Tank internal defect detection method and system

Abstract

The invention relates to the technical field of defect detection, in particular to a tank internal defect detection method and system.The deviation degree of each wavelength on a detection spectrum is accurately quantified by analyzing the difference between the detection spectrum and a baseline spectrum; further deeply analyzing the group discreteness of the detection spectrum through the difference between the detection spectrum of the detection point and the detection spectrum of other detection points; according to the difference between any wave band and other wave bands in the detection spectrum, the abnormal degree of each wave band in the detection spectrum is evaluated carefully; the correlation of the wave band pairs with intersection in the detection spectrums of two adjacent detection points is combined, and the abnormal coincidence degree of the wave band pairs is fully considered; and finally, a plurality of target wavelength sections are identified, the longitudinal performance specific conditions in the target wavelength sections are combined, and the sensitivity degree of the target wavelength sections is analyzed, so that the internal defects of the tank body can be quickly and accurately positioned, and the detection efficiency and reliability are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of defect detection, and in particular to a method and system for detecting defects inside a tank. Background Art

[0002] In industrial production, tanks serve as critical containers for the storage and transportation of liquids, gases, and other media. Their structural integrity and safety are directly linked to product quality and public safety. Corrosion on the tank's inner wall, residual media, and other issues can lead to abnormal material composition within the tank. These hazards are easily missed during traditional visual inspections or random destructive testing, posing potential risks to the tank's sealing and durability.

[0003] In this context, detection technology based on spectral analysis can non-contact and highly accurately characterize the material composition distribution, defect morphology and contaminant residue by acquiring the spectral curves of several detection points in the internal area of ​​the tank in real time - that is, the continuous response characteristics of the material's reflectivity, absorption rate and transmittance to light of different wavelengths, thereby achieving full coverage screening and quantitative evaluation of tiny defects.

[0004] Spectroscopic technology can identify defects or anomalies within a material by analyzing its absorption, reflection, or emission characteristics for light of different wavelengths. In existing technologies, known defects are mapped to specific wavelengths, reflecting the various defects of the can. However, the detection spectrum contains overall spectral characteristics and is influenced by a variety of factors. Directly analyzing the spectral curve at a fixed detection wavelength while ignoring the correlation between wavelengths makes it difficult to accurately analyze defects. Furthermore, in the detection spectra of two detection points, the detection areas may overlap, and the spectral data will also contain detection spectra corresponding to the same area, thus interfering with the identification of the corresponding wavelength range of the spectral data. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method and system for detecting internal defects of a tank.

[0006] According to a first aspect of an embodiment of the present invention, a method for detecting internal defects of a tank is provided, and the technical solution adopted is specifically as follows:

[0007] Collect the test spectrum at the inspection point of the tank body and the baseline spectrum of the defect-free area;

[0008] Analyzing the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum;

[0009] Analyzing the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection points;

[0010] Analyzing the difference between any waveband in the detection spectrum and other wavebands to obtain the abnormality degree of each waveband in the detection spectrum;

[0011] Analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and obtain the abnormal overlap degree of the band pairs in combination with the abnormal degree of the bands;

[0012] Analyze the wavelength intersection range of the detection spectra of any two detection points to obtain the target wavelength band;

[0013] The sensitivity of the target wavelength band is obtained by combining the deviation, the group discreteness, the abnormality degree and the abnormal overlap degree to complete defect detection.

[0014] In some embodiments of the present invention, analyzing the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum includes:

[0015] For each wavelength, the reflectivity difference between the detection spectrum and the baseline spectrum is analyzed, as well as the difference between the reflectivity of the detection spectrum at each wavelength and the mean reflectivity of the detection spectrum is analyzed. Combined with the reflectivity stability of the baseline spectrum, the deviation at each wavelength on the detection spectrum is obtained.

[0016] In some embodiments of the present invention, analyzing the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection points includes:

[0017] For each detection point, the difference between the reflectivity of the detection spectrum of the detection point at each wavelength and the mean reflectivity of the detection spectra of all other detection points at the corresponding wavelength is analyzed. Combined with the reflectivity stability of the detection spectra of all detection points at the corresponding wavelength, the group discreteness of the detection spectrum of the detection point is obtained.

[0018] In some embodiments of the present invention, analyzing the difference between any wavelength band in the detection spectrum and other wavelength bands to obtain the abnormality degree of each wavelength band in the detection spectrum includes:

[0019] In the detected spectrum, all bands are located using a peak detection algorithm;

[0020] Obtaining the dominance of the band according to the band width and band curvature in the detection spectrum;

[0021] For each detection point, the difference between the reflectivity of the detection spectrum at the extreme point of each band and the mean reflectivity of the detection spectrum at the extreme points of all bands is analyzed, and combined with the dominance, the abnormality degree of each band in the detection spectrum is obtained.

