CN114675261B - Urban underground disease body full life cycle management method based on ground penetrating radar - Google Patents
Urban underground disease body full life cycle management method based on ground penetrating radar Download PDFInfo
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- 201000010099 disease Diseases 0.000 title claims abstract description 46
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 46
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- 238000007726 management method Methods 0.000 title claims abstract description 16
- 238000001514 detection method Methods 0.000 claims abstract description 56
- 230000002159 abnormal effect Effects 0.000 claims abstract description 41
- 230000005856 abnormality Effects 0.000 claims abstract description 22
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 14
- 239000011800 void material Substances 0.000 claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 7
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract
The invention discloses a city underground disease body full life cycle management method based on ground penetrating radar, which comprises the following steps: step 1, comprehensively detecting the region which is detected for the first time and reaches the detection period by adopting a rapid vehicle-mounted ground penetrating radar mode, and processing ground penetrating radar data; step 2, the region corresponding to the census abnormality is processed, ground penetrating radar data are processed, fine detection abnormality is screened, and sizes of the void, the cavity, the loose body and the rich water body are quantized; step 3, calculating a risk occurrence probability score according to the scale of the fine detection abnormality, and dividing risk probability grades; step 4, classifying the evaluation areas; and 5, distinguishing abnormal identification into disease and normal areas. The invention establishes a full life cycle management method for detecting, evaluating, early warning, treating and maintaining underground diseases of urban roads based on the technical means of the ground penetrating radar, perfects management flow and mechanism, thereby improving the underground safety early warning capability of roads and reducing the occurrence of road collapse accidents.
Description
Technical Field
The invention belongs to the field of underground target detection, and particularly relates to a full life cycle management method of urban underground disease bodies based on ground penetrating radar data.
Background
The ground penetrating radar is electromagnetic detection equipment for determining the internal morphological structure of the underground medium distribution based on electromagnetic wave exploration, has the advantages of no damage, rapidness and shallow high resolution, and is widely applied to urban underground disease body detection. A large number of engineering applications find that urban road collapse accidents are mainly caused by hidden underground disease bodies. The underground disease bodies are different in depth, shape and filling due to different formation reasons, the current research is mainly focused on the aspect of single detection, identification and early warning based on ground penetrating radar data, the occurrence and development processes of the underground disease bodies cannot be effectively monitored and predicted, and how to track and verify the confirmed and treated disease bodies is also freshly reported.
The patent 'a ground penetrating radar subgrade disease target detection method based on a convolutional neural network' (202011027009. X) discloses a method: collecting, preprocessing and marking a ground penetrating radar image; constructing a data set by the image and the marking information; wherein the training set trains, the verification set fine-tunes the convolution network model, and the test set evaluates the performance; and finally, accurately detecting the subgrade disease target. The disadvantages of this patent are: only the information of the target category, the coordinates and the like is stored in the xml file, and how to use the information for collapse accident monitoring and early warning is not related.
The patent 'road underground cavity detection early warning method based on deep learning and ground penetrating radar' (202110245588.7) discloses a method: the method comprises the steps of performing amplification treatment on a denoising ground penetrating radar echo signal by adopting a generated countermeasure neural network; detecting the radar echo signal by adopting a fast convolution neural network to obtain a first detection early warning result; and carrying out quantization processing on the first detection early-warning result to obtain a second detection early-warning result. The disadvantages of this patent are: only detect the early warning to single detection data, how to monitor its development to this detection has not yet reached the cavity disease of early warning value, whether to need to handle this detection early warning, how to judge and handle the effect and do not mention.
For a long time, the related management departments do not formulate a set of scientific detection, evaluation and decision methods, but only carry out qualitative analysis and evaluation on the road surface conditions and determine the road surface conditions through some working experiences of engineers. Because of instability of experience values and no objective quantitative data on road diseases, the treatment scheme is impractical, funds are wasted, and the road service performance is reduced and the road cost is increased. In particular, there is insufficient historical test data to predict inaccurate maintenance requirements across years, resulting in limited capital but not maximum benefit. The result is that the smoothness of the road is affected, the city safety is threatened, and the quick development of the economy in China is restricted.
