CN117233755B - Rapid automatic detection system for road subgrade diseases and underground disease bodies - Google Patents
Rapid automatic detection system for road subgrade diseases and underground disease bodies Download PDFInfo
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Abstract
The invention relates to the technical field of road subgrade detection, and discloses a rapid automatic detection system for road subgrade diseases and underground diseases, which comprises an acquisition unit, a processing unit, a display unit, an extraction unit, a recognition unit, a comparison unit and a judgment unit, wherein the acquisition unit acquires electromagnetic wave data of underground harmful bodies by adopting a ground penetrating radar method and sends the electromagnetic wave data to the processing unit, the processing unit carries out optimization treatment on the electromagnetic wave data and then sends the electromagnetic wave data to the display unit and the extraction unit respectively, and the display unit is used for carrying out visual display on the electromagnetic wave data; according to the invention, the acquisition unit, the processing unit, the extraction unit and the identification unit are arranged, the electromagnetic wave data of the underground harmful body information is acquired through the ground penetrating radar method, after the electromagnetic wave data are processed, the abnormal points in the electromagnetic wave data are extracted, the problem type is judged according to the abnormal points, and the depth of the problem can be known according to the speed of the electromagnetic wave, so that the harmful body can be detected quickly, and the working efficiency is high.
Description
Technical Field
The invention relates to the technical field of road subgrade detection, in particular to a rapid automatic detection system for road subgrade diseases and underground disease bodies.
Background
The highway engineering in the operation period is limited by the design concept or construction technology, and the like, so that risks such as landslide collapse and the like possibly exist under the influence of natural environments such as rainfall temperature change, and geological bodies such as void, holes, loose bodies and the like which threaten urban safety can often appear under the ground of the city, so that the road engineering is required to be conveniently and rapidly detected for ensuring normal operation of the highway engineering and urban safety;
when the ground penetrating radar is adopted for road detection in the prior art, operators are required to push the radar vehicle to walk back and forth, danger is brought to the operators at the moment, the accuracy of a detection result cannot be ensured when the ground penetrating radar is adopted for position detection at a fixed position, and the detection time is increased when the radar vehicle is pushed to carry out back and forth detection, so that the working efficiency is reduced;
when the detection is carried out, as the road subgrade diseases and the underground disease bodies are generally positioned at the positions of several meters or even more than ten meters in the ground, the traditional ground penetrating radar can detect the positions of the underground diseases, but cannot judge the types of the diseases, the diseases can be maintained after the diseases are dug, and different maintenance equipment is needed to be adopted for coping with different disease types, so that the working time is wasted.
Disclosure of Invention
In order to overcome the above-mentioned defects of the prior art, the embodiment of the invention provides a rapid automatic detection system for road subgrade diseases and underground diseases, so as to solve the technical problems in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: the rapid automatic detection system for the road subgrade diseases and the underground diseases comprises an acquisition unit, a processing unit, a display unit, an extraction unit, a recognition unit, a comparison unit and a judgment unit, wherein the acquisition unit acquires electromagnetic wave data of the underground diseases by adopting a ground penetrating radar method and sends the electromagnetic wave data to the processing unit, the processing unit carries out optimization treatment on the electromagnetic wave data and then sends the electromagnetic wave data to the display unit and the extraction unit respectively, the display unit is used for carrying out visual display on the electromagnetic wave data, the extraction unit extracts abnormal points in the electromagnetic wave data and sends the electromagnetic wave data to the recognition unit, the recognition unit judges the types of the electromagnetic wave data and sends the electromagnetic wave data to the judgment unit after judging the types of the road subgrade diseases and the underground diseases, the comparison unit detects the types of the road subgrade diseases and the underground diseases by adopting a high-density resistivity method and sends the result to the judgment unit, and the judgment unit receives the data of the recognition unit and outputs the recognition unit when the types of the road subgrade diseases and the underground diseases of the recognition unit are inconsistent, and the detection is carried out again when the types are inconsistent;
the acquisition unit adopts a ground penetrating radar to acquire harmful body information of road bed and urban underground, the antennas are arranged at two ends of the detection points to emit electromagnetic waves, the acquisition unit receives the electromagnetic waves sent by the antennas and transmitted underground, and generates a recording time window, wherein the recording time window is thatWherein K is a weight coefficient, the value range is 1.2-1.5, d max And v is the equivalent electromagnetic wave speed of the underground medium, the acquisition unit acquires electromagnetic wave data in a recording time window, and the acquisition unit sends the acquired information data to the processing unit.
