CN113419288B - Data detection and pretreatment method for inversion of underground shelter - Google Patents
Data detection and pretreatment method for inversion of underground shelter Download PDFInfo
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- CN113419288B CN113419288B CN202110595086.7A CN202110595086A CN113419288B CN 113419288 B CN113419288 B CN 113419288B CN 202110595086 A CN202110595086 A CN 202110595086A CN 113419288 B CN113419288 B CN 113419288B
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Abstract
The invention discloses a data detection and preprocessing method for inversion of an underground shelter, which comprises three parts, namely task parameter calculation, data acquisition and preprocessing, inversion into a graph and identification, and is used for an underground shelter detection system. The invention has the beneficial effects that: the frequency resolution is increased by adopting a frequency spectrum refining method, so that rich frequency domain characteristics are obtained, and the inversion of the underground shelter into a graph with high precision is realized; the data is subjected to grouping FFT calculation, so that the occupation of the memory space is reduced, and the real-time performance of data processing is greatly improved; the frequency analysis can observe the signal characteristics according to the frequency, the characteristic information is more concise in the frequency domain, and the problem analysis is deeper and more convenient when the signal is observed at the frequency.
Description
Technical Field
The invention relates to an underground shelter inversion data detection and preprocessing technology, in particular to an underground shelter inversion data detection and preprocessing method.
Background
At present, underground shelter detection is an indispensable step in actual ground construction, and the underground shelter is a shallow underground building poured by thick and high-quality concrete in order to defend against high-temperature light radiation and shock wave killing caused by high-altitude explosion or ground explosion, and is one form. Taking the air-raid shelter as an example, a large number of air-raid shelters are built between 30 and 70 years of the 20 th century to prevent air attacks of enemy and ensure the safety of ground residents, and casualties and property losses can be greatly reduced in war periods, but most of the air-raid shelters are abandoned as time goes on and as time goes on. The air-raid shelter is generally characterized by the following points: (1) the hole diameter difference is larger, the space is generally larger at the center of the hole by 3-5 meters, more people can be accommodated and simultaneously co-located, and the hole diameter at the position of the hole body channel is only about 0.5 meter; (2) the cavities and channels in the cavities are densely distributed, the air-raid shelter is generally densely distributed in a certain area, the continuous relation of the channels is difficult to distinguish by a common detection method, and the network-shaped distribution further increases the detection difficulty; (3) the air-raid shelter is actually a horizontal irregular column filled with air, and the air and the shallow medium have obvious physical parameters different from each other, even if collapse occurs in the air, the medium in the air is loose soil and the physical parameters of the shallow medium have obvious differences.
In the period of peaceful development, along with the continuous perfection and development of infrastructure, old city transformation is also developing at a high speed, and the air-raid shelter has caused very big influence on ground construction, for example, the collapse of the air-raid shelter causes the basic building to hang in the air in a building in the big even city in recent years, and the third teaching building of the university of bloom is influenced by the air-raid shelter and the distribution room local subsidence causes wall body fracture etc. Therefore, the method has practical significance for investigation and accurate positioning of the air-raid shelter, but the air-raid shelter is buried in the shallow layer of several meters to tens of meters underground, the air-raid shelter cannot be identified and positioned through naked eyes and general instruments, and the positions and structures of the air-raid shelter cannot be controlled by people who lose relevant data drawings and lose repair over time.
