A crack detection and early warning method and system for highway construction

Abstract

The present invention relates to the technical field of electronic digital data processing, and specifically provides a crack detection and early warning method and system for highway construction. The method of the present invention includes responding to signals of different signal types, obtaining detection piece data matching the signal; substituting the signal and the detection piece data matching the signal into a crack detection and early warning model, so that according to the signal type, the detection piece data is processed accordingly to obtain a display scheme corresponding to the signal, wherein the display scheme includes a three-dimensional model matching the detection piece data, or a three-dimensional model and an abnormal early warning scheme corresponding to the three-dimensional model; based on the display scheme corresponding to the signal, a display or early warning corresponding to the display scheme is executed. The automatic generation of the display scheme is realized to realize the three-dimensional display and three-dimensional early warning of the crack detection results to the management personnel, so that the maintenance personnel can accurately know the crack location and crack situation and repair them in time.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and in particular to the technical field of crack detection and early warning for highways, and in particular provides a crack detection and early warning method and system for highway construction. Background Art

[0002] Expressway, referred to as highway, refers to a road designed for high-speed driving. During the construction of expressways, the detection method of road cracks is a key technical link, which is directly related to the quality, safety and service life of the road.

[0003] However, the road crack detection method in the prior art generally uses a camera or a drone to photograph the road to determine whether there are cracks on the road. This detection method can only detect cracks on the road surface, resulting in incomplete detection, which may cause internal cracks in the highway during use but cannot be detected, and may even cause the highway to collapse during long-term use.

[0004] Accordingly, the art needs a new crack detection and early warning solution for highway construction to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least partially solve the technical problem that the detection method in the prior art can only detect cracks on the road surface, resulting in incomplete detection, which makes it impossible to detect internal cracks in the highway during use, and even causes the highway to collapse during long-term use.

[0006] In a first aspect, the present invention provides a crack detection and early warning method for highway construction, the method is applied to a crack detection and early warning system, the system includes a plurality of detection components, and the method includes the following steps:

[0007] In response to signals of different signal types, acquiring detection component data matching the signals, wherein the signal types include detection signals and abnormal signals;

[0008] Substituting the signal and the detection piece data matching the signal into the crack detection warning model, so that according to the signal type, corresponding processing is performed on the detection piece data to obtain a display scheme corresponding to the signal, wherein the display scheme includes a three-dimensional model matching the detection piece data, or a three-dimensional model matching the detection piece data and an abnormal warning scheme corresponding to the three-dimensional model;

[0009] Based on the display scheme corresponding to the signal, a display or warning corresponding to the display scheme is executed.

[0010] In one technical solution of the crack detection and early warning method for highway construction, before responding to signals of different signal types and acquiring detection piece data matching the signals, the method further includes:

[0011] Acquire construction data of the expressway, wherein the construction data includes construction location, construction scope, and type of construction to be performed;

[0012] Based on the construction data of the expressway, obtaining environmental information corresponding to the construction data, wherein the environmental information includes environmental data corresponding to the construction location and geological data within the construction range;

[0013] Substituting the construction data of the expressway and the environmental information corresponding to the construction data into the crack detection and early warning model, obtaining a detection scheme of the detection parts corresponding to the construction data, wherein the detection scheme of the detection parts includes at least one detection part model, the number of detection parts of each detection part model, the embedded information of each detection part, and the detection information of each detection part;

[0014] Based on the detection part pre-embedding plan, multiple detection parts are pre-embedded.

[0015] In one technical solution of the crack detection and early warning method for highway construction, the construction data of the highway and the environmental information corresponding to the construction data are substituted into the crack detection and early warning model to obtain the detection scheme of the detection piece corresponding to the construction data, including:

[0016] Performing settlement prediction based on the construction data of the expressway to obtain multiple sets of settlement prediction data with different predicted settlement durations, wherein the settlement prediction data includes settlement location, settlement depth and settlement value;

[0017] Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the detection component detection scheme corresponding to each group of settlement prediction data;

[0018] Based on the multiple sets of settlement prediction data, determining the level of each set of settlement prediction data;

[0019] Based on the level of each set of settlement prediction data, a cluster analysis is performed on the detection schemes of the detection parts corresponding to each set of settlement prediction data to obtain the detection schemes of the detection parts corresponding to the construction data.

[0020] In a technical solution of the crack detection and early warning method for highway construction, the multiple groups of settlement prediction data with different predicted settlement durations are screened based on the environmental information corresponding to the construction data, and the detection schemes of the detection parts corresponding to each group of settlement prediction data are obtained respectively, including:

[0021] Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data;

[0022] Based on the preset construction time, the filtered multiple sets of settlement prediction data are secondary screened to obtain the secondary screened multiple sets of settlement prediction data and the predicted settlement time of each set of settlement prediction data;

[0023] Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, the inspection plan for the inspection piece corresponding to each group of settlement prediction data is obtained respectively.