In a preferred embodiment, the processing unit includes a preprocessing module, an advanced processing module, and a visualization module, where the preprocessing module is configured to perform a horizontal distance normalization process on the data collected by the collecting unit, where a formula of the horizontal distance normalization process isWherein A is the horizontal distance between the two antenna transmission pointsB is the vertical distance between the two antenna transmitting points, n is the number of times acquired by a time window, S is the processed electromagnetic wave data, and the preprocessing module transmits the processed data to the advanced processing module.
In a preferred embodiment, the advanced processing module removes noise in the data by adopting a smooth denoising mode, and a calculation formula of the smooth denoising is as followsWherein F (x, y) is filtered data, δ is mean variance, v is noise variance, F (x, y) is electromagnetic wave data processed by the preprocessing module, G (x, y) is a standard value of the electromagnetic wave data, and the advanced processing module sends the processed data to the visualization module and the extraction unit.
In a preferred embodiment, the visualization module performs visualization processing on the received data, and sends the data to a display unit on site after the data is made into a chart, wherein the data visualization processing process is as follows:
a1, defining a chart template by adopting XML description, and describing data sources and style settings associated with a chart;
a2, a Java language builds a background system, after reading data, uses ChartData to store and convert the data into ChartGlyph objects, and invokes an interface to output the JSON data;
and A3, receiving JSON data by a display unit, and displaying the data in the display unit in a chart form by adopting a D3.js plug-in.
In a preferred embodiment, the extracting unit receives the processed electromagnetic wave data, extracts an abnormal point in the electromagnetic wave data, and sends the extracted abnormal point to the identifying unit, wherein the identifying unit classifies road subgrade diseases and underground disease bodies into four types of problems, namely: the recognition unit is used for matching abnormal points with the four problems and determining the types of road subgrade diseases and underground diseases.
In a preferred embodiment, the extraction rule of the abnormal point in the extraction unit is that when an error between a certain point value and a previous point value in the electromagnetic wave data is 100% or more, the point is marked as the abnormal point, and the electromagnetic wave group in the electromagnetic wave data in which the abnormal point exists is transmitted to the identification unit.
In a preferred embodiment, when the recognition unit detects that the electromagnetic wave group is formed into a continuous isotropic reflection wave group at the top and is in a flat plate shape, the problem of the road bed disease and the underground disease is void, when the recognition unit detects that the electromagnetic wave group is an approximately spherical cavity reflection wave group and is in an inverted hyperbolic form, the problem is a spherical hole, when the electromagnetic wave group is approximately square hole and is in a forward continuous flat plate state, the problem is a square hole, the recognition unit detects that the electromagnetic wave group is formed into a continuous isotropic reflection wave group at the top, the waveform structure of the multiple waves is disordered, the problem of the road bed disease and the underground disease is a loose body, when the recognition unit detects that the electromagnetic wave group is formed into a continuous isotropic reflection wave group at the top, the multiple waves do not develop, the problem of the road bed disease and the underground disease is a rich body when the diffracted waves are not obvious, and the recognition unit sends the detected result to the judgment unit.
In a preferred embodiment, the comparing unit includes a detecting module and a matching module, the detecting module detects road subgrade diseases and underground diseases by adopting a high density resistivity method, the electrode buried number is the minimum value reaching the standard, the detecting module sends detected data to the matching module, the matching module classifies the problems of the road subgrade diseases and the underground diseases into three types of holes, loose bodies and rich bodies, when the problems are holes, the data received by the matching module is the relatively high resistivity abnormality on the resistivity slope, when the problems are loose bodies, the resistivity characteristic of the data is the relatively low resistivity abnormality, when the problems are rich bodies, the resistivity characteristic of the data is the relatively low resistivity abnormality, and when the problems are rich bodies, the matching module sends the detected results to the judging unit.