[0022] In some embodiments of the present invention, obtaining the dominance of the band according to the band width and band curvature in the detection spectrum includes:

[0023] Obtaining the curvature at each wavelength corresponding to the wavelength band in the detection spectrum to obtain a curvature sequence of the wavelength band;

[0024] Calculating the mean curvature of the curvature sequence of the band, and calculating the mean curvature difference between all two adjacent data points in the band, to obtain the slowness of the change trend of the band;

[0025] Obtaining a band width according to a wavelength range corresponding to the band;

[0026] The dominance of the band is obtained by combining the slowness of the change trend with the width of the band.

[0027] In some embodiments of the present invention, analyzing the correlation of intersecting waveband pairs in the detection spectra of two adjacent detection points, and combining the abnormality degree of the wavebands to obtain the abnormal overlap degree of the waveband pairs includes:

[0028] In the detection spectra of any two adjacent detection points, the wavelength ranges corresponding to all the bands are obtained respectively, and a number of band pairs with overlapping wavelength ranges are obtained;

[0029] Obtaining the wavelength intersection range of the band pair, and combining the larger value of the wavelength ranges corresponding to the two bands in the band pair to obtain the wavelength overlap degree of the band pair;

[0030] Calculating the Pearson correlation coefficient between the two wavelengths in the wavelength pair, and combining the wavelength overlap degree to obtain the correlation of the wavelength pair;

[0031] According to the correlation, combined with the average of the abnormality levels corresponding to the two bands in the band pair, the abnormal overlap level of the band pair is obtained.

[0032] In some embodiments of the present invention, analyzing the wavelength intersection range of the wavelength bands in the detection spectra of any two detection points to obtain the target wavelength band includes:

[0033] Among all the bands in the detection spectra of all detection points, when two bands have an intersection and the intersection is greater than half of the wavelength range of any one of the two bands, the wavelength ranges corresponding to the two bands are merged to obtain several target wavelength bands.

[0034] In some embodiments of the present invention, the sensitivity of the target wavelength band is obtained by combining the deviation, the group discreteness, the abnormality degree, and the abnormality overlap degree, and defect detection is performed on the tank body, including:

[0035] Obtaining the longitudinal anisotropy of each target wavelength band according to the standard deviation of the deviation corresponding to each wavelength in the target wavelength band and the standard deviation of the band width corresponding to all wavelength bands in the target wavelength band;

[0036] Obtaining a sensitivity coefficient for each detection point according to the population discreteness corresponding to the detection point, the abnormality degree of the band within the target wavelength band of the detection point, and the abnormal overlap degree of the band pairs within the target wavelength band of the detection point;

[0037] Traversing the detection points included in the target wavelength band, calculating the sensitivity coefficient, and combining the longitudinal anisotropy of the band to obtain the sensitivity of the target wavelength band;

[0038] According to the sensitivity, combined with the reflectivity of the band in the target wavelength band, defect detection is performed on the tank body.

[0039] According to a second aspect of an embodiment of the present invention, a tank internal defect detection system is provided, comprising: a memory and a processor, wherein:

[0040] The memory is used to store program code;

[0041] The processor is configured to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0042] In some embodiments of the present invention, the processor includes:

[0043] Spectral data acquisition module, used to collect the detection spectrum at the inspection point of the tank body and the baseline spectrum of the defect-free area;

[0044] a deviation analysis module, configured to analyze the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum;

[0045] a spectrum group discreteness analysis module, configured to analyze the difference between the detection spectra of the detection point and other detection points, and obtain the group discreteness of the detection spectra of the detection point;

[0046] a band anomaly degree analysis module, configured to analyze the difference between any band in the detection spectrum and other bands, and obtain the degree of anomaly of each band in the detection spectrum;

[0047] The module for analyzing the abnormal overlap degree of band pairs is used to analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and to obtain the abnormal overlap degree of the band pairs in combination with the abnormal degree of the bands;

[0048] The target wavelength band identification module is used to analyze the intersection range of the wavelength bands in the detection spectra of any two detection points to obtain the target wavelength band;

[0049] The target wavelength band sensitivity analysis module is used to combine the deviation, the group discreteness, the abnormality degree and the abnormality overlap degree to obtain the sensitivity of the target wavelength band and complete defect detection.