At present, the research on underground targets is usually realized by using a geophysical exploration method, most of the current air-raid shelter exploration methods are also realized by geophysical exploration, and the detection and data processing of air-raid shelter are generally realized by adopting a high-density electrical method and a ground penetrating radar method, wherein the high-density electrical method belongs to a resistivity method, the basic principle is completely the same as that of the traditional resistivity method, the distribution rule of conducting current under the action of a stable electric field applied manually to a stratum is researched by taking the conductivity difference of a medium as a judgment basis, the apparent resistivity of a shallow medium is calculated, the characteristics of the electrical property, the structure and the like of a rock stratum are analyzed by observing the change of the apparent resistivity, the inversion result of the high-density electrical method is a two-dimensional apparent resistivity profile, and compared with other scenes applied in the geophysical exploration method, the air-raid shelter belongs to a shallow anomaly, so that although the high-density electrical method has arranged a high-density point distance, quite large data are obtained, but the position and the outline of the air-raid shelter is reflected, the inversion of the network-like air-raid shelter structure cannot be accurately formed, and the manpower is greatly consumed in the earlier stage than the preparation; the ground penetrating radar method is characterized in that high-frequency electromagnetic waves are sent into the ground in the form of broadband short pulses by a ground transmitting antenna, the high-frequency electromagnetic waves are reflected back to the ground when the ground encounters different mediums and are received by another antenna, wherein the paths, the electromagnetic wave intensities and the waveforms of the electromagnetic waves change along with the changes of the electrical property and the geometric form of the contacted mediums when the electromagnetic waves propagate in the mediums, so that the structure of the underground mediums can be judged by researching the two-way time, waveform and amplitude change rules of the received electromagnetic waves, whether the electrical property and the geometric form of the mediums in the air-raid are different from those of other mediums in shallow layers or not can be judged by analyzing the waveforms of the geological radar, the method is similar to the high-density resistivity method, the ground penetrating radar method can not accurately invert the network-shaped structure of the air-raid into a graph, and only can judge whether the air-raid is in the ground, and due to the limitation of the ground penetrating radar, when the air-raid is under the twenty meters, the ground penetrating radar method is out of function, in addition, the high-density resistivity method and the data processing of the ground penetrating radar method consume more time, and the real-time performance is worse.
In practical engineering detection, in order to know the accurate position and the underground structure of the underground shelter as soon as possible, the inversion of the map after data processing is required to have higher image resolution and meet the requirement of real-time performance, and the data processing is required to obtain a result as soon as possible; however, the conventional underground shelter detection method is difficult to realize rapid high-precision detection data processing, and whether a rapid high-precision inversion detection and pretreatment method for the underground shelter can be invented is not solved at present, and no relevant research results are reported at home and abroad.
Disclosure of Invention
In order to overcome the defects of the existing pretreatment speed and precision of the underground shelter bomb detection data, the invention provides a data detection and pretreatment method for inversion of the underground shelter.
The technical scheme adopted by the invention is as follows: a data detection and preprocessing method for inversion of underground shelter comprises three parts including task parameter calculation, data acquisition and preprocessing, inversion into a graph and identification, and is used for connecting a probe T1, a probe T2 and a probe T by an underground shelter detection instrument through a detection cablenIn the detection process, the data acquisition and preprocessing part is performed in real time, and the task parameter calculation part and the inversion drawing and recognition part are performed in non-real time; the method is characterized in that: the task parameter calculation part firstly plans the detection task according to the detection requirement and detects the depth range according to the requirementh 2 ~h 1 Determining the lower limit of the analysis frequency rangef 1 =ρ(503.292121 / h 1 ) 2 Upper limit off 2 =ρ(503.292121 / h 2 ) 2 Then the resolution delta of the image is requiredhDesign analysis spectral window width q=Δh*（h 1 - h 2 ) And spectral resolution deltaf=（f 2 - f 1 ) Sampling frequency of Qf s >2(f 2 - f 1 ) Calculate the actual sampling point n=p×q and decompose into p=int [ ]f s /(Δf *Q)+0.5]Group q=2 x Point, finally, by analyzing frequency rangef 1 ~f 2 And sampling frequencyf s Calculating and caching filter coefficients of order Kh(k) The method comprises the steps of carrying out a first treatment on the surface of the The data acquisition and preprocessing part is performed in six steps, and a data pointer is arranged in the first stepi=0、j=0 and at sampling frequencyf s Sampling P groups of Q point data, taking 1 group of Q point sampled data, supplementing K/2 zeros before and after the sampling data, and pressing
Performing Q times of operation to obtain passband filter data, performing Q-point FFT on the filtered Q-point passband filter data and caching,fourth, repeating the second and third steps P times, and fifth step from the spectral line position of the result of the Q point FFT P timesl=int(f 1 /Δf+0.5) start pressing
Performing Q times of operation to obtain a refined spectrum of the observation window, and judging whether underground shelter features exist in the Q refined spectrum lines or not through an energy concentration criterion, a pole discrete criterion and an interference factor criterion, and after the refined spectrum features are stored, jumping to the first step for execution until the detection work is ended and quitting; the inversion mapping and identification part is used for inverting mapping according to the maximum pole spectral line according to the refined spectral characteristic data of the whole detection engineering, and analyzing and identifying the underground shelter construction condition according to the distribution rule of the spectral lines around the poles.