[0024] In one technical solution of the crack detection and early warning method for highway construction, the detection schemes for the detection parts corresponding to each set of settlement prediction data are obtained based on the multiple sets of settlement prediction data after secondary screening and the predicted settlement duration of each set of settlement prediction data, respectively, including:

[0025] Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, determine the model of at least one detection component corresponding to each group of settlement prediction data and the number of detection components of each detection component model;

[0026] Based on the valid detection data corresponding to the model of each detection component, selectively screening at least one detection component corresponding to each set of settlement prediction data to obtain the screened model of at least one detection component corresponding to each set of settlement prediction data;

[0027] Based on each set of settlement prediction data and the effective detection data corresponding to the model of each detection part, the pre-embedded information and detection information of each detection part are generated;

[0028] Based on at least one detection part model corresponding to each set of filtered settlement prediction data, the number of detection parts of each detection part model, and the embedded information and detection information of each detection part, a detection plan for the detection part corresponding to each set of settlement prediction data is generated.

[0029] In a technical solution of the crack detection and early warning method for highway construction, the detection piece data includes at least one detection piece, and current position data and current angle data of each detection piece, the crack detection and early warning model stores a preset detection piece history database and a preset abnormal early warning comparison database, and the signal and the detection piece data matching the signal are substituted into the crack detection and early warning model, so that the detection piece data is processed accordingly according to the signal type, and the display scheme corresponding to the signal is obtained, including:

[0030] Based on the inspection piece data, construct a three-dimensional model matching the inspection piece data;

[0031] When the signal type of the signal is a detection signal:

[0032] Based on the detection part data matched with the signal and a preset detection part history database, determining whether each detection part is abnormal;

[0033] Based on the judgment result, selectively generate an abnormality warning scheme corresponding to the three-dimensional model;

[0034] or,

[0035] When the signal type of the signal is an abnormal signal:

[0036] Based on the test piece data and a preset abnormal warning comparison database, abnormal warning labels matching each test piece in the test piece data are obtained respectively;

[0037] And all abnormal warning labels matching each detection part are marked in the three-dimensional model matching the detection part data, so as to obtain the abnormal warning scheme corresponding to the three-dimensional model.

[0038] In one technical solution of the crack detection and early warning method for highway construction, judging whether each detection part is abnormal based on the detection part data matching the signal and a preset detection part history database includes:

[0039] Based on the detection piece data matched with the signal and a preset detection piece history database, determining at least one detection piece corresponding to the detection piece data and obtaining the latest detection piece data corresponding to each detection piece;

[0040] Comparing the latest detection piece data corresponding to each detection piece with the detection piece data matching the signal to obtain a comparison result for each detection piece;

[0041] Based on the comparison results of each test piece, determine whether each test piece has any abnormality.

[0042] In one technical solution of the crack detection and early warning method for highway construction, the selective generation of an abnormal early warning solution corresponding to the three-dimensional model based on the judgment result includes:

[0043] If it is determined that all the inspection parts are normal, then based on the inspection part data, the preset inspection part history database is updated;

[0044] or,

[0045] If it is determined that the detection piece is abnormal, an abnormal warning label matching the detection piece is generated based on the comparison result of the detection piece;

[0046] Furthermore, if the number ratio of abnormal detection parts exceeds a preset abnormal ratio threshold, the detection scheme of the detection parts corresponding to the construction data is adjusted to obtain the adjusted detection scheme of the detection parts corresponding to the construction data, and the abnormal warning labels of all abnormal detection parts are marked in the three-dimensional model matching the detection part data to obtain the abnormal warning scheme corresponding to the three-dimensional model;

[0047] If the number ratio of abnormal test pieces does not exceed the preset abnormal ratio threshold, the abnormal warning labels of all abnormal test pieces are marked in the three-dimensional model matching the test piece data to obtain the abnormal warning scheme corresponding to the three-dimensional model.

[0048] In a technical solution of the crack detection and early warning method for highway construction, the abnormal warning labels matching each detection piece in the detection piece data are obtained based on the detection piece data and a preset abnormal warning comparison database, including:

[0049] Based on the detection piece data, determining the abnormal type and abnormal condition of each detection piece in the detection piece data, and generating abnormal marking labels matching each detection piece according to the abnormal type and abnormal condition of each detection piece;

[0050] Based on the abnormal type and abnormal situation of each test piece and the preset abnormal warning comparison database, a warning instruction label matching each test piece is generated respectively;

[0051] By using the abnormal marking labels and early warning instruction labels that match each detection part, abnormal early warning labels that match each detection part are obtained respectively.

[0052] In a second aspect, the present invention provides a crack detection and early warning system for highway construction, the system comprising a plurality of detection components, a crack detection and early warning model and a control device, each detection component interacting with the control device, the crack detection and early warning model storing a preset detection component history database and a preset abnormal early warning comparison database, the control device comprising a processor and a memory, the memory being suitable for storing a plurality of program codes, the program codes being suitable for being loaded and run by the processor to execute the crack detection and early warning method for highway construction described in any one of the technical solutions of the above-mentioned crack detection and early warning method for highway construction.