[0050] Compared with the existing technology, the present invention provides a method and system for detecting internal defects of a tank body, which has the following beneficial effects:

[0051] The present invention first establishes a baseline spectrum of a defect-free sample to accurately quantify the degree of deviation of the detection spectrum wavelength, thereby providing a benchmark for anomaly detection; and then, due to the complex spectral feature redundancy of the detection spectrum, the difference between the detection spectrum of the detection point and other detection points is used to deeply analyze the group discreteness of the detection spectrum of each detection point, and the data distribution characteristics are mined; on this basis, the difference between any band in the detection spectrum and other bands is used to carefully evaluate the degree of anomaly of a single spectral band, and capture local subtle changes; and combined with the correlation of the intersecting band pairs in the detection spectra of two adjacent detection points, the overlap of a small part of the area between the detection points is fully considered to ensure data integrity and analysis accuracy; finally, several target wavelength bands are successfully identified, combined with the longitudinal performance specificity within the target wavelength band, and its sensitivity is analyzed, so that the internal defects of the tank can be located quickly and accurately, the detection efficiency and reliability can be significantly improved, and the safety hazards and economic losses caused by missed detection and false detection due to traditional detection methods can be effectively avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. 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 any creative work.

[0053] Figure 1 A schematic diagram of the basic flow of a method for detecting internal defects of a tank provided by one embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a baseline spectrum curve of a defect-free, normal qualified area provided by one embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a detection spectrum curve of a detection point provided by an embodiment of the present invention;

[0056] Figure 4A schematic diagram of detection spectrum curves of two adjacent detection points provided by one embodiment of the present invention;

[0057] Figure 5 A schematic diagram of the basic components of a tank internal defect detection system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0058] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a method and system for detecting internal defects in tanks according to the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. Terms such as "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further limitations, the phrase "comprising a ..." to define an element does not preclude the presence of other identical elements in the article or device comprising the element.

[0060] The specific scheme of the method for detecting internal defects of a tank body provided by the present invention is described in detail below with reference to the accompanying drawings.

[0061] See also Figure 1 , which shows the basic process of a tank internal defect detection method provided by an embodiment of the present invention.

[0062] like Figure 1 As shown, an embodiment of the present invention provides a method for detecting internal defects of a tank, specifically comprising:

[0063] S100: Collect the detection spectrum at the inspection point of the tank body and the baseline spectrum of the defect-free area.

[0064] Select several detection points inside the tank, use a fiber optic probe or linear array CCD spectrometer to collect arc spectra, covering the ultraviolet-visible-near infrared band (200-1100nm); and use a diffuse reflection light source (such as a bowl-shaped LED) to suppress the high reflective interference of the tank; obtain the reflectivity detection spectrum curve at each detection point, where the x-axis is the spectrum wavelength in nm and the y-axis is the reflectivity in %. Figure 2 shown.

[0065] Also, collect the baseline spectrum curve of the defect-free normal qualified area as a reference for the normal state, such as Figure 2 shown.

[0066] S200: Analyze the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum.

[0067] Reflectivity reflects the ability of a material surface to reflect incident light. Defects (such as cracks and oxidation) will change the surface morphology and composition, resulting in an abnormal reflectivity spectrum. Therefore, when the detection point is located in the defect section, there will be a large difference in the reflectivity value between the detection spectrum and the baseline spectrum at a certain wavelength.

[0068] Based on the above analysis, in an embodiment of the present invention, the deviation at each wavelength on the detection spectrum is obtained by analyzing the difference between the detection spectrum and the baseline spectrum. Specifically, for each wavelength, the reflectivity difference between the detection spectrum and the baseline spectrum is analyzed, and the difference between the reflectivity of the detection spectrum at each wavelength and the reflectivity mean of the detection spectrum is analyzed. Combined with the reflectivity stability of the baseline spectrum, the deviation at each wavelength on the detection spectrum is obtained. The calculation formula for the deviation at wavelength x on the detection spectrum is constructed as follows:

[0069]

[0070] Where, F x Indicates the deviation of the detection spectrum at wavelength x; f x represents the reflectance value of the detection spectrum at wavelength x; f 0x Indicates the reflectance value of the baseline spectrum at wavelength x; Δf x It represents the difference between the reflectance value of the detection spectrum at wavelength x and the mean reflectance of the detection spectrum at all wavelengths; σ(f0) represents the standard deviation of the reflectance of the baseline spectrum at all wavelengths; ε represents a constant, which can be taken as 0.1 to prevent the denominator from being 0.

[0071] In the detection spectrum, when the reflectance value difference between the detection spectrum and the baseline spectrum at wavelength x (|f x -f 0x |) is larger, and the difference (Δf x ) is larger, the greater the deviation between the detection spectrum and the baseline spectrum at wavelength x; and when the baseline spectrum presents a more stable reflectance distribution, that is, the smaller the standard deviation (σ(f0)) of the baseline spectrum is, the greater the deviation of the abnormal distribution of the reflectance value of the detection spectrum at wavelength x.