The method has the advantages that the frequency resolution is increased by adopting a frequency spectrum refining method, so that abundant frequency domain characteristics are obtained, and the inversion of the underground shelter into a graph with high precision is realized; the data is subjected to grouping FFT calculation, and the refined spectral line of the analysis frequency range can be obtained by only carrying out Q-point DFT calculation at the end of each sampling period, so that the speed of data inversion preprocessing is improved, the occupation of memory space is reduced, the real-time performance of data processing is greatly improved, and the requirement of a real-time detection system of an underground shelter can be met; the frequency analysis can observe the signal characteristics according to the frequency, the characteristic information is more concise in the frequency domain, and the problem analysis is deeper and more convenient when the signal is observed at the frequency.
Drawings
FIG. 1 is a flow chart of the detection and preprocessing of the present invention;
FIG. 2 is a schematic diagram of a refined spectral analysis of an embodiment of the present invention;
fig. 3 is a schematic diagram of a sub-surface shelter detection system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention; it will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to the drawings, FIG. 1 is a flow chart of the detection and preprocessing of the present invention; FIG. 2 is a schematic diagram of a refined spectral analysis of an embodiment of the present invention; fig. 3 is a schematic diagram of a sub-surface shelter detection system according to an embodiment of the present invention. A data detection and preprocessing method for inversion of underground shelter comprises three parts including task parameter calculation, data acquisition and preprocessing, inversion into a graph and identification, and is used for connecting a probe T1, a probe T2 and a probe T by an underground shelter detection instrument through a detection cablenIs a underground shelter detection system; the task parameter calculation part firstly plans the detection task according to the detection requirement and detects the depth range according to the requirementh 2 ~h 1 Determining an analysis frequency rangef 1 ~f 2 Then the resolution delta of the image is requiredhDesign analysis spectral window width Q and spectral resolution deltafSampling frequencyf s >2(f 2 - f 1 ) Calculating the actual sampling point N and decomposing the actual sampling point N into P groups of Q points, and finally analyzing the frequency rangef 1 ~f 2 And sampling frequencyf s Calculating and caching the order as K filter coefficienth(k) The method comprises the steps of carrying out a first treatment on the surface of the The data acquisition and preprocessing part is performed in six steps, and a data pointer is arranged in the first stepi=0、j=0 and at sampling frequencyf s Sampling P groups of Q point data, taking the Q point data to carry out passband filtering, carrying out Q point FFT on the filtered Q point data and caching in the third step, repeatedly executing the second step and the third step P times, solving a refined spectrum according to the result of the Q point FFT in the P times in the fifth step, analyzing and storing the refined spectrum characteristic data in the sixth step, jumping to the first step to execute until the detection work is finished, and exiting; the inversion map forming and identifying part is used for carrying out inversion map forming and underground shelter identification according to the detailed spectrum characteristic data of the whole detection engineering; in the detection process, the data acquisition and preprocessing part is performed in real time, and the task parameter calculation part, the inversion graph and the identification part are performed in non-real time.