In a preferred embodiment, the judging unit receives the data sent by the identifying unit and the data sent by the comparing unit, when the identifying unit is consistent with the data sent by the comparing unit, the judging of the road subgrade diseases and the underground diseases is completed, and when the identifying unit is inconsistent with the data sent by the comparing unit, the detecting is needed until the results received by the judging unit are consistent.
The invention has the technical effects and advantages that:
1. the invention is provided with the acquisition unit, the processing unit, the extraction unit and the identification unit, acquires the electromagnetic wave data of the road subgrade and the urban underground harmful body information through the ground penetrating radar method, extracts the abnormal points in the electromagnetic wave data after the electromagnetic wave data are processed, judges the problem type according to the abnormal points, and can know the depth of the problem according to the speed of the electromagnetic wave, so that the detection of the harmful body can be rapidly carried out, and the working efficiency is high;
2. according to the invention, the pretreatment module is used for carrying out horizontal distance normalization processing on the acquired data compared with the acquired data by the acquisition unit, so that the height between the harmful body and the ground can be reflected more accurately by the normalized data, and the problem that a final result is subjected to larger error when single signal fluctuates is avoided, thereby affecting the accuracy of judging the harmful body;
3. the detection module in the comparison unit adopts a high-density resistivity method to detect, and only performs comparison use without confirming the detailed position, so that whether the ground penetrating radar adopted by the acquisition unit is detected correctly or not is judged, and the detection of harmful substances on the road subgrade and underground in cities is completed rapidly.
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FIG. 1 is a schematic diagram of the overall system configuration of the present invention.
FIG. 2 is a schematic diagram showing the constitution of the identification unit of the present invention.
Detailed Description
The embodiments of the present invention will be clearly and completely described below with reference to the drawings in the present invention, and the configurations of the structures described in the following embodiments are merely examples, and the rapid automatic detection system for road bed diseases and underground diseases according to the present invention is not limited to the structures described in the following embodiments, and all other embodiments obtained by a person having ordinary skill in the art without making any creative effort are within the scope of the present invention.
The invention provides a rapid automatic detection system for road subgrade diseases and underground diseases, which comprises an acquisition unit, a processing unit, a display unit, an extraction unit, a recognition unit, a comparison unit and a judgment unit, wherein the acquisition unit acquires electromagnetic wave data of underground diseases by adopting a ground penetrating radar method and sends the electromagnetic wave data to the processing unit, the processing unit carries out optimization processing on the electromagnetic wave data and then sends the electromagnetic wave data to the display unit and the extraction unit respectively, the display unit is used for carrying out visual display on the electromagnetic wave data, the extraction unit extracts abnormal points in the electromagnetic wave data and sends the electromagnetic wave data to the recognition unit, the recognition unit judges the types of the electromagnetic wave data to judge the types of the road subgrade diseases and the underground diseases and then sends the electromagnetic wave data to the judgment unit, the comparison unit detects the types of the road subgrade diseases and the underground diseases by adopting a high-density resistivity method and sends the result to the judgment unit, and the judgment unit outputs the data of the recognition unit when the types of the road subgrade diseases and the underground diseases of the recognition unit are consistent, and the detection is carried out again when the types of the electromagnetic wave data are inconsistent;
the acquisition unit adopts a ground penetrating radar to acquire harmful body information of road bed and urban underground, the antennas are arranged at two ends of the detection points to emit electromagnetic waves, the acquisition unit receives the electromagnetic waves sent by the antennas and transmitted underground, and generates a recording time window, wherein the recording time window is thatWherein K is a weight coefficient, the value range is 1.2-1.5, d max And v is the equivalent electromagnetic wave speed of the underground medium, the acquisition unit acquires electromagnetic wave data in a recording time window, and the acquisition unit sends the acquired information data to the processing unit.
In this embodiment of the application, the acquisition unit is detecting the time through ground penetrating radar, sets up the transmitting point of antenna in the both sides that need carry out the probe point, all gathers the electromagnetic wave of both sides this moment, carries out the back of gathering and handles, compares with traditional cart-type, detects the speed higher to detect in both sides, guarantee the accurate degree of detection.