[0072] S300: Analyze the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection points.

[0073] Among all the selected detection points, the more significant the abnormal difference between the spectral data of the detection point and the spectral data of the other detection points, the more likely the location of the detection point is within the abnormal range inside the tank.

[0074] Therefore, in an embodiment of the present invention, the group discreteness of the detection spectrum of the detection point is obtained by analyzing the difference between the detection spectrum of the detection point and other detection points. Specifically, the group discreteness of the detection spectrum of each detection point can be determined based on the difference in reflectance values ​​at different wavelengths between the spectral curves; therefore, for each detection point, the difference between the reflectance of the detection spectrum of the detection point at each wavelength and the mean reflectance of the detection spectra of all other detection points at the corresponding wavelength is analyzed, and the group discreteness of the detection spectrum of the detection point is obtained by combining the reflectance stability of the detection spectra of all detection points at the corresponding wavelength. The formula for calculating the group discreteness of the detection spectrum of the detection point is constructed as follows:

[0075]

[0076] Where, L a represents the population discreteness of the detection spectrum of detection point a; f a (λ x ) represents the reflectivity value at wavelength x in the detection spectrum of detection point a; f(λ x ) represents the mean reflectivity value of all detection points at wavelength x; σ f (λ x ) represents the standard deviation of the reflectance of all detection points at wavelength x; n represents the number of all wavelengths in the detection spectrum of detection point a; ε represents a constant, which can be taken as 0.1 to prevent the denominator from being 0.

[0077] When f a (λ x )-f(λ x ) value is larger, that is, when the difference between the reflectance value at each wavelength in the detection spectrum of the detection point a and the overall reflectance value at the wavelength is larger, the group discreteness of the detection spectrum of the detection point is stronger; and when σ f (λ x ) value is larger, that is, when the standard deviation of the reflectance values ​​of all detection points at a certain wavelength is larger, the reflectance value at this wavelength is more unstable and the group discreteness is stronger.

[0078] S400: Analyze the difference between any waveband in the detection spectrum and other wavebands to obtain the abnormality degree of each waveband in the detection spectrum.

[0079] At any inspection point, the spectrometer emits and detects the recovered light. Within the inspection area, there may be qualified cans or defects. The spectral data from a single monitoring point should contain several bands, representing reflections at different wavelengths within the inspection area, or, in other words, different content areas. A sudden increase or decrease in reflectivity at a specific wavelength range that significantly deviates from the overall reflectivity is considered an abnormal band signal.

[0080] Among all the bands in the detection spectrum of a detection point, the main area of ​​the tank body should be reflected in the detection spectrum data corresponding to the band with a larger wavelength range, and the trend of the band shows a slow change. Therefore, for any band of a detection point, it is analyzed whether the corresponding wavelength range of each band in the tank body is more likely to be the qualified area of ​​the tank body, such as Figure 3 As shown, the more dominant the A band is, the more likely it is to be the wavelength band corresponding to the qualified area of ​​the tank.

[0081] Based on the above analysis, in an embodiment of the present invention, the abnormality degree of each band in the detection spectrum is obtained by analyzing the difference between any band in the detection spectrum and other bands. Further including:

[0082] First, in the detection spectrum at the detection point, all bands are located using a peak detection algorithm.

[0083] Then, the dominance of the band is obtained based on the band width and band curvature in the detection spectrum. Specifically, the curvature at each wavelength corresponding to the band in the detection spectrum is obtained to obtain the curvature sequence of the band; the curvature mean of the curvature sequence of the band is calculated, and the mean of the curvature difference between all two adjacent data points in the band is calculated to obtain the slowness of the band's change trend; the band width is obtained based on the wavelength range corresponding to the band; the dominance of the band is obtained by combining the slowness of the change trend and the band width. The calculation formula for the dominance of band y in the detection spectrum is constructed as follows:

[0084]

[0085] Where, D(λ′ y ) represents the dominance of band y in the detection spectrum; w(λ′ y ) represents the bandwidth of band y in the detection spectrum; k(λ′ y ) represents the mean value of all curvatures in the curvature sequence corresponding to the band y in the detection spectrum; Δk(λ′ y ) represents the mean value of the difference between two adjacent curvature values ​​(the absolute value of the difference between two adjacent curvature values) in the curvature sequence corresponding to the band y in the detection spectrum.

[0086] When the width of the band y is wider, that is, w(λ′ y) value is larger, indicating that the wavelength range corresponding to band y is larger, and its dominance is stronger; and since the detection spectrum data corresponding to the qualified tank area with strong dominance should present a slowly changing band, the smaller the curvature of all data points in band y of the detection spectrum, that is, k(λ′ y ) value is smaller, and the curvature difference between two adjacent data points is smaller, that is, Δk(λ′ y ) value is smaller, the more dominant the corresponding band is.

