envelope value calculation formula of the mixed spectrum data, according to the linear function calculation formula, express The mixed spectral data of the measurements are at wavelength The slope between the corresponding reflectances, Indicates the corresponding The difference interval corresponds to the reflectance value interval corresponding to the upper envelope segment of the final spectral data, Represents the wavelength of the final mixed spectral data The upper envelope value of the lower envelope.

[0087] Furthermore, the envelope removal result is specifically: obtaining the envelope removal result of the mixed spectral data according to the ratio between the reflectivity of the mixed spectral data at each wavelength and the upper envelope value of the mixed spectral data.

[0088] According to the envelope removal method, the calculation formula for removing the envelope removal result of the mixed spectral data can be expressed as:

[0089]

[0090] In the formula, Indicates The mixed spectral data of the measurements are at wavelength The reflectivity at Indicates The mixed spectral data of the measurements are at wavelength The upper envelope value at ; Indicates the The mixed spectral data of the measurements are at wavelength Envelope removal result at .

[0091] Furthermore, the highway tunnel detection system provided in this embodiment also includes an alteration detection module 106, which is used to perform mineral alteration anomaly detection on the mixed spectral data after the envelope is removed based on the upper envelope, and obtain the location of defects in the tunnel.

[0092] Among them, the method for performing mineral alteration anomaly detection on the spectral data after the envelope line is removed and obtaining the location of defects in the tunnel is specifically as follows: the spectral data after the envelope line is removed is subjected to a continuous projection algorithm to perform feature extraction of multiple characteristic bands; anomaly detection is performed on the extracted multiple spectral feature data by an isolation forest algorithm; a first threshold value of the anomaly score is preset, and when the anomaly score corresponding to the spectral data feature at a certain position is greater than or equal to the first threshold value, the spectral data at the corresponding position is abnormal; and the corresponding position in the tunnel is marked as a defect position.

[0093] Specifically, based on the spectral data after the envelope removal result, the successive projections algorithm (SPA) is used to extract the features of multiple characteristic bands, and then the traditional isolation forest algorithm is used to perform anomaly detection on the extracted multiple spectral feature data. The first threshold of the abnormality score is preset as a constant of 0.8. When the first threshold of the abnormality score is ≥0.8, the spectral data at the corresponding position is abnormal. The system marks the location and degree of defects in the tunnel, providing a reference for the subsequent maintenance and repair of highway tunnels.

[0094] The above-mentioned highway tunnel detection system for highway engineering provided by this embodiment can identify the correlation strength between different bands and the material to be detected by deeply analyzing the relationship between spectral data at different positions, retain the information of spectral data in the altered area, and help to construct the envelope more accurately, avoid mistakenly removing key defect information as background noise, ensure that the constructed envelope is more accurate, effectively avoid the loss of key defect information, and improve the accuracy of subsequent detection; in addition, by analyzing the relationship between spectral data and the material to be detected, dynamically adjust the parameters of envelope removal to ensure the accuracy and flexibility of the envelope removal process. This dynamic adjustment mechanism helps to adapt to different types of tunnel materials and environmental conditions, and enhances the robustness and adaptability of the detection system. This embodiment can ensure that the preprocessing of highway tunnel spectrum data is more reliable, avoid the loss of some key information, and further improve the accuracy of subsequent highway tunnel detection.