[0053] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0054] By responding to signals of different signal types and acquiring the corresponding detection piece data, timely acquisition of detection piece data of detection pieces in multiple positions is achieved, and then the detection piece data and signals are substituted into the crack detection and early warning model, so that according to the signal type, corresponding processing is performed on the detection piece data to obtain a display scheme corresponding to the signal, thereby achieving automatic generation of the display scheme, and according to the display scheme, executing the corresponding display or early warning, so as to realize a three-dimensional display and three-dimensional early warning of the crack detection results to the management personnel, so as to facilitate maintenance personnel to accurately know the crack location and crack conditions and repair them in time, thereby avoiding the detection method in the prior art that can only detect cracks on the road surface, resulting in incomplete detection, resulting in internal road fractures during the use of the highway but cannot be detected, and even causing the highway to collapse during long-term use.

[0055] In the technical solution for implementing the present invention, the construction data of the highway is obtained, and then the environmental data corresponding to the construction data is obtained. Then, the construction data and the environmental data are substituted into the crack detection and early warning model to obtain the detection scheme of the detection parts corresponding to the construction data. According to the detection scheme of the detection parts, a plurality of detection parts corresponding thereto are pre-buried to facilitate the subsequent acquisition of the underground detection part data, thereby realizing the timely knowledge and detection of the underground crack conditions of the highway, and thus improving the intelligent processing capability of the crack detection and early warning model for different data.

[0056] In the technical solution of the present invention, in the model processing, the corresponding three-dimensional model is constructed through the detection piece data, and the three-dimensional mapping of the current situation of the highway is realized, so that the management personnel can intuitively know the current situation of the highway; when the signal is a detection signal, it is judged whether each detection piece is abnormal according to the detection piece data and the preset detection piece history database, so as to realize the timely self-inspection of each detection piece, so as to realize the timely knowledge of the abnormal situation, and then selectively generate the corresponding abnormal warning scheme according to the judgment result; or, when the signal is an abnormal signal, the abnormal warning label of each detection piece in the detection piece data is obtained through the detection piece data and the preset abnormal warning comparison database, and each abnormal warning label is marked in the three-dimensional model corresponding to the detection piece data to obtain the corresponding abnormal warning scheme, so as to realize the timely warning of the abnormal situation of the highway, so as to facilitate the maintenance personnel to repair the highway in time according to the abnormal situation, and realize the crack detection warning model to generate the display scheme corresponding to the signal according to the detection piece data, thereby realizing the intelligent data processing capability of the crack detection warning model. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In addition, similar numbers in the figures are used to represent similar components, among which:

[0058] Figure 1 This is a schematic flow chart of the main steps of a crack detection and early warning method for highway construction according to an embodiment of the present invention;

[0059] Figure 2 It is a schematic flow chart of the main steps of data processing of a crack detection and early warning model of a crack detection and early warning method for highway construction according to an embodiment of the present invention;

[0060] Figure 3 It is a schematic diagram of the main structure block diagram of a crack detection and early warning system for highway construction according to an embodiment of the present invention.

[0061] Description of reference numerals:

[0062] 300: crack detection and early warning system; 301: control device; 3011: processor; 3012: memory; 3013: program code; 302: crack detection and early warning model; 3021: test piece history database; 3022: abnormal early warning comparison database; 303: test piece. DETAILED DESCRIPTION

[0063] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0064] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, and memories, and may also include software parts, such as program codes, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware, or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store program codes, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and the like. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B", and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0065] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart showing the main steps of a crack detection and early warning method for highway construction according to an embodiment of the present invention. Figure 1 As shown, the crack detection and early warning method for highway construction in the embodiment of the present invention is applied to a crack detection and early warning system for highway construction. The system includes several detection components. The method mainly includes the following steps S101 to S103.

[0066] Step S101: in response to signals of different signal types, acquiring detection component data matching the signals, wherein the signal types include detection signals and abnormal signals;

[0067] Furthermore, in some embodiments, before obtaining detection component data matching the signal in response to the signal of different signal types, the method further includes:

[0068] Acquire construction data of the expressway, wherein the construction data includes construction location, construction scope, and type of construction to be performed;

[0069] Based on the construction data of the expressway, obtaining environmental information corresponding to the construction data, wherein the environmental information includes environmental data corresponding to the construction location and geological data within the construction range;

[0070] Substituting the construction data of the expressway and the environmental information corresponding to the construction data into the crack detection and early warning model, obtaining a detection scheme of the detection parts corresponding to the construction data, wherein the detection scheme of the detection parts includes at least one detection part model, the number of detection parts of each detection part model, the embedded information of each detection part, and the detection information of each detection part;

[0071] Based on the detection part pre-embedding plan, multiple detection parts are pre-embedded.