[0087] Finally, among all the bands in the detection spectrum of a detection point, the stronger the dominance of the band, that is, the more likely its corresponding wavelength range is to be the spectrum manifestation within the qualified area of ​​the detection point, and therefore the worse the dominance of the band, the greater the degree of band anomaly of the single spectrum. And in the detection spectrum of a detection point, the smaller the reflectivity value of the band, and the more prominent the reflectivity value of a certain band in the detection spectrum of the detection point, the higher the degree of anomaly. Therefore, for each detection point, the degree of difference between the reflectivity of the detection spectrum at the extreme point of each band and the mean reflectivity of the detection spectrum at the extreme points of all bands is analyzed, and combined with the dominance, the degree of anomaly of each band in the detection spectrum is obtained. The calculation formula for the degree of anomaly of band y in the detection spectrum of detection point a is constructed as follows:

[0088]

[0089] Where Y a (λ′ y ) represents the abnormality of band y in the detection spectrum of detection point a; f a (λ′ y ) represents the reflectance value of the detection spectrum of detection point a at the extreme point of band y; represents the mean reflectivity of all extreme points in the detection spectrum of detection point a; D(λ′ y ) represents the dominance of band y in the detection spectrum; ε represents a constant, and in order to prevent the denominator from being 0, the value can be 0.1.

[0090] The smaller the reflectivity value at the extreme point of the band, and the more deviated the overall reflectivity value at the extreme points of all bands in the detection spectrum of the detection point, the higher the degree of abnormality; the lower the dominance of the wavelength range corresponding to the band, the higher the degree of abnormality of the band.

[0091] In this way, the abnormality degree of all bands in the detection spectrum of all detection points is obtained, and the wavelength range of the corresponding bands is obtained.

[0092] S500: analyzing the correlation of the intersecting band pairs in the detection spectra of two adjacent detection points, and combining the abnormality degree of the bands to obtain the abnormal overlap degree of the band pairs.

[0093] Since the monitoring areas of the detection points may overlap when performing spectral detection on the inside of the tank, the possibility of overlap of the detection areas between adjacent monitoring points is considered. When overlap occurs, there will be a strong correlation between the intersecting band pairs, and the wavelength intersection range will be larger.

[0094] Based on the above analysis, in an embodiment of the present invention, by analyzing the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, combined with the abnormal degree of the bands, the abnormal overlap degree of the band pairs is obtained. Specifically, in the detection spectra of any two adjacent detection points, the wavelength ranges corresponding to all the bands are obtained respectively, and several band pairs with intersections in the wavelength ranges are obtained (the two bands in a band pair come from two adjacent detection points respectively), such as Figure 4 As shown in the figure, the wavelength intersection range of the band pair is obtained, and the wavelength overlap degree of the band pair is obtained by combining the larger value of the wavelength range corresponding to the two bands in the band pair; the Pearson correlation coefficient between the two bands in the band pair is calculated, and the correlation of the band pair is obtained by combining the wavelength overlap degree; based on the correlation, the abnormal degree of the two bands in the band pair is combined with the average value of the abnormal degree to obtain the abnormal overlap degree of the band pair. The calculation formula for the abnormal overlap degree of the band pair is constructed as follows:

[0095]

[0096] Where H represents the abnormal overlap degree of the band pair; J a,b (λ′) represents the intersection of the wavelength ranges corresponding to the two bands a and b in the band pair; max(λ′) represents the larger value of the wavelength ranges of the two bands a and b in the band pair; ρ a,b (λ′) represents the Pearson correlation coefficient of the two bands a and b in the band pair; Indicates the mean of the abnormality of the two bands a and b in the band pair.

[0097] In the detection spectra of two adjacent detection points, when the relative wavelength ranges of the two bands intersect The larger the value, the larger the Pearson correlation coefficient between the two bands (ρ a,b (λ′)), the stronger the correlation of the waveforms, the more likely they are to overlap; and at this time, the overlap of the corresponding bands of the qualified area of ​​the tank should be eliminated, so when the average abnormality of the two bands in the band pair is The larger the value is, the greater the abnormal overlap of the band pair.

[0098] S600: Analyze the wavelength intersection range of the wavelength bands in the detection spectra of any two detection points to obtain the target wavelength band.

[0099] Among all the wavelength bands in the detection spectra of all detection points, when two wavelength bands intersect and the intersection is greater than half of the wavelength range of either wavelength band, the wavelength ranges corresponding to the two wavelength bands are merged, thereby obtaining several target wavelength bands on the wavelength coordinate axis of the detection spectrum curve. It should be noted that the wavelength bands of the several detection points that meet the merging conditions may be two or more.