Referring to fig. 1, the processing unit includes a preprocessing module, an advanced processing module, and a visualization module, where the preprocessing module is configured to perform a horizontal distance normalization process on the data collected by the collecting unit, and the horizontal distance normalization process formula is as followsWherein A is the horizontal distance between two antenna transmitting points, B is the vertical distance between two antenna transmitting points, n is the number of times that the time window was gathered, S is the electromagnetic wave data after handling, and preprocessing module sends the data after handling to advanced processing module, through preprocessing module, carry out horizontal distance normalization processing with the data that gathering unit gathered, the data after carrying out normalization processing can reflect the height between harmful body and the ground more accurately, when avoiding single signal fluctuation, can cause great error to final result, and then influence the accuracy of judging harmful body.
Further, the advanced processing module removes noise in the data by adopting a smooth denoising mode, and a calculation formula of the smooth denoising is as followsWherein F (x, y) is filtered data, delta is mean variance, v is noise variance, F (x, y) is electromagnetic wave data processed by the preprocessing module, G (x, y) is a standard value of the electromagnetic wave data, and the advanced processing module sends the processed data to the visualization module and the extraction unit, and after denoising the preprocessed data, the influence of noise on the electromagnetic wave data can be avoided at the moment, so that the follow-up research on the type of harmful object is more accurate, and the failure of detecting the depth of the noise harmful object due to the influence of the noise on the electromagnetic wave data is preventedAnd the smooth denoising mode is adopted, so that the denoising process is quicker, and the detection speed of road subgrade diseases and underground disease bodies is improved.
Further, the visualization module performs visualization processing on the received data, and sends the data into a chart to a display unit on site, wherein the data visualization processing process is as follows:
a1, defining a chart template by adopting XML description, and describing data sources and style settings associated with a chart;
a2, a Java language builds a background system, after reading data, uses ChartData to store and convert the data into ChartGlyph objects, and invokes an interface to output the JSON data;
and A3, receiving JSON data by a display unit, displaying the data in the display unit in a chart form by adopting a D3.js plug-in unit, performing visual processing on the data, and converting the data into the chart form, so that a detector working on site can clearly know the change of electromagnetic wave data, and the detector is convenient for different persons on site to clearly recognize road subgrade diseases and underground diseases.
Referring to fig. 2, the extracting unit receives the processed electromagnetic wave data, extracts an abnormal point in the electromagnetic wave data, and sends the extracted abnormal point to the identifying unit, and the identifying unit classifies road subgrade diseases and underground disease bodies into four types of problems, which are respectively: the method comprises the steps of taking off, holes, loose bodies and rich water bodies, matching abnormal points with the four types of problems by an identification unit, and determining types of road subgrade diseases and underground diseases, wherein the extraction rule of the abnormal points by the extraction unit is that when the error between a certain point value and a previous point value in electromagnetic wave data is 100% or more, the abnormal points are marked, the electromagnetic wave groups with the abnormal points in the electromagnetic wave data are sent to the identification unit, the abnormal points in the electromagnetic wave data are extracted by the extraction unit, when the road subgrade diseases and underground diseases exist, the electromagnetic wave is changed into an air medium or an aqueous medium from an original earth medium during transmission, the electromagnetic wave is changed sharply, so that the error between the certain point value and the previous point value of the electromagnetic wave is 100% or more, the abnormal point is marked, and the wave group where the abnormal point is located is sent to the identification unit, so that the identification unit can confirm the types of the problems conveniently.
Referring to fig. 2, when the recognition unit detects that the electromagnetic wave group is formed as a continuous isotropic reflection wave group at the top and appears as a flat plate, the problem of the road bed disease and the underground disease is void, when the recognition unit detects that the electromagnetic wave group is an approximately spherical hollow reflection wave group and appears as an inverted hyperbolic form, the problem is spherical holes, when the electromagnetic wave group is approximately square holes and appears as a forward continuous flat plate, the problem is square holes, the recognition unit detects that the electromagnetic wave group is formed as a continuous isotropic reflection wave group at the top, the waveform structure of the multiple waves is disordered, the problem of the road bed disease and the underground disease is loose, the recognition unit detects that the electromagnetic wave group is formed as a continuous isotropic reflection wave group at the top, the multiple waves do not develop, the problem of the road bed disease and the underground disease is rich in water, and the recognition unit sends the detected result to the judgment unit.