The specific method comprises the following steps:according to the detection requirement, planning detection task, burying matrix probes T1 and T2 in the suspected underground shelter area until probe TnThe interval between the probes is D, and all the probes are connected to an underground shelter detection instrument by detection cables; as can be seen from the cosine change of field intensity along with depth and the exponential decay, the displacement current is ignored, and in the nonmagnetic medium, when the phase change is 2 pi radian, the incident depth is a wavelengthλI.e.λ=2π(2/⍵μσ) 0.5 =2πhWhen the depth is equal toδWhen the electric field amplitude decays to 1/e of the surface value, i.e. the depthhIs defined as the skin depth of the skin,h=λ/2π=503.292121(ρ/f) 0.5 ，⍵is a frequency of a circle, and the frequency of the circle,μis the magnetic permeability of the air, and the air is the air,σin order to be of electrical conductivity,ρis the dielectric resistivityσThe skin depth can be used for calculating the electromagnetic sounding depth in the frequency domain and is only related to the medium resistivity and the frequency, so that the medium resistivity is determined at a certain measuring pointρIs a constant value when the frequency isfThe lower the penetration depth is, the deeper the penetration depth is, so that the detection instrument can achieve the purpose of changing the detection depth by changing the detection frequency, and the shallowest depth is needed to be achieved by detectionh 2 The analysis frequency upper limit can be determinedf 2 =ρ(503.292121 / h 2 ) 2 By the deepest depth to be reached by the probeh 1 Determining an analysis frequency lower limitf 1 =ρ(503.292121 / h 1 ) 2 I.e. it can be determined that the analysis frequency range isf 1 ~f 2 And obtain the center frequencyf 0 =(f 1 +f 2 ) 2; according to the required image resolution deltahSelecting analysis spectral window width Q and spectral resolution deltafWhere the spectral window width q=Δ is analyzedh*（h 1 - h 2 ) According to the practical application requirement, the width Q=2 of the analysis spectrum window is obtained x Spectral resolution deltaf=（f 2 - f 1 ) Q, according to the analysis frequency rangef 1 ~f 2 Data acquisition is carried out on the detection point, and the sampling frequency of the acquisition point meeting the sampling theorem can be preliminarily determined by the Nyquist (Nyquist) sampling theoremf s =β(f 2 - f 1 ) In which the coefficients are sampledβCalculating theoretical sampling point number N' from sampling frequency and frequency spectrum interval not less than 2f s /ΔfAccording to the FFT symmetry principle q=2 x Then 2 can be observed x-1 Each group of data is a Q point, the data is divided into P=INT (N'/Q+0.5) groups by adopting a one-step method according to an arbitrary base FFT, the number of the actually-processed sampled data is N=P×Q, the grouping P can be increased as much as possible according to actual requirements, and the Q point is reduced as much as possible; according to the analysis frequency range off 1 ~f 2 And sampling frequency offline calculation and buffer storage of filter coefficient with order Kh(k) For an analysis frequency range off 1 ~f 2 The time sequence of the (C) which needs to be refined is as followsx(n) Sampling frequencyf s =β(f 2 - f 1 ) Using Q/2 lines to display the analysis frequency rangef 1 ~f 2 The FFT point number is Q, and the filter coefficient can be obtained according to the idea of the complex modulation refined spectrum analysis method based on the analytic band-pass filteringh(k) The real part and the imaginary part of (a) are respectively:
wherein K is the filter order;k=0, 1,2, …, K-1; from the above, complex analytic band pass filter coefficientsh(k) The calculation of (2) is only related to the number Q of the filter order K, FFT, time seriesx(n) And filter coefficientsh(k) There is no direct relation and therefore the spare can be calculated off-line and buffered before the data sampling.
The data acquisition and preprocessing part is performed in six steps.
The first step is to buffer the spare filter coefficients in a periodh(k) Is arranged to P x Q samplesSample data buffer unit for setting data pointeri=0、j=0 and at sampling frequencyf s Sampling P groups of Q point data; the second step is to carry out passband filtering, and the steps of passband filtering are as follows: step one, 1 group of Q point sampling data is taken, K/2 zeros are respectively supplemented before and after the Q point sampling data, and step two, K data and filtering coefficients are taken from Q+K point data in sequence each timeh(k) Accumulating after multiplication, solving the average value of the accumulated sum in the second step to master 1 filtering value, repeatedly executing the second step and the third step Q times to obtain passband filtering data, and specifically using a filter to carry out a data filtering operation formula as follows