[0095] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A highway tunnel detection system for highway engineering, characterized in that: The system comprises: A spectral data acquisition module, used to acquire mixed spectral data in the tunnel and standard spectral data of different minerals in the tunnel; A mineral alteration response degree acquisition module is used to obtain the mineral alteration response degree at the corresponding wavelength of each band of the mixed spectral data based on the minimum reflectance value of the standard spectral data; A reflectivity correction module is used to obtain reflectivity correction values ​​at corresponding wavelengths of other bands in the neighborhood of each band according to the mineral alteration response degree at corresponding wavelengths of other bands in the neighborhood of each band; The drift correction degree acquisition module is used to obtain the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points according to the reflectivity correction values ​​of other bands in the neighborhood of each band at the corresponding wavelengths; An upper envelope acquisition module is used to obtain the upper envelope of the mixed spectrum data according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points; An alteration detection module is used to perform mineral alteration anomaly detection on the mixed spectrum data after the envelope is removed based on the upper envelope, and obtain the location of defects in the tunnel; The method of taking the minimum reflectivity value of the standard spectral data as the standard to obtain the mineral alteration response degree of different minerals in the tunnel at the wavelength corresponding to each band is specifically as follows: according to the ratio of the minimum reflectivity value of each mineral in the standard spectral data to the reflectivity of the mixed spectral data corresponding to the mineral in the highway tunnel at the wavelength corresponding to each band, the mineral alteration response degree at the wavelength corresponding to each band of the mixed spectral data is obtained; The obtaining of the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band according to the mineral alteration response degree at the corresponding wavelength of other bands in the neighborhood of each band is specifically as follows: obtaining the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band according to the reflectivity at the corresponding wavelength of other bands in the neighborhood of each band of the mixed spectral data, the mineral alteration response degree, and the average of the reflectivity of multiple other bands in the neighborhood of each band; The greater the mineral alteration response degree at the corresponding wavelengths of other bands in the neighborhood of each band, the greater the difference between the mean reflectivity of multiple other bands in the neighborhood of each band and the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band, and the greater the correction of the reflectivity at the corresponding wavelengths of other bands in the neighborhood of each band of the mixed spectral data; The method of obtaining the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points according to the reflectivity correction values ​​of other bands corresponding to wavelengths in the neighborhood of each band is specifically as follows: According to the standard deviation of the first-order difference of the reflectivity correction value at the corresponding wavelength of other bands in the neighborhood of each band, the drift correction degree at the corresponding wavelength of each band is obtained; According to the drift correction degree at the wavelength corresponding to the wavelength band where any two adjacent reflectivity maximum value points are located, the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum value points is obtained; The upper envelope of the mixed spectrum data is obtained according to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points: According to the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectivity maximum points and the number of two adjacent reflectivity maximum points in all bands, the overall average drift correction degree between any two adjacent reflectivity maximum points in all bands is obtained; According to the relationship between the average drift correction degree of the wavelength interval corresponding to any two adjacent reflectance maximum points and the overall average drift correction degree between any two maximum points in all bands, the connecting line segment of the upper envelope of the mixed spectral data is obtained.

2. A highway tunnel detection system for highway engineering according to claim 1, characterized in that: The method for obtaining the mixed spectral data in the tunnel and the standard spectral data of different minerals in the tunnel is specifically: Sampling points are set at equal distances along the highway tunnel, and mixed spectral data of minerals in the highway tunnel at different positions are collected using a spectrometer; Analyze the geological conditions in the highway tunnel, obtain the mineral information in the highway tunnel, build a spectral library for the tunnel site, and obtain the standard spectral data corresponding to different minerals in the highway tunnel in the spectral library for the tunnel site.

3. A highway tunnel detection system for highway engineering according to claim 1, characterized in that: The envelope removal result is specifically: obtaining the envelope removal result of the mixed spectrum data according to the ratio between the reflectivity of the mixed spectrum data at each wavelength and the upper envelope value of the mixed spectrum data.

4. A highway tunnel detection system for highway engineering according to claim 3, characterized in that: The upper envelope value of the mixed spectral data is specifically: The upper envelope value of the mixed spectral data is obtained according to the slope of the connecting line segments of each upper envelope and the reflectivity of the mixed spectral data at each wavelength.

5. A highway tunnel detection system for highway engineering according to claim 1, characterized in that: The method for performing mineral alteration anomaly detection on the spectral data after the envelope is removed based on the upper envelope to obtain the location of defects in the tunnel is specifically as follows: The spectral data after the envelope removal is subjected to the continuous projection algorithm to extract the features of multiple characteristic bands; The extracted multiple spectral feature data are used for anomaly detection through isolation forest algorithm; A first threshold value of the abnormality score is preset, and when the abnormality score corresponding to the spectral data feature at a certain position is greater than or equal to the first threshold value, the spectral data at the corresponding position is abnormal; The position in the corresponding tunnel is marked as the defect position.

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