[0100] S700: By combining the deviation, group discreteness, abnormality, and abnormality overlap, the sensitivity of the target wavelength band is obtained to complete defect detection.

[0101] The greater the abnormality of the target wavelength band corresponding to the wavelength band at all detection points, and the stronger the group discreteness of the detection spectrum of the corresponding detection point, the stronger the sensitivity of the detection point in the corresponding target wavelength band.

[0102] Therefore, in the embodiment of the present invention, by combining the deviation, group discreteness, abnormality and abnormal overlap, the sensitivity of the target wavelength band is obtained to complete the defect detection.

[0103] First, to determine the sensitive wavelength range for the target wavelength band on the wavelength coordinate axis of the detection spectrum, it is necessary to analyze the longitudinal differences within each band within the target wavelength band. Specifically, for a particular monitoring point within the target wavelength band, the greater its significant deviation from all longitudinal bands, the greater its sensitivity for that target wavelength band. Therefore, the longitudinal anisotropy within each target wavelength band is derived by combining the standard deviation of the deviations for each wavelength within the target wavelength band with the standard deviation of the band widths for all bands within the target wavelength band.

[0104]

[0105] Where Z b represents the longitudinal anisotropy of the band within the target wavelength band b; σ(F) represents the standard deviation of the deviation between the detection spectrum of all detection points corresponding to each wavelength in the target wavelength band b and the baseline spectrum; σ[w(λ′)] represents the standard deviation of the band width of all bands in the target wavelength band b; ε represents a constant. In order to prevent the denominator from being 0, the value can be 0.1.

[0106] When the standard deviation of the deviation is larger, that is, the σ(Δf) value is larger, the reflectivity values ​​between the detection points within the target wavelength band are unstable, and the longitudinal anomaly within the target wavelength band is larger; when the standard deviation of the band width is smaller, that is, the σ[w(λ′)] value is smaller, the reference of the deviation of the reflectivity value of the detection spectrum band is stronger. When the standard deviation of the band width is larger, the content inside the tank reflected by the band may have different meanings, so the reference of its spectrum deviation is smaller, and the longitudinal anomaly of the band within the target wavelength band is also smaller.

[0107] Then, the sensitivity coefficient of each detection point is obtained based on the discreteness of the group corresponding to the detection point, the abnormal degree of the band within the target wavelength band of the detection point, and the abnormal overlap degree of the band pair within the target wavelength band of the detection point; and the detection points contained in the target wavelength band are traversed to calculate the sensitivity coefficient, and the sensitivity of the target wavelength band is obtained by combining the longitudinal anisotropy of the band. The sensitivity calculation formula for the target wavelength band b is constructed as follows:

[0108]

[0109] Where M b Indicates the sensitivity of the target wavelength band b; Z b Indicates the longitudinal anisotropy of the target wavelength band b; L i,b Y represents the group discreteness of the detection spectrum of the detection point i contained in the target wavelength band b; i,b (λ′ y ) represents the abnormality degree of the corresponding wavelength band within the target wavelength band b at the detection point i; (H i,b ) max Indicates the maximum value of the abnormal overlap degree of the corresponding band pair within the target wavelength band b at the detection point i; N b Indicates the number of detection points contained in the target wavelength band b.

[0110] For a target wavelength band, when the degree of abnormality of the band of the detection point within the target wavelength band is greater and the overall group discreteness of the detection spectrum of the detection point is greater, the abnormal performance of the band in the target wavelength band is more significant, and there is positive feedback on the sensitivity quantification of the target wavelength band; when there is abnormal overlap in the band, there is negative feedback on the sensitivity quantification of the target wavelength band, so the greater the abnormal overlap, the lower the sensitivity of the target wavelength band.

[0111] Thus, several target wavelength bands within the wavelength range of the entire detection spectrum and the sensitivity of each target wavelength band are obtained. The more sensitive the target wavelength band, the stronger the correlation between the spectral characteristics within the band and the tank defects, and the more likely it is that it corresponds to the characteristic wavelength band range of the defect in the detection spectrum.

[0112] All target wavelength bands are sorted from largest to smallest according to their sensitivity, forming an ordered sensitivity sequence. Among all the data, the two sensitivity data points corresponding to the maximum difference between the two adjacent sensitivity data points are found. Based on these two sensitivity data points and their left and right sides, the ordered sensitivity sequence is divided into two parts. The larger value part is recorded as the sensitive data, and the target wavelength band corresponding to the sensitive data is recorded as the sensitive wavelength band. This results in all sensitive wavelength bands and their sensitivities. Therefore, the sensitive wavelength band with the highest sensitivity corresponds to the characteristic wavelength range of the defect in the detection spectrum. The sensitive wavelength band may correspond to a defect in the tank caused by a material change due to certain factors. The location of this sensitive wavelength band is the possible location of the defect.