In this embodiment of the application, the recognition element divide into four types of problems of taking off, the hole, loose body and rich water body with road subgrade disease and underground disease body, these four types of problems just cover the whole kinds of the problem that present road subgrade disease and underground disease body take place, consequently match electromagnetic wave data with this four types, thereby can know the problem that road subgrade disease and underground disease body appear fast, send the problem that it appears to processing unit, make processing unit can in time and accurate processing, and the differentiation of these four types of problems all goes on through the difference between the wave group of electromagnetic wave, thereby guarantee the accuracy that road subgrade disease and underground disease body detected.
Further, the comparison unit comprises a detection module and a matching module, the detection module detects road subgrade diseases and underground diseases by adopting a high-density resistivity method, the electrode ground buries the minimum value up to standard, the detection module sends detected data to the matching module, the matching module divides the problems of the road subgrade diseases and the underground diseases into three types of holes, loose bodies and rich bodies, when the problems are holes, the data received by the matching module are relatively high resistivity anomalies on the slope, when the problems are loose bodies, the resistivity characteristics of the problems are relatively low resistivity anomalies, when the problems are rich bodies, the resistivity characteristics of the problems are relatively low resistivity anomalies, the judgment unit sends detected results to the judgment unit, the judgment unit receives the data sent by the identification unit and the data sent by the comparison unit, when the identification unit is inconsistent with the data sent by the comparison unit, the road subgrade diseases and the underground diseases need to be detected until the judgment unit keeps consistent with the received results.
In this embodiment of the present application, the detection module in the comparison unit adopts the high-density resistivity method to detect, and the electrode buries the minimum that quantity is up to standard, therefore the detection module only makes the comparison use, and does not confirm in detail the position, thereby judge whether the ground penetrating radar that the acquisition unit adopted detects correctly, when the result that the ground penetrating radar detected is unanimous with the detection result of high-density resistivity method, it indicates that this detection is correct, consequently regard as final testing result with the road subgrade that the ground penetrating radar detected and the harmful body information in urban underground, thereby accomplish the detection to road subgrade and urban underground harmful body fast.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions in accordance with the embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired means from one website site, computer, server, or data center. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc. that contain one or more collections of available media. The usable medium may be a magnetic medium, an optical medium, or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. The utility model provides a road subgrade disease and quick automatic detecting system of underground disease body which characterized in that: the system comprises an acquisition unit, a processing unit, a display unit, an extraction unit, a recognition unit, a comparison unit and a judgment unit, wherein the acquisition unit acquires electromagnetic wave data of underground harmful bodies by adopting a ground penetrating radar method and transmits the electromagnetic wave data to the processing unit, the processing unit performs optimization treatment on the electromagnetic wave data and then transmits the electromagnetic wave data to the display unit and the extraction unit respectively, the display unit is used for performing visual display on the electromagnetic wave data, the extraction unit extracts abnormal points in the electromagnetic wave data and transmits the electromagnetic wave data to the recognition unit, the recognition unit judges the types of the electromagnetic wave data and then transmits the electromagnetic wave data to the judgment unit, the comparison unit detects the types of the road subgrade diseases and the underground harmful bodies by adopting a high-density resistivity method and transmits the result to the judgment unit, and the judgment unit outputs the data of the recognition unit when the types of the recognition unit are inconsistent with the types of the road subgrade diseases and the underground harmful bodies of the comparison unit;
the acquisition unit adopts a ground penetrating radar to acquire harmful body information of road bed and urban underground, the antennas are arranged at two ends of the detection points to emit electromagnetic waves, the acquisition unit receives the electromagnetic waves sent by the antennas and transmitted underground, and generates a recording time window, wherein the recording time window is thatWherein K is a weighting coefficient, the value range is 1.2-1.5, d max The maximum detection depth, v is the equivalent electromagnetic wave speed of the underground medium, the acquisition unit acquires electromagnetic wave data in a recording time window, and the acquisition unit sends the acquired information data to the processing unit;
the recognition unit detects that the electromagnetic wave group is a continuous isotropic reflection wave group formed at the top and appears as a flat plate, at the moment, the problems of road subgrade diseases and underground diseases are void, the recognition unit detects that the electromagnetic wave group is an approximately spherical cavity reflection wave group and appears as a reverse suspension hyperbolic form and is a spherical hole, when the electromagnetic wave group is an approximately square hole and appears as a forward continuous flat plate, the recognition unit detects that the electromagnetic wave group is a continuous isotropic reflection wave group formed at the top, the waveform structure of multiple waves is disordered, at the moment, the problems of road subgrade diseases and underground diseases are loose bodies, the recognition unit detects that the electromagnetic wave group is a continuous isotropic reflection wave group formed at the top, multiple waves do not develop, the diffraction waves are not obvious, and the problems of the road subgrade diseases and the underground diseases are rich bodies at the moment, and the recognition unit sends the detected result to the judgment unit.