Disclosure of Invention
The technical problem to be solved by the invention is to provide the urban underground disease body full life cycle management method based on the ground penetrating radar, which can comprehensively maintain the detection data and result information of a plurality of test lines, and can not only carry out space statistics, attribute analysis and risk evaluation on the underground disease body, but also compare historical data of a plurality of times across time, thereby achieving the purposes of monitoring, prediction, decision making, verification and backtracking.
The invention adopts the following technical scheme:
in the method for managing the whole life cycle of the urban underground disease body based on the ground penetrating radar, the improvement comprises the following steps:
Step 1, arranging measuring lines according to lanes in the areas which are detected for the first time and reach a detection period, comprehensively detecting by adopting a rapid vehicle-mounted ground penetrating radar mode, processing ground penetrating radar data, and determining general investigation abnormality according to the rule of a radar map, wherein the areas which comprise void, hollowness, loose bodies and rich water bodies and are not abnormal are conventional areas;
The characteristics of the void on the ground penetrating radar map are shown as no clutter reflection, but the interface reflection of the structural layer is obvious, the phase is reversed, and the phase axis is convex upwards. The cavity on the ground penetrating radar map is characterized in that reflected signal energy is strong, the frequency, amplitude and phase change of the reflected signal are obvious, the lower multiple reflected waves are obvious, and the boundary possibly accompanies diffraction phenomenon; the morphological characteristics of the loose body on the ground penetrating radar map are mainly clutter and irregularity of wave groups, including energy change of reflected signals, discontinuous phase shafts and the like, and the clutter and irregularity degree of the wave groups is aggravated along with the increase of the loose degree; because of the rapid attenuation of electromagnetic waves in water, the wave group causing the water-rich body abnormality shows a reflected wave form mainly of the top surface, and the reflected wave at the lower part of the top surface shows weaker due to the rapid attenuation.
Step 2, a region corresponding to the general survey abnormality, a region in which serious deformation occurs on the ground and a region in which collapse accidents occur are determined as important regions, grid measuring lines are laid in the important regions, fine detection is performed in a manual pushing ground detection radar mode, ground detection radar data are processed, fine detection abnormality is screened, and sizes of void, cavity, loose body and rich water are quantified;
The anomaly depth is calculated according to the following formula:
Wherein: h is an abnormal body depth value, v is the propagation speed of electromagnetic waves in a medium, t is the double-pass time between an abnormal reflection echo recorded by a ground penetrating radar and a ground reflection echo, c is the propagation speed of the electromagnetic waves in vacuum, namely the speed of light, and epsilon r is the relative dielectric constant of the medium;
the abnormal body length l l and the abnormal body width l w are calculated according to the following formulas:
ll＝scanDIl×scanNOl
lw＝scanDIw×scanNOw
Wherein: scanDI l is the sampling interval of the measuring line in the length direction of the abnormal body; scanDI w is the sampling interval of the measuring line in the width direction of the abnormal body; scanNO l is the number of sampling channels occupied by the abnormal body in the length direction; scanNO w is the number of sampling channels occupied by the abnormal body in the width direction;
the anomaly height is calculated according to the following formula:
d＝he-hs
Wherein: d is the abnormal height; h e is the abnormal termination depth; h s is the abnormal body starting depth;
The abnormal body area S is calculated according to the following formula:
S＝ll×lw
step 3, calculating a risk occurrence probability score according to the scale of the fine detection abnormality, and dividing risk probability grades;
the risk occurrence likelihood score is calculated as follows:
P＝KPA＝K(0.7PA1+0.3PA2)
Wherein: p is the risk occurrence probability score; p A is an index of the scale of the underground disease body; k is the type coefficient of the underground disease body, 1.0 is taken when the underground disease body is empty, 0.9 is taken when the underground disease body is severely loosened, 0.7 is taken when the underground disease body is rich, and 0.5 is taken when the underground disease body is normally loosened; p A1 is an index of the area of the underground disease body; p A2 is an index of the height of the underground disease body;
for the void, cavity, serious loose body, rich water body and general loose body, the artificial judgment is carried out according to the description in the JGJ-T437-2018 urban underground disease body comprehensive detection and risk assessment technical standard at present.