[0113] Finally, when performing defect detection inside the tank, the tank is inspected for defects based on the sensitivity and the reflectivity of the mid-band in the target wavelength band. Specifically, based on the sensitivity and reflectivity of the sensitive wavelength band, defect detection is performed to confirm the possible location of the defect, thereby achieving accurate identification and positioning of defects inside the tank.

[0114] See also Figure 5 , which shows the basic composition of a tank internal defect detection system provided by an embodiment of the present invention.

[0115] like Figure 5 As shown, a tank internal defect detection system includes: a memory 10 and a processor 20, wherein:

[0116] Memory 10, for storing program code;

[0117] The processor 20 is used to read the program code stored in the memory 10 and execute the acquisition of the detection spectrum at the detection point of the tank body and the baseline spectrum of the defect-free area; analyze the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum; analyze the difference between the detection spectrum of the detection point and other detection points to obtain the group discreteness of the detection spectrum of the detection point; analyze the difference between any band in the detection spectrum and other bands to obtain the degree of abnormality of each band in the detection spectrum; analyze the correlation of the band pairs with intersection in the detection spectra of two adjacent detection points, and obtain the degree of abnormal overlap of the band pairs in combination with the degree of abnormality of the bands; analyze the band intersection range of the bands in the detection spectra of any two detection points to obtain the target wavelength band; combine the deviation, group discreteness, abnormality and abnormal overlap to obtain the sensitivity of the target wavelength band to complete defect detection.

[0118] Furthermore, the processor 20 includes a spectral data acquisition module 21, a deviation analysis module 22, a spectral group discreteness analysis module 23, a band abnormality degree analysis module 24, a band pair abnormal overlap degree analysis module 25, a target wavelength band identification module 26, and a target wavelength band sensitivity analysis module 27. Among them:

[0119] Spectral data acquisition module 21, used to collect detection spectra at detection points on the tank body and baseline spectra of defect-free areas;

[0120] The deviation analysis module 22 is used to analyze the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum;

[0121] The spectrum group discreteness analysis module 23 is used to analyze the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection point;

[0122] The band abnormality degree analysis module 24 is used to analyze the difference between any band in the detection spectrum and other bands to obtain the abnormality degree of each band in the detection spectrum;

[0123] The band pair abnormal overlap degree analysis module 25 is used to analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and obtain the abnormal overlap degree of the band pairs in combination with the abnormal degree of the bands;

[0124] The target wavelength band identification module 26 is used to analyze the wavelength band intersection range of the detection spectra of any two detection points to obtain the target wavelength band;

[0125] The target wavelength band sensitivity analysis module 27 is used to combine the deviation, group discreteness, abnormality degree and abnormal overlap degree to obtain the sensitivity of the target wavelength band and complete defect detection.

[0126] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for detecting internal defects of a tank, characterized in that: The method comprises: Collect the test spectrum at the inspection point of the tank body and the baseline spectrum of the defect-free area; Analyzing the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum; Analyzing the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection points; Analyzing the difference between any waveband in the detection spectrum and other wavebands to obtain the abnormality degree of each waveband in the detection spectrum; Analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and obtain the abnormal overlap degree of the band pairs in combination with the abnormal degree of the bands; Analyze the wavelength intersection range of the detection spectra of any two detection points to obtain the target wavelength band; The sensitivity of the target wavelength band is obtained by combining the deviation, the group discreteness, the abnormality degree and the abnormal overlap degree to complete defect detection.

2. The method for detecting internal defects of a tank according to claim 1, characterized in that: Analyzing the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum includes: For each wavelength, the reflectivity difference between the detection spectrum and the baseline spectrum is analyzed, as well as the difference between the reflectivity of the detection spectrum at each wavelength and the mean reflectivity of the detection spectrum is analyzed. Combined with the reflectivity stability of the baseline spectrum, the deviation at each wavelength on the detection spectrum is obtained.

3. The method for detecting internal defects of a tank according to claim 1, wherein: Analyzing the difference between the detection spectra of the detection point and other detection points to obtain the group discreteness of the detection spectra of the detection point, including: For each detection point, the difference between the reflectivity of the detection spectrum of the detection point at each wavelength and the mean reflectivity of the detection spectra of all other detection points at the corresponding wavelength is analyzed. Combined with the reflectivity stability of the detection spectra of all detection points at the corresponding wavelength, the group discreteness of the detection spectrum of the detection point is obtained.