2. The rapid automated detection system for road subgrade damage and subsurface damage as recited in claim 1, wherein: the processing unit comprises a preprocessing module, an advanced processing module and a visualization module, wherein the preprocessing module is used for carrying out horizontal distance normalization processing on the data acquired by the acquisition unit, and the horizontal distance normalization processing formula is as followsWherein A is the horizontal distance between two antenna transmitting points, B is the vertical distance between two antenna transmitting points, n is the number of times acquired by a time window, S is the processed electromagnetic wave data, and the preprocessing module transmits the processed data to the advanced processing module.
3. The rapid automatic detection system for road bed damage and subsurface damage according to claim 2, wherein: the advanced processing module adopts a smooth denoising mode to remove noise in data, and a calculation formula of the smooth denoising is thatWherein F (x, y) is filtered data, delta is mean variance, v is noise variance, F (x, y) is electromagnetic wave data processed by the preprocessing module, G (x, y) is a standard value of the electromagnetic wave data, and the advanced processing module sends the processed data to the visualization module and the extraction unit.
4. A rapid automatic detection system for road bed damage and subsurface damage as recited in claim 3, wherein: the visualization module performs visualization processing on the received data, and sends the data into a chart and then into a display unit on site, wherein the data visualization processing process is as follows:
a1, defining a chart template by adopting XML description, and describing data sources and style settings associated with a chart;
a2, a Java language builds a background system, after reading data, uses ChartData to store and convert the data into ChartGlyph objects, and invokes an interface to output the JSON data;
and A3, receiving JSON data by a display unit, and displaying the data in the display unit in a chart form by adopting a D3.js plug-in.
5. The rapid automated detection system for road subgrade damage and subsurface damage as recited in claim 1, wherein: the extraction unit receives the processed electromagnetic wave data, extracts abnormal points in the electromagnetic wave data, and sends the extracted abnormal points to the identification unit, wherein the identification unit divides road subgrade diseases and underground diseases into four types of problems, and the four types of problems are respectively: the recognition unit is used for matching abnormal points with the four problems and determining the types of road subgrade diseases and underground diseases.
6. The rapid automated detection system for roadway subgrade damage and subsurface damage as recited in claim 5, wherein: the extraction rule of the abnormal point of the extraction unit is that when the error between a certain point value and the previous point value of the electromagnetic wave group in the electromagnetic wave data is 100% or more, the point is marked as the abnormal point, and the electromagnetic wave group in the electromagnetic wave data with the abnormal point is sent to the identification unit.
7. The rapid automated detection system for road subgrade damage and subsurface damage as recited in claim 1, wherein: the comparison unit comprises a detection module and a matching module, the detection module detects road subgrade diseases and underground disease bodies by adopting a high-density resistivity method, the electrode buried quantity is the minimum value reaching the standard, the detection module sends detected data to the matching module, the matching module divides the problems of the road subgrade diseases and the underground disease bodies into three types of holes, loose bodies and rich water bodies, when the problems are holes, the data received by the matching module are abnormal with relatively high resistivity on a resistivity slope, when the problems are loose bodies, the resistivity characteristics are abnormal with relatively low resistivity, when the problems are rich water bodies, the resistivity characteristics are abnormal with relatively low resistivity, and the matching module sends detected results to the judgment unit.