The method comprises the steps of carrying out a first treatment on the surface of the Thirdly, performing Q point FFT on the filtered Q point data, caching, adopting an arbitrary base FFT algorithm with Q being an integer power of 2, directly performing FFT operation on the Q point data, and fully utilizing and combining the advantages of the Q point data and the Q point data; the fourth step is to repeatedly execute the second step and the third step until the pass band filtering and FFT operation of the P groups of Q points are completed to obtain the result of P times of Q points FFT; the fifth step is to calculate the refined spectrum according to the result of P times of Q point FFT, the method of calculating the refined spectrum is carried out in four steps, the first step is to calculate the initial spectral line position of the observation window of the refined spectrum, and the initial spectral line position can be calculated and known according to the lower limit of the analysis frequency range and the frequency resolutionl=int(f 1 /Δf+0.5), the position of the end point spectral line can be calculated according to the upper limit of the analysis frequency range and the frequency resolutionl'=int(f 2 /Δf-0.5), step two, calculating the starting spectral line positionlData position in Q-point FFT resultsk=l-Q*int(lQ), calculating the end spectral line positionl'Data position in Q-point FFT resultsk'=l-Q*int(l'Q), step three pairs in P sets of Q point FFT resultskThe position data is used for obtaining 1 refined spectrum value according to the DFT principle, and the position data is calculated according to the following formula:
in the middle ofk=l-Q*int(l/Q)，l=0，1，2，…，P-1；Y i (k)=Y i (Z*Q+y)=Y i (y)，Y i (y) is a value in the P groups of FFT results, Z is a positive integer, and 0 is less than or equal toyQ-1, step four data positionsk=k+1 and repeating the steps three Q times to obtain a refined spectrum of the observation window,l~l'the Q times of refinement spectrum values calculated are the required refinement spectrum; sixth, analyzing and storing the refined spectrum characteristic data, and jumping to the first step to execute until the detection work is finished, and exiting, wherein the refined spectrum characteristic analysis method is to receive electromagnetic field signals reflected, refracted, diffracted, scattered and absorbed by the underground medium through the underground shelter detection system, and analyze the frequency range after refinementf 1 ~f 2 And judging the energy concentration, the pole discrete criterion and the interference factor of the middle Q spectral lines to judge whether the underground shelter exists. The energy concentration is judged by searching the maximum value spectral line L in the Q spectral lines MAX With n next-largest amplitude spectral lines L MAX1 、L MAX2 、L MAX3 、…、L MAXn Presence and location information of (1) by L MAX And L MAXn Spectral line L is the maximum value spectral line with the magnitude and the next largest amplitude of the average amplitude MAX Judging the front and back distribution condition, if the maximum value spectral line L of the Q spectral lines MAX An average amplitude of not less than 20 times, n sub-large amplitude spectral lines L MAX1 、L MAX2 、L MAX3 、…、L MAXn The spectral lines with the n sub-maximum amplitude are distributed at the front and rear positions of the maximum spectral line, if the energy concentration exists, otherwise, the energy concentration does not exist; the pole discrete criterion is that the maximum amplitude spectrum L of the Q spectrum lines is obtained MAX Judging whether a plurality of extreme points exist before and after the method, and aiming at avoiding the influence of the spectrum value of the irrelevant frequency component in the analysis spectrum, the searching mode of the extreme points is as follows: (1) comparing the sizes of each spectral line and the adjacent spectral lines from the second spectral line of the Q spectral lines, (2) judging the maximum point if the spectral line is larger than or equal to the adjacent spectral line, (3) judging the minimum point if the spectral line is smaller than or equal to the adjacent spectral line, and in general, judging the maximum point if the spectral line is L MAX Judging if more than two extreme points exist in the front and back 6 spectral linesBreaking into pole discrete; the interference factor is determined by the maximum amplitude spectral line L when the energy is concentrated and the poles are not discrete MAX The frequency is compared with the known natural frequency in the power frequency and measuring point areas to judge, and in order to avoid a series of influences caused when the current field passes through the non-uniform substances, the specific judging method is as follows: (1) Finding the maximum spectral line L when the phenomenon of energy concentration and non-discrete poles exists MAX (2) according to the spectral resolution sum L MAX Finding the frequency corresponding to the maximum amplitude spectral linef max =L MAX* Δf, (3) iff max Judging whether the phase difference from the power frequency or higher harmonic thereof is one percentf max Is the power frequency or the higher harmonic thereof, (3) combines the probe T1, the probe T2 and up to the probe TnIs to judge the detection result of (1)f max Whether or not it is a natural frequency component in the region, if the maximum amplitude spectral line L MAX Corresponding frequencyf max If the characteristic information is not the power frequency or the higher harmonic wave of the characteristic information and is irrelevant to other natural frequency components of the area, the underground shelter characteristic information exists in the area, otherwise, the characteristic information of the underground shelter does not exist.