[0072] Specifically, in some embodiments, substituting the construction data of the highway and the environmental information corresponding to the construction data into the crack detection and early warning model to obtain a detection scheme for the detection piece corresponding to the construction data includes:

[0073] Performing settlement prediction based on the construction data of the expressway to obtain multiple sets of settlement prediction data with different predicted settlement durations, wherein the settlement prediction data includes settlement location, settlement depth and settlement value;

[0074] Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the detection component detection scheme corresponding to each group of settlement prediction data;

[0075] Based on the multiple sets of settlement prediction data, determining the level of each set of settlement prediction data;

[0076] Based on the level of each set of settlement prediction data, a cluster analysis is performed on the detection schemes of the detection parts corresponding to each set of settlement prediction data to obtain the detection schemes of the detection parts corresponding to the construction data.

[0077] Specifically, in some embodiments, the multiple groups of settlement prediction data with different predicted settlement durations are screened based on the environmental information corresponding to the construction data to obtain the detection schemes of the detection parts corresponding to each group of settlement prediction data, respectively, including:

[0078] Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data;

[0079] Based on the preset construction time, the filtered multiple sets of settlement prediction data are secondary screened to obtain the secondary screened multiple sets of settlement prediction data and the predicted settlement time of each set of settlement prediction data;

[0080] Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, the inspection plan for the inspection piece corresponding to each group of settlement prediction data is obtained respectively.

[0081] Specifically, in some embodiments, based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data, including:

[0082] Based on the environmental information corresponding to the construction data, simulating the multiple groups of settlement prediction data with different predicted settlement durations to obtain the occurrence probability of each group of settlement prediction data;

[0083] If the occurrence probability of the settlement prediction data exceeds a preset probability threshold, retaining the settlement prediction data;

[0084] Otherwise, the settlement prediction data is eliminated to achieve screening of multiple groups of settlement prediction data with different predicted settlement durations, thereby obtaining the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data.

[0085] Specifically, in some embodiments, the preset probability threshold may be 85% or 70%. The setting of the preset probability threshold here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be elaborated here.

[0086] Specifically, in some embodiments, based on the preset construction duration, the filtered multiple sets of settlement prediction data are secondary screened to obtain the secondary screened multiple sets of settlement prediction data and the predicted settlement duration of each set of settlement prediction data, including:

[0087] If the difference between the predicted settlement duration corresponding to the screened multiple groups of settlement prediction data and the preset construction duration does not reach a preset difference threshold, retaining the settlement prediction data;

[0088] If the predicted settlement duration corresponding to the screened multiple sets of settlement prediction data exceeds the preset construction duration and the difference reaches a preset difference threshold, the settlement prediction data is discarded, and a secondary screening of the screened multiple sets of settlement prediction data is performed to obtain the secondary screened multiple sets of settlement prediction data and the predicted settlement duration of each set of settlement prediction data.

[0089] Specifically, in some embodiments, the preset construction time can be 1 month or 1 year. The setting of the preset construction time here is only an example. In actual testing, those skilled in the art can set it according to actual needs, which will not be repeated here.

[0090] Specifically, in some embodiments, the preset difference threshold may be 3 days or 15 days. The setting of the preset difference threshold here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be repeated here.

[0091] Specifically, in some embodiments, based on the multiple groups of sedimentation prediction data after secondary screening and the predicted sedimentation duration of each group of sedimentation prediction data, the detection schemes of the detection parts corresponding to each group of sedimentation prediction data are obtained respectively, including:

[0092] Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, determine the model of at least one detection component corresponding to each group of settlement prediction data and the number of detection components of each detection component model;

[0093] Based on the valid detection data corresponding to the model of each detection component, selectively screening at least one detection component corresponding to each set of settlement prediction data to obtain the screened model of at least one detection component corresponding to each set of settlement prediction data;

[0094] Based on each set of settlement prediction data and the effective detection data corresponding to the model of each detection part, the pre-embedded information and detection information of each detection part are generated;

[0095] Based on at least one detection part model corresponding to each set of filtered settlement prediction data, the number of detection parts of each detection part model, and the embedded information and detection information of each detection part, a detection plan for the detection part corresponding to each set of settlement prediction data is generated.

[0096] Specifically, the effective detection data of the detection piece corresponding to the detection piece model matches the settlement position, settlement depth, settlement value and predicted settlement duration in the settlement prediction data.

[0097] Specifically, the effective detection data of the detection parts of each detection part model is stored in the crack detection early warning model.

[0098] In the above embodiment, by acquiring the construction data of the highway, and then obtaining the environmental data corresponding to the construction data, and then substituting the construction data and the environmental data into the crack detection and early warning model, a detection scheme for detection parts corresponding to the construction data is obtained, and according to the detection scheme for detection parts, a plurality of detection parts corresponding thereto are pre-buried to facilitate the subsequent acquisition of underground detection part data, thereby realizing timely knowledge of the underground crack conditions of the highway, and thereby improving the intelligent processing capability of the crack detection and early warning model for different data.