8. The rapid automated detection system for road subgrade damage and subsurface damage as recited in claim 1, wherein: the judging unit receives the data sent by the identifying unit and the data sent by the comparing unit, when the data sent by the identifying unit and the data sent by the comparing unit are consistent, the judgment of the road subgrade diseases and the underground disease bodies is completed, and when the data sent by the identifying unit and the data sent by the comparing unit are inconsistent, detection is needed at the moment until the results received by the judging unit are consistent.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1996006367A1 (en) * | 1994-08-25 | 1996-02-29 | Geo Search Co., Ltd. | Method and device for investigating underground |
| CN108614307A (en) * | 2018-05-14 | 2018-10-02 | 招商局重庆交通科研设计院有限公司 | A kind of inverted arch quality determining method and system using Integrated Geophysical Prospecting |
| CN109001839A (en) * | 2018-06-15 | 2018-12-14 | 山东大学 | A kind of vehicle-mounted Comprehensive Geophysics detection system in city and working method |
| KR20190024416A (en) * | 2017-08-31 | 2019-03-08 | 한국도로공사 | Evaluation device for the cavum under the pavement of a road and method thereof |
| CN110082762A (en) * | 2019-06-06 | 2019-08-02 | 北京市市政工程研究院 | A kind of underdamping antenna transient electromagnetic radar and the method for detecting tunnel-liner disease |
| CN115097445A (en) * | 2022-06-20 | 2022-09-23 | 中国铁建港航局集团有限公司 | Three-dimensional ground penetrating radar detection method, system, equipment and terminal for road subgrade diseases |
| CN115561822A (en) * | 2022-09-26 | 2023-01-03 | 浙江静远电力实业有限公司 | Method and system for detecting cavities of backfill layer of extra-high voltage transformer substation based on high-frequency electromagnetic wave technology |
| CN116597365A (en) * | 2023-05-24 | 2023-08-15 | 筑升科技有限公司 | Underground disease object identification method based on neural network |
| CN116931101A (en) * | 2023-07-24 | 2023-10-24 | 四川省地质矿产勘查开发局成都水文地质工程地质中心 | Method and device for detecting underground shallow disease body, electronic equipment and storage medium |
-
2023
- 2023-11-08 CN CN202311477631.8A patent/CN117233755B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1996006367A1 (en) * | 1994-08-25 | 1996-02-29 | Geo Search Co., Ltd. | Method and device for investigating underground |
| KR20190024416A (en) * | 2017-08-31 | 2019-03-08 | 한국도로공사 | Evaluation device for the cavum under the pavement of a road and method thereof |
| CN108614307A (en) * | 2018-05-14 | 2018-10-02 | 招商局重庆交通科研设计院有限公司 | A kind of inverted arch quality determining method and system using Integrated Geophysical Prospecting |
| CN109001839A (en) * | 2018-06-15 | 2018-12-14 | 山东大学 | A kind of vehicle-mounted Comprehensive Geophysics detection system in city and working method |
| CN110082762A (en) * | 2019-06-06 | 2019-08-02 | 北京市市政工程研究院 | A kind of underdamping antenna transient electromagnetic radar and the method for detecting tunnel-liner disease |
| CN115097445A (en) * | 2022-06-20 | 2022-09-23 | 中国铁建港航局集团有限公司 | Three-dimensional ground penetrating radar detection method, system, equipment and terminal for road subgrade diseases |
| CN115561822A (en) * | 2022-09-26 | 2023-01-03 | 浙江静远电力实业有限公司 | Method and system for detecting cavities of backfill layer of extra-high voltage transformer substation based on high-frequency electromagnetic wave technology |
| CN116597365A (en) * | 2023-05-24 | 2023-08-15 | 筑升科技有限公司 | Underground disease object identification method based on neural network |
| CN116931101A (en) * | 2023-07-24 | 2023-10-24 | 四川省地质矿产勘查开发局成都水文地质工程地质中心 | Method and device for detecting underground shallow disease body, electronic equipment and storage medium |
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