The inversion map and identification part is used for carrying out inversion map and underground shelter identification according to the detailed spectrum characteristic data of the whole detection engineering.
Analysis frequency range refined for each measuring pointf 1 ~f 2 The Q spectral lines in the underground shelter are judged, and the characteristic information of the underground shelter is judged through the spectrum energy fading judgment, the pole spectral line dispersion judgment and the interference rejection judgment, and the method is combinednThe probes are according to the probes T1, T2 and up to the probe TnIs used for judging the position information of the underground shelter by the position information and the characteristic information of the underground shelter, and is formed by the skin depthh=503.292121(ρ/ f) 0.5 The depth information of the underground shelter can be obtained by combining the refined spectrum of each measuring point, and the space between the probes is 0.3m, and the spectrum resolution also meets the requirement of 0.3m, namely the final inversion diagram requirement can also meet the requirement of 0.3m of image resolution. In the detection process, the data acquisition and preprocessing part is performed in real time, and the task parameter calculation part, the inversion graph and the identification part are non-seriesPerformed in real time.
In summary, the spectrum resolution is increased by adopting the spectrum refining method, so that abundant frequency domain characteristics are obtained, and the inversion of the underground shelter into a graph with high precision is realized; the data is subjected to grouping FFT calculation, and the refined spectral line of the analysis frequency range can be obtained by only carrying out Q-point DFT calculation at the end of each sampling period, so that the speed of data inversion preprocessing is improved, the occupation of memory space is reduced, the real-time performance of data processing is greatly improved, and the requirement of a real-time detection system of an underground shelter can be met; the frequency analysis can observe the signal characteristics according to the frequency, the characteristic information is more concise in the frequency domain, and the problem analysis is deeper and more convenient when the signal is observed at the frequency.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (1)
1. A data detection and preprocessing method for inversion of underground shelter comprises task parameter calculation, data acquisition and preprocessing, inversion into a graph and identification, and is used for connecting a probe T1, a probe T2 and a probe T from an underground shelter detection instrument through a detection cablenThe method comprises the steps that inverted refined spectrum characteristics are identified from Q refined spectrum lines detected and refined by an underground shelter detection system through an energy concentration criterion, a pole discrete criterion and an interference factor criterion, in the detection process, a data acquisition and preprocessing part is carried out in real time, and a task parameter calculation part and an inversion graph and identification part are carried out in non-real time; the method is characterized in that: the task parameter calculation part firstly plans the detection task according to the detection requirement and detects the depth range according to the requirementh 2 ~h 1 Determining the lower limit of the analysis frequency rangef 1 =ρ(503.292121 / h 1 ) 2 Upper limit off 2 =ρ(503.292121 / h 2 ) 2 Then the resolution delta of the image is requiredhDesign analysis spectral window width q=Δh*( h 1 - h 2 ) And spectral resolution deltaf=( f 2 - f 1 ) Sampling frequency of Qf s >2(f 2 - f 1 ) Calculate the actual sampling point n=p×q and decompose into p=int [ ]f s /(Δf *Q) +0.5]Group q=2 x Point, finally, by analyzing frequency rangef 1 ~f 2 And sampling frequencyf s Calculating and caching filter coefficients of order Kh(k) The method comprises the steps of carrying out a first treatment on the surface of the The data acquisition and preprocessing part is performed in six steps, and a data pointer is arranged in the first stepi=0、j=0 and at sampling frequencyf s Sampling P groups of Q point data, taking 1 group of Q point sampled data, supplementing K/2 zeros before and after the sampling data, and pressing
Performing Q times of operation to obtain passband filter data, performing Q-point FFT on the filtered Q-point passband filter data and caching, repeatedly performing the second and third steps P times, and performing the fifth step from the spectral line position of the P times of Q-point FFT resultl=int(f 1 /Δf+0.5) start pressing
Performing Q times of operation to obtain a refined spectrum of the observation window, analyzing and storing the refined spectrum characteristics of the underground shelter, and jumping to the first step for execution until the detection work is ended and quitting; the inversion mapping and identification part is used for inverting mapping according to the maximum pole spectral line according to the refined spectral characteristic data of the whole detection engineering, and analyzing and identifying the underground shelter construction condition according to the distribution rule of the spectral lines around the poles. />
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