If the spoil coring verification has been performed, a determination can be made based on the rock-soil, engineering, and drilling characteristics of the spoil. Specific divisions are described in the standard JGJ-T437-2018 tables 4.0.2 and 4.0.4.
The underground disease bodies of the table 4.0.2 are classified according to engineering characteristics
Table 4.0.4 loose body grading
If only ground penetrating radar detection is performed, and core verification is not performed yet, the judgment can be made according to the waveform, amplitude, phase and frequency spectrum characteristics of the data. The specific identification features are shown in a table 6.2.18 in a standard JGJ-T437-2018
Ground penetrating radar characteristic of surface 6.2.18 underground disease body
The following table is an index system for evaluating the risk occurrence probability of underground diseases
The following table classifies the risk occurrence probability of the underground disease body
| Grade | Risk occurrence likelihood score | Literal description |
| A | 0≤P＜30 | Unlikely to happen in the near term and very unlikely to happen in the long term |
| B | 30≤P＜50 | The probability of recent occurrence is small, and the probability of long-term occurrence can be low |
| C | 50≤P＜70 | The probability of recent occurrence is smaller, and the probability of long-term occurrence is larger |
| D | 70≤P＜90 | Has a high probability of occurring in the near future |
| E | 90≤P≤100 | The probability of recent occurrence is extremely high |
Step 4, determining an abnormal corresponding area evaluated as A, B grades as a conventional area; the corresponding area of the C-level abnormality is listed as a wind control area, and the detection period of the wind control area is halved; core verification is carried out on the corresponding abnormal region of D, E grades;
Step 5, coring verification abnormality is confirmed to be a disease, detection is carried out again after treatment and repair are carried out, the treatment effect is checked through data comparison until the disease is completely remedied, and the area is redetermined to be a conventional area; coring verification is carried out, the abnormal corresponding area is listed as a wind control area, and the detection period of the wind control area is halved;
And 6, repeating the steps 1-5 according to the corresponding detection period to comprehensively review and detect the conventional area and the wind control area, and carrying out coring verification on the abnormal corresponding area which is higher than the previous detection level in the step 4 and processing according to the step 5. And (3) processing the newly-appeared and unchanged-evaluation-level refined detection abnormality compared with the last result according to the step (4).
The beneficial effects of the invention are as follows:
The invention establishes a full life cycle management method for detecting, evaluating, early warning, treating and maintaining underground diseases of urban roads based on the technical means of the ground penetrating radar, perfects management flow and mechanism, thereby improving the underground safety early warning capability of roads and reducing the occurrence of road collapse accidents.
The invention establishes a scientific and complete whole life cycle management method for underground diseases, can change the current management situation, improves the safety of urban roads, provides objective road disease evaluation and prediction for management decision-making departments, and intelligent treatment and maintenance decisions, and can meet the requirements of modern, large-scale and high-quality urban road underground safety management.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a lane-wise layout line;
FIG. 3 is a schematic diagram of a grid line;
FIG. 4 is a radar map of a general loose body anomaly;
FIG. 5 is a radar map of rich water anomalies;
FIG. 6 is a radar map of a void anomaly;
FIG. 7 is a radar map of cavity anomalies;
Fig. 8 is a radar map without anomalies.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Embodiment 1, this embodiment discloses a method for managing the whole life cycle of a primarily detected mild underground disease body, which comprises daily census, key detailed examination and evaluation decision-making processes as shown in fig. 1.