[0099] Step S102: Substituting the signal and the detection component data matching the signal into the crack detection warning model, so that according to the signal type, the detection component data is processed accordingly to obtain a display scheme corresponding to the signal, wherein the display scheme includes a three-dimensional model matching the detection component data, or a three-dimensional model matching the detection component data and an abnormal warning scheme corresponding to the three-dimensional model;

[0100] like Figure 2 As shown, specifically, in some embodiments, the detection component data includes at least one detection component, and current position data and current angle data of each detection component, the crack detection warning model stores a preset detection component history database 3021 and a preset abnormal warning comparison database, and the signal and the detection component data matching the signal are substituted into the crack detection warning model, so that according to the signal type, the detection component data is processed accordingly, and the display scheme corresponding to the signal is obtained, including:

[0101] Based on the inspection piece data, construct a three-dimensional model matching the inspection piece data;

[0102] When the signal type of the signal is a detection signal:

[0103] Based on the detection part data matched with the signal and the preset detection part history database 3021, determining whether each detection part is abnormal;

[0104] Based on the judgment result, selectively generate an abnormality warning scheme corresponding to the three-dimensional model;

[0105] or,

[0106] When the signal type of the signal is an abnormal signal:

[0107] Based on the test piece data and a preset abnormal warning comparison database, abnormal warning labels matching each test piece in the test piece data are obtained respectively;

[0108] And all abnormal warning labels matching each detection part are marked in the three-dimensional model matching the detection part data, so as to obtain the abnormal warning scheme corresponding to the three-dimensional model.

[0109] Specifically, in some embodiments, judging whether each detection component is abnormal based on the detection component data matching the signal and the preset detection component history database 3021 includes:

[0110] Based on the detection piece data matched with the signal and the preset detection piece history database 3021, determine at least one detection piece corresponding to the detection piece data and obtain the latest detection piece data corresponding to each detection piece;

[0111] Comparing the latest detection piece data corresponding to each detection piece with the detection piece data matching the signal to obtain a comparison result for each detection piece;

[0112] Based on the comparison results of each test piece, determine whether each test piece has any abnormality.

[0113] Specifically, in some embodiments, selectively generating an abnormality warning scheme corresponding to the three-dimensional model based on the judgment result includes:

[0114] If it is determined that all the test pieces are normal, the preset test piece history database 3021 is updated based on the test piece data;

[0115] or,

[0116] If it is determined that the detection piece is abnormal, an abnormal warning label matching the detection piece is generated based on the comparison result of the detection piece;

[0117] Furthermore, if the number ratio of abnormal detection parts exceeds a preset abnormal ratio threshold, the detection scheme of the detection parts corresponding to the construction data is adjusted to obtain the adjusted detection scheme of the detection parts corresponding to the construction data, and the abnormal warning labels of all abnormal detection parts are marked in the three-dimensional model matching the detection part data to obtain the abnormal warning scheme corresponding to the three-dimensional model;

[0118] If the proportion of the number of abnormal test pieces does not exceed the preset abnormal proportion threshold, the abnormal warning labels of all abnormal test pieces are marked in the three-dimensional model that matches the test piece data, and the abnormal warning plan corresponding to the three-dimensional model is obtained to achieve abnormal marking of abnormal conditions of the test pieces and timely warning.

[0119] Specifically, in some embodiments, the preset abnormal ratio threshold may be 25% or 30%. The setting of the preset abnormal ratio threshold here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be repeated here.

[0120] Specifically, in some embodiments, the construction technology of constructing a three-dimensional model that matches the detection part data and marking abnormal warning labels of all abnormal detection parts in the three-dimensional model that matches the detection part data can be a technology for constructing three-dimensional models in the prior art. The choice of construction technology here is only an exemplary explanation. In actual testing, technical personnel in this field can make a choice according to actual needs, as long as it can be achieved according to the acquired detection part data, to construct a three-dimensional model that matches the detection part data and to mark abnormal warning labels of all abnormal detection parts in the three-dimensional model that matches the detection part data, it will not be repeated here.

[0121] Specifically, in some embodiments, generating an abnormal warning label matching the detection element based on the comparison result of the detection element includes:

[0122] Based on the comparison result of the detection part, determining the abnormal type and abnormal situation of the detection part;

[0123] Generate an abnormality mark label matching the detection piece according to the abnormality type and abnormality condition of the detection piece;

[0124] Based on the abnormal type and abnormal situation of the detection part and a preset abnormal warning comparison database, generate a warning instruction label matching the detection part;

[0125] The abnormality marking label and the early warning instruction label matching the detection piece are used to obtain the abnormality early warning label matching the detection piece.

[0126] Specifically, the preset abnormal warning comparison database includes multiple abnormal types of the detection component, multiple abnormal situations corresponding to each abnormal type, and warning instructions corresponding to each abnormal situation.