4. The method for detecting internal defects of a tank according to claim 1, wherein: Analyzing the differences between any band in the detection spectrum and other bands to obtain the abnormality degree of each band in the detection spectrum includes: In the detected spectrum, all bands are located using a peak detection algorithm; Obtaining the dominance of the band according to the band width and band curvature in the detection spectrum; For each detection point, the difference between the reflectivity of the detection spectrum at the extreme point of each band and the mean reflectivity of the detection spectrum at the extreme points of all bands is analyzed, and combined with the dominance, the abnormality degree of each band in the detection spectrum is obtained.

5. The method for detecting internal defects of a tank according to claim 4, characterized in that: The dominance of the band is obtained based on the band width and band curvature in the detection spectrum, including: Obtaining the curvature at each wavelength corresponding to the wavelength band in the detection spectrum to obtain a curvature sequence of the wavelength band; Calculating the mean curvature of the curvature sequence of the band, and calculating the mean curvature difference between all two adjacent data points in the band, to obtain the slowness of the change trend of the band; Obtaining a band width according to a wavelength range corresponding to the band; The dominance of the band is obtained by combining the slowness of the change trend with the width of the band.

6. The method for detecting internal defects of a tank according to claim 1, wherein: Analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and combine the abnormality degree of the bands to obtain the abnormal overlap degree of the band pairs, including: In the detection spectra of any two adjacent detection points, the wavelength ranges corresponding to all the bands are obtained respectively, and a number of band pairs with overlapping wavelength ranges are obtained; Obtaining the wavelength intersection range of the band pair, and combining the larger value of the wavelength ranges corresponding to the two bands in the band pair to obtain the wavelength overlap degree of the band pair; Calculating the Pearson correlation coefficient between the two wavelengths in the wavelength pair, and combining the wavelength overlap degree to obtain the correlation of the wavelength pair; According to the correlation, combined with the average of the abnormality levels corresponding to the two bands in the band pair, the abnormal overlap level of the band pair is obtained.

7. The method for detecting internal defects of a tank according to claim 1, wherein: Analyze the intersection range of the wavelength bands in the detection spectrum of any two detection points to obtain the target wavelength band, including: Among all the bands in the detection spectra of all detection points, when two bands have an intersection and the intersection is greater than half of the wavelength range of any one of the two bands, the wavelength ranges corresponding to the two bands are merged to obtain several target wavelength bands.

8. The method for detecting internal defects of a tank according to claim 4, characterized in that: Combining the deviation, the group discreteness, the abnormality degree, and the abnormality overlap degree to obtain the sensitivity of the target wavelength band, and performing defect detection on the tank body, including: Obtaining the longitudinal anisotropy of each target wavelength band according to the standard deviation of the deviation corresponding to each wavelength in the target wavelength band and the standard deviation of the band width corresponding to all wavelength bands in the target wavelength band; Obtaining a sensitivity coefficient for each detection point according to the population discreteness corresponding to the detection point, the abnormality degree of the band within the target wavelength band of the detection point, and the abnormal overlap degree of the band pairs within the target wavelength band of the detection point; Traversing the detection points included in the target wavelength band, calculating the sensitivity coefficient, and combining the longitudinal anisotropy of the band to obtain the sensitivity of the target wavelength band; According to the sensitivity, combined with the reflectivity of the band in the target wavelength band, defect detection is performed on the tank body.

9. A tank internal defect detection system, characterized in that: The system comprises: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 8.

10. The tank internal defect detection system according to claim 9, characterized in that: The processor includes: Spectral data acquisition module, used to collect the detection spectrum at the inspection point of the tank body and the baseline spectrum of the defect-free area; a deviation analysis module, configured to analyze the difference between the detection spectrum and the baseline spectrum to obtain the deviation at each wavelength on the detection spectrum; a spectrum group discreteness analysis module, configured to analyze the difference between the detection spectra of the detection point and other detection points, and obtain the group discreteness of the detection spectra of the detection point; a band anomaly degree analysis module, configured to analyze the difference between any band in the detection spectrum and other bands, and obtain the degree of anomaly of each band in the detection spectrum; The module for analyzing the abnormal overlap degree of band pairs is used to analyze the correlation of the band pairs that have intersections in the detection spectra of two adjacent detection points, and to obtain the abnormal overlap degree of the band pairs in combination with the abnormal degree of the bands; The target wavelength band identification module is used to analyze the intersection range of the wavelength bands in the detection spectra of any two detection points to obtain the target wavelength band; The target wavelength band sensitivity analysis module is used to combine the deviation, the group discreteness, the abnormality degree and the abnormality overlap degree to obtain the sensitivity of the target wavelength band and complete defect detection.

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