Step 1, distributing a survey line according to the figure 2 for the initially detected area, and carrying out comprehensive detection in a quick vehicle-mounted mode. In the embodiment, two general investigation anomalies are detected, namely a general loose body and a rich water body, and radar maps are shown in fig. 4 and 5;
And 2, determining the corresponding areas of the general loose bodies and the rich water bodies detected by the embodiment as key areas, laying grid measuring lines according to the figure 3, wherein the distance between the measuring lines is 50cm, and carrying out detailed detection by adopting a manual pushing mode. And respectively screening out the ground penetrating radar data with the clearest response in the transverse and longitudinal directions, wherein the intersection point of the corresponding transverse and longitudinal lines is the accurate position of the fine detection abnormality. Quantifying the size of the fine detection abnormality, and calculating to obtain an abnormal area and an abnormal height according to the formula in the step 2; by way of example, the general loose body area in this example is 18m 2, height 75cm, p A1 value 95, p A2 value 65; the water-rich body area is 2.5m 2, the height is 60cm, the P A1 value is 35, and the P A2 value is 65;
And 3, according to a formula, in the embodiment, risk probability scores P of a general loose body and a rich water body are respectively 43 and 30.8, corresponding evaluation grades are B, detection evaluation results are recorded, corresponding areas are determined to be conventional areas, and the next detection period is waited.
Embodiment 2, this embodiment discloses a full life cycle management method for rechecking wind-controlled areas and detecting medium and heavy underground diseases, which comprises daily census, key detailed examination, evaluation decision, monitoring and early warning, emergency treatment and history tracking processes as shown in fig. 1.
And (6) distributing the survey lines according to the figure 2 for the wind control area needing to be reexamined for the detection period, and carrying out comprehensive detection in a quick vehicle-mounted mode. In the embodiment, two census anomalies are detected, namely, a void and a cavity, and radar maps are shown in fig. 6 and 7;
And (2) repeating the step, determining the corresponding area of the void and the cavity detected by the embodiment as a key area, laying grid test lines according to the figure 3, and adopting a manual pushing mode to carry out detailed detection, wherein the distance between the test lines is 50 cm. And respectively screening out the ground penetrating radar data with the clearest response in the transverse and longitudinal directions, wherein the intersection point of the corresponding transverse and longitudinal lines is the accurate position of the fine detection abnormality. Quantifying the size of the fine detection abnormality, and calculating to obtain an abnormal area and an abnormal height according to the formula in the step 2; for example, the void area in this embodiment is 3m 2, the height is 25cm, the value of p A1 is 60, and the value of p A2 is 65; the area of the cavity is 6.5m 2, the height is 1m, the value of P A1 is 60, and the value of P A2 is 65;
and (3) repeating the step (3), wherein the risk probability scores P of the void and the cavity are 61.5 according to the formula, and the score corresponds to the evaluation grade C.
According to step 6, comparing with the last detection result, for example, in this embodiment, the last risk evaluation result of the void anomaly is C, the risk level is unchanged, the corresponding area is defined as the wind control area, and the detection period is halved; and B, carrying out coring verification when the risk evaluation result of the cavity abnormality is B and the risk level is increased.
And 5, confirming the damage after coring, coordinating related departments to repair, and re-detecting after repair to obtain the abnormal-free ground penetrating radar data shown in fig. 8 only with normal structural layer and pipeline target reaction. This area is re-divided into regular areas, restoring the original detection period.