[0127] Specifically, in some embodiments, the preset inspection part history database 3021 includes different construction projects, at least one inspection part corresponding to each construction project, all inspection part data historically acquired for each inspection part, and the acquisition time corresponding to each inspection part data.

[0128] Specifically, in some embodiments, the obtaining of abnormal warning labels matching each detection component in the detection component data based on the detection component data and a preset abnormal warning comparison database includes:

[0129] Based on the detection piece data, determining the abnormal type and abnormal condition of each detection piece in the detection piece data, and generating abnormal marking labels matching each detection piece according to the abnormal type and abnormal condition of each detection piece;

[0130] Based on the abnormal type and abnormal situation of each test piece and the preset abnormal warning comparison database, a warning instruction label matching each test piece is generated respectively;

[0131] By using the abnormal marking labels and early warning instruction labels that match each detection part, abnormal early warning labels that match each detection part are obtained respectively.

[0132] Specifically, in some embodiments, the abnormal type of the detection piece is a crack. The setting of the abnormal type of the detection piece here is only an exemplary description. In actual testing, those skilled in the art can set it according to actual needs, which will not be repeated here.

[0133] Specifically, in some embodiments, the abnormal condition of the detection component can be an abnormal level or an abnormal urgency, wherein the abnormal level can be Level A, Level B, or Level C, and the abnormal urgency can be Level 1 urgency, Level 2 urgency, or Level 3 urgency. The setting of the abnormal condition of the detection component here is only an exemplary description, and in actual testing, those skilled in the art can make settings according to actual needs, which will not be repeated here.

[0134] In the above embodiment, in the model processing, the corresponding three-dimensional model is constructed through the detection piece data, and the three-dimensional mapping of the current situation of the highway is realized, so that the management personnel can intuitively know the current situation of the highway; when the signal is a detection signal, it is judged whether each detection piece is abnormal according to the detection piece data and the preset detection piece history database 3021, so as to realize the timely self-inspection of each detection piece, so as to realize the timely knowledge of the abnormal situation, and then selectively generate the corresponding abnormal warning scheme according to the judgment result; or, when the signal is an abnormal signal, the abnormal warning label of each detection piece in the detection piece data is obtained through the detection piece data and the preset abnormal warning comparison database, and each abnormal warning label is marked in the three-dimensional model corresponding to the detection piece data to obtain the corresponding abnormal warning scheme, so as to realize the timely warning of the abnormal situation of the highway, so as to facilitate the maintenance personnel to repair the highway in time according to the abnormal situation, and realize the crack detection warning model to generate the display scheme corresponding to the signal according to the detection piece data, thereby realizing the intelligent data processing capability of the crack detection warning model.

[0135] Step S103: Based on the display scheme corresponding to the signal, execute the display or warning corresponding to the display scheme.

[0136] Based on the above steps S101 to S103, by responding to signals of different signal types and acquiring the corresponding detection piece data, timely acquisition of detection piece data of detection pieces in multiple positions is achieved, and then the detection piece data and signals are substituted into the crack detection and early warning model, so that according to the signal type, corresponding processing is performed on the detection piece data to obtain a display scheme corresponding to the signal, thereby realizing automatic generation of the display scheme, and according to the display scheme, executing the corresponding display or early warning, so as to realize a three-dimensional display and a three-dimensional early warning of the crack detection results to the management personnel, so as to facilitate the maintenance personnel to accurately know the crack location and crack condition and repair them in time, thereby avoiding the detection method in the prior art that can only detect cracks on the road surface, resulting in incomplete detection, resulting in internal road fractures during use of the highway but cannot be detected, and even leading to technical problems such as collapse of the highway during long-term use.

[0137] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not have to be performed in such an order, and they can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present invention.

[0138] Furthermore, the present invention also provides a crack detection and early warning system for highway construction.

[0139] See attached Figure 3 , Figure 3 FIG. 1 is a main structural block diagram of a crack detection and early warning system for highway construction according to an embodiment of the present invention. Figure 3 As shown, the crack detection and early warning system 300 for highway construction in the embodiment of the present invention mainly includes a plurality of detection components 303, a crack detection and early warning model 302 and a control device 301, each detection component 303 interacts with the control device 301, the crack detection and early warning model 302 stores a preset detection component history database 3021 and a preset abnormal early warning comparison database 3022, the control device 301 includes a processor 3011 and a memory 3012, the memory 3012 can be configured to store a program code 3013 for executing the crack detection and early warning method for highway construction in the above method embodiment, the processor 3011 can be configured to execute the program code 3013 in the memory 3012, the program includes but is not limited to executing the program code 3013 for the crack detection and early warning method for highway construction in the above method embodiment. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, and the specific technical details are not disclosed, please refer to the method part of the embodiment of the present invention. The control device 301 can be a control device device formed by various electronic devices.