Claims (2)
1. The urban underground disease body full life cycle management method based on the ground penetrating radar is characterized by comprising the following steps of:
Step 1, arranging measuring lines according to lanes in the areas which are detected for the first time and reach a detection period, comprehensively detecting by adopting a rapid vehicle-mounted ground penetrating radar mode, processing ground penetrating radar data, and determining general investigation abnormality according to the rule of a radar map, wherein the areas which comprise void, hollowness, loose bodies and rich water bodies and are not abnormal are conventional areas;
Step 2, a region corresponding to the general survey abnormality, a region in which serious deformation occurs on the ground and a region in which collapse accidents occur are determined as important regions, grid measuring lines are laid in the important regions, fine detection is performed in a manual pushing ground detection radar mode, ground detection radar data are processed, fine detection abnormality is screened, and sizes of void, cavity, loose body and rich water are quantified;
The anomaly depth is calculated according to the following formula:
Wherein: h is an abnormal body depth value, v is the propagation speed of electromagnetic waves in a medium, t is the double-pass time between an abnormal reflection echo recorded by a ground penetrating radar and a ground reflection echo, c is the propagation speed of the electromagnetic waves in vacuum, namely the speed of light, and epsilon r is the relative dielectric constant of the medium;
the abnormal body length l l and the abnormal body width l w are calculated according to the following formulas:
ll＝scanDIl×scanNOl
lw＝scanDIw×scanNOw
Wherein: scanDI l is the sampling interval of the measuring line in the length direction of the abnormal body; scanDI w is the sampling interval of the measuring line in the width direction of the abnormal body; scanNO l is the number of sampling channels occupied by the abnormal body in the length direction; scanNO w is the number of sampling channels occupied by the abnormal body in the width direction;
the anomaly height is calculated according to the following formula:
d＝he-hs
Wherein: d is the abnormal height; h e is the abnormal termination depth; h s is the abnormal body starting depth;
The abnormal body area S is calculated according to the following formula:
S＝ll×lw
step 3, calculating a risk occurrence probability score according to the scale of the fine detection abnormality, and dividing risk probability grades;
the risk occurrence likelihood score is calculated as follows:
P＝KPA＝K(0.7PA1+0.3PA2)
Wherein: p is the risk occurrence probability score; p A is an index of the scale of the underground disease body; k is an underground disease body type coefficient; p A1 is an index of the area of the underground disease body; p A2 is an index of the height of the underground disease body;
The grade A is the grade when P is more than or equal to 0 and less than 30, the grade B is the grade when P is more than or equal to 30 and less than or equal to 50, the grade C is the grade when P is more than or equal to 50 and less than or equal to 70, the grade D is the grade when P is more than or equal to 70 and less than or equal to 90, and the grade E is the grade when P is more than or equal to 90 and less than or equal to 100;
Step 4, determining an abnormal corresponding area evaluated as A, B grades as a conventional area; the corresponding area of the C-level abnormality is listed as a wind control area, and the detection period of the wind control area is halved; core verification is carried out on the corresponding abnormal region of D, E grades;
Step 5, coring verification abnormality is confirmed to be a disease, detection is carried out again after treatment and repair are carried out, the treatment effect is checked through data comparison until the disease is completely remedied, and the area is redetermined to be a conventional area; coring verification is carried out, the abnormal corresponding area is listed as a wind control area, and the detection period of the wind control area is halved;
and 6, repeating the steps 1-5 according to the corresponding detection period to comprehensively review and detect the conventional area and the wind control area, and carrying out coring verification on the abnormal corresponding area which is higher than the previous detection level in the step 4 and processing according to the step 5.
2. The method for managing the whole life cycle of the urban underground disease body based on the ground penetrating radar according to claim 1, wherein the method comprises the following steps: in the step 3, K is 1.0 when the cavity is empty, 0.9 when the cavity is severely loosened, 0.7 when the cavity is rich in water, and 0.5 when the cavity is generally loosened; p A1 takes 90-100 when the abnormal body area S is more than or equal to 15m 2, 70-90 when 10m 2≤S＜15m2, 50-70 when 3m 2≤S＜10m2, and 20-50 when S is less than 3m 2; p A2 is 90-100 when the height d of the abnormal body is more than 4m, 80-90 when d is more than 2m and less than or equal to 4m, 70-80 when d is more than 1m and less than or equal to 2m, and 60-70 when d is less than or equal to 1 m.
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| CN115162947B (en) * | 2022-06-29 | 2023-03-21 | 北京科技大学 | System and method for determining density of underground disease area of road |
| CN115220035B (en) * | 2022-09-20 | 2022-12-09 | 江苏筑升土木工程科技有限公司 | Road void detection system and detection method |
| CN117233752B (en) * | 2023-11-08 | 2024-01-30 | 江苏筑升土木工程科技有限公司 | Road underground disease body water content calculation and analysis method based on radar nondestructive detection |
| CN117233751B (en) * | 2023-11-08 | 2024-02-02 | 江苏筑升土木工程科技有限公司 | Road underground disease body full life cycle management method based on ground penetrating radar |
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