[0140] Specifically, in some embodiments, the preset detection component history database 3021 includes different construction projects, at least one detection component 303 corresponding to each construction project, and all the detection component data acquired historically for each detection component and the acquisition time corresponding to each detection component data;

[0141] The preset abnormal warning comparison database 3022 includes multiple abnormal types of the detection element 303, multiple abnormal situations corresponding to each abnormal type, and warning instructions corresponding to each abnormal situation.

[0142] In one implementation, the description of the specific implementation functions may refer to steps S101 to S103.

[0143] The above-mentioned crack detection and early warning system 300 for highway construction is used to perform Figure 1 The crack detection and early warning method embodiment for highway construction shown in the figure has similar technical principles, technical problems solved and technical effects produced. Technicians in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the crack detection and early warning system 300 for highway construction can refer to the contents described in the embodiment of the crack detection and early warning method for highway construction, which will not be repeated here.

[0144] It is understood by those skilled in the art that the present invention implements all or part of the processes in the method of the above embodiment, and can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor 3011, the steps of each of the above method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electric carrier signal and telecommunication signal.

[0145] Further, the crack detection and early warning system 300 for highway construction of the present invention also includes a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program for executing the crack detection and early warning method for highway construction of the above method embodiment, and the program can be loaded and run by the processor 3011 to implement the above crack detection and early warning method for highway construction. For ease of explanation, only the part related to the embodiment of the present invention is shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium can be a memory 3012 formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0146] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor 3011 itself, or a part of the software, a part of the hardware, or a part of the combination of software and hardware in the processor 3011. Therefore, the number of each module in the figure is only schematic.

[0147] Those skilled in the art will appreciate that the modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present invention.

[0148] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A crack detection and early warning method for highway construction, characterized in that: The method is applied to a crack detection and early warning system, the system includes a plurality of detection components, and the method includes the following steps: In response to signals of different signal types, acquiring detection component data matching the signals, wherein the signal types include detection signals and abnormal signals; Substituting the signal and the detection piece data matching the signal into the crack detection warning model, so that according to the signal type, corresponding processing is performed on the detection piece data to obtain a display scheme corresponding to the signal, wherein the display scheme includes a three-dimensional model matching the detection piece data, or a three-dimensional model matching the detection piece data and an abnormal warning scheme corresponding to the three-dimensional model; Based on the display scheme corresponding to the signal, executing the display or warning corresponding to the display scheme; The detection component data includes at least one detection component, and current position data and current angle data of each detection component. The crack detection warning model stores a preset detection component history database and a preset abnormal warning comparison database. Substituting the signal and the detection component data matching the signal into the crack detection warning model so that the detection component data is processed accordingly according to the signal type, and obtaining a display scheme corresponding to the signal includes: Based on the inspection piece data, construct a three-dimensional model matching the inspection piece data; When the signal type of the signal is a detection signal: Based on the detection part data matched with the signal and a preset detection part history database, determining whether each detection part is abnormal; Based on the judgment result, selectively generate an abnormality warning scheme corresponding to the three-dimensional model; or, When the signal type of the signal is an abnormal signal: Based on the test piece data and a preset abnormal warning comparison database, abnormal warning labels matching each test piece in the test piece data are obtained respectively; and marking all abnormal warning labels matching each detection part in the three-dimensional model matching the detection part data, to obtain an abnormal warning scheme corresponding to the three-dimensional model; Before acquiring detection component data matching the signals in response to the signals of different signal types, the method further includes: Acquire construction data of the expressway, wherein the construction data includes construction location, construction scope, and type of construction to be performed; Based on the construction data of the expressway, obtaining environmental information corresponding to the construction data, wherein the environmental information includes environmental data corresponding to the construction location and geological data within the construction range; Substituting the construction data of the expressway and the environmental information corresponding to the construction data into the crack detection and early warning model, obtaining a detection scheme of the detection parts corresponding to the construction data, wherein the detection scheme of the detection parts includes at least one detection part model, the number of detection parts of each detection part model, the embedded information of each detection part, and the detection information of each detection part; Based on the pre-embedding scheme of the inspection parts, multiple inspection parts are pre-embedded; The selectively generating an abnormal warning scheme corresponding to the three-dimensional model based on the judgment result includes: If it is determined that all the inspection parts are normal, then based on the inspection part data, the preset inspection part history database is updated; or, If it is determined that the detection piece is abnormal, an abnormal warning label matching the detection piece is generated based on the comparison result of the detection piece; Furthermore, if the number ratio of abnormal detection parts exceeds a preset abnormal ratio threshold, the detection scheme of the detection parts corresponding to the construction data is adjusted to obtain an adjusted detection scheme of the detection parts corresponding to the construction data, and abnormal warning labels of all abnormal detection parts are marked in the three-dimensional model matching the detection part data to obtain an abnormal warning scheme corresponding to the three-dimensional model; If the number ratio of abnormal test pieces does not exceed the preset abnormal ratio threshold, the abnormal warning labels of all abnormal test pieces are marked in the three-dimensional model matching the test piece data, and the abnormal warning scheme corresponding to the three-dimensional model is obtained; Substituting the construction data of the expressway and the environmental information corresponding to the construction data into the crack detection and early warning model to obtain a detection scheme for the detection piece corresponding to the construction data includes: Performing settlement prediction based on the construction data of the expressway to obtain multiple sets of settlement prediction data with different predicted settlement durations, wherein the settlement prediction data includes settlement location, settlement depth and settlement value; Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the detection component detection scheme corresponding to each group of settlement prediction data; Based on the multiple sets of settlement prediction data, determining the level of each set of settlement prediction data; Based on the level of each set of settlement prediction data, a cluster analysis is performed on the detection schemes of the detection parts corresponding to each set of settlement prediction data to obtain the detection schemes of the detection parts corresponding to the construction data.

2. The crack detection and early warning method for highway construction according to claim 1 is characterized in that: The method of screening the multiple groups of settlement prediction data with different predicted settlement durations based on the environmental information corresponding to the construction data to obtain the detection schemes of the detection parts corresponding to each group of settlement prediction data includes: Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data; Based on the preset construction time, the filtered multiple sets of settlement prediction data are secondary screened to obtain the secondary screened multiple sets of settlement prediction data and the predicted settlement time of each set of settlement prediction data; Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, the inspection plan for the inspection piece corresponding to each group of settlement prediction data is obtained respectively.

3. The crack detection and early warning method for highway construction according to claim 2 is characterized in that: Based on the environmental information corresponding to the construction data, the multiple groups of settlement prediction data with different predicted settlement durations are screened to obtain the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data, including: Based on the environmental information corresponding to the construction data, simulating the multiple groups of settlement prediction data with different predicted settlement durations to obtain the occurrence probability of each group of settlement prediction data; If the occurrence probability of the settlement prediction data exceeds a preset probability threshold, retaining the settlement prediction data; Otherwise, the settlement prediction data is eliminated to achieve screening of multiple groups of settlement prediction data with different predicted settlement durations, thereby obtaining the screened multiple groups of settlement prediction data and the predicted settlement duration of each group of settlement prediction data.

4. The crack detection and early warning method for highway construction according to claim 3 is characterized in that: The detection schemes of the detection parts corresponding to each set of settlement prediction data are obtained based on the multiple sets of settlement prediction data after secondary screening and the predicted settlement duration of each set of settlement prediction data, respectively, including: Based on the multiple groups of settlement prediction data after secondary screening and the predicted settlement duration of each group of settlement prediction data, determine the model of at least one detection component corresponding to each group of settlement prediction data and the number of detection components of each detection component model; Based on the valid detection data corresponding to the model of each detection component, selectively screening at least one detection component corresponding to each set of settlement prediction data to obtain the screened model of at least one detection component corresponding to each set of settlement prediction data; Based on each set of settlement prediction data and the effective detection data corresponding to the model of each detection part, the pre-embedded information and detection information of each detection part are generated; Based on at least one detection part model corresponding to each set of filtered settlement prediction data, the number of detection parts of each detection part model, and the embedded information and detection information of each detection part, a detection plan for the detection part corresponding to each set of settlement prediction data is generated.

5. The crack detection and early warning method for highway construction according to claim 4 is characterized in that: The determining whether each detection component is abnormal based on the detection component data matched with the signal and a preset detection component history database includes: Based on the detection piece data matched with the signal and a preset detection piece history database, determining at least one detection piece corresponding to the detection piece data and obtaining the latest detection piece data corresponding to each detection piece; Comparing the latest detection piece data corresponding to each detection piece with the detection piece data matching the signal to obtain a comparison result for each detection piece; Based on the comparison results of each test piece, determine whether each test piece has any abnormality.

6. The crack detection and early warning method for highway construction according to claim 5 is characterized in that: The abnormal warning labels that match each detection piece in the detection piece data are obtained based on the detection piece data and a preset abnormal warning comparison database, including: Based on the detection piece data, determining the abnormal type and abnormal condition of each detection piece in the detection piece data, and generating abnormal marking labels matching each detection piece according to the abnormal type and abnormal condition of each detection piece; Based on the abnormal type and abnormal situation of each test piece and the preset abnormal warning comparison database, a warning instruction label matching each test piece is generated respectively; By using the abnormal marking labels and early warning instruction labels that match each detection part, abnormal early warning labels that match each detection part are obtained respectively.

7. A crack detection and early warning system for highway construction, characterized in that: The system includes a plurality of detection parts, a crack detection and early warning model and a control device, each detection part exchanges information with the control device, the crack detection and early warning model stores a preset detection part history database and a preset abnormal early warning comparison database, the control device includes a processor and a memory, the memory is suitable for storing a plurality of program codes, the program codes are suitable for being loaded and run by the processor to execute the crack detection and early warning method for highway construction described in any one of claims 1 to